INFECTION OF BLUEBERRIES BY COLLETOTRICHUM ACUTATUM: HOST DEFENSES,
INHERITANCE OF RESISTANCE AND ENVIRONMENTAL EFFECTS
By
Timothy David Miles

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Plant Pathology
2011
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ABSTRACT
INFECTION OF BLUEBERRIES BY COLLETOTRICHUM ACUTATUM: HOST DEFENSES,
INHERITANCE OF RESISTANCE AND ENVIRONMENTAL EFFECTS
By
Timothy David Miles
Anthracnose fruit caused by Colletotrichum acutatum is the most important postharvest
disease of blueberries (Vaccinium corymbosum). In order to develop a disease forecasting model
for anthracnose fruit rot in blueberries, the effects of temperature, wetness duration, relative
humidity and wetness interruptions were studied on appressorium formation and infection of green
and blue fruit by C. acutatum. Three-dimensional response surfaces were fitted to the data. A
model combining all variables was developed. The resistance response in blueberry cultivar
‘Elliott’ was investigated. Using suppression subtraction hybridization, several defense-related
genes as well as abiotic stress-related genes were found to be upregulated in ‘Elliott’ but not in
‘Jersey’ fruit within 24 hours after inoculation. Some genes were related to oxidative stress in plant
tissues. Higher levels of hydrogen peroxide were also found in 'Elliott' than 'Jersey' fruit after
inoculation. To investigate the role of antifungal compounds in resistance, a series of fruit
extractions was performed with water, methanol, and ethyl acetate, and fractions were tested for
antifungal activity in agar plate bioassays. The methanolic extract was the most biologically active;
disease incidence was reduced by 88% when ‘Jersey’ fruit was pretreated with a 4% solution prior
to inoculation with C. acutatum. Spectrophotometry showed that this fraction mainly contained
flavonoids. Anthocyanins and flavonols were then quantified and identified in both cultivars using
HPLC-MS. ‘Elliott’ fruit overall contained more anthocyanins than ‘Jersey’ fruit but the same
compounds were found in both cultivars. However, two unique flavonols were present in ‘Elliott’.

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A total of 26 blueberry cultivars were screened for anthracnose resistance using several different
techniques. A cut-fruit technique was promising for use as a rapid screening method. A positive
linear correlation was observed between resistance and fruit sugar content but not fruit pH. The
growth of C. acutatum in culture was restricted at higher sugar and lower pH levels. The
inheritance of resistance was also investigated to facilitate future breeding work. Using inoculated
fruit from F-1 populations of specific crosses between resistant and susceptible cultivars, resistance
ratings based on AUDPC values were compared to resistance ratings predicted from previous
studies. Significant correlations were observed, providing strong evidence that anthracnose
resistance is highly heritable in highbush blueberries. The results from these studies provide a
significant contribution to the understanding of the biology and management of anthracnose fruit
rot in blueberry.

iii

For my parents Paula and David who have supported me since the beginning and my wife Laura
who has been a great source of motivation and inspiration.

iv

ACKNOWLEDGMENTS
I would like to express my genuine gratitude to Dr. Annemiek Schilder, who has provided
me with guidance and support that was vital for the success of my Ph.D. I would like to thank the
members of my guidance committee; Drs. Muraleedharan Nair, Brad Day, and Ray
Hammerschmidt. Their direction was invaluable throughout my program.
I would also like to thank members of my laboratory for helping me throughout my
program. Special thanks go to Roger Sysak; Jerri Gillett, my second advisor; Stephen Jordan, my
surrogate big brother; and undergraduate students that have assisted me: Christine Bates, Daniel
Svoboda and Christopher Woelk. I would like to especially thank Michigan State University for
the opportunity to meet my wife, throughout my Ph.D. Laura has provided me with love and
support and I don’t think I could have made it without her.
I would like to thank Dr. Andy Jarosz for help with infection modeling, Dr. James Hancock
for his help in supporting my research ideas, and Dr. Daniel Jones and Christine Vandervoort for
assistance with my HPLC-MS and MS-MS analyses. All of these faculty members have provided
invaluable advice.
A special thanks to goes to my mother Paula, my father David, and my grandmother Mary.

v

TABLE OF CONTENTS
LIST OF TABLES .................................................................................................................... ix
LIST OF FIGURES .................................................................................................................. xii
CHAPTER I: LITERATURE REVIEW .................................................................................... 1
Introduction ................................................................................................................................. 1
Blueberry production in Michigan .............................................................................................. 9
Anthracnose fruit rot of blueberry ............................................................................................ 11
Environmental requirements for infection ................................................................................ 14
The infection process ................................................................................................................ 16
Passive host defenses ................................................................................................................ 18
Active host defenses ................................................................................................................. 21
Genetics of resistance ............................................................................................................... 23
Conclusions ............................................................................................................................... 25
CHAPTER II: THE EFFECT OF ENVIRONMENTAL FACTORS ON INFECTION OF
BLUEBERRY FRUIT BY COLLETOTRICHUM ACUTATUM ............................................. 26
Abstract ..................................................................................................................................... 26
Introduction ............................................................................................................................... 27
Materials and Methods .............................................................................................................. 29
Results ....................................................................................................................................... 37
Discussion ................................................................................................................................. 50
Acknowledgments..................................................................................................................... 53
CHAPTER III: IDENTIFICATION OF DIFFERENTIALLY EXPRESSED GENES IN A
RESISTANT VERSUS SUSCEPTIBLE CULTIVAR AFTER INFECTION BY
COLLETOTRICHUM ACUTATUM......................................................................................... 54
Abstract ..................................................................................................................................... 54
Introduction ............................................................................................................................... 55
Materials and Methods .............................................................................................................. 58
Results ....................................................................................................................................... 67
Discussion ................................................................................................................................. 82
Acknowledgments..................................................................................................................... 87
CHAPTER IV: CHARACTERIZATION AND BIOLOGICAL ACTIVITY OF FLAVONOIDS
FROM RIPE FRUIT OF AN ANTHRACNOSE-RESISTANT BLUEBERRY CULTIVAR 88
Abstract ..................................................................................................................................... 88
Introduction ............................................................................................................................... 89
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Materials and Methods .............................................................................................................. 91
Results and Discussion ............................................................................................................. 96
Conclusions ............................................................................................................................. 108
Acknowledgments................................................................................................................... 109
CHAPTER V: EVALUATION OF SCREENING METHODS AND FRUIT COMPOSITION
IN RELATION TO ANTHRACNOSE FRUIT ROT RESISTANCE IN BLUEBERRIES .. 110
Abstract ................................................................................................................................... 110
Introduction ............................................................................................................................. 111
Materials and Methods ............................................................................................................ 114
Results ..................................................................................................................................... 119
Discussion ............................................................................................................................... 135
Acknowledgments................................................................................................................... 139
CHAPTER VI: INHERITANCE OF RESISTANCE TO COLLETOTRICHUM ACUTATUM IN
HIGHBUSH BLUEBERRY (VACCINIUM CORYMBOSUM L.) FRUIT ............................ 141
Abstract ................................................................................................................................... 141
Introduction ............................................................................................................................. 141
Materials and Methods ............................................................................................................ 143
Results ..................................................................................................................................... 147
Discussion ............................................................................................................................... 151
Acknowledgments................................................................................................................... 155
CONCLUSIONS AND FUTURE DIRECTIONS ................................................................. 156
APPENDICES ........................................................................................................................ 161
Appendix A – Raw data figures from chapter II..................................................................... 162
Appendix B – Supplemental tables and figures from chapter III ........................................... 167
Appendix C – Supplemental figures from chapter IV ............................................................ 172
Appendix D – Pathologicity of various isolates of Colletotrichum acutatum on ‘Jersey’
blueberries ............................................................................................................................... 176
Appendix E – Screening daughter blueberry plants from a ‘Draper’ x ‘Jewel’ cross for resistance
to Colletotrichum acutatum .................................................................................................... 178
Appendix F – The role of ethylene in blueberry anthracnose fruit rot resistance................... 184
Appendix G – First report of grape root rot caused by Roesleria subterranea in Michigan .. 187
Appendix H – First report of Pythium sterilum causing root rot of blueberry in the United States
................................................................................................................................................. 189
REFERENCES ....................................................................................................................... 191

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LIST OF TABLES
Table 1.1. Colletotrichum species that cause diseases on fleshy fruits. ........................................ 2
Table 2.1. Fitted-models for the development of melanized appressoria and infection level of
immature and mature blueberry fruits by Colletotrichum acutatum using temperature (°C), wetness
duration (h), wetness interruption (h), and relative humidity (%). Nine equations were developed
based on curve fitting the raw data from a mixture of experiments and models were examined for
2
goodness of fit (R ), standard error of the estimate (SEE), the P value of the regression and the
mean squared error (MSE) of the residuals (* denotes a chosen equation) .................................. 35
Table 2.2. Proposed model for the development of melanized appressoria and the infection level of
immature and mature blueberry fruits by Colletotrichum acutatum. Nine equations were developed
based on curve fitting the raw data from a mixture of experiments and these equations were used to
make three combined models........................................................................................................ 39
Table 3.1. Characteristics and predicted physiological function of differentially expressed
sequence tags (ESTs) from ripe fruit of highbush blueberry cultivars Elliott versus Jersey after
inoculation with Colletotrichum acutatum.The hypothetical function is based on homology to
sequences in translated nucleotide databases (DDBJ/EMBL/GenBank) using TBLASTX. This
-5
table only displays putative plant sequences with homologous E values lower than 1 x 10 . .... 72
Table 3.2. Primer DNA sequences, guanine-cytosine (GC) percentages, calculated primer melting
temperatures (Tm), expected product size, product melting temperature, Q-RT-PCR standard curve
plot slope, and calculated primer efficiency used in semi-quantitative and quantitative RT-PCR
expression analysis of differentially expressed sequence tags in blueberry fruit in response to C.
acutatum inoculation.. ................................................................................................................... 74
Table 4.1. Anthocyanins from the resistant blueberry cultivar Elliott and the susceptible blueberry
cultivar Jersey identified in HPLC/MS analysis and quantified using HPLC/PDA. Compounds
were putatively identified based on previous research, available spectra, standards, retention times
and m/z ratios. Anthocyanins were quantified at a wavelength of 520 nm using a standard curve
plot of cyanidin 3-O-glucoside.. ................................................................................................. 100
Table 4.2. Non-anthocyanin flavonoids from the resistant blueberry cultivar Elliott and the
susceptible blueberry cultivar Jersey identified in HPLC/MS analysis and quantified using
HPLC/PDA. Compounds were putatively identified based on previous research, available spectra,
standards, retention times and m/z ratios. Non-anthocyanin flavonoids were quantified at a
wavelength of 255 nm using a standard curve plot of quercetin 3-O-rhamnoside. .................... 103
Table 5.1. Anthracnose fruit rot resistance profiles of different blueberry cultivars after artificial
inoculation with Colletotrichum acutatum as measured by infection incidence (proportion of fruit
infected), infection severity (the percentage of the fruit surface supporting sporulation), and
sporulation capacity (number of conidia produced on the cut surface of a half berry). Ripe fruit was
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collected from a field planting in Grand Junction, MI, USA in July and August of 2008 and 2009
(n = 10 unless otherwise noted and SE = standard error of the mean). ...................................... 122
Table 5.2. Pearson correlation coefficients (r) and statistical significance (P) for regressions
between different measures of anthracnose fruit rot resistance after artificial inoculation of a range
of blueberry cultivars with Colletotrichum acutatum. Infection incidence (proportion of fruit
infected), infection severity (the percentage of the fruit surface supporting sporulation), sporulation
capacity (number of conidia produced on the cut surface of a half berry) and previously published
resistance ratings (Polashock et al., 2005) were subjected to linear regression. All values were log
transformed prior to regression. R-values in boldface are statistically significant at α < 0.05... 126
Table 5.3. Characteristics of fruit of different blueberry cultivars collected from a field planting in
Grand Junction, MI, USA from 2005 to 2008. Values shown are averages and standard errors over
4 years. Five berries were used per replicate. ............................................................................. 128
Table 5.4. Pearson correlation coefficients (r) for regressions of various measures of anthracnose
fruit rot resistance after artificial inoculation of blueberry fruit with Colletotrichum acutatum
(Table 5.1) against fruit characteristics (Table 5.1). Infection incidence (proportion of fruit
infected), infection severity (percentage of the fruit surface supporting sporulation), sporulation
capacity (number of conidia produced on the cut surface of a half berry) and previously published
resistance ratings (Polashock et al., 2005) were subjected to linear regression against fruit
variables. Statistically significant r-values are indicated in boldface. ....................................... 130
Table 6.1. Previous anthracnose fruit rot resistance profiles of blueberry cultivars used in this
study using proportion decayed values (24) and sporulation capacity (17). Both studies used
artificial inoculation, however, Polashock et al. (2005) inoculated green fruit and rated on disease
incidence (proportion decayed) and Miles et al. (2011b) inoculated the cut surface of ripe fruit and
rated on the quantity of conidia produced on a cut fruit surface (sporulation capacity).. .......... 145
Table 6.2. Area under the disease progress (AUDPC) values of the incidence of Colletotrichum
acutatum on various blueberry cultivars and cross families screened by artificial inoculation in
2010 and 2011 at the Southwest Michigan Research and Extension Center (Benton Harbor, MI).
Fruit of 4 to 7-year old bushes were inoculated when immature, harvested when ripe, incubated,
and rated at 5, 8 and 12 days. A statistically significant effect of year (P = 0.008) so data from the
two years was analyzed separately. ............................................................................................ 149
Table B.1. Characteristics and predicted physiological function of differentially expressed
sequence tags (ESTs) from ripe fruit of highbush blueberry cultivar Elliott versus cultivar Jersey
after inoculation with Colletotrichum acutatum. The hypothetical function is based on homology to
sequences in translated nucleotide databases (DDBJ/EMBL/GenBank) using TBLASTX. Some
ESTs are likely of fungal origin based on homology with fungal genes. ................................... 167
Table C.1. Bioactivity of extracts and fractions from the anthracnose-resistant blueberry cultivar
Elliott and susceptible cultivar Jersey as measure by their ability to inhibit microconidiation of
Colletotrichum acutatum on solid media (+ = activity, - = no activity) .................................... 172

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Table D.1. Pathogenicity of various isolates of Colletotrichum acutatum on detached fruit of the
susceptible blueberry cultivar Jersey. Isolates were obtained from various hosts including highbush
blueberry (Vaccinium corymbosum), currant (Ribes spp.), cranberry (Vaccinium macrocarpon),
raspberry (Rubus spp.), blackberry (Rubus spp.), strawberry (Fragaria x ananassa), and grape
(Vitis spp.). Ripe ‘Jersey’ fruits were harvested from a field planting in Harrietta, MI in August
6
2006, spray-inoculated with 10 conidia per ml, incubated at 100% relative humidity, and rated for
incidence of disease 10 days post inoculation (n = 5 and SE = standard error of the mean). .... 176
Table E.1. Anthracnose resistance ratings of detached blueberryfruits from several daughters of a
Draper x Jewel cross. Fruits were harvested in Interlachen, FL between 26 April and 12 May in
2011, stored, and shipped overnight to Michigan State University and inoculated with 106
spores/ml by spraying (whole fruit assays) or by a 50 µl droplet on a cut fruit surface (cut fruit
assays). Fruits incubated at 100% relative humidity at 22-24°C and rated at 3 days (for cut fruit
assays) or 10 days ( for whole fruit assays). For each daughter 5 fruits were screened per replicate
(25 in total, and n = 5) per type of inoculation. .......................................................................... 178
Table E.2. Anthracnose resistance ratings of detached blueberryfruits from several daughters of a
Draper x Jewel cross. Fruits were harvested in Corvallis, OR between 20 July and 11 August in
2011, stored, and shipped overnight to Michigan State University and inoculated with 106
spores/ml by a 50 µl droplet on a cut fruit surface. Fruits incubated at 100% relative humidity at
22-24°C and rated at 3 days. For each daughter 5 fruits were screened per replicate (25 in total,
and n = 5) per type of inoculation. .............................................................................................. 181

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LIST OF FIGURES
Figure 1.1. Representative symptoms on ripe fruit of infection by Colletotrichum spp. A) apple
(Malus domestica Borkh. - image 1233007) B) blueberry (Vaccinium corymbosum L.), courtesy A.
Schilder, C) lychee (Litchi chinensis Sonn. – image 5403527), D) cantaloupe (Cucumis melo L. –
image 5405331), E) peach (Prunus persica L. Batsch – image 5407867), F) sweet pepper
(Capsicum annuum L. – image 5435606), G) tomato (Lycopersicon esculentum Mill. – image
1236163), and H) strawberry (Fragaria × ananassa Duchesne), courtesy A. Schilder. Numbered
images courtesy of IPM images (http://www.ipmimages.org/); photographer information included,
Clemson University - USDA Cooperative Extension Slide Series (A and G), Yuan-Min Shen,
Taichung District Agricultural Research and Extension Station (C and F), and Paul Bachi,
University of Kentucky Research and Education Center (D and E). For interpretation of the
references to color in this and all other figures, the reader is referred to the electronic version of
this thesis......................................................................................................................................... 4
Figure 1.2. Conidium germination of Colletotrichum acutatum on parafilm-covered glass slides.
A) Ungerminated conidia B) Germinated conidium with germ tube, C) Unmelanized appressorium
and D) Melanized appressoria with internal light spots (ILS) (Bars = 10 µm).. ............................ 7
Figure 1.3. A) A close-up of the skin of an infected blueberry reveals small open blisters
(acervuli) in which the spores are produced.B) Acervulus bursting through the fruit epidermis
(electron micrograph). Conidia can be seen in the matrix (Bar = 50 µm)... ................................... 7
Figure 1.4. Chemical structures of two common flavonoids present in fruit of highbush
blueberries. A) Anthocyanin backbone which is typically glycosylated at the R3 position. B)
Flavonol backbone. ....................................................................................................................... 10
Figure 1.5. Disease cycle of anthracnose fruit rot caused by Colletotrichum acutatum on
blueberries. (Illustration by Jennifer Pagan.). ............................................................................... 13
Figure 2.1. The effect of temperature on mycelial growth of Colletotrichum acutatum (isolate
#0001) on quarter-strength potato dextrose agar. Colony diameter was measured in two
perpendicular directions and averaged after a 10-day incubation at each temperature. Values are
the average of three replications and error bars denote the standard error of the mean. .............. 38
Figure 2.2. The effect of temperature and wetness duration on the predicted development of
melanized appressoria of Colletotrichum acutatum on parafilm-covered glass slides. A Gaussian
equation (Table 2.2, Equation A) was used to fit the data. Shading intensity of the surface indicates
changes in the percentage of melanized appressoria at 20% intervals starting at zero................. 40
Figure 2.3. The effect of temperature and wetness duration on the predicted infection level of
immature (A) and mature (B) blueberry fruits by Colletotrichum acutatum. Separate Gaussian
equations were fit to the data for immature fruit (Table 2.2, Equation D) and mature fruit (Table
2.2, Equation G). Shading intensity of the surface indicates changes in the percentage of infected
fruit at 20% intervals starting at zero... ......................................................................................... 41
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Figure 2.4. The effect of interrupted wetness periods (0-, 1-, 4-, and 16-h of dry time in the middle
of 12-, 24-, and 48-h wet periods) on the development of melanized appressoria (%) of
Colletotrichum acutatum (A-C) and the percentage immature (D-F) and mature (G-I) blueberry
fruit infected by C. acutatum. Values are the average of four replications and error bars denote the
standard error of the mean... ......................................................................................................... 42
Figure 2.5. The effect of wetness duration and interrupted wetness periods on the predicted
development of melanized appressoria of Colletotrichum acutatum on parafilm-coated glass slides.
Values are calculated as the percent melanized appressoria relative to the continuous wetness
treatment. A Planer equation (Table 2.2, Equation B) was fit to the data. Shading intensity of the
surface indicates changes with the percentage of melanized appressoria at 20% intervals starting at
zero................................................................................................................................................ 44
Figure 2.6. The effect of wetness duration and interrupted wetness periods on the predicted
infection level of immature (A) and mature (B) blueberry fruit by Colletotrichum acutatum. Values
are calculated as the percent infected fruit relative to the continuous wetness control. Planer
equations (Table 2.2, Equation E) were fit to the data for immature fruit and mature fruit (Table
2.2, Equation H). Shading intensity of the surface indicates changes in the percentage of infected
fruit at 20% intervals starting at zero. ........................................................................................... 45
Figure 2.7. The effect of temperature and relative humidity on the predicted development of
melanized appressoria (%) of Colletotrichum acutatum (A), and the predicted infection level of
mature blueberry fruits (B) by C. acutatum. A Gaussian equation (Table 2.2, Equation C) was fit to
the data for melanized appressoria and a Lorentzian equation (Table 2.2, Equations F and I) was
used to fit the data for mature fruit. Shading intensity of the surface indicates changes in the
percentage of melanized appressoria and percentage infected fruit at 20% intervals, respectively,
starting at zero.. ............................................................................................................................. 47
Figure 3.1. Symptoms and signs of Colletotrichum acutatum infection of highbush blueberry fruit
A) Fruit appearance 8 d after inoculation in the susceptible cultivar Jersey, and B) the resistant
cultivar Elliott. Scanning electron micrograph of acervuli on the fruit surface of C) ‘Jersey’ and D)
‘Elliott’. Bar = 0.5 mm.................................................................................................................. 68
Figure 3.2. A) Average diameter of acervuli of C. acutatum on fruit of the susceptible blueberry
cultivar ‘Jersey’ (white bars) and resistant cultivar ‘Elliott’ (black bars) (n = 50). B) Quantity of C.
acutatum conidia produced on ‘Jersey’ (open bars) and ‘Elliott’ (closed bars) after 8 d of
incubation (n = 5). Error bars denote standard error of the mean. Means with the same letter are not
significantly different from each other according to Student’s paired t-test (P < 0.05). .............. 69
Figure 3.3. The percentage of C. acutatum conidia that formed melanized appressoria at 24 h post
inoculation on blueberry fruit at different stages of development in the susceptible cultivar Jersey
(white bars) and resistant cultivar Elliott (black bars). Error bars denote the standard error of the
mean (n = 5). Within each development stage, means with the same letter are not significantly
different from each other according to Student’s paired t-test (P < 0.05) .................................... 70

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Figure 3.4. Suppression subtractive hybridization to detect differential expression of genes in
‘Elliott’ (resistant) compared to ‘Jersey’ (susceptible) blueberry fruit after inoculation with C.
acutatum. A) Colony PCR products obtained from forward-subtracted ‘Elliott’ cDNA library with
T7 and Sp6 primers used for dot blot analysis and visualized through gel electrophoresis. Lanes 1
and 24, 1-kb+ DNA ladder; lane 2, negative control; lane 3, EV=empty vector; lanes 4 through 23
PCR products from ‘Elliott’ forward-subtracted cDNA library. B) PCR products from the forward
‘Elliott’ library hybridized with the reverse ‘Jersey’ library DIG probe. C) PCR products from the
forward ‘Elliott’ library hybridized with the forward ‘Elliott’ DIG probe. Dotted lines surround the
actin PCR product which served as an internal standard. ............................................................. 75
Figure 3.5. Temporal pattern of transcript accumulation and origin determination of putative genes
in blueberry fruit of the resistant cultivar Elliott and the susceptible cultivar Jersey after
inoculation with C. acutatum. A) Transcript accumulation of expressed sequence tags (Table 3.1)
at 0, 24, 48, 96, and 144 hours post inoculation in semi-quantitative RT-PCR. B) The origin of the
ESTs as determined by PCR using genomic DNA from ‘Elliott’, ‘Jersey’ and C. acutatum. In A
and B, experiments were performed with specific primers constructed for each individual EST of
interest (Table 3.2). Controls were performed with primers specific for actin (Table 3.2) and the
fungal ITS region (ITS1F-ITS4).. ................................................................................................. 77
Figure 3.6. Ratio of transcript accumulation of expressed sequence tags (ESTs) relative to actin in
quantitative RT-PCR at 0, 24, 48, 96, and 144 hours post inoculation of ripe blueberry fruit of a
susceptible cultivar Jersey and a resistant cultivar Elliott with C. acutatum or water (control).
Mean expression levels were normalized with mean endogenous actin levels, and an induced
sample was used to generate the standard curve plots for each individual EST. ∆Rn thresholds
varied between 0.15 and 0.75. Error bars denote standard error of the means of the replicates
within a representative experiment (n = 3). .................................................................................. 78
Figure 3.7. H2O2 accumulation in epidermal peels of green and ripe fruit of the susceptible
blueberry cultivar Jersey and resistant cultivar Elliott inoculated with C. acutatum or water
(control) at 0, 12, 18, 24 and 48 hours post inoculation (n=5). H2O2 was detected by the Amplex®
Red Hydrogen Peroxide/Peroxidase Kit. Results from a representative experiment out of three
independent experiments are displayed ........................................................................................ 81
Figure 4.1. Anthracnose infection incidence in fruit of the susceptible cultivar Jersey pretreated
with methanol-soluble fractions from ‘Jersey’ and ‘Elliott’ followed by inoculation with
Colletotrichum acutatum. Bars denote the standard error of the mean (n = 5). From left to right:
Negative control = uninoculated fruit with no extract applied, Positive control = inoculated fruit
with no extract applied, J.M.S. = ‘Jersey’ methanol-soluble fraction, and E.M.S. = ‘Elliott’
methanol-soluble fraction. ............................................................................................................ 97
Figure 4.2. HPLC chromatograms of anthocyanins from the anthracnose-resistant blueberry
cultivar Elliott (A) and susceptible cultivar Jersey (B) using 10-μl injections at λ = 520 nm... ... 99
Figure 4.3. HPLC chromatograms of non-anthocyanin flavonoids from the anthracnose-resistant
blueberry cultivar Elliott (A) and susceptible cultivar Jersey (B) using 10-μl injections at λ 255 nm.
Arrows denote compounds selected for further analysis. ........................................................... 102
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Figure 4.4. MS/MS and UV/Vis spectra of two flavonoid compounds unique to the anthracnoseresistant cultivar Elliott. (A) Daughter ions detected when selecting for the parent ion of quercetin
3-O-rhamnoside (compound 08F in Table 4.2). (B) UV/Vis spectrum of quercetin 3-O-rhamnoside
(compound 08F in Table 4.2). (C) Daughter ions detected when selecting for the parent ion of
dimethylmyricetin methyl pentoside (compound 09F in Table 4.2). (D) UV/Vis spectrum of
dimethylmyricetin methyl pentoside (compound 09F in Table 4.2)........................................... 105
Figure 4.5. Change in the optical density (λ 590 nm) of liquid medium inoculated with conidia of
Colletotrichum acutatum over time in the presence of various fractions (50 μg per 100 μl of
culture) from ripe fruit of the anthracnose-resistant blueberry cultivar Elliott and susceptible
cultivar Jersey. (A) Anthocyanin-containing extracts and fractions from ‘Elliott ‘and ‘Jersey’ as
well as the standard cyanidin 3-O-glucoside. (B) Flavonol-containing extracts and fractions from
‘Elliott’ and ‘Jersey’ as well as the standards quercetin 3-O-glucoside and quercetin 3-Orhamnoside. The positive control denotes the fungus alone in the medium. Bars denote the
standard error of the mean (n = 3). Note , Postive control = methanol only, Cy-gluc = cyanidin 3glucoside, Q-gluc = quercetin-3-O-glucoside, Q-rham = quercetin3-O-rhamnoside, J.M.E. =
‘Jersey’ methanol extract, E.M.E. = ‘Elliott’ methanol extract, E.A.F. = ‘Elliott’ anthocyanin
fraction, J.A.F. = ‘Jersey’ anthocyanin fraction, E.N.A.F. = ‘Elliott’ non-anthocyanin flavonoid
fraction, and J.N.A.F = ‘Jersey’ non-anthocyanin flavonoid fraction. ....................................... 107
Figure 5.1. Signs and symptoms of fruit infection by Colletotrichum acutatum on two different
blueberry cultivars, Jersey (A to E), and Elliott (F to J) after inoculation with a conidial suspension
using different techniques, such as applying a 10-µL droplet into the calyx cup (A and F), spraying
the berries until runoff (B and G), injecting 50 µL into the interior of the fruit with a syringe
(needle still visible) (C and H), and applying a 50-µL droplet to the open surface of a cut fruit (D
and I). Fifty microliters of sterile deionized water served as a control in the cut fruit experiments
(E and J). All treatments were incubated for 10 days after inoculation, except the cut-fruit
treatments (3 days) ...................................................................................................................... 120
Figure 5.2. Conidium production on fruit of blueberry cultivars Jersey and Elliott after inoculation
with a Colletotrichum acutatum conidial suspension using different inoculation methods (applying
a 10-µL droplet into the calyx cup, spraying the berries until runoff, injecting 50 µL into the
interior of the fruit with a syringe, and applying a 50-µL droplet to the open surface of a cut fruit).
All treatments were incubated for 10 days after inoculation, except the cut-fruit treatment (3 days).
Bars denote the standard error of the mean (n = 5 with 10 fruits per replicate).. ....................... 121
Figure 5.3. Relationship between the concentration of an aqueous suspension of Colletotrichum
acutatum conidia and optical density at 590 nm. A) Conidia produced on PDA. B) Conidia from
cut fruit surfaces from a Draper x Jewel F1 population. C) Conidia produced on cut fruit surfaces
of selected blueberry cultivars .................................................................................................... 125
Figure 5.4. Mycelial growth of Colletotrichum acutatum on minimal medium with different sugar
(50/50 D-glucose/D-fructose) concentrations: 8% (w/v) (A), 12% (w/v) (B), and 16% (w/v) (C)
after 7 days. D) The effect of sugar content in minimal medium on mycelial growth of C. acutatum
after 7 days using D-glucose, D-fructose and a 50/50 D-glucose/D-fructose mixture. E) The effect
xiv

of sugar content in minimal medium on mycelial growth of C. acutatum after 7 days using a 50/50
D-glucose/D-fructose mixture in the physiological range for blueberries. In D and E, error bars
denote standard error of the mean ............................................................................................... 132
Figure 5.5. A) The effect of initial pH in potato dextrose broth and minimal medium on the
amount of mycelial growth (dry weight) of Colletotrichum acutatum after 7 days in 3ml cultures.
Initial pH is indicated here since the pH changed as cultures grew. Error bars denote standard error
of the mean. B) The effect of initial pH and sugar content (using a 50/50 D-glucose/D-fructose
mixture) on mycelial growth (dry weight) of C. acutatum after 7 days. Different degrees of shading
indicate different mycelial weights, with darker shades indicating less growth......................... 133
Figure 6.1. The proportion of all blueberry fruit infected over time by Colletotrichum acutatum in
2010 and 2011 at 5, 8 and 12 days post incubation averaged over all of the cross families and
cultivars... .................................................................................................................................... 148
Figure 6.2. Distribution of anthracnose fruit rot resistance (expressed as area under the disease
progress curves (AUDPC)) in a susceptible x moderate cross (‘Nelson’ x ‘Ozarkblue’) and a
resistant x resistant cross (‘Bluegold’ x ‘Elliott’) in 2010 and 2011. A) ‘Nelson’ x ‘Ozarkblue’ in
2010, B) ‘Nelson’ x ‘Ozarkblue’ in 2011, C) ‘Bluegold’ x ‘Elliott’ in 2010, and D) ‘Bluegold’ x
‘Elliott’ in 2011. Discrete levels were defined every 50 AUDPC values.. ................................. 150
Figure 6.3. Correlation between the average anthracnose fruit rot incidence on various blueberry
cultivars and cross families expressed as area under the disease progress curves (AUDPC) against
actual and predicted proportion decayed values from Polashock et al. (2005) in (A) 2010 and (B)
2011. Abbreviations for parent cultivars: BG = Bluegold; BR = Brigitta; DU = Duke; E = Elliott;
LE = Legacy; N = Nelson;O = Ozarkblue. ................................................................................. 152
Figure 6.4. Correlation between the average anthracnose fruit rot incidence on various blueberry
cultivars and cross families expressed as area under the disease progress curves (AUDPC) against
actual and predicted sporulation capacity values from Miles et al. (2011b) in (A) 2010 and (B)
2011. Abbreviations for parent cultivars: BR = Brigitta; DU = Duke; DR = Draper; E = Elliott; LI
= Liberty; N = Nelson.. ............................................................................................................... 153
Figure A.1. The effect of temperature and wetness duration on the development of melanized
appressoria of Colletotrichum acutatum on parafilm slides. Discrete transitions indicate levels of
melanized appressoria every 20% starting at zero ...................................................................... 162
Figure A.2. The effect of temperature and wetness duration on the infection level of immature (A)
and mature (B) blueberry fruits by Colletotrichum acutatum. Discrete transitions indicate levels of
infected fruit every 20% starting at zero.. ................................................................................... 163
Figure A.3. The effect of wetness duration and interrupted wetness periods on the development of
melanized appressoria of Colletotrichum acutatum on parafilm slides. Values are calculated as the
melanized appressoria (%) relative to the no interruption control. Discrete transitions indicate
levels of melanized appressoria every 20% starting at zero. ...................................................... 164

xv

Figure A.4. The effect of wetness duration and interrupted wetness periods on the infection level
of immature (A) and mature (B) blueberry fruits by Colletotrichum acutatum. Values are
calculated as the infected fruit (%) relative to the no interruption control. Discrete transitions
indicate levels of infected fruit every 20% starting at zero.. ...................................................... 165
Figure A.5. The effect of temperature and relative humidity on the development of melanized
appressoria (%) of Colletotrichum acutatum (A), and the infection level of mature blueberry fruits
(B) by C. acutatum. Discrete transitions indicate levels of melanized appressoria every 20%
starting at zero and in mature fruit levels are indicated every 20% starting at zero. .................. 166
Figure B.1. Optimization of cDNA amplification using various PCR amplification cycles (15-30),
for C. acutatum-inoculated fruit of blueberry cultivars Jersey (lanes 2-7) and Elliott (lanes 9-14) (5
µL loaded per well). Lanes 1 and 8, 1-kb+ DNA ladder; lanes 2 and 9, 15 cycles; lanes 3 and 10,
18 cycles; lanes 4 and 11, 21 cycles; lanes 5 and 12, 24 cycles; lanes 6 and 13, 27 cycles; lanes 7
and 14, 30 cycles. Twenty one cycles was found to be optimal for both libraries and those products
were used for digestion and adapter ligation... ........................................................................... 169
Figure B.2. Restriction enzyme digestion of pooled cDNA libraries of the blueberry cultivars
Jersey and Elliott after inoculation with C. acutatum for the generation of shorter, blunt-end
fragments (necessary for adaptor ligation and subtraction). Lanes 1 and 4, 1-kb+ DNA ladder;
lanes 2 and 5, samples from ‘Jersey’ and ‘Elliott’ before digestion, respectively; lanes 3 and 6,
samples from ‘Jersey’ and ‘Elliott’ after digestion, respectively.. ............................................. 170
Figure B.3. Primary (lanes 2-5) and secondary (lanes 7-10) PCR products of pooled cDNA
libraries in subtracted and nonsubtracted samples of blueberry cultivars Elliott and Jersey after
inoculation with C. acutatum. These products were used for the construction of DIG probes and for
cloning of the subtractive libraries for differential screening. Lanes 1 and 6, 1-kb+ DNA ladder;
lanes 2 and 3, ‘Elliott’ and ‘Jersey’ subtracted primary PCR products, respectively; lanes 4 and 5,
‘Elliott’ and ‘Jersey’ nonsubtracted primary PCR products, respectively; lanes 7 and 8, ‘Elliott’
and ‘Jersey’ subtracted secondary PCR products, respectively; lanes 9 and 10, ‘Elliott’ and ‘Jersey’
nonsubtracted secondary PCR products, respectively.. .............................................................. 171
Figure C.1. TLC plate assay showing inhibition of microconidiation of Colletotrichum acutatum
and UV/Vis spectra of methanolic extracts from ripe fruit of the anthracnose-resistant blueberry
cultivar Elliott and susceptible cultivar Jersey. (A) Cellulose TLC plate after inoculation with
conidia of C. acutatum and stained with iodine crystals. (B) UV/Vis spectra of the boxed area in
the TLC plate. (Note: 1 = methanolic extract of uninoculated ‘Elliott’ fruit, 2 = methanolic extract
of ‘Elliott’ fruit 4 days after inoculation, 3 methanolic extract of uninoculated ‘Jersey’ fruit, and 4
= methanolic extract of ‘Jersey’ fruit 4 days after inoculation.. ................................................. 173
Figure C.2. Schematic presentation of the extraction procedures for biochemical analysis of
blueberry fruit using fresh fruit material and the solvents water, methanol, and ethyl acetate.. 174
Figure C.3. Schematic presentation of the extraction procedures for biochemical analysis of
blueberry fruit using lyophilized fruit material and the solvents methanol, and ethyl acetate. .. 175

xvi

Figure E.1. Relationship between the concentration of an aqueous suspension of Colletotrichum
acutatum from anthracnose resistance cut fruit screenings (590 nm) (Table E.1 and Table E.2
values) of detached blueberry fruits from several daughters of a Draper x Jewel cross ............ 183
Figure F.1. External differences in ethylene concentration in ‘Elliott’ and ‘Jersey’ fruits after
inoculation of Colletotrichum acutatum or sterile deionized water. Fruits were spray-inoculated
6
with 10 conidia/ml, incubated at 100% relative humidity for 48 hours at 22-24°C, placed in quart
sized mason jars, ethylene concentration was measured using then was measured 2 hours later
using previously described methods (1). Error bars denote standard error of the mean. ........... 184
Figure F.2. Internal differences in ethylene concentration within ‘Elliott’ and ‘Jersey’ fruits. Fruits
were immersed in a saturated solution of KCl, a vaccum was applied and headspace analysis was
used to measure the concentration of ethylene in accordance with previous methods (1, 2). Error
bars denote standard error of the mean... .................................................................................... 185
Figure F.3. Effect of ethylene on anthracnose symptom development in ‘Elliott’ and ‘Jersey’
fruits. A) Amount of conidia produced per berry in ‘Elliott’ and ‘Jersey’ fruits in each chamber
(ethylene or air). B) Levels of ethylene in both chambers throughout a 14 day period. Two 30gallon tanks were used to simulate an environment with 1ppm ethylene or air. Fruits were sprayinoculated with 106 conidia/ml, incubated at 100% relative humidity for 14 days at 22-24°C ,
ethylene concentration was measured in accordance with previous methods (1). Closed circles
represent the ethylene chamber, open circles represent the air chamber. Error bars denote standard
error of the mean.. ....................................................................................................................... 186

xvii

CHAPTER I: LITERATURE REVIEW

INTRODUCTION
Colletotrichum species are ubiquitous fungi and have been recovered from almost every
plant species. Several members of the genus commonly cause anthracnose fruit rot of fleshy
fruits, including C. acutatum J. H. Simmonds, C. coccodes (Wallr.) S. Hughes , and C.
gloeosporioides (Penz.) Penz. & Sacc. (Table 1.1, Figure 1.1). In this case, tomatoes and peppers
are included here also as they are fruits in a botanical sense.
The disease cycle for Colletotrichum spp. that infect fruit varies by host and climate. In
temperate regions, the fungus overwinters in infected host tissues. During rainy periods in the
spring, conidia are released that infect green fruit. The infections remain latent until the fruit
ripens (200). The fungus can also survive and reproduce without causing symptoms during this
stage (112). The latent phase of the infection often causes problems in estimating whether the
disease is present and when the infection actually takes place.
When fruits ripen, the initial symptoms are softening and shriveling on the fruit, followed
by the appearance of acervuli bursting through the fruit surface. Secondary infections will also
occur on nearby ripe fruit via splash dispersal of conidia produced on the surface of infected
fruit.
The infection process typically starts when a conidium lands on the host, attaches itself,
and begins to germinate. Germination gives rise to a germ tube (Figure 1.2B), followed by the
formation of an appressorium (Figure 1.2C), which will eventually become melanized (Figure
1.2D) and develops an internal light spot that corresponds to the penetration pore (54). The
melanin inside the appressorium then generates a hypotonic environment and increased turgor
pressure allows the fungus to directly penetrate the host epidermis.
1

Table 1.1. Colletotrichum species that cause diseases on fleshy fruits.
Colletotrichum spp.
C. acutatum J. H. Simmonds

Host common name (scientific name)
Apple (Malus × domestica Borkh.)
Blueberry (Vaccinium corymbosum L.)
Cherry (Prunus spp.)
Citrus (Citrus spp.)
Cranberry (Vaccinium macrocarpon Ait.)
Grape (Vitis spp.)
Guava (Psidium guajava L.)
Mango (Mangifera indica L.)
Olive (Olea europaea L.)
Peach and nectarine (Prunus persica L.)
Pear (Pyrus communis L.)
Pepper (Capsicum spp.)
Strawberry (Fragaria × ananassa Duch.)
Tomato (Lycopersicon esculentum Mill.)

C. ananas Garud

Pineapple (Ananas comosus L. Merr.)

C. capsici (Syd.) E. J. Butler & Bisby

Pepper (Capsicum spp.)

C. coccodes (Wallr.) S. J. Hughes

Pepper (Capsicum spp.)
Tomato (Lycopersicon esculentum Mill.)

C. fragariae A. N. Brooks

Strawberry (Fragaria × ananassa Duch.)

C. gloeosporioides (Penz.) Penz. & Sacc.

Apple (Malus × domestica Borkh.)
Avocado (Persea Americana Mill.)
Blueberry (Vaccinium corymbosum L.)
Caneberry (Rubus spp.)
Cherry (Prunus spp.)
Citrus (Citrus spp.)
Coffee (Coffea spp.)
Cranberry (Vaccinium macrocarpon Ait.)
Guava (Psidium guajava L.)
Grape (Vitis spp.)
Mango (Mangifera indica L.)
Olive (Olea europaea L.)
Papaya (Carica papaya L.)
Passion fruit (Passiflora edulis Sims.)
Peach and nectarine (Prunus persica L.)
Pear (Pyrus communis L.)
Pepper (Capsicum spp.)
Pineapple (Ananas comosus L. Merr.)
Strawberry (Fragaria × ananassa Duch.)
Tomato (Lycopersicon esculentum Mill.)
2

Table 1.1. (cont’d.)
C. kahawae Waller & Bridge

Coffee (Coffea spp.)

C. musae (Berk. & M. A. Curtis) Arx

Banana and plantain (Musa spp.)

C. orbiculare (Berk. & Mont.) Arx

Cucurbits (Citrullus spp., Cucumis spp.,
Cucurbita spp., and others)
Information from the USDA Systematic Mycology and Microbiology Laboratory Fungus-Host
Distribution Database (http://nt.ars-grin.gov/fungaldatabases/fungushost/fungushost.cfm)

3

A

C

B

E

D

F

G

H

Figure 1.1.

4

Figure 1.1 (cont’d.). Representative symptoms on ripe fruit of infection by Colletotrichum spp.
A) apple (Malus domestica Borkh. - image 1233007) B) blueberry (Vaccinium corymbosum L.),
courtesy A. Schilder, C) lychee (Litchi chinensis Sonn. – image 5403527), D) cantaloupe
(Cucumis melo L. – image 5405331), E) peach (Prunus persica L. Batsch – image 5407867), F)
sweet pepper (Capsicum annuum L. – image 5435606), G) tomato (Lycopersicon esculentum
Mill. – image 1236163), and H) strawberry (Fragaria × ananassa Duchesne), courtesy A.
Schilder. Numbered images courtesy of IPM images (http://www.ipmimages.org/); photographer
information included, Clemson University - USDA Cooperative Extension Slide Series (A and
G), Yuan-Min Shen, Taichung District Agricultural Research and Extension Station (C and F),
and Paul Bachi, University of Kentucky Research and Education Center (D and E). For
interpretation of the references to color in this and all other figures, the reader is referred to the
electronic version of this thesis.

5

Following direct penetration of host tissues, Colletotrichum species generally have one of
two different host colonization strategies, depending on the tissue or host being colonized:
intracellular hemibiotrophy and subcuticular intramural necrotrophy (139). Intracellular
hemibiotrophy is the direct invasion of the initial host cell by a primary infection vesicle,
followed by the proliferation of thick primary hyphae and thin secondary hyphae; this strategy is
common in many non-fruit hosts of Colletotrichum spp., including bean (137), pea (138),
sorghum (199), and tobacco (173). In subcuticular intramural necrotrophy, Colletotrichum spp.
will invade superficially under the cuticle, generally producing thinner necrotrophic hyphae
sooner, which will not invade the host cell intracellularly. This type of strategy is known to
exclusively occur in infection by C. capsici (Schwein.) Andrus & W.D. Moore on the leaves of
cowpea (151) and cotton (162). Following colonization, acervuli will begin to develop and
eventually burst through the host epidermis (Figure 1.3).
In a number of pathosystems, correlations have been found between the presence of
pectinolytic enzymes, disease symptoms, and pathogen virulence (61). In the C. lindemuthianum
(Sacc. & Magn.) Scribn.-bean pathosystem, the pathogen uses a number of pectin-degrading
enzymes such as pectin lyase (a.k.a. pectin methyltranseliminase). It is the only known pectinase
capable of degrading highly esterified pectins into small molecules via β-elimination without
producing toxic methanol by enzymatically cleaving 1-4-alpha-D-galacturonan methyl esters
(205). Pectin lyases are usually characterized as being alkaline or acidic. In most Colletotrichumplant interactions following pectin lyase secretion, a shift to a more alkaline pH is usually
detected in host tissues (204). Other pectin-degrading enzymes that have been investigated in the
C. lindemuthianum-bean pathosystem include endopolygalacturonase (endoPG) which

6

A

B

C

D

Figure 1.2. Conidium germination of Colletotrichum acutatum on parafilm-covered glass slides.
A) Ungerminated conidia B) Germinated conidium with germ tube, C) Unmelanized
appressorium and D) Melanized appressoria with internal light spots (ILS) (Bars = 10 µm).

A

B

Figure 1.3. A) A close-up of the skin of an infected blueberry reveals small open blisters
(acervuli) in which the spores are produced.B) Acervulus bursting through the fruit epidermis
(electron micrograph). Conidia can be seen in the matrix (Bar = 50 µm).

7

enzymatically hydrolyzes 1,4-alpha-D-galactosiduronic linkages, and the resulting
oligogalacturonides have been shown to elicit the production of pathogensis-related (PR) related
proteins (32, 110).
A variety of defense responses against infection by Colletotrichum species are employed
by plant hosts during the infection process, including host cell wall modifications, a
hypersensitive response and the production of phytoalexins, pathogenesis-related proteins, and
reactive oxygen species. Cell wall modifications and the hypersensitive response constitute the
initial physical line of defense against Colletotrichum spp. and make it difficult for the pathogen
to colonize plant cells. The fortification of the plant cell walls, reduces the available nutrients
and their production can be utilized as a signal to neighboring plant cells (81, 135, 186). A
hypersensitive response in tangerines has been associated with a reduced risk of anthracnose
infection (24). These researchers observed host cell death and a collapse of the cytoplasm against
the cell wall distal from the area of fungal penetration.
In some cases, host antimicrobial compounds (phytoalexins) against Colletotrichum spp.
are induced upon inoculation and are antimicrobial by preventing pathogen growth. Their
chemical structure varies significantly such as 3-deoxyanthocyanidin in sorghum (Sorghum
bicolor (L.) Moench) (117), methylhipariochromene A in mistflower (Eupatorium riparium
Regel) (77) and lα- and lβ-hydroxydihydrocomin aglycones in Alibertia macrophylla K. Schum
(77) . Peroxidases (82), β-1, 3 glucanases (92, 110), hydroxyproline-rich glycoproteins (186)
and chitinases (45) are also thought to play a role in the host resistance response because a
number of Colletotrichum-resistant cultivars boast increased levels of these compounds. The
goal of this review is to discuss blueberry production in Michigan, information about
anthracnose fruit rot of blueberries,

8

the environmental requirements for infection, different infection strategies, passive and active
host defenses and the heritability of resistance in Colletotrichum fruit pathosystems.

BLUEBERRY PRODUCTION IN MICHIGAN
The United States is the largest blueberry producing country in the world, with a
production of 203,663 metric tons per year. Michigan is the leading state producing blueberries
in the US, with 44,906 metric tons of fruit representing 22% of US production and worth $102
million U.S. dollars in 2009 (106). Maine is the second largest producer (20% of total
production), however, this consists predominantly of wild lowbush blueberries (V. angustifolium
Aiton), unlike other states which raise cultivated highbush (V. corymbosum L.) or rabbiteye (V.
ashei J. M. Reade) blueberries. In Michigan, the majority of blueberry fields (75%) are irrigated
and the most common methods are overhead sprinkler (57% of total irrigated hectarage) and drip
(trickle) irrigation (21% of total irrigated hectarage) (105). In 2007, there were 7,810 harvested
blueberry hectares in Michigan and planted primarily (78%) to three cultivars Bluecrop, Elliott
and Jersey (105).
Demand for blueberries and other fruit crops continues to rise as the health benefits are
becoming increasingly apparent due to compounds with antioxidant (96, 116, 147) and antiinflammatory properties (94) that can reduce cardiovascular and neurodegenerative diseases in
humans (174). In fact, anthocyanins, the predominant class of flavonoids in blueberries, have
been shown to aid in obesity prevention (91), cardiovascular health (48), act as antiinflammatory compounds (196) and have anti-cancer effects (18, 172, 179) . Another common
flavonoid present in highbush blueberries are flavonol glycosides such as quercetin and
myricetin are also common in highbush blueberries (Figure 1.4.)

9

A

B

Figure 1.4. Chemical structures of two common flavonoids present in fruit of highbush
blueberries. A) Anthocyanin backbone which is typically glycosylated at the R3 position. B)
Flavonol backbone.

10

ANTHRACNOSE FRUIT ROT OF BLUEBERRY
Anthracnose fruit rot or ripe rot is the most common and widespread fruit disease of
blueberries in Michigan and the United States. In northern growing regions, this disease is
typically caused by Colletotrichum acutatum, whereas, C. gloeosporioides may be more
common in the southern regions of the United States (40). Anthracnose fruit rot can lead to
substantial fruit losses, including reduced yield, shelf life and fruit quality. Pre-harvest crop
losses may reach 10-20%, and in severe cases, post-harvest losses up to 100% (128). In addition,
high levels of anthracnose fruit rot may contribute to unacceptable mold counts in frozen
processed fruit. Warm, wet seasons are particularly conducive to disease development (169).

Symptoms
Infected immature green berries are symptomless. Fruit rot symptoms usually do not
become apparent until the fruit ripens, hence the name “ripe rot” (128). Initial symptoms are
softening and shriveling of the fruit, particularly on the “king” berry which is the first to ripen,
followed by the appearance of small orange dots (spore masses) on the surface (Figure 1.1A).
Spores (conidia) are produced in fruiting structures (acervuli), which break through the fruit
epidermis (Figure 1.1B). Depending on relative humidity, spore masses may look wet or dry.
Infected berries eventually shrivel up and fall off the bush. Even berries that look perfectly
healthy on the bush can rot soon after harvest. However, refrigeration delays rot development.
Colletotrichum acutatum may also cause blighting of blossoms and twigs but these
symptoms are difficult to distinguish from Phomopsis twig blight or Botrytis blossom blight

11

without doing fungal isolations from the infected tissues. Cane cankers, and occasionally leaf
spots caused by C. acutatum, have been observed during particularly rainy seasons (123).

Disease cycle
In spring and summer, conidia are produced on dead twigs, spent fruit trusses and
dormant buds (49) which are dispersed by rain splash (85, 146). Although fruit infections are
only obvious at maturity, fruit may be infected anytime between flowering and harvest.
Reportedly, the fungus requires at least 12 hours of continuous wetness to penetrate the fruit
surface and initiate an infection. The optimum temperature for fruit infection is 25ºC (74) but
infections can take place at temperatures as low as 10ºC (193). After the fungus enters the
developing fruit using a penetration peg produced from a melanized appressorium, it remains
quiescent until the berry starts to ripen (Figure 1.2). At this point, the fungus begins to grow and
produce enzymes (such as pectinases) that destroy host tissue, resulting in collapse and
shriveling of the fruit (46). Within days, spore masses develop and eventually cover most of the
berry. The time from infection of ripe fruit to the first appearance of symptoms is about 4 days
(201). Secondary infections occur by direct contact or when spores are splashed from infected to
nearby healthy berries. Contaminated surfaces of harvesting or sorting equipment can also be a
source of infection. The fungus survives the winter in old fruit trusses and live buds that are
infected in late summer or early fall (Figure 1.5) (49).

Management
Anthracnose is very common in blueberries, except in dry regions (146). Since fruit rot
symptoms do not become apparent until close to harvest, preventive control strategies are
12

LATE
SPRING

Latent infections of
developing fruit between
flowering and harvest

Rain splash
dispersal of
conidia

EARLY
SPRING

EARLY
SUMMER

Sporulation on infected
bud scales and twigs
Rain splash
dispersal of
conidia

Overwintering
infections in
buds and
former fruit
trusses
Conidia produced in an
acervulus

Spore germination
and appressorium
formation
MID-LATE
SUMMER

Ripe rot of infected berries

WINTER

Figure 1.5. Disease cycle of anthracnose fruit rot caused by Colletotrichum acutatum on
blueberries. (Illustration by Jennifer Pagan.).

13

important, especially in fields with a history of the disease. Timely harvesting, processing, and
cooling reduce pre- and post-harvest losses (84). Pruning out dead twigs and old fruit trusses can
reduce the incidence of fruit infection. However, the high cost associated with this type of
detailed pruning may make it uneconomical. Another option is to plant resistant cultivars or less
susceptible cultivars (150). A preventive fungicide spray program is most effective when focused
on the period from pink bud to harvest (169).

ENVIRONMENTAL REQUIREMENTS FOR INFECTION
Anthracnose fruit rot in many crops is often difficult to control and disease prediction
models have been developed to predict melanized appressorium development and infection.
Many disease prediction models use regression equations, such as those based on polynomials
(65, 170), logistic equations (26, 170) and complex three-dimensional response surfaces (21, 29,
207). Important environmental variables to consider include temperature, wetness duration,
interrupted wetness periods and relative humidity.
Temperature and wetness duration have been shown to have a direct effect on the
development of melanized appressoria and fruit infection. In the C. coccodes-tomato
pathosystem; melanized appressoria can form on foliage and fruit as early as 6 hours after
incubation at optimal temperatures (16°C to 28°C) (27, 167). In strawberries, C. acutatum
infection was investigated on both immature and mature fruit (206). In that study, disease
incidence was generally higher in mature fruit and always increased with longer wetness
durations (up to 48 hours) except at extreme temperatures (≤ 10°C and ≥ 30°C). Wilson et al.
(1990) used a regression model with the logit of disease incidence of C. acutatum as the
dependent variable which accurately described infection incidence as a function of wetness
14

duration and temperature. Temperature has also been identified as having a strong effect on the
sporulation of C. acutatum on strawberry fruit (optimum temperatures of 22°C to 26°C) (104).
Researchers have also looked at the role of interruptions in the wetness duration and the
role of relative humidity on the development of melanized appressoria and infection in
Colletotrichum pathosystems. In Stylosanthes scabra Vogel, infection by C. gloeosporioides was
relatively unaffected by brief interruptions (2 to 4 hours) in wetness periods when they occurred
after the initial 12 hours of wetness and were followed by another 24 hours of continuous
wetness (33). However, they did not investigate longer periods of dryness or at different stages
of the infection process. Relative humidity has also been investigated in relationship to the
development of melanized appressoria of C. gloeosporioides on 1-month-old mango leaves (56).
These researchers found that conidia were able to germinate and form appressoria at relative
humidity values between 95 and 100% even though free water was only visible at 100%.
In blueberries, a previous study showed that temperatures of ≤ 10°C and ≥ 30°C
inhibited mycelial growth of C. gloeosporioides on potato dextrose agar. Based on in vitro spore
germination studies, the authors suggested that 12 hours of continuous wetness at 15-27°C are
required for conidial infection (85). In another study in British Columbia, the optimum
temperature for anthracnose fruit rot infection was 20°C but infection was possible at
temperatures between 7°C and 30°C (192). These researchers then conducted further studies on
environmental requirements by placing potted plants in a commercial field at weekly intervals
with weather monitoring. Fruit was allowed to ripen naturally and evaluated for anthracnose
infection. When comparisons were made between peak infection periods and weather data,

15

regression values were not significant but infection occurred after a minimum of 10 hours of
wetness at 11°C, 15°C, and 14°C in 2001, 2002, and 2003, respectively (193).

THE INFECTION PROCESS
Host tissue and its relationship to infection strategy
Multiple studies have investigated the infection strategies of Colletotrichum species on a
variety of fruits, including almond (53), avocado (41), blueberry (201), olive (75), and
strawberry (43). As previously stated, Colletotrichum species generally have two types of
colonization strategies, intercellular hemibiotrophy and subcuticular intramural necrotrophy.
Intracellular hemibiotrophy requires a close cytoplasmic interaction between the host and the
pathogen. Pathogens with this strategy are considered specialists, while subcuticular intramural
necrotrophy does not require this closeness, therefore, these pathogens could be considered
generalists (146). C. acutatum is known to use both infection strategies on almond (53),
blueberries (201), olive (75) and strawberry (43). In blueberries, the type of infection strategy
was associated with a susceptible or a resistant interaction (201). However, while both these
strategies were observed in olives, it was not related to host plant resistance (75). Different
infection strategies in strawberry appear to be associated with tissue type: intercellular
hemibiotrophy occurs on leaves (9) and subcuticular intramural necrotrophy occurs on petioles,
stolons and leaves (9, 43).
In blueberries, a lower rate of conidium germination and appressorium formation was
observed on a resistant cultivar compared to a susceptible cultivar (201). A possible reason for
this phenomenon could be differences in the structure or composition of the waxy cuticle in
susceptible fruit that stimulates conidium germination and appressorium formation. In avocados,
16

cuticular wax has been shown to trigger conidium germination and appressorium formation of C.
gloeosporioides. However, waxes from non-host plants strongly inhibited appressorium
formation (148).

pH modulation by the pathogen
Studies have shown that ammonia secretion by Colletotrichum spp. increases the pH of
host tissues, and tissues that are originally unsuitable for growth become inhabitable. The
modulation of fruit pH is important for pathogenicity on almond (55), apple (157), avocado (157)
and tomato (3, 157). Additional research suggests that tissue alkalization and the presence of
nitrogen are important factors for C. gloeosporioides attack and development in a fruit host and
these factors appear to be independent (59).
The process of pH modulation involves ammonia accumulation at the site of infection,
which is influenced by the initial environmental pH (3). In controlled experiments using a lowpH buffer at the infection site, the authors have observed high levels of ammonia secretion and
increased virulence of C. coccodes as compared to similar treatments using a neutral-pH buffer.
Furthermore, researchers have identified a set of genes involved in ammonia accumulation and
regulation by C. gloeosporioides. These genes include a NAD+-specific glutamate
dehydrogenase (GDH2) and the ammonia exporter AMET. Genes involved in ammonia uptake
(MEP) import glutamate (GLT) and glutamine synthase (GS1). The expression of these genes
was dependent on ambient pH and involved in the metabolism and catabolism of ammonia (129).
In almonds, alkalinization of host tissue has been visualized using pH-indicating fluorescent dyes
and occurred between 24 and 72 hours post inoculation (55).

17

Cell wall-degrading enzymes
In beans, necrotrophy was associated with enhanced excretion of plant cell walldegrading enzymes such as endo-polygalacturonases by C. lindemuthianum (204, 205). Pectin
lyase activity correlates well with the onset of necrotrophy and the subsequent development of
lesions. Pectin lyases have been identified as the main pathogenicity factor in a number of
Colletotrichum species including C. acutatum (214), C. coccodes (15) and C. gloeosporioides
(19, 198). As avocado fruits mature, the pectin lyase activity of C. gloeosporioides increases
(159). This increase has been linked to the increase in ambient pH associated with fruit ripening
(209) and a slow decrease in the flavonoid epicatechin which acts as an inhibitor of pectin lyase
(159). Laccases (p-diphenol:dioxygen oxido-reductases) produced by C. gloeosporioides have
also been shown to degrade this inhibitor and increase pathogenicity on avocado fruits (79).

PASSIVE HOST DEFENSES
Fruit physiological factors
The infection process of Colletotrichum spp. on fruits has been studied in a number of
plant pathosystems and in general, as fruits start to ripen they become increasingly susceptible to
infection (36, 131, 159, 206). During fruit ripening, many physiological changes occur, such as a
reduction in fruit firmness, changes in pH and cell wall composition and an increase in soluble
sugars and secondary metabolites, such as anthocyanins (20, 164). In avocado, several factors
have been associated with increased fruit susceptibility to infection by Colletotrichum
gloeosporioides as fruit ripens, including an increase in fruit pH (159), a decrease in preformed
antimicrobial compounds (155) and pathogenicity factor inhibitors, such as epicatechin (79).

18

Soluble sugars may also play a role in defense responses during ripening. Guava cultivars
that contained high levels of soluble sugars and ascorbic acid also were the most resistant to
Glomerella cingulata (Stoneman) Spauld. & H. Schrenk (176). In grapes, the accumulation of
antifungal proteins and sugars during fruit ripening is an important defense mechanism against
the fungal pathogens Botrytis cinerea Pers.:Fr. and Guignardia bidwellii (Ellis) Viala & Ravaz
(165, 185).
Antimicrobial fruit volatiles have been investigated in relationship to anthracnose
resistance. In strawberries, the effects of aldehydes, alcohols and esters on mycelial growth were
investigated and (E)-Hex-2-enal was identified as the most biologically active. This compound
altered the structure of the conidial cell wall and plasma membrane, causing disorganization and
lysis of organelles, eventually, cell death (8). In blueberries, many of these compounds were also
identified but the quantity of the volatile compounds (especially (E)-Hex-2-enal) was not
correlated with anthracnose fruit rot resistance in the various blueberry cultivars (149, 150).
The role of plant hormones such as ethylene also has been investigated in relationship to
anthracnose resistance. In tobacco leaves, ethylene production increased between 24 and 48
hours after infection of C. destructivum O'Gara (34). In bananas, it has been shown that rot
develops both in ethylene-inhibited and ripe banana fruits. Additionally, the researchers also
showed that ethylene is not directly involved in the host–pathogen relationship but plays a role in
infection in storage by ripening fruits prematurely (35, 36).

Pre-formed antimicrobial compounds
Several pre-formed compounds have been identified in resistant hosts in response to
Colletotrichum infection. Resistance to C. gloeosporioides in unripe avocado fruit is correlated

19

with the presence of fungitoxic concentrations of the preformed antifungal compound 1-acetoxy2-hydroxy-4-oxoheneicosa-12,15-diene in the pericarp of unripe fruits (155). A second
antifungal compound was subsequently purified from unripe avocado fruit and identified as 1acetoxy-2,4-dihydroxy-n-heptadeca-16-ene (158). When fruits ripen, the activity of the plantderived enzyme lipoxygenase increases causing the degradation of these preformed antifungal
compounds and fruit gradually becomes more susceptible to infection (159). Interestingly, the
lipoxygenase activity in avocado fruits is affected by the flavonoid epicatechin, which acts as a
natural inhibitor (154). In green fruit, the concentration of this compound gradually decreases
upon ripening until the fruit becomes completely susceptible. As previously mentioned, this
compound is also capable of inhibiting the activity of pectin lyase produced by fungal pathogens.
In unripe mangos, resistance to C. gloeosporioides has been associated with a mixture of
antifungal compounds consisting of 5-12-cis-heptadecenyl resorcinol and 5-pentadecenyl
resorcinol (58). These resorcinols occur at fungitoxic levels and they decrease to nontoxic levels
at the same time that decay appears. Additionally, the concentration of the resorcinols decreases
faster during ripening in disease-susceptible cultivars than in resistant cultivars. There is also
evidence that mature fruit of green mango varieties with higher concentrations of these
resorcinols are more resistant to C. gloeosporioides (86).
Host resistance in other Colletotrichum fruit pathosystems is less well studied. In
bananas, resistance has been attributed to dopamine and its oxidation products, which was
isolated from the peel of unripe banana in concentrations that inhibited C. musae (Berk. & M.A.
Curtis) Arx in vitro; it was therefore presumed to be a possible preformed antifungal compound.
However, the concentration of the compound was not synchronized with changes in decay
development (132). In blueberries, several studies have been carried out into the antifungal

20

properties of extracts from ripe blueberry fruit from wild highbush blueberry plants as they relate
to fruit decay and herbivore preference (37-39). These studies indicated that the main antifungal
compounds present in ripe blueberry fruit were water-soluble phenolics and acids. They also
proposed that resistance in ripe blueberries may be due to an interaction between simple phenolic
compounds and organic acids and not necessarily individual fungitoxic compounds.

ACTIVE HOST DEFENSES
Cell wall modifications
Cell wall modifications in relationship to host defenses of fruit have been observed in
various Colletotrichum-host plant interactions. Several studies have microscopically examined
the infection process on attached and detached fruit such as almonds (53), avocados (41),
blueberries (46, 201), citrus fruits (22), grapes (47), olives (75) and strawberries (43). In papaya
fruit, resistance has been attributed to callose deposited beneath the fungal penetration peg (178).
Resistant chili pepper fruit tissues showed evidence of structural modifications and increases in
the thickness of the cuticle layer compared with those of susceptible and noninoculated fruit
(101). Additionally, resistant cultivars had evidence of programmed cell death. Cell wall
modifications have a direct benefit to the host by preventing pathogen ingress, and there is
mounting evidence that cell wall fragments, particularly polysaccharides, can act as signaling
molecules in plant-pathogen interactions (194).

Induced antimicrobial compounds
Limited research is available on inducible antimicrobial compounds in Colletotrichumfruit pathosystems. However, in avocados, the activity of the pre-formed antimicrobial diene

21

compound can be modulated by inducing its production and/or preventing its decrease during
ripening (159). Research on C. sublineolum Henn. in sorghum has associated host plant
resistance with 3-deoxyanthocyanidins, including luteolinidin, apigeninidin, and a caffeic acid
ester of arabinosyl-5-O-apigeninidin (117). The researchers also found that these phytoalexins
were concentrated in cells immediately below the infection site and that the majority of the
antimicrobial compounds were highly localized (117). Other research on C. lindemuthianum on
bean (Phaseolus vulgaris) has linked the phytoalexin phaseollin (a prenylated pterocarpan ) to
resistance (12).

Defense-related proteins
A variety of defense mechanisms in other Colletotrichum-plant interactions have been
observed, including the production of host-derived cell wall-degrading enzymes including
chitinases and β-1-3-glucanases (31, 76, 110, 204). When the genes coding for these products are
overexpressed in plant tissue, the result is often increased disease resistance. For example, in
transgenic tobacco plants, the over expression of a chitinase gene led to broad resistance against
the fungal pathogen Rhizoctonia solani J.G. Kühn, and the bacterial pathogen Pseudomonas
syringae pv. tabaci (44). Upon infection of pepper fruits (Capsicum annuum L.), by C.
gloeosporioides, defense-related proteins like cytochrome P450 (141), defensin, thionin-like
protein (140), thaumatin-like protein (103) and esterase (107) are induced in incompatible
interactions.
Research has shown that C. acutatum infection is reduced significantly by a
polygalacturonase inhibitor protein extracted from the fruit (78). This type of host plant
resistance to fungi is found in apple (211), raspberry (93), and tomato (180) fruits. These

22

inhibitor proteins are predominantly expressed in the epidermal layers of the fruit and regulated
in response to infection and wounding (211).
A novel protein has been identified in pumpkin rinds is capable of inhibiting the growth
of C. coccodes in vitro at 10-20 μM. This protein was found to be nonphytotoxic and heat-stable,
and is proposed to be a possible natural antifungal agent (145).

Reactive oxygen species
Reactive oxygen species such as H2O2 are important in the resistance response in the C.
coccodes-tomato fruit interaction. Expression appears to occur around 24 to 48 hours after
inoculation, corresponding with melanized appressorium formation and attempted fungal
penetration (122). In strawberries, H2O2 generation plays a role in restricting fungal penetration
and inhibiting fungal invasion, leading to the hypersensitive response and triggering rapid
necrosis at infection sites, or activating defense-related genes (25).

GENETICS OF RESISTANCE
In recent years there have been many successes in breeding resistant crop varieties
against Colletotrichum species. In bean, resistance to anthracnose is primarily controlled by nine
major independent genes. Most of these genes are dominant and behave in a Mendelian fashion
and most likely exist in clusters (99).
In other Colletotrichum-host pathosystems, host plant resistance has been shown to be
controlled by a single gene, several genetic loci or a combination. In the C. acutatum-strawberry
pathosystem, a single dominant gene (Rca2) has been shown to be responsible for high-level
resistance, and minor resistance appeared to be quantitative and controlled by a number of minor
23

genes (50). In the C. acutatum-chili pepper pathosystem, resistance was mapped to a single
recessive gene at the mature green fruit stage and a single dominant gene at the ripe fruit stage
(119). In another species of pepper, resistance to C. capsici has been associated with a single
recessive gene (144). Mapping of host plant resistance in Phaseolus vulgaris L. has revealed
that two independent resistance genes within the same cluster confer resistance to different
strains of C. lindemuthianum (72). Furthermore, resistance to C. higginsianum Sacc. has been
shown to be localized to a single genetic locus RCH1 in the Arabidopsis ecotype Eil-0 (134).
Quantitative resistance to plant pathogens is typically controlled by multiple genetic loci
of small effect and is common in many Colletotrichum-host pathosystems (30, 50, 73, 89). While
this phenomenon has been documented in many plant pathosystems it is poorly understood. In
strawberries, different modes of inheritance of resistance to anthracnose have been suggested
based on pathogenicity groups of Colletotrichum (51). Resistance to pathogenicity group 1 is
quantitative. However, a single dominant gene, Rca2, controls resistance to pathogenicity group
2, although minor genes may also contribute to resistance in several cultivars (50).
In previous studies, anthracnose fruit rot resistance in blueberries was not correlated with
resistance to foliar infection (64) or the production of antimicrobial fruit volatiles (149).
However, resistance has been associated with different infection strategies by C. acutatum
(201).While there is information on relative anthracnose fruit rot resistance of many cultivars
based on our own studies and those of Polashock et al. (2005), the information about inheritance
of resistance in current breeding programs is largely unknown. Additionally, heritability of
disease resistance is of particular interest in cultivated highbush blueberries due to decreasing
heterozygosity because of increased intraspecific hybridization and the fact that the majority of
genetic diversity is derived from only four wild selections (83). The effect of limited genetic

24

diversity on disease resistance and whether that resistance is dominant, recessive or quantitative
is important in order to understand how resistance to C. acutatum is inherited.

CONCLUSIONS
The infection process of Colletotrichum spp. on fruit is complex and environmental
factors play a significant role. The infection strategies that Colletotrichum spp. utilize on various
hosts depends greatly on the tissue type and how specialized a pathogen is to a particular host.
Host resistance against Colletotrichum spp. involves multiple mechanisms. Fruit
physiological factors like sugar content and surface waxes can affect the growth of the fungus.
Preformed antimicrobial compounds like antifungal dienes, resorcinols or flavonoids may be
extremely important in unripe and ripe fruit resistance. Active defenses including cell wall
modifications, induced antimicrobial compounds, oxidative bursts and defense-related proteins
may also be important in the resistant response.
Further study of how resistance in inherited might lead to the development of new
anthracnose-resistant cultivars and allow us to better understand the basis of resistance on a
genetic level.
The objectives of this thesis are to: 1) investigate the minimum environmental factors
(temperature, humidity, and wetness) required for infection in blueberries.2) identify
differentially expressed genes of resistant blueberry fruits and the timing of their expression
following pathogen inoculation, 3) investigate the role of secondary metabolites in the resistant
interaction, 4) evaluate various inoculation techniques in several blueberry cultivars and identify
significant correlations between fruit characteristics and resistance, and 5) investigate how
resistance to blueberry anthracnose is inherited.

25

CHAPTER II: THE EFFECT OF ENVIRONMENTAL FACTORS ON INFECTION OF
BLUEBERRY FRUIT BY COLLETOTRICHUM ACUTATUM

ABSTRACT
Anthracnose fruit rot of blueberries caused by Colletotrichum acutatum is a serious
problem in humid blueberry-growing regions of North America. In order to develop a disease
prediction model, the environmental factors that affect mycelial growth, conidial germination
appressorium formation, and fruit infection by C. acutatum were investigated. Variables included
temperature, wetness duration, wetness interruption, and relative humidity. The optimal
temperature for mycelial growth was 26°C and little or no growth was observed at 5 and 35°C.
The development of melanized appressoria was studied on parafilm-covered glass slides and
infection was evaluated in immature and mature blueberry fruits. In all three assays, the optimal
temperature for infection was identified as 25°C and infections increased up to a wetness
duration of 48 hours. Three-dimensional Gaussian equations were used to assess to effect of
2

temperature and wetness duration on the development of melanized appressoria (R = 0.89) and
2

2

infection in immature (R = 0.86) and mature (R = 0.90) blueberry fruits. Interrupted wetness
periods of different durations were investigated and models were fitted to the response of
2

2

2

melanized appressoria (R = 0.95) and infection in immature (R = 0.91) and mature (R = 0.85)
blueberry fruits. Additionally, the development of melanized appressoria and fruit infection was
2

2

modeled in relationship to relative humidity (R = 0.99 and R = 0.97, respectively). Three
summarized equations were then developed that incorporate the aforementioned variables. Our

26

results lay the ground work for the development of a disease prediction model for anthracnose
fruit rot in blueberries.

INTRODUCTION
Blueberries are a popular fruit with nutraceutical benefits (48). The United States is the
leading producer of blueberries in the world and Michigan is the number one blueberryproducing state. Anthracnose fruit rot, caused by Colletotrichum acutatum J. H. Simmonds, is a
serious problem in most blueberry-growing regions, with reported annual yield losses as high as
10 to 20% (128). Various protectant and systemic fungicides are currently available that are
effective against this disease (169). Sprays are usually initiated at pink bud or bloom and
continued at 10 to 14 day intervals through fruit development and ripening (123). C. acutatum
overwinters in infected twigs, fruit trusses and buds from which conidia are rain-splash dispersed
during the growing season. Trapping of C. acutatum conidia in Michigan over several years has
shown one or two peaks in conidial dispersal, one around bloom and the other around fruit
ripening (202). Other research in Michigan has documented up to three peaks of C.
gloeosporioides spore dispersal: at bloom, green fruit, and ripe fruit with spores present
throughout the season (85). In that study, C. acutatum may have been misidentified as C.
gloeosporioides since subsequent sampling in Michigan blueberry fields has confirmed C.
acutatum to be the predominant pathogen (169). In addition to spore dispersal by rain, other
environmental variables such as temperature, wetness duration and relative humidity are thought
to play a role in the infection process.
In other pathosystems, temperature and wetness duration had a direct effect on the
development of melanized appressoria and fruit infection. In the C. coccodes-tomato

27

pathosystem, melanized appressoria can form on foliage and fruit in as early as 6 hours at
optimal temperatures (16°C to 28°C) (27, 167). In strawberries, C. acutatum infection was
investigated in both immature and mature fruit (206). In that study, disease incidence was
generally higher in mature fruit than in immature fruit and increased with longer wetness
durations (up to 48 hours) except at temperatures of ≤ 10°C and ≥ 30°C. The optimum
temperature for infection was between 25 and 30°C. Similar temperatures also had a comparable
effect on the sporulation of C. acutatum on strawberry fruit (104).
Researchers have also looked at interrupted wetting periods and the role of relative
humidity on the development of melanized appressoria and infection in Colletotrichum
pathosystems. In Stylosanthes scabra Vogel, infection by C. gloeosporioides was relatively
unaffected by brief interruptions (2 to 4 hours) in wetness when they occurred after the initial 12
hours and were followed by another 24 hours of continuous wetness (33). However, they did not
investigate longer periods of dryness or at different stages of the infection process. The effect of
relative humidity (RH) has also been investigated on the development of melanized appressoria
of C. gloeosporioides on 1-month old mango leaves; conidia were able to germinate and form
appressoria at RH values between 95 and 100% even though free water was only visible at 100%
(56).
In blueberries, a previous study indicated that temperatures of ≤ 5°C and ≥ 30°C
inhibited mycelial growth of C. gloeosporioides on potato dextrose agar (PDA). Based on in
vitro conidium germination studies, the authors suggested that 12 hours of continuous wetness at
15-27°C would be required for fruit infection (85). Another study indicated that the optimum
temperature for anthracnose fruit rot infection in British Columbia was 20°C but infection was
28

possible at temperatures between 7°C and 30°C (192). These researchers then conducted further
studies on temperature requirements by placing potted plants in a commercial field at weekly
intervals with weather monitoring. Fruit was allowed to ripen naturally and evaluated for
anthracnose infection. When comparisons were made between peak infection periods and
weather data, regression values were not significant but infection occurred after a minimum of
10 hours of wetness at 11°C, 15°C, and 14°C in 2001, 2002, and 2003, respectively (193). In all
the above cases, background infection by C. acutatum tended to be a complicating factor.
A successful blueberry disease management program depends on the grower’s ability to
recognize and anticipate problems. Knowing the critical periods when infection risk is highest
can help in optimizing fungicide timing and effectiveness. The purpose of this study was to
determine the role of temperature, wetness duration, interrupted wetness and relative humidity on
infection parameters for C. acutatum on blueberries under controlled conditions and use the
results to develop a disease prediction model.

MATERIALS AND METHODS
Fungal and plant material
A single-conidium isolate of C. acutatum from blueberry fruit collected in Grand
Junction, MI, USA in August 2006 (isolate #0001) was used for all experiments except the initial
temperature wetness duration experiment on immature fruit. For this initial experiment, a singleconidium isolate from an infected sporulating blueberry bud was used. Both isolates were stored
as previously described (125) and cultures were grown on potato dextrose agar (PDA) for a
period of 14 days, after which conidia were harvested, re-cultured on one-quarter-strength PDA
and allowed to microconidiate (produce conidia directly on conidia) for 3 to 4 days. For
29

inoculum production, sporulating cultures were flooded with 3 mL of sterile deionized water
(SDW), and microconidia were dislodged using a sterilized L-shaped glass rod. The conidium
concentration was determined using a haemocytometer, and the appropriate concentration was
achieved via dilution with SDW. To study the development of melanized appressoria on parafilm
5

glass slides, a suspension of 1 × 10 conidia/ml was utilized. For all fruit infection experiments,
6

a suspension of 1 × 10 conidia was applied directly to the fruit surface.
Several preliminary experiments were done on detached and attached immature and
mature fruit but because of difficulty with background infections or suspected fungicide residues
on the fruit, results from only a small subset were considered acceptable for further analysis.
Also, to avoid background infection as much as possible, fruit was collected from multiple
sources. All experiments presented here had little or no evidence of background infections.
For the temperature and wetness duration assays, 20-cm-long detached ‘Jersey’ shoots
bearing immature fruit were collected in June 2006 and 2007 from the Michigan State University
(MSU) Horticulture Teaching and Research Center in East Lansing, MI. Detached mature
‘Jersey’ fruit were obtained from a commercial farm in Harrietta, MI in September 2006 and
‘Bluecrop’ fruit were obtained from a commercial farm in Traverse City, MI in September 2007.
For interrupted wetness period experiments, immature ‘Jersey’ fruits were obtained from MSU’s
Southwest Michigan Research and Extension Center in Benton Harbor, MI in July 2011, and
detached mature ‘Bluecrop’ fruit were obtained from a commercial farm in Traverse City, MI in
August 2011. For relative humidity assays, detached mature fruit were obtained from Sun Belle
Berries (Miami, FL) (originating from Florida) and believed to be a southern highbush blueberry
cultivar (southern-adapted V. corymbosum, usually with some introgressed V. darrowi Camp

30

and/or V. ashei Reade) based on appearance and harvest timing. In a preliminary experiment, the
cultivar was susceptible to C. acutatum with similar symptoms to those of ‘Bluecrop’ or ‘Jersey’.

Effect of temperature and wetness duration
The optimal temperature for the growth of our isolate (#0001) was investigated by
transferring 5.5-mm mycelial plugs to one-quarter strength PDA in 9-cm Petri dishes, and
incubating the cultures in the dark at various temperatures for 10 days. Culture diameter (in mm)
was then measured and results reported are the combined results of six experiments. Initially, 10,
15, 20, 25, and 30°C were tested and more detailed temperatures were evaluated in subsequent
experiments. The following temperatures were tested across all experiments 5, 10, 15, 20, 22, 24,
25, 26, 28, 30, 31, 33, and 35°C. For each temperature, four replicate cultures were used to
calculate the mean (n = 4) and each temperature was evaluated at least twice.
To determine the effects of temperature and wetness duration on the formation of
6

melanized appressoria, 20-µl droplets of a conidial suspension (10 conidia/ml) were placed on
parafilm-covered glass slides and placed in Petri dishes (90 mm diameter, 15 mm deep) with wet
Whatman filter paper to create a humidity chamber. Plates were incubated at 10, 15, 20, 25, or
30°C in the dark with 4, 6, 8, 12, 16, 20, 24, 36, or 48 hours of wetness. For each temperature, 5
replicate droplets were used and 50 random conidia were counted per droplet (250 conidia in
total) (n = 5). This experiment was conducted twice and experiments were normalized together
using the highest mean melanized appressoria (%). No significant effect of experiment was
observed during an ANOVA (P = 0.302), so therefore the average incidence of infected fruit was
plotted in SigmaPlot for curve fitting.
31

For experiments with immature ‘Jersey’ fruit, detached fruit clusters were collected from
mature field-grown plants in East Lansing, MI, and were placed in wet Florafoam® in 1 liter
6

plastic containers. The fruit was inoculated with C. acutatum (10 conidia/ml) and enclosed in a
plastic bag. Fruit clusters wetted with SDW served as a control. Inoculated fruit clusters were
incubated at 10, 15, 20, 25, or 30°C in the dark with 6, 12, 18, 24, 36, or 48 hours of wetness.
Four twigs were used per treatment combination. At the end of the wetness period, ten green
berries were removed from each twig, surface sterilized in 10% bleach, rinsed three times in
SDW, cut in half and placed on potato dextrose agar in Petri dishes. Berries were observed for
the presence of C. acutatum infection over a 2-week period. This experiment was conducted
twice in 2006 and 2007 and experiments were normalized together using the highest mean
infection rate (%). No significant effect of experiment was observed during an ANOVA (P =
0.287) so therefore, the average incidence of infected fruit was then plotted in SigmaPlot for
curve fitting.
For experiments with mature fruit, ten detached fruit per replicate (n = 4) were inoculated
6

by placing a 30-μl drop of C. acutatum (10 conidia/ml) in the calyx cup of each fruit. Fruit were
then subjected to the same temperature-wetness period combinations as described for immature
fruit. At the end of the wetness period, the fruit were surface sterilized, incubated at 100% RH,
and observed for C. acutatum infection as described above. This experiment was conducted
twice using ‘Jersey’ fruits in 2006 and ‘Bluecrop’ fruits in 2007 and experiments were
normalized together using the highest mean infection rate (%). No significant effect of
experiment was observed during an ANOVA (P = 0.416) so therefore, the average incidence of
infected fruit was then plotted in SigmaPlot for curve fitting.

32

Effect of interrupted wetness periods
To determine the effect of interrupted wetness on formation of melanized appressoria,
6

10-µl droplets of a conidial suspension of 10 conidia/ml were placed on parafilm-covered glass
slides as described above. Slides were then placed in humidity chambers and incubated at room
temperature (22 to 24°C) with wetness durations of 12, 24 and 48 hours. Interruptions of 1, 4,
and 16 hours were then applied in the middle of each wetting period by removing parafilmcovered glass slides from humidity chambers and placing them in a laminar flow hood at room
temperature (22 to 24°C and approximately 40% relative humidity). Following the interruption,
10-µl droplets of SDW were applied to the dried droplet location and the slides were returned to
the humidity chambers. For each treatment, 4 replicate droplets were used and 50 conidia were
counted per droplet (200 conidia in total) (n = 4). The mean was calculated for each treatment,
average values were standardized against the uninterrupted control and data were plotted in
SigmaPlot for curve fitting. This experiment was conducted twice.
For experiments with immature and mature fruit, a 10-µl droplet of conidial suspension
was placed on the side of detached ‘Jersey’ fruit placed equidistantly on wire-mesh screens. Fruit
were then placed in humidity chambers and incubated at room temperature (22 to 24°C) with
wetness durations of 12, 24 and 48 hours. Interruptions of 1, 4, and 16 hours were then applied in
the middle of each wetting period by removing fruit from humidity chambers and placing them
in a laminar flow hood at room temperature (22 to 24°C and approximately 40% relative
humidity). Following the interruption, 10-µl droplets of SDW were applied to the sites of the
dried droplets and the fruit were returned to the humidity chamber. At the end of the wetness
period, fruit were removed, surface sterilized as described above, cut in half and placed on potato
33

dextrose agar in Petri dishes. For each treatment, four replicates of 10 fruit each were used (40
fruit in total per maturity level). The mean was calculated for each treatment, average values
were standardized against the uninterrupted control and data were plotted in SigmaPlot for curve
fitting. This experiment was conducted twice.

Effect of relative humidity
To determine the effect of relative humidity (RH) on formation of melanized appressoria,
6

10-µl droplets of a conidial suspension (10 conidia/ml) were placed on parafilm-covered glass
slides and allowed to dry in a laminar flow hood as described above. Slides were then placed in
chambers with varying RH levels using using different concentrations of glycerol (0, 10, 33, and
66%) in water. For each treatment, three replicates were used and 50 conidia were counted per
replicate (150 conidia in total). Model 450 Watchdogs (Spectrum Technologies Inc., Plainfield,
IL) were used to monitor relative humidity in the chambers. Relative humidity varied with
temperature. The following RH values were achieved at 20°C: 100%, 96%, 86%, and 56%; at
25°C: 100%, 95%, 84%, and 54%; and at 30°C: 100%, 94%, 80%, and 50%. Slides were
incubated for 3 days and monitored daily for the production of melanized appressoria. Melanized
appressoria were observed after 2 days at 100% RH at all temperatures but were not observed at
lower relative humidity values for 3 days. The percentage of appressorium formation was
calculated for each treatment and average values were plotted in SigmaPlot for curve fitting.
6

For the mature fruit experiment, a conidial suspension (10 conidia/ml) was sprayed until
runoff on the surface of detached mature fruit and allowed to dry as described above. Fruit were
then placed in humidity chambers and incubated at various temperatures (20, 25 and 30°C) with
34

Table 2.1. Fitted-models for the development of melanized appressoria and infection level of
immature and mature blueberry fruits by Colletotrichum acutatum using temperature (°C),
wetness duration (h), wetness interruption (h), and relative humidity (%). Nine equations were
developed based on curve fitting the raw data from a mixture of experiments and models were
2

examined for goodness of fit (R ), standard error of the estimate (SEE), the P value of the
regression and the mean squared error (MSE) of the residuals (* denotes a chosen equation).

35

Table 2.1 (cont’d.)
Fitted-model
(corresponding
equation)
Planer
Parabolic
Gaussian* (Eq. A)
Lorentzian

0.699
0.790
0.890
0.846

Wetness duration
Temperature
Immature infected fruit

Planer
Parabolic
Gaussian* (Eq. D)
Lorentzian

Wetness duration
Temperature
Mature infected fruit
Wetness interruption
Wetness duration
Relative melanized
appressoria

Independent/Dependent
variables

Adj.
2
R

P-value

Residual
MSE

0.684 10.348
0.769
8.848
0.879
6.406
0.831
7.569

< 0.001
< 0.001
< 0.001
< 0.001

107.075
78.285
41.030
57.295

0.718
0.781
0.856
0.814

0.700 14.816
0.752 13.474
0.837 10.941
0.790 12.414

< 0.001
< 0.001
< 0.001
< 0.001

219.519
181.542
119.715
154.098

Planer
Parabolic
Gaussian* (Eq. G)
Lorentzian

0.633
0.701
0.899
0.859

0.610 18.164
0.661 16.940
0.885
9.870
0.840 1.6413

< 0.001
< 0.001
< 0.001
< 0.001

329.921
286.951
97.421
135.559

Planer* (Eq. B)
Parabolic

0.945
0.971

0.926
0.943

< 0.001
0.002

44.881
54.967

Gaussian

Could not fit – exceeded maximum iterations

Lorentzian

Could not fit – exceeded maximum iterations

Planer* (Eq. E)
Parabolic

0.897
0.916

0.862 11.299
0.833 12.448

0.001
0.020

127.664
154.951

Gaussian

0.908

0.816

13.049

0.024

170.287

Lorentzian

0.794

0.589

21.148

0.110

447.241

Planer* (Eq. H)
Parabolic

0.781
0.837

0.708 17.991
0.674 18.995

0.011
0.071

323.681
360.820

Gaussian

0.851

0.702

18.157

0.060

329.675

Lorentzian

0.851

0.702

18.157

0.060

329.675

Relative humidity
Temperature
Melanized appressoria

Planer
Parabolic
Gaussian* (Eq. C)
Lorentzian

0.183 0.002 12.467
0.402 155.430
0.494 0.204 11.132
0.252 123.914
0.996 0.993
1.022 < 0.001
1.045
Could not fit – exceeded maximum iterations

Relative humidity
Temperature
Mature infected fruit

Planer
Parabolic
Gaussian
Lorentzian* (Eq. F,I)

0.663 0.588 14.114
0.008 199.191
0.907 0.854
8.411
0.001
70.736
Could not fit – exceeded maximum iterations
0.971 0.954
4.735 < 0.001
22.424

Wetness duration
Temperature
Melanized appressoria

Wetness interruption
Wetness duration
Relative immature
infected fruit
Wetness interruption
Wetness duration
Relative mature
infected fruit

2

R

36

SEE

6.699
5.913

varying levels of relative humidity (same levels as described above) for 3 days. For each
temperature-RH combination, 10 fruits were used, replicated four times (40 fruits total per fruit
maturity level). At the end of the incubation period, fruit were removed, surface sterilized as
described above, placed equidistantly on wire mesh grates and incubated at 100% relative
humidity. Fruit were observed for the presence of C. acutatum infection at 10 days post
inoculation. Mean values were then calculated and plotted in SigmaPlot for curve fitting.

Statistical analysis
All statistical analyses were performed with SIGMAPLOT version 11 (SYSTAT
Software, Chicago, IL). Regression analyses were used to develop quantitative models relating to
temperature, wetness duration, interrupted wetness periods, and relative humidity. Threedimensional nonlinear regressions including Planer, Parabolic Gaussian, and Lorentzian were fit
to the data from two experiments. Criteria for selecting the best statistical models included an
2

examination of normality, equality of variance, R values, and residual plots (Table 2.1).
Equations were chosen and three models were proposed predicting the development of
melanized appressoria and the infection levels of immature and mature blueberry fruits (Table
2.2). A summarized equation for each model was developed that best fit the data.

RESULTS
Temperature and wetness duration have an effect on the development of melanized
appressoria and fruit infection
Mycelial growth of our isolate of C. acutatum increased with increasing temperature
from 10 to 26°C but then declined sharply between 27 and 30°C (Figure 2.1). Little to no
37

Colony diameter (mm) after 10 days

80

60

40

20

0
0

5

10

20

15

25

30

35

40

Temperature (°C)

Figure 2.1. The effect of temperature on mycelial growth of Colletotrichum acutatum (isolate
#0001) on quarter-strength potato dextrose agar. Colony diameter was measured in two
perpendicular directions and averaged after a 10-day incubation at each temperature. Values are
the average of three replications and error bars denote the standard error of the mean.

38

Table 2.2. Proposed model for the development of melanized appressoria and the infection level of immature and mature blueberry
fruits by Colletotrichum acutatum. Nine equations were developed based on curve fitting the raw data from a mixture of experiments
and these equations were used to make three combined models.
Independent/Dependent Variables
Equation Type
X
Y
Z
A
Gaussian
Wetness
Temperature Melanized
duration
appressoria
B
Planer
Interruption Wetness
Relative
duration
Melanized
appressoria
C
Gaussian
Relative
Temperature Melanized
humidity
appressoria
D
Gaussian
Wetness
Temperature Immature
duration
infection level
E
Planer
Interruption Wetness
Immature
duration
infection level
F
Lorentzian Relative
Temperature Immature
humidity
infection level
G
Gaussian
Wetness
Temperature Mature
duration
infection level
Mature
H
Planer
Interruption Wetness
duration
infection level
I
Lorentzian Relative
Temperature Mature
humidity
infection level
1

1

x0
48.6677

Coefficients
y0
a
21.7020
68.5131

b
16.6815

c
6.8695

N/A

8.7148

-1.6989

1.3201

N/A

99.7093

23.8718

50.0223

2.2937

2.2990

46.7302

24.6465

94.4065

24.7335

10.5797

N/A

14.9471

-0.0945

1.8141

N/A

104.1017

25.8143

80.4083

10.7745

6.1264

42.5273

23.5491

101.6045

N/A

54.2761

-1.3035

1.7641

N/A

104.1017

25.8143

80.4083

10.7745

6.1264

17.4474

6.6446

2

Various equations where used to fit data as follows Planer: f (Z) = y0+a*x+b*y, Gaussian: f (Z)=a*exp(-0.5*( ((x-x0)/b) + ((y2

2

2

y0)/c) )), and Lorentzian: f (Z) = a/((1+((x-x0)/b) )*(1+((y-y0)/c) ))).
.

39

2

R = 0.89

P < 0.001

80

60

40

20
40
30

0
30

25

20
20

10

15
10

Figure 2.2. The effect of temperature and wetness duration on the predicted development of
melanized appressoria of Colletotrichum acutatum on parafilm-covered glass slides. A
Gaussian equation (Table 2.2, Equation A) was used to fit the data. Shading intensity of the
surface indicates changes in the percentage of melanized appressoria at 20% intervals
starting at zero.

40

2

R = 0.86

R = 0.90

120

120

80

80

40

40

0
30
A

2

P < 0.001

25

20

15

10

40
30
20
10

0
30

25

B

20

P < 0.001

15

10

40
30
20
10

Figure 2.3. The effect of temperature and wetness duration on the predicted infection level
of immature (A) and mature (B) blueberry fruits by Colletotrichum acutatum. Separate
Gaussian equations were fit to the data for immature fruit (Table 2.2, Equation D) and
mature fruit (Table 2.2, Equation G). Shading intensity of the surface indicates changes in
the percentage of infected fruit at 20% intervals starting at zero.

41

Infected fruit (%)

Infected fruit (%)

Melanized appressoria (%)

Wetness duration (h)
12

48

24
B

C

D

E

F

60 G

H

I

60 A
40
20
0
40
30
20
10
0

40
20
0

0

1

4

16

0

1

4

16

0

1

4

16

Interruption (h)
Figure 2.4. The effect of interrupted wetness periods (0-, 1-, 4-, and 16-h of dry time in the
middle of 12-, 24-, and 48-h wet periods) on the development of melanized appressoria (%)
of Colletotrichum acutatum (A-C) and the percentage immature (D-F) and mature (G-I)
blueberry fruit infected by C. acutatum. Values are the average of four replications and error
bars denote the standard error of the mean.

42

growth was observed at 5°C and 35°C. The optimal temperature for melanized appressorium
formation was 25°C and development was significantly reduced at 10 and 30°C. At 25°C, a
minimum of 8 hours of continuous wetness was required for the development of melanized
appressoria. However, 12 hours were required at 30°C and 24 hours were required at 10°C.
2

A Gaussian model was found to be the best fit for the raw data (R = 0.89) (Table 2.2,
Equation A, and Figure 2.2).
In the infection assays of immature and mature fruit, low levels of infection were
seen after wetness durations of 6 hours (Figure 2.3). However, the infection percentage
increased considerably after 12 to 18 hr of wetness at 20ºC to 25ºC, 18 to 24 hours at 30ºC,
24 hours at 15ºC, and 36 to 48 hours at 10ºC (Figure 2.3). The optimal temperature for fruit
infection by C. acutatum was determined to be 25ºC based on infection incidence. For both
immature and mature fruit experiments a Gaussian model was found to be the best fit for the
2

2

raw data sets (R = 0.86, R = 0.90, respectively) (Table 2.2, Equations D and G). In both
immature and mature fruit studies presented here, no background infections were observed
on uninoculated control fruit.

Interrupted wetness periods reduce melanized appressorium formation and infection at
shorter wetness durations
In general, the longer the wetness period, the higher the percentage of melanized
appressoria formed and infected fruit. However, interruption of the wetness period

43

2

R = 0.95

P < 0.001

80

60

40

20

16
14
12
10

0
8
45

40

6
35

30

4
25

20

15

2

Figure 2.5. The effect of wetness duration and interrupted wetness periods on the predicted
development of melanized appressoria of Colletotrichum acutatum on parafilm-coated glass
slides. Values are calculated as the percent melanized appressoria relative to the continuous
wetness treatment. A Planer equation (Table 2.2, Equation B) was fit to the data. Shading
intensity of the surface indicates changes with the percentage of melanized appressoria at
20% intervals starting at zero.
44

2

R = 0.90

2

P < 0.001

R = 0.78

120

120

80

80

40
0
45
A

40

16
12

0

8
35

25

P < 0.001

4
15

16
12
45

B

8
35

25

4
15

Figure 2.6. The effect of wetness duration and interrupted wetness periods on the predicted
infection level of immature (A) and mature (B) blueberry fruit by Colletotrichum acutatum.
Values are calculated as the percent infected fruit relative to the continuous wetness control.
Planer equations (Table 2.2, Equation E) were fit to the data for immature fruit and mature
fruit (Table 2.2, Equation H). Shading intensity of the surface indicates changes in the
percentage of infected fruit at 20% intervals starting at zero.

45

significantly reduced successful appressorium formation and infection. The average
percentage of melanized appressoria produced on parafilm-covered slides with no
interruption in the wetness duration was 6%, 30%, and 63% after 12, 24, and 48 hours of
wetness, respectively. For all three incubation times, the longer the wetness interruption, the
greater the reduction in the number of melanized appressoria produced (Figure 2.4A-C). In
order to compare the interrupted wetness treatments with the continuous wetness duration
treatments, the control from each incubation time was used to standardize the amount of
2

melanized appressoria relative to no interruption. A Planer model best fit the raw data (R =
0.95) (Table 2.2, Equation B, and Figure 2.5).
The percentage of infected immature fruit was 15%, 17%, and 30%, respectively,
after 12, 24, and 48 hours of continuous wetness. At the 12- and 24-hour incubation times,
interruptions of any duration dramatically reduced the percentage of infected fruit (Figure
2.4D and E). No reduction in the percentage of infected immature fruit was observed at the
48 hour incubation time (Figure 2.4F). In order to compare the interruption treatments with
the continuous wetness duration treatments the control from each incubation time was used
to standardize the amount of infected fruit relative to no interruption. A Planer model was
2

found to be the best fit for the raw data (R = 0.90) (Table 2.2, Equation E, and Figure 2.6A).
The percentage of infected mature fruit was 25%, 28%, and 38%, repectively at 12,
24, and 48 hours of continuous wetness. At the 12-hour incubation time, there was a
reduction in fruit infection but the duration of the interruption did not seem to matter (Figure
2.4G). No reduction in the percentage of mature fruit infection due to interrupted wetness
was observed at the 24- and 48-h incubation times (Figure 2.4H and I). In order to compare

46

2

R = 0.99

2

R = 0.97

P < 0.001

80

P < 0.001

120

60
80

40
20
0
30 28
26 24
A
22

40

100

0
30 28
26 24
22
B

80
60
20

100
80
60
20

Figure 2.7. The effect of temperature and relative humidity on the predicted development of
melanized appressoria (%) of Colletotrichum acutatum (A), and the predicted infection level
of mature blueberry fruits (B) by C. acutatum. A Gaussian equation (Table 2.2, Equation C)
was fit to the data for melanized appressoria and a Lorentzian equation (Table 2.2,
Equations F and I) was used to fit the data for mature fruit. Shading intensity of the surface
indicates changes in the percentage of melanized appressoria and percentage infected fruit at
20% intervals, respectively, starting at zero.

47

the interruption treatments with the continuous wetness duration treatments, the control from
each incubation time was used to standardize our amount of infected fruit relative to no
2

interruption. A Planer model best fit the raw data (R = 0.78) (Table 2.2, Equation H, and
Figure 2.6B).

Relative humidity affects melanized appressorium development and fruit infection
Conidia germinated and had formed melanized appressoria on parafilm-covered glass
slides at 100% relative humidity at all temperatures tested after 48 h with an increase seen
after 72 h of incubation. At 25°C, the percentage of melanized appressoria was 5%, 1%, and
0% at 95%, 84%, and 54% relative humidity, respectively. A Gaussian model best fit the raw
2

data (R = 0.99) (Table 2.2, Equation C, and Figure 2.7A).
Mature fruit was infected at all temperatures, and increasing relative humidity led to
higher infection incidence. At 20°C, the percentage of infected fruit was 43%, 20%, 7% and
3% at 100%, 96%, 86%, and 56% relative humidity, respectively. At 25°C, the percentage of
infected fruit was 67%, 50%, 17% and 3% at 100%, 95%, 84%, and 54% relative humidity,
respectively. At 30°C, the percentage of infected fruit was 47%, 30%, 13% and 0% at 100%,
94%, 80%, and 50% relative humidity, respectively. A Lorentzian model best fit the raw data
2

(R = 0.97) (Table 2.2, Equation F and I, Figure 2.7A). Since immature fruit was not tested,
this model was included in the proposed comprehensive model for immature fruit infection
(Table 2.2, Equation F).

48

Comprehensive models for appressorium development and infection of immature and
mature fruit
Three models were constructed based on three nonlinear regressions described above
for temperature in relation to wetness duration and relative humidity, and wetness duration in
relation to wetness interruption (Table 2.2). For the formation of melanized appressoria, each
2

component of the proposed model had R values greater than 0.89 (Table 2.1). For the
2

percentage of infected immature fruit, each component of the proposed model had R values
greater than 0.86 (Table 2.2). For the percentage of infected mature fruit, each component of
2

the proposed model had R values greater than 0.78 (Table 2.3). For all models, an analysis
of residuals did not reveal outliers or particular patterns. Therefore three general equations
were developed for the development of melanized appressoria and infection in immature and
mature fruit using chosen equations in Table 2.2.

For the development of melanized appressoria:
	

	 %

	 	

	

	

	

	 	

	

	

	

For infection level of immature fruit:
	

	

	 %

For infection level of mature fruit:
	

	

	 %

	 	

49

	

	

	

DISCUSSION
Results of this study indicate that temperature, wetness duration, wetness
interruptions and relative humidity have a direct effect on the development of melanized
appressoria and infection of both immature and mature blueberry fruits by C. acutatum. The
relationship between temperature and wetness conforms to previous studies of
Colletotrichum spp. on other fruit crops (130, 168, 206). Temperature effects were also
consistent with the mycelial growth assay. While the optimum temperature was found to be
26°C for mycelial growth, we did not investigate the effect of temperature in such small
increments for appressorium formation and infection for which 25°C was found to be
optimum when using 5°C increments.
The development of melanized appressoria was observed as early as 8 hours after
incubation on parafilm slides and infection as early as 6 hours after inoculation of immature
and mature fruit at the optimum temperature of 25°C. Previous microscopy studies
conducted on detached, ripe ‘Jersey’ fruit incubated at room temperature (22 to 24ºC)
showed that 4 hours after inoculation, 10.6% of conidia had germinated (30). At 8 hours post
inoculation, 41.5% of conidia had formed unmelanized appressoria and 11.4 % had formed
melanized appressoria with an internal light spot, which is thought to indicate formation of a
penetration peg (201). It is therefore possible that a small percentage of conidia could have
successfully infected the fruit as early as 6 hours after inoculation under optimal conditions.
Differences in the minimum environmental requirements for infection and the development
of melanized appressoria on parafilm covered glass slides may be due to the presence of
plant-derived waxes on the surface of blueberry fruits. The surface wax of avocado fruit has
50

been shown to induce germination and appressorium formation in the spores of
Colletotrichum gloeosporioides (148). Additionally, disease incidence was generally higher
in mature fruit than in immature fruit indicating greater tissue susceptibility, which is similar
to other work in strawberries (206).
This study also demonstrates that wetness interruptions play an inhibitory role in the
infection process. Previous research on Cercospora kikuchii T. Matsumoto & Tomoy. on
soybean leaves has shown that interruptions of different durations in 24-hour wetness periods
have a significant effect on overall disease severity and the number of infections. Also, they
found that the relative humidity during the interruption was important for disease severity in
the sense that interruptions during which the relative humidity was high had less of an effect
those during which the relative humidity was low (171). In our study, a greater inhibition of
infection at lower initial wetness durations and longer interruptions was observed. This is
likely due to the fact that the fungus has not yet developed protective structures or penetrated
the host tissue and was therefore more vulnerable to desiccation.
This study also identifies and quantifies relative humidity as an important
environmental factor in the infection process of C. acutatum on blueberry. Our results agree
with previous work on Colletotrichum gloeosporioides on mango which showed that
appressoria are capable of developing between 95 and 100% relative humidity (56).
Additionally, research on C. gloeosporioides on citrus fruits has shown that sustained high
relative humidity for three days dramatically increases disease incidence (22). This
component of our model is relevant in humid growing regions like Michigan where average
daily relative humidity can remain above 90% for several days during the growing season.

51

High relative humidity may also reduce the impact of wetness interruptions on appressorium
formation and infection.
Many disease prediction models use regression equations, such as those based on
polynomials (65, 170), logistic equations (26, 170), and complex three-dimensional response
surfaces (21, 29, 207). Wilson et al. (1990) used a regression model with the logit of disease
incidence of C. acutatum as the dependent variable which accurately described infection
level as a function of wetness duration and temperature. In the C. coccodes-tomato
pathosystem, fruit infection was correlated with the amount and duration of rain alone and in
combination with other meteorological variables, accouting for 72% of the variation in
anthracnose incidence. Infection was also negatively correlated with the number of hours
during which no rainfall occurred within 4-day intervals that tomato fruit were exposed to
field conditions (168). Another study used polynomial equations to describe the relationship
between C. orbiculare infection on watermelon leaves in relationship to temperature and leaf
wetness (130).
Our models focus on the environmental requirements for infection; however, there
are other epidemiological variables to consider such as pathogen dispersal and survival.
Colletotrichum spp. have been classically identified as rain-splash-dispersed pathogens, and
numerous studies link dispersal of conidia to rainfall (14, 210). Additionally, survival of
Colletotrichum spp. over the winter in soil, host tissue and plant debris has been described in
numerous pathosystems (49, 62, 68, 136, 212) while survival over the summer has been
described on symptomless leaves of strawberry (112), which also is an important factor when
predicting disease risk. While the assumption for our model is that inoculum is uniformly

52

distributed and unlimited, this may not be the case and inoculum availability needs to be
taken into account when determining infection risk.
This study provides useful information on temperature and wetness requirements for
infection of blueberry fruit by Colletotrichum acutatum under controlled conditions. The
absence of or suppression of background infection is very important to obtain accurate
results. This information is the first step towards the development of a disease prediction
model for anthracnose fruit rot in blueberries. Further research is needed to validate these
results under field conditions. In the field, fruit clusters may stay wet longer than an exposed
leaf wetness sensor of a weather station. Further studies are needed to determine how fruit
wetness relates to behavior of electronic wetness sensors.

ACKNOWLEDGEMENTS
I would like to gratefully acknowledge funding from Michigan State University
Project GREEEN (Generating Research and Extension to meet Economic and Environmental
Needs) and the Michigan Blueberry Growers (the Blueberry People). I would also like to
thank Christopher Woelk and Daniel Svoboda for technical assistance and Laura Avila for
critical reading of the manuscript.

53

CHAPTER III: IDENTIFICATION OF DIFFERENTIALLY EXPRESSED GENES IN A
RESISTANT VERSUS SUSCEPTIBLE CULTIVAR AFTER INFECTION BY
COLLETOTRICHUM ACUTATUM

Published in the peer-reviewed journal Molecular Plant Pathology (June 2011, Volume 12,
Pages 463–477)

ABSTRACT
Anthracnose fruit rot, caused by the fungus Colletotrichum acutatum, is an important
disease of blueberries worldwide. Cultivar Elliott is resistant, severely restricting fungal
growth and sporulation compared to the susceptible cultivar Jersey. The objectives of this
research were to: 1) Analyze pre-penetration events in ‘Elliott’ and ‘Jersey’ at different
stages of fruit development, 2) Identify putative defense genes in ‘Elliott’ fruit, and 3)
Monitor timing of the oxidative burst in both cultivars. Light microscopy revealed no
differences in pre-penetration activities of C. acutatum on immature fruit of both cultivars.
However, at fruit ripening, conidia germinated and formed appressoria faster on ‘Jersey’ than
in ‘Elliott’ fruit. Using suppression subtractive hybridization, 37 differentially expressed
sequence tags (ESTs) were detected in ‘Elliott’ versus ‘Jersey’ upon infection. Several of the
ESTs had homology to known plant defense genes, such as a class II chitinase, pathogenesisrelated protein 10 (PR10), and β-1-3 glucanase. Two putative genes involved in oxidative
stress were identified: a metallothionein-like protein and monodehydroascorbate reductase.
ESTs of fungal origin were also detected. Many ESTs had no homology to known genes.
Using semi-quantitative and quantitative RT-PCR, expression of most of the candidate genes

54

was detected earlier in ‘Elliott’ than in ‘Jersey’, some within 24 hours post infection (hpi).
Monitoring of the oxidative burst showed that the overall H2O2 concentration was two to
three times higher in ‘Elliott’ than in ‘Jersey’ at 24 hpi. Elucidation of the basis of resistance
to C. acutatum in blueberries will facilitate the development of new anthracnose fruit rotresistant cultivars.

INTRODUCTION
Colletotrichum species are ubiquitous fungal pathogens, infecting numerous
agronomically important plant species (2, 13, 16, 17, 67, 69, 189). Colletotrichum acutatum
J.H. Simmonds causes fruit rots in a range of hosts, including almonds, apples, citrus, olives,
stone fruits and strawberries (1, 131, 146). C. acutatum was first described as a separate
species in 1965 (175). While initial studies referred to C. gloeosporioides (Penz.) Penz. &
Sacc. as the causal agent of anthracnose fruit rot on highbush blueberries (46, 85, 128), C.
acutatum is now considered the primary cause of the disease in temperate regions (146, 150,
169, 192, 213).
The main symptom of anthracnose on blueberries is rotting of ripe fruit in the field
before harvest and in storage after harvest (128). Initially, sunken areas develop on the fruit
surface followed by the formation of acervuli exuding salmon-colored conidial masses. This
disease can have a severe economic impact, with pre-harvest losses estimated at 10-20% and
post-harvest losses as high as 100% in storage (128). Most blueberry cultivars are susceptible
to anthracnose fruit rot. However, several resistant cultivars have been identified including
‘Elliott’, which displays strong resistance in the field and in laboratory inoculation studies
(63, 150).
55

Host-pathogen interactions have been well characterized in only a few
Colletotrichum-fruit pathosystems, including avocado (159), citrus (23, 189), mango (86),
strawberry (8, 9, 25, 31) and pepper (7, 101, 102, 107, 119). Following direct penetration of
host tissues, Colletotrichum species generally have two different host colonization strategies
depending on the tissue or host being colonized: intracellular hemibiotrophy and subcuticular
intramural necrotrophy. Intracellular hemibiotrophy is the direct invasion of the initial host
cell by a primary infection vesicle, followed by the proliferation of primary and secondary
hyphae; this strategy is common in Colletotrichum spp. infecting bean (137), pea (138),
sorghum (199), and tobacco (173). In subcuticular intramural necrotrophy, Colletotrichum
spp. will invade the plant superficially under the cuticle, generally producing necrotrophic
hyphae sooner, proliferate intramurally, and only later invading the host cell intracellularly.
This type of strategy is typical for infection by C. capsici on cowpea (151) and cotton (162).
C. acutatum is known to use both infection strategies on almond (53), olive, (75) and
strawberry (43).
A recent study of the infection process on ripe blueberry fruit showed that C.
acutatum exhibits different infection strategies depending on the cultivar being colonized
(201). In the susceptible cultivar Jersey, the host-pathogen interaction was described as
intracellular hemibiotrophy, and in the resistant cultivar Elliott as intramural necrotrophy. A
build-up of phenolic compounds, degradation of fungal hyphae and an accumulation of
anthocyanins were noticed in ‘Elliott’, suggesting an active resistance response (124, 201). In
addition, conidium germination and appressorium formation were slower on ‘Elliott’ than
‘Jersey’ fruit (201). The infection process on immature fruit tissues of either cultivar was not
investigated.

56

A variety of defense mechanisms in other Colletotrichum-plant interactions have
been observed, including the production of reactive oxygen species (25), host-derived cell
wall-degrading enzymes (31, 76, 110, 204), enzymes involved in secondary metabolism (7,
28, 111), host cell wall modification (101, 178), and pre-formed and induced antifungal
compounds (58, 159). Upon infection of pepper fruits (Capsicum annuum L.) by C.
gloeosporioides, many defense-related proteins like cytochrome P450 (141), defensin,
thionin-like protein (140), thaumatin-like protein (103) and esterase (107) are induced in
incompatible interactions. Since most of these defense responses can be monitored at the
transcriptional level, a broad genetic screen can provide insight into the type of defense
mechanism involved in a particular plant pathosystem.
Defense responses in fruit to infection by Colletotrichum spp. have been studied
mostly in immature fruit during the latent (or quiescent) phase of the infection (156), and are
typical of ontogenic resistance. As avocado fruits mature, the pectin lyase activity of C.
gloeosporioides increases as the inhibitor epicatechin slowly decreases in concentration. In
addition, antifungal diene compounds are degraded by fruit lipoxygenases, and the fruit
gradually become increasingly susceptible to infection (159). With the exception of the C.
gloeosporioides-C. annuum system, to our knowledge, no research has been published on the
defense mechanisms in ripe fruit at different stages of the infection process. Casado-Diaz et
al. (2006) studied the resistance response of ripe strawberry fruit to C. acutatum by
comparing naturally infected fruit to uninfected fruit without regard to infection timing. The
C. acutatum-blueberry pathosystem is of interest because the defense response occurs in ripe
fruit, and moreover, the infection strategy of the pathogen changes depending on host
susceptibility (201).

57

A better understanding of the basis of resistance in the C. acutatum-blueberry
pathosystem will aid the development of alternative management strategies for a major
blueberry disease that is currently controlled primarily with fungicides (169). While
anthracnose fruit rot resistance is an objective of blueberry breeding programs, no genotypic
or phenotypic markers are currently available for rapid resistance screening of blueberry
breeding lines. Evaluation of plants for anthracnose fruit rot resistance can only be
accomplished when they bear fruit in sufficient quantities for inoculation, usually at 2 to 3
years of age. In previous studies, anthracnose fruit rot resistance in blueberries was not
correlated with resistance to foliar infection (64) or production of antimicrobial fruit volatiles
(149). Identification of anthracnose fruit rot resistance mechanisms and associated molecular
markers could improve resistance screening procedures. The goal of this research was to
compare the infection process by C. acutatum in fruit of the resistant cultivar Elliott versus
the susceptible cultivar Jersey at different stages of fruit development, and to analyze the
molecular mechanisms that underpin host plant resistance to anthracnose fruit rot in ‘Elliott’
blueberries.

MATERIALS AND METHODS
Fungal cultures and media
A single-conidium isolate of Colletotrichum acutatum from blueberry fruit collected
in Grand Junction, MI, USA in August of 2006 was used for all experiments. The isolate was
stored as conidia in a nutrient solution (20% glycerol, 0.04% yeast extract, 0.1% malt extract,
0.04% glucose, 0.02% K2HPO4) at -80 °C. Cultures were grown on ¼-strength potato
dextrose agar (PDA) for a period of 14 d, after which conidia were harvested, re-cultured on
58

¼-strength PDA, and allowed to microconidiate for 3 to 4 d. This procedure was used to
prepare conidial suspensions for storage and inoculum production and has been utilized in
previous studies (177, 201, 203). For inoculum production, sporulating cultures were flooded
with 3 mL of sterile deionized water (SDW), and microconidia were dislodged using a
sterilized L-shaped glass rod. Conidia were counted using a hemacytometer, and the
appropriate concentration was achieved via dilution with SDW.

Plant material and inoculation procedures
To confirm virulence of the pathogen and the host resistance phenotype observed in
Wharton and Schilder (2008), ripe fruit were collected on 6 August 2006 from mature
‘Elliott’ and ‘Jersey’ bushes at the Southwest Michigan Research and Extension Center in
Benton Harbor, MI, USA. Ten fruit of each cultivar were spray-inoculated until run-off with
6

a conidial suspension containing 10 conidia per milliliter, placed equidistantly on wire mesh
over a layer of water in covered aluminum pans that acted as humidity chambers, and
incubated for 8 d at 22-24°C. After 5 d, fruits were macroscopically examined daily for
disease symptoms and signs. For scanning electron micrographs, ten fruit epidermal peels of
(1 mm in diameter) each cultivar were dehydrated with ethanol, critical point dried, mounted
on aluminum mounting stubs, and coated with gold using a gold sputter coater (EMSCOPE
SC500 Sputter coater, Ashford, Kent, UK). Images were captured on a scanning electron
microscope (SEM) (JEOL 6400V, Japan Electron Optics Laboratories, Tokyo, Japan).
Micrographs were used to measure the diameter (in two perpendicular directions) of 50
randomly selected acervuli per cultivar. To quantify sporulation, inoculated fruit were
incubated at 100% humidity on wire mesh screens in aluminum pans for 8 days (10 fruit per
59

replicate with five replicates). After incubation, ten inoculated fruit per replicate were shaken
in 10 mL of sterile water for 5 minutes, and conidium concentration was determined using a
hemacytometer.
In order to monitor the pre-penetration activities of C. acutatum on fruit at different
stages of development, 10-cm-long twigs with attached fruit clusters were collected from
mature ‘Elliott’ and ‘Jersey’ bushes in Benton Harbor, Michigan, in 2008. The bushes had
not been treated with fungicides for at least two months before removing the fruit clusters.
Fruit clusters were collected at the following growth stages: petal fall (1 June), green fruit
(16 June), fruit coloring (14 July for ‘Jersey’ and 28 July for ‘Elliott’), and ripe fruit (11
August). Fruiting twigs were placed with the cut ends in wet Oasis® Floral foam (SmithersOasis, Kent, OH, USA) and fruit were inoculated with 10-µL droplets of C. acutatum (1 x
5

10 conidia/mL) and incubated in round plastic containers (~950 mL) for 24, 48, 96, and 144
hours post inoculation (hpi) at 22–24 °C and 100% RH under continuous fluorescent light.
After incubation, epidermal peels were collected from the inoculation sites, and were fixed
and stained in accordance with procedures use by Wharton and Schilder (2008). A total of
100 conidia per replicate for five replicates were examined for germination and formation of
unmelanized and melanized appressoria using light microscopy.
All statistical analyses of the data were performed using a paired Student’s T-test
(α=0.05) using the StatGraphics statistical computer program (StatPoint Inc., Warrenton,
VA, USA) after checking for equality of variance.
For the molecular experiments, ripe fruit of ‘Elliott’ and ‘Jersey’ (not treated with
fungicides for at least 3 weeks prior to harvest) were provided by Hortifrut Chile S.A.
(Santiago, Chile) and were equidistantly placed on wire mesh grates in humidity chambers
60

constructed from two Petri dish bottoms (15-cm diameter x 2.5-cm height) with moist filter
paper on the bottom. Fruit were inoculated with 10-µL droplets of an aqueous suspension C.
6

acutatum (10 conidia/mL) or sterile deionized water (control) and incubated at 25°C in the
dark. Fruit epidermal samples were collected prior to inoculation and at 24, 48, 96, and 144
hours after inoculation using a size 2 cork borer (5.5 mm in diameter) and forceps to remove
the inoculated sections of the peel. The epidermal peels were placed in 100-mg aliquots (~5
to 6 peels) in microcentrifuge tubes and were flash frozen in liquid nitrogen. Ten aliquots
were collected for each combination of cultivar, time interval after inoculation, and treatment
(inoculation or water control). Samples were then stored at -80 °C until RNA extraction was
performed.

RNA extraction and cDNA library synthesis
Total RNA was extracted from 100 mg of epidermal peels (five to six fruits) per
cultivar (Elliott and Jersey) and time point (0, 24, 48-, 96- and 144-hpi) combination using a
phenol-chloroform-based protocol that was adapted for use in a refrigerated microcentrifuge
(166). The RNA extracts were then treated with a DNA-free kit (Applied
Biosystems/Ambion, Austin, TX, USA) to remove residual genomic DNA. Extracted total
RNA was denatured in glyoxal containing sample-loading dye (Ambion, Austin, TX, USA)
at 50°C and was visualized on a 1.0%-agarose Tris-Acetate-EDTA (TAE) gel.
Total RNA in each sample was quantified using a Nanodrop 2000 spectrophotometer
(Thermo Scientific, Wilmington, DE, USA). For construction of the cDNA libraries for
suppression subtractive hybridization, one compound sample per cultivar was created by

61

combining 0.2 µg RNA from each time point after inoculation with C. acutatum. cDNA
synthesis was performed using 1.0 µg of RNA from each composite library in the Super
SMART cDNA synthesis kit (Clontech Laboratories, Inc., Palo Alto, CA, USA) in
accordance with the manufacturer’s protocols.

Suppression subtractive hybridization, differential screening and sequencing
Suppression subtractive hybridization (SSH) was performed with the cDNA from
the Super SMART cDNA synthesis kit using 21 cycles to enrich the initial cDNA (Figure
B.1) and the Suppression Subtractive Hybridization Kit (Clontech Laboratories, Inc.) in
accordance with the manufacturer’s protocols (Figs. S2 and S3). A forward-subtracted
‘Elliott’ library (where ‘Elliott’ served as the tester and ‘Jersey’ as the driver) and a reversesubtracted ‘Jersey’ library (where ‘Jersey’ served as the tester and ‘Elliott’ as the driver)
were constructed. The forward-subtracted cDNA library of ‘Elliott’ was cloned using the
pGEM-T Easy Kit (Promega, Madison, WI, USA). Then 5 µL of the ligation reaction was
used to transform DH5α ElectroMAX competent cells (Invitrogen, Carlsbad, CA, USA) by
electroporation with the following parameters: 2.0 kV, 200 Ω, 25 μF.
‘Elliott’ cDNA clones were screened using a southern dot blot technique according
to (183). To construct probes for each library, the PCR DIG Probe Synthesis Kit (Roche
Applied Science, Mannheim, Germany) and 1 µL of the primary PCR product from the
forward- and the reverse-subtracted libraries (derived from the SSH kit) were used as the
template. The primers T7 (5'-AAT ACG ACT CAC TAT AG-3') and Sp6 (5'-ATT TAG
GTG ACA CTA TAG-3') were used in a PCR reaction to amplify the insert from each of the
clones (Figure 3.4A). For the blots, the DIG Luminescent Detection Kit for Nucleic Acids

62

(Roche Applied Science) was used and a 1-µL PCR product was loaded onto two separate
0.45-µ MAGNACHARGE nylon transfer membranes (GE Water and Process Technologies,
Trevose, PA, USA) in a high-throughput 96-well system. One membrane was probed using
15 µL of the forward ‘Elliott’ library DIG PCR product and the other with 15 µL of the
reverse ‘Jersey’ library DIG PCR product. Clones were considered differentially expressed if
the diameter of the spot was more than 50% of that in the ‘Jersey’ reverse blot. Differentially
expressed clones were independently screened three times, and a putative actin gene of
-31

Vaccinium corymbosum with significant homology (E-value 7.0 x 10

using BLASTn) to a

Prunus avium actin gene (GenBank accession no. FJ560908) served as an internal standard
(Figure 3.4).
The differentially expressed clones were sequenced in both directions using the PCR
product from the blot screens and the primers T7 and Sp6. The sequences were combined to
form contigs using Lasergene software (DNAStar, Madison, WI, USA) and analyzed using
BLASTX and TBLASTX (11). For each contig, the nucleotide sequence with highest
homology that had an annotated physiological role and an E-value of less than 0.01 using
TBLASTX was chosen (Table 3.1). All DNA sequences were submitted to GenBank at the
National Center for Biotechnology Information (http://blast.ncbi.nlm.nih.gov/) and grouped
into the categories according to their putative physiological function, such as protein
synthesis and processing, signal transduction and post-translational regulation, defenserelated, abiotic stimuli and development, hypothetical proteins, and no homology to known
proteins (52). The isoelectric point (pI) was calculated for the homologous protein sequence
of each putative plant EST using the ProtParam tool at the ExPASy Proteomic Server
(http://ca.expasy.org/tools/protparam.html).
63

Semi-quantitative RT-PCR and origin determination
Total RNA was extracted from epidermal peels at each of the time points as described
above and treated with the DNA-free kit. cDNA was then synthesized using SuperScript III
Reverse Transcriptase (Invitrogen) and an oligo DT primer (20 bp). Two independent cDNA
synthesis reactions were performed per sample. Eight expressed sequence tags (ESTs) were
chosen based on their sequence similarities with genes or proteins related to disease
resistance (EST01, EST03, EST04, EST05, EST08, EST10, EST11, and EST13), and
primers were constructed for each EST using Primer Express Software (Applied Biosystems,
Foster City, CA, USA) (Table 3.2). Primers were optimized by varying primer concentration
and annealing temperature. A protocol using 25 cycles, a 58ºC annealing temperature, and
300 nM of each primer was found to be consistently optimal across the different primer sets.
Semi-quantitative RT-PCR was carried out to determine the presence or absence of gene
transcripts in both cultivars following inoculation. PCR reactions always contained cDNA
reverse transcribed from 1.0 µg of total RNA as the template, which was extracted from 100mg of tissue aliquots (~5-6 epidermal peels). The amplification protocol included an initial
denaturation step at 94ºC for 2 min followed by 25 cycles at 94°C for 1 min, 58ºC for 1 min,
and 72°C for 1 min and 30 sec. The reaction was completed by a 10-min extension at 72ºC.
PCR products were separated on a 2.0% agarose TAE gel. Experiments were repeated with
two independent biological samples. For all time points, the putative actin protein described
above was used as an internal loading standard. Semi-quantitative RT-PCR products were
sequenced to ensure that the correct gene was being amplified from the template.

64

Additionally, the DNAse-treated total RNA of each sample was tested for evidence of
contaminating genomic DNA by using it as a template in a PCR reaction with the putative
actin gene primers.
To confirm the plant or fungal origin of each EST, DNA was extracted from fungal
mycelium according to (113) and from young leaves of ‘Elliott’ and ‘Jersey’ blueberry plants
according to (57). To confirm the presence of genomic DNA, the putative actin gene and the
fungal internal transcribed spacer region (ITS) were amplified using PCR with the primers
ACT-F/ACT-R (Table 3.2) and ITS1F/ITS4 (71), respectively. Finally, PCR was performed
as described above using extracted genomic DNA (using 35 instead of 25 cycles) and
appropriate primers for semi-quantitative RT-PCR (Table 3.2). PCR products were
visualized on a 2.0% agarose TAE gel.

Quantitative RT-PCR
For quantitative reverse transcriptase PCR (Q-RT-PCR) the same primers were used
as described above in order to validate the previous techniques using two independent
biological samples (Table 3.2). Q-RT-PCR was performed to detect differences in transcript
levels of the selected ESTs and to look for an induction at particular time points following
infection in both cultivars. For each sample, 1.0 µg of treated RNA was converted to cDNA
using the protocol described above. Amplification was determined by using SYBR Green
PCR Master Mix (Applied Biosystems) in the Applied Biosystems 7900HT sequence
detection system (Research Technology Support Facility, Michigan State University, East
Lansing, MI, USA). The appropriate primers were used at a concentration of 300 nM under
the following conditions: 50°C for 2 min, 95°C for 10 min, and 40 cycles of 95°C for 15 sec

65

followed by 60°C for 1 min. (Table 3.2). PCRs were carried out in triplicate and were
conducted at least twice, and the mean of the three replicates was used to generate an average
concentration. Using a dilution series, cDNA from a representative sample (‘Elliott’
inoculated, 96 hpi) was used to generate standard curves and threshold values (CT) for each
EST of interest. Standard curves were considered reliable if slopes were between -2.9 and 3.5. The quality of the amplification was assessed by dissociation curves, and product size
was verified by gel electrophoresis. The concentration mean of each EST was then
normalized to the endogenous putative actin control to obtain the normalized value for each
gene. Samples were also tested for the presence of contaminating genomic DNA in the
treated RNA samples prior to cDNA synthesis using the DNA-free kit mentioned above.

H2O2 detection
Green and ripe fruit were collected from the same location described above on 2
August 2010 and stored at 4°C. No fungicides were applied in the last 3 weeks prior to
harvest. Fruit were inoculated with a 10-µl drop of an aqueous suspension containing 10

6

conidia/mL or water (untreated control) and then placed equidistantly on wire mesh grates in
Petri dishes at 100% RH. After 0, 12, 18, 24, and 48 hpi, inoculated peel sections were
excised with a cork borer (size 1, 4.5-mm diameter). H2O2 was detected using the Amplex®
Red Hydrogen Peroxide/Peroxidase Kit (Invitrogen) as described in (4) with the following
exceptions: epidermal peels of ~4.5mm in diameter were used instead of a fruit disk (10 mm
diameter and 10 mm deep), and the reaction volume was 1 mL of phosphate buffered saline
as opposed to 5 mL. A standard curve plot was used to calculate the H2O2 concentration
66

2

using a 10-fold-dilution series from 1 millimole to 1 nanomole of H2O2 (R = 0.95). Based
on this curve, values in the 1-mL reaction ranged between 1 and 754 nanomoles and these
2

values were divided by the total area of the peels (3 peels x 15.9 mm per peel) to calculate
2

the concentration in nanomoles/mL/mm . Three independent experiments were conducted
with five replicates per treatment.

RESULTS
Inoculation of C. acutatum at different stages of fruit development
Detached fruit inoculation experiments demonstrated a host resistance phenotype
that was previously described by Wharton and Schilder (2008). In the susceptible cultivar
Jersey, conidial masses were seen as early as 5 d after inoculation, and at 8 d started to
coalesce and cover the entire surface of the fruit (Figure 3.1A, C). Acervulus diameter
ranged from 56–224 µm with an average of 126 µm (Figure 3.2A), and an average of 2.65 x
7

10 conidia were produced per berry (Figure 3.2B). In the resistant cultivar Elliott, berries
remained firm and acervuli were not visible until 8 d after inoculation (Figure 3.1B).
Acervuli were few and constricted, with small orange cirrhi. The average acervulus diameter
was less than half of that on ‘Jersey’ fruit: 58 µm with a range of 26–106 µm (Figure 3.1D).
6

About tenfold fewer conidia (2.8 x 10 per berry) were produced in ‘Elliott’ compared to
‘Jersey’ (Figure 3.2B).
Examination of pre-penetration activities of C. acutatum on immature fruit of both
cultivars showed similar rates of conidium germination and appressorium formation.

67

A

B

C

D

Figure 3.1. Symptoms and signs of Colletotrichum acutatum infection of highbush blueberry
fruit A) Fruit appearance 8 d after inoculation in the susceptible cultivar Jersey, and B) the
resistant cultivar Elliott. Scanning electron micrograph of acervuli on the fruit surface of C)
‘Jersey’ and D) ‘Elliott’. Bar = 0.5 mm.

68

n = 50

A

6

120

35
b

100
80
60

Number of conidia per berry (10 )

Acervulus diameter (micrometers)

140

a

40
20
0

30
25

n=5

B

b

20
15
10
5
a

0
Jersey

Jersey

Elliott

Elliott

Figure 3.2. A) Average diameter of acervuli of C. acutatum on fruit of the susceptible
blueberry cultivar ‘Jersey’ (white bars) and resistant cultivar ‘Elliott’ (black bars) (n = 50).
B) Quantity of C. acutatum conidia produced on ‘Jersey’ (open bars) and ‘Elliott’ (closed
bars) after 8 d of incubation (n = 5). Error bars denote standard error of the mean. Means
with the same letter are not significantly different from each other according to Student’s
paired t-test (P < 0.05).

69

Melanized appressoria (%)

100

80

60

Jersey
Elliott
a

b
a

a

a

a

a

a

40

20

0
Petal fall

Green fruit

Fruit coloring

Ripe fruit

Fruit development stage
Figure 3.3. The percentage of C. acutatum conidia that formed melanized appressoria at 24 h
post inoculation on blueberry fruit at different stages of development in the susceptible
cultivar Jersey (white bars) and resistant cultivar Elliott (black bars). Error bars denote the
standard error of the mean (n = 5). Within each development stage, means with the same
letter are not significantly different from each other according to Student’s paired t-test (P <
0.05).

70

However, on ripe fruit, significantly more conidia had germinated and formed melanized
appressoria by 24 hours post inoculation (hpi) on ‘Jersey’ than on ‘Elliott’ (Figure 3.3). Since
the formation of melanized appressoria indicates attempted penetration of the plant
epidermis, the infection process appears to advance more rapidly in ‘Jersey’ than in ‘Elliott’.
However, by 48 hpi, 96 to 100% of germinated conidia had produced melanized appressoria
regardless of fruit developmental stage or cultivar.

Suppression subtractive hybridization of ‘Elliott’ and ‘Jersey’ cDNA libraries
We constructed two representative subtracted cDNA libraries of ripe fruit from
‘Elliott’ and ‘Jersey’, each containing five discrete time points (0, 24, 48, 96, 144 hpi)
following inoculation with C. acutatum. The pooled subtracted ‘Elliott’ cDNA library was
cloned into the vector pGEM-T-Easy, and we screened 1,056 clones against the pooled
subtracted ‘Jersey’ library. Using Southern blot analysis, 37 clones were found to be
differentially expressed (Figure 3.4). DNA sequence analysis using TBLASTX identified
significant homology of these clones with genes producing proteins involved in a variety of
cellular processes. The 37 clones were grouped according to their putative physiological
function, including defense-related (5 clones), abiotic stimuli and development responses (4
clones), protein synthesis and processing (3 clones), signal transduction and posttranslational regulation (1 clone), and hypothetical proteins (9 clones) (Tables 3.1 and B.1).
As was the case in similar studies conducted to date, a large number (41%) of DNA
sequences had no significant homology to known genes. Additionally, the theoretical
isoelectric point (pI) of the most homologous protein was also calculated for each putative
plant EST. A class II chitinase (EST01) and a beta-1,3 glucanase (EST08) were found to be

71

Table 3.1. Characteristics and predicted physiological function of differentially expressed sequence tags (ESTs) from ripe fruit of
highbush blueberry cultivars Elliott versus Jersey after inoculation with Colletotrichum acutatum.The hypothetical function is based
on homology to sequences in translated nucleotide databases (DDBJ/EMBL/GenBank) using TBLASTX. This table only displays
-5

putative plant sequences with homologous E values lower than 1 x 10 .

ID code

a

Size
b
(bp)

Redundancy

c

Genbank
Accession
No.

Homologous Gene
(BLAST Hit Accession
Number)

Homologous
Species

Max
Score

Class II chitinase
(AB465728)
Beta-1,3-glucanase
(X75946)
Pathogenesis-related
protein 10 (AM489568)

Vaccinium
corymbosum

353

5.0 x 10

Beta vulgaris

72.1

3.0 x 10

Actinidia
deliciosa

71.2

2.0 x 10

Monodehydroascorbate
reductase (EU327873)
Metallothionein-like
(AY857933)
Hydroxyproline-rich
glycoprotein precursor
(U18791)
Dihydroflavonol 4reductase (AY221249)

Vaccinium
corymbosum
Gossypium
hirsutum

127

7.0 x 10

100

3.0 x 10

Phaseolus
vulgaris

40.9

6.0 x 10

Allium cepa

51.5

1.0 x 10

E value

pI

d

Defense-related
e

EST01*

432

1

GW397252

EST08*

159

1

GW397259

EST10*

239

3

GW397261

-95

8.82

-11

9.37

-10

5.36

-28

5.78

-19

4.83

-5

9.70

-5

5.86

Abiotic stimuli and development
EST03*

186

1

GW397254

EST05*

236

1

GW397256

EST07

138

1

GW397258

EST11*

389

1

GW397262

72

Table 3.1 (cont’d).
Protein synthesis and processing
Small nuclear
EST06
223
1
GW397257
ribonucleoprotein E
(EU974208)
Signal transduction and post-translational regulation
Ubiquitin-conjugating
EST04*
220
1
GW397255
enzyme (NM_104180)
a

b

68.9

4.0 x 10

9.03

Arabidopsis
thaliana

-21

1.0 x 10

6.22

101

-19

Zea mays

c

d

ID code = identification code; bp=number of base pairs; = number of times sequence was recovered; = theoretical isoelectric
e

point (pI) of the most homologous protein; = * denotes ESTs selected for further study.

73

Table 3.2. Primer DNA sequences, guanine-cytosine (GC) percentages, calculated primer melting temperatures (Tm), expected
product size, product melting temperature, Q-RT-PCR standard curve plot slope, and calculated primer efficiency used in semiquantitative and quantitative RT-PCR expression analysis of differentially expressed sequence tags in blueberry fruit in response to C.
acutatum inoculation.

Primer
Name

Sequence (5’-3’)

EST01-F
EST01-R
EST03-F
EST03-R
EST04-F
EST04-R
EST05-F
EST05-R
EST08-F
EST08-R
EST10-F
EST10-R
EST11-F
EST11-R
EST13-F
EST13-R
ACT-F
ACT-R

ATC CCC GGT AGT TCC AAA AC
TGA GGA CTC TGG CAC TCC TT
CAG ATT GGA GCT TTT GTT CTT ATG G
GGA AGA AAT GCT TAT TCA GCC TAC A
GGG CAG ACC TTA CCA CAA TCA
TGG CGG TCT TCG AAT AAA CC
GAG GTA CCG CAC TTG CAC TT
CCA TTC ACA CCC AAG CTA CA
TCC AGT CAA GAA GCA GTT GAC C
CAT CCT TCC AAT GCC ATT GG
ACC CTA CAA TGT CTT TCA CCA ACA
CGG CCG AGG TAC TTT CCA C
GTG TTC ACA TCG TCT GCT GGA
TCG GTT GTT GGT GCT CTT GA
ACC AGC CCG TCT TTA GTC CT
TGA GCA CGT TGC CTG TTA CT
TCA AGA GCC ACG TAT GCA AG
TGC CCT CAT GAA GAT CCT TAC

Primer
GC
(%)

Primer
Tm(°C)

50.0
55.0
40.0
40.0
52.4
50.0
55.0
50.0
50.0
50.0
41.7
63.2
52.0
50.0
55.0
50.0
50.0
47.6

54.8
57.9
59.0
59.0
57.1
55.2
57.7
55.0
57.1
54.3
56.5
58.2
58.0
59.0
58.1
56.9
55.2
54.2

74

Size
(number
of base
pairs)

Product
Tm (°C)

Q-RT-PCR
Standard
Curve Plot
Slope

Q-RT-PCR
Primer Set
Efficiency
(%)

206

81.3

-3.30

100.9

98

74.1

-3.32

100.0

50

73.5

-3.53

91.9

225

83.2

-3.38

97.5

50

73.4

-3.21

104.9

50

74.0

-3.12

109.1

52

75.9

-3.24

103.5

197

79.8

-2.95

118.1

105

78.8

-3.47

94.3

1
A

2 3 4
(-) EV

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

1000
500
200

B

C

Figure 3.4. Suppression subtractive hybridization to detect differential expression of genes in
‘Elliott’ (resistant) compared to ‘Jersey’ (susceptible) blueberry fruit after inoculation with C.
acutatum. A) Colony PCR products obtained from forward-subtracted ‘Elliott’ cDNA library with
T7 and Sp6 primers used for dot blot analysis and visualized through gel electrophoresis. Lanes 1
and 24, 1-kb+ DNA ladder; lane 2, negative control; lane 3, EV=empty vector; lanes 4 through 23
PCR products from ‘Elliott’ forward-subtracted cDNA library. B) PCR products from the forward
‘Elliott’ library hybridized with the reverse ‘Jersey’ library DIG probe. C) PCR products from the
forward ‘Elliott’ library hybridized with the forward ‘Elliott’ DIG probe. Dotted lines surround the
actin PCR product which served as an internal standard.

75

fairly basic (pI = 8.82 and 9.37, respectively). However, other homologous proteins were found to
be acidic such as metallothionein-like (EST05) protein and pathogenesis-related protein 10
(EST10) (pI = 4.83 and 5.36, respectively).

Expression profiling and origin determination of selected ‘Elliott’ clones
5

Eight ESTs with significant homology (E value < 1.0 x 10- ) to known protein and gene
sequences in the translated nucleotide database at the National Center for Biotechnology
Information were further analyzed (Table 3.1). Specific primers were designed for analysis of
temporal expression profiles through semi-quantitative RT-PCR (Table 3.2). Among these ESTs
were a class II chitinase (EST01), monodehydroascorbate reductase (EST03), ubiquitinconjugating enzyme (EST04), metallothionein-like protein (EST05), beta-1,3-glucanase (EST08),
pathogenesis-related protein 10 (EST10), dihydroflavonol 4-reductase (EST11) and a hypothetical
protein from Mus musculus (EST13). EST13 was chosen because it had weak homology to a
barley (Hordeum vulgare) cysteine proteinase inhibitor (accession number CAG38123, E value
4.3, maximum identity 27%) using BLASTX, and according to the CATH version 3.3
classification, it structurally contains a domain common in other plant cysteine proteinase
inhibitors known as superfamily 3.10.450.10 (E value 1.4 x 10

-05

) (142). In all cases, EST

expression increased at an earlier time point in the host-pathogen interaction in ‘Elliott’ than in
‘Jersey’. Many of the ESTs in ‘Elliott’ were detected as early as 24 hpi, while others were detected
at 48 hpi (Figure 3.5A). None of the ESTs was detected prior to inoculation, except
dihydroflavonol 4-reductase (EST11), which was constitutively expressed. Also, the initial total
RNA preparation after a DNAse treatment yielded no measurable amplification when visualized

76

A

Jersey

0

24

48

B

Elliott

96 144

0

24 48

96 144

Hours after inoculation

EST01

EST01

EST03

EST03

EST04

EST04

EST05

EST05

EST08

EST08

EST10

EST10

EST11

EST11

EST13

EST13

Actin

Actin
ITS1F –
ITS4

Figure 3.5. Temporal pattern of transcript accumulation and origin determination of putative genes
in blueberry fruit of the resistant cultivar Elliott and the susceptible cultivar Jersey after
inoculation with C. acutatum. A) Transcript accumulation of expressed sequence tags (Table 3.1)
at 0, 24, 48, 96, and 144 hours post inoculation in semi-quantitative RT-PCR. B) The origin of the
ESTs as determined by PCR using genomic DNA from ‘Elliott’, ‘Jersey’ and C. acutatum. In A
and B, experiments were performed with specific primers constructed for each individual EST of
interest (Table 3.2). Controls were performed with primers specific for actin (Table 3.2) and the
fungal ITS region (ITS1F-ITS4).

77

EST/ actin expression

1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0

B

A

Monodehydroascorbate reductase
(EST03)

Class II Chitinase (EST01)

C

D

Ubiquitin-conjugating enzyme
(EST04)

Metallothionein-like (EST05)

E

F
PR10 (EST10)

Beta-1,3-glucanase (EST08)

G

H

Dihydroflavonol 4-reductase
(EST11)

0

20 40

Jersey-inoculated

60

Hypothetical protein
(EST13)

80 100 120 140
0 20 40
Hours after inoculation
Jersey-water

Figure 3.6.
78

60

80 100 120 140

Elliott-inoculated

Elliott-water

Figure 3.6 (cont’d.). Ratio of transcript accumulation of expressed sequence tags (ESTs) relative
to actin in quantitative RT-PCR at 0, 24, 48, 96, and 144 hours post inoculation of ripe blueberry
fruit of a susceptible cultivar Jersey and a resistant cultivar Elliott with C. acutatum or water
(control). Mean expression levels were normalized with mean endogenous actin levels, and an
induced sample was used to generate the standard curve plots for each individual EST. ∆Rn
thresholds varied between 0.15 and 0.75. Error bars denote standard error of the means of the
replicates within a representative experiment (n = 3).

79

through gel electrophoresis, indicating that the genomic DNA was eradicated from the samples
following the DNAse treatment. Additionally, sequencing of the semi-quantitative RT-PCR
products indicated that the designed primers were amplifying their intended targets.
The origin (plant or fungal) of the eight ESTs was then determined by PCR using the
putative actin and the fungal internal transcribed spacer (ITS) as controls. PCR products for all
eight of the ESTs were only seen when using the genomic DNA of the host plant as the template
for the PCR reaction (Figure 3.5B). No PCR products were observed in the reaction with fungal
genomic DNA, except for the control ITS1F-ITS4 reaction. This indicates that all of the selected
ESTs originated from the host plant.
Using quantitative RT-PCR, selected ESTs were also detected earlier in ‘Elliott’ than
‘Jersey’ (Figure 3.6). Throughout the experiments, the expression of putative actin remained
relatively constant. For this reason the putative actin gene was treated as an endogenous control
and the expression of the candidate genes was normalized with it. In general, normalized
expression levels began to increase at 24 hpi (EST01, EST03, EST04, EST08, EST10, EST11 and
EST13) and 48 hpi (EST05) in ‘Elliott’. If there was expression in ‘Jersey’, it visibly increased at
48 hpi (EST11) and 144 hpi (EST01, EST05, EST10, and EST13). There was virtually no
expression of any of the selected ESTs in the water-treated control of either cultivar (Figure 3.6).

Oxidative burst in green and ripe fruit after inoculation with C. acutatum
Based on the identification and temporal expression of genes putatively involved in the
oxidative burst response, we monitored the accumulation of H2O2, an indicator of reactive oxygen
species, in inoculated epidermal peels of green and ripe fruit of both cultivars. Measurements were
taken at 0, 12, 18, 24, and 48 hours after inoculation with C. acutatum. Overall, H2O2 levels were
80

2

H2O2 (nanomoles/mL/min )

0.8
0.6

A
Green fruit

n=5

n=5

12

0.4

8

0.2
0.0

16 B
Ripe fruit

4
0

10
20
30
40
50
Hours post inoculation
Jersey-water
Jersey-inoculated

0

0

10
20
30
40
50
Hours post inoculation
Elliott-inoculated
Elliott-water

Figure 3.7. H2O2 accumulation in epidermal peels of green and ripe fruit of the susceptible
blueberry cultivar Jersey and resistant cultivar Elliott inoculated with C. acutatum or water
(control) at 0, 12, 18, 24 and 48 hours post inoculation (n=5). H2O2 was detected by the Amplex®
Red Hydrogen Peroxide/Peroxidase Kit. Results from a representative experiment out of three
independent experiments are displayed.

81

significantly lower in green fruit than in ripe fruit (Figure 3.7). An increase in H2O2 was observed
at 18 h and a peak at 24 h after inoculation in both cultivars regardless of fruit maturity stage.
However, H2O2 levels were two to three times higher in ‘Elliott’ than in ‘Jersey’. Even in the
water control, the initial and maximum H2O2 concentrations were higher in ‘Elliott’ than in
‘Jersey, particularly in green fruit.

DISCUSSION
Following direct penetration of host tissues, Colletotrichum species have two different host
colonization strategies depending on the host or tissue being colonized: intracellular hemibiotrophy
or subcuticular intramural necrotrophy,(43, 53, 75, 137, 151). Wharton and Schilder (2008) linked
the strategy of subcuticular intramural necrotrophy by C. acutatum on blueberry to host plant
resistance and noted defense responses such as the production of amorphous phenolic globules
around intracellular hyphae. They also observed a lower rate of conidium germination and
appressorium formation on the resistant cultivar Elliott compared to the susceptible cultivar Jersey.
However, they did not investigate the infection process on immature fruit. Our results suggest that
differences in pre-penetration activities of C. acutatum are confined to ripe fruit, as no differences
were observed on immature fruit of the two cultivars. The difference appears to be the result of a
relative increase in the rate of appressorium formation on ‘Jersey’ as the fruit ripens, whereas the
rate on ‘Elliott’ remains steady across fruit development stages. A possible reason for this
phenomenon could be a change in the structure or composition of the waxy cuticle in ‘Jersey’ fruit
that stimulates conidium germination and appressorium formation. In avocados, cuticular wax has

82

been shown to trigger conidium germination and appressorium formation of C. gloeosporioides
(148). More research is needed to determine the cause of the observed differences.
This study represents the first investigation of gene expression in a VacciniumColletotrichum interaction at different stages of the infection process and provides additional
evidence for an active resistance response in the blueberry cultivar Elliott. It appears that this
cultivar recognizes the pathogen at an earlier time point during infection than the susceptible
cultivar Jersey, as expression of defense-related and other genes was detected earlier in ‘Elliott’
than in ‘Jersey’, often within 24 hours after inoculation. Given the scarcity of DNA sequence
information for blueberry and Vaccinium spp. in general, the most limiting constraint on these
experiments was the identification of homologous sequences. Many of the differentially expressed
DNA sequences (41%) found in this study had no homology to known sequences. In addition,
pooling of cDNA from multiple time points after inoculation into a single cDNA library for each
cultivar for cost-efficient SSH screening may have reduced our ability to detect certain genes that
were differentially expressed at specific time points. For example, defense genes expressed late in
the infection process in the susceptible cultivar could have masked early over-expression in the
resistant cultivar. In addition, cloning the cDNA library of ‘Elliott’ only could have limited our
ability to detect specific plant genes that were upregulated in ‘Jersey’ as well as fungal genes that
were upregulated in the compatible host-pathogen interaction.
Nonetheless, this study provides valuable new insight in the molecular mechanisms
underpinning fruit rot resistance in blueberries and also forms a basis for comparing defenseassociated genes of blueberry fruit tissue with those of other plant species. The selected ESTs may
be useful in the development of markers for breeding new disease-resistant cultivars and as
possible markers for the expression of systemic acquired resistance (SAR).

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Limited research has been done on the molecular basis of host plant resistance to the fruit
rot pathogen C. acutatum. In strawberries, researchers found that several defense-related proteins
such as peroxidases and chitinases were induced in infected fruit. Interestingly, they also noticed
reduced expression of defense-related genes in the susceptible cultivar as opposed to an induction
in the resistant cultivar (31). In addition, expression was found to be tissue-dependent when
comparing infected fruits and crowns. We investigated the expression profiles of three putative
defense-related genes: a class II chitinase (EST01), beta-1,3-glucanase (EST08), and pathogenesisrelated protein 10 (EST10). These genes have been classically identified as pathogenesis-related
proteins, i.e. they are induced upon pathogen inoculation and are also known to be important in the
hypersensitive response (190). Furthermore, given the homology of EST08 and EST01 with other
known proteins and their induction upon pathogen inoculation, they could also be referenced as
PR-2 and PR-3, respectively (190). When these genes are overexpressed in plant tissue, the result
is often increased disease resistance. For example, in transgenic tobacco plants, the overexpression
of a chitinase gene led to broad resistance against the fungal pathogen Rhizoctonia solani and the
bacterial pathogen Pseudomonas syringae pv. tabaci (44). Interestingly, the class II chitinase
(EST01) that we identified has also been shown to accumulate in stems of blueberries at low
temperatures and appears to be important in cold hardiness (100). Both EST01 and EST08 are
homologous to genes coding for basic proteins, i.e. their expression is most likely linked to the
ethylene/jasmonic acid pathway, and the proteins are likely not secreted into the apoplast.
However, the most homologous protein to EST10 was in fact acidic, suggesting it may be linked to
the salicylic acid signaling pathway, and could be secreted into the plant apoplast during infection
(190).

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In the group of ESTs related to abiotic stimuli and development, the dihydroflavonol 4reductase gene (EST11) was expressed constitutively, but expression was boosted by inoculation
with C. acutatum in both cultivars, albeit earlier in the infection process in ‘Elliott’ than in
‘Jersey’. This enzyme typically catalyzes the reduction of leucoanthocyanidins to anthocyanidins
(133). Previous research has shown an accumulation of anthocyanins in ‘Elliott’ in response to
infection by C. acutatum (124). This gene possibly plays a role in the production of anthocyanins
and maybe an antifungal compound detected in ‘Elliott’ fruit and capable of inhibiting the growth
of C. acutatum in vitro (Miles and Schilder, unpublished).
Other identified genes such as monodehydroascorbate reductase (EST03) and a
metallothionein-like protein (EST05) are often associated with oxidative stress and protecting the
plant from oxidative damage (108, 115). In the C. acutatum-blueberry fruit pathosystem, the
timing of the increase in H2O2 is similar to that previously published in the C. coccodes-tomato
fruit interaction (122) and seems to correlate well with the formation of melanized appressoria
(201), indicating attempted penetration. However, reactive oxygen species may be plant or
pathogen derived. If it is plant derived, the H2O2 may be important in the resistance response in
‘Elliott’ by preventing fungal penetration. On the other hand, if the H2O2 is pathogen derived this
could indicate preferential necrotrophy of C. acutatum on ‘Elliott’ fruit. Since H2O2 can be a
pathogenicity factor for necrotrophic pathogens, it may be important in the initial colonization of
‘Elliott’ fruit. However, because of the relatively short duration of the H2O2 boost and coincident
timing with peak appressorium formation, it seems likely that it serves to prevent pathogen ingress.
In either case, the above-mentioned genes are likely upregulated in ‘Elliott’ fruit to prevent
oxidative damage to plant tissues.
85

The ubiquitin-conjugating enzyme or E2 ligase gene we identified (EST04) was present in
both ‘Elliott’ and ‘Jersey’ but appears to be expressed only in ‘Elliott’. The ubiquitin-proteasome
system is important in signal transduction in cellular processes including defense responses (181).
E2 ligases enzymatically transfer ubiquitin and bind with E3 ligases, which target proteins for
proteasomal degradation by ubiquitination. However, there is also evidence that E2 ligase genes
can be upregulated in response to elicitors (184), UV light (160), and heat shock (66). The
identified E2 ligase may play a role in the resistance response in ‘Elliott’ fruit.
Our results clearly show a time delay between inoculation and measurable gene expression.
Consequently, there was a significant lag period before a defense response was detectable, which
would correlate well with previous microscopy studies outlined in Wharton and Schilder (2008).
This could be due to the amount of time required by the host for measurable expression of defenserelated genes or delayed recognition of the invading pathogen by the host. In support of the latter
hypothesis, a similar result was observed in sorghum mesocotyls when inoculated with C.
sublineolum (118). While the expression of PR-10 was detected as early as 4 h after inoculation
with the fungus Cochliobolus heterostrophus, the authors did not record significant expression of
PR-10 until 36 h and peak expression at 48 h after inoculation with C. sublineolum (118).
Therefore, the lag period in the C. acutatum-blueberry pathosystem is most likely due to the
amount of time required by the fungus to gain entry and be recognized by the host.
Our results add new insight into the host responses of blueberry fruit to infection by C.
acutatum at the molecular level and suggest that pathogen ingress into the host is required for the
activation of resistance. A more detailed investigation of gene expression during the early stages of
infection, including pre-penetration events, will help to pinpoint when the host first recognizes that
it is being attacked by C. acutatum and initiates the resistance response. Furthermore, chemical

86

analysis and studies on the genetic inheritance of resistance will complement molecular research in
elucidating the basis of anthracnose fruit rot resistance in blueberries.

ACKNOWLEDGEMENTS
I would like to gratefully acknowledge funding from Michigan State University Project
GREEEN (Generating Research and Extension to meet Economic and Environmental Needs). I
would also like to thank Dr. James Hancock and Hortifrut Chile S.A. for providing fruit, Dr.
Miaoying Tian for technical training, Christine Bates for technical assistance, and Dr. Paul
Goodwin (University of Guelph, Canada) and Dr. Raymond Hammerschmidt for critical review of
the manuscript.

87

CHAPTER IV: CHARACTERIZATION AND BIOLOGICAL ACTIVITY OF FLAVONOIDS
FROM RIPE FRUIT OF AN ANTHRACNOSE-RESISTANT BLUEBERRY CULTIVAR

ABSTRACT
Anthracnose fruit rot, caused by Colletotrichum acutatum, is among the most important
diseases of blueberries. Most cultivars are susceptible but ‘Elliott’ is resistant. Our objective was to
identify possible antifungal compounds that play a role in the resistance response. Chemical
fractions from freeze-dried, ripe fruit of ‘Elliott’ and the susceptible cultivar Jersey were extracted
with methanol and ethyl acetate. Extracts were screened on solid media for suppression of
microconidiation of C. acutatum. The methanolic extract was fractionated and the soluble
methanolic fraction from ‘Elliott’ was the most biologically active. This fraction was dried,
dissolved in water, and screened in vivo by pre-treating ripe ‘Jersey’ fruit with 0.5, 1, 2, and 4%
solutions (w/v) and subsequently inoculating the fruit with C. acutatum. An 88% reduction in
infection incidence was observed after 12 days with the 4% solution. Anthocyanins and other
flavonoids were then quantified in fruit of the two cultivars using HPLC-MS. ‘Elliott’ fruit
contained more anthocyanins (4.87 mg/g of freeze-dried tissue) than ‘Jersey’ (3.27 mg/g of freezedried tissue); however, the same compounds were found in both cultivars. ‘Elliott’ fruit also
contained more non-anthocyanin flavonoids (0.18 mg/g of freeze-dried tissue) than ‘Jersey’ (0.12
mg/g of freeze-dried tissue), including two unique compounds in ‘Elliott’. The non-anthocyanin
flavonoid fractions of both ‘Elliott’ and ‘Jersey’ significantly decreased the growth of C. acutatum
in a liquid bioassay, and the effect was somewhat more pronounced in the ‘Elliott’ fraction.
MS/MS analysis of the two unique ‘Elliott’ compounds was also conducted. These results provide

88

new insights into the role of anti-fungal compounds in the resistance response in ripe ‘Elliott’
blueberries.

INTRODUCTION
Anthracnose fruit rot caused by the fungus Colletotrichum acutatum J.H. Simmonds is a
major postharvest disease of blueberries (Vaccinium corymbosum L.). Most blueberry cultivars are
susceptible to anthracnose fruit rot but some resistant blueberry cultivars exist (150). The
blueberry cultivar Elliott has been consistently identified as resistant to C. acutatum, whereas the
cultivar Jersey has been identified as susceptible (84, 150). However, the mechanism of disease
resistance is not known. Screening attempts have found no correlation between resistance to fruit
and foliar infection (64) or the production of antimicrobial fruit volatiles (149).
Host-pathogen interactions have only been well characterized in a few Colletotrichum-fruit
pathosystems, including avocado, citrus, and mango (23, 189), and most of the information on
resistance mechanisms in fruit comes from studies of C. gloeosporioides on avocado (153, 159). A
microscopy study of infection of ripe blueberry fruit by C. acutatum showed different infection
strategies depending on the cultivar being colonized. In addition, an accumulation of amorphous
phenolic globules was observed around the site of infection in the resistant cultivar (201). More
recent studies have identified an oxidative burst following infection (125) and higher sugar content
in resistant blueberry cultivars (126). However, the role of antifungal compounds in the resistance
response also needs to be investigated.
The biochemical composition, particularly anthocyanin content, of ripe blueberry fruit has
been investigated from a nutraceutical perspective (90, 95, 97, 152). However, the role of chemical
constituents in host plant defense in blueberries to plant pathogens is largely unknown. Several

89

studies have been carried out on the antifungal properties of extracts of ripe fruit from wild
highbush blueberry plants as they relate to fruit decay and herbivore preference (37-39). Although
these studies did not investigate cultivated blueberries or identify individual compounds, they
indicated that the main antifungal compounds present in ripe blueberry fruit were water-soluble
phenolics and acids. They also proposed that resistance to fungal decay in ripe blueberries may be
due to an interaction between simple phenolic compounds and organic acids and not necessarily
individual fungitoxic compounds.
Demand for blueberries and other fruit crops continues to rise as the health benefits are
becoming increasingly apparent with respect to cardiovascular and neurodegenerative diseases in
humans (94, 96, 116, 147). Blueberries are rich in antioxidants in the form of anthocyanins and
other phenolic compounds (96). Blueberries contain many different flavonoids: five main classes
of anthocyanins (70), three classes of flavonols (80), and one class of flavan-3-ols (10). In fact,
anthocyanins (the predominate class of flavonoids in blueberries) have been shown to aid in
obesity prevention (91), cardiovascular health (48), act as an anti-inflammatory (196) and have
anti-cancer effects (18, 172, 179) .
Chemical compounds have been implicated in host plant resistance to Colletotrichum spp. in
various crops. For instance, in avocado, antifungal dienes (154) and the flavonoid epicatechin (79)
play a role in ontogenic resistance of unripe fruit to infection by C. gloeosporioides. A reduction in
these compounds as fruit ripens is correlated with increased susceptibility to infection. Researchers
have also identified constitutive alk(en)ylresorcinols in fruit of Colletotrichum-resistant mango
varieties (86). In sorghum, 3-deoxyanthocyanidin accumulated in response to infection by C.
sublineolum and this compound exhibited higher fungitoxicity than other phytoalexin components
(117). Based on microscopic observations in blueberry and chemical resistance mechanisms in

90

other fruit crops mentioned above, the potential role of chemical constituents in the defense against
anthracnose fruit rot in blueberry merits investigation as well. Therefore, the objectives of this
study were to: (1) assess chemical extracts of blueberry fruit for biological activity against C.
acutatum, and (2) identify and quantify specific compounds in the active fractions.

MATERIALS AND METHODS
Plant and fungal material
Ripe fruit of blueberry (Vaccinium corymbosum L.) cultivars Elliott and Jersey were
harvested in August 2010 from mature bushes at the Michigan State University Southwest
Michigan Research and Extension Center in Benton Harbor, MI, USA and a commercial field in
Traverse City, MI, USA. From each cultivar, a composite sample of approximately 10 kg of
blueberries was harvested and transported to the laboratory. For analysis, 0.5 kg of fruit was stored
overnight at -20°C and freeze-dried. Freeze-dried material was stored at -20°C until chemical
extraction.
A single-conidium isolate of Colletotrichum acutatum (#0001) from blueberry fruit
collected in Grand Junction, MI, USA in August of 2006 was used for all experiments. The isolate
was stored as conidia, and cultured in accordance with previous studies (125, 201). For inoculum
production, sporulating cultures were flooded with 3 ml of sterile deionized water (SDW), and
conidia were dislodged using a sterilized L-shaped glass rod. Conidia were counted using a
6

hemacytometer, and a concentration of 10 conidia/ml was achieved via dilution with SDW and
used for all experiments.

91

Chemical extraction and fractionation
Initially, fruits of ‘Elliott’ and ‘Jersey’ (prior to inoculation and 4 days post inoculation)
were homogenized for 5 min with a Sorvall tissue homogenizer (Thermo Fisher Scientific,
Waltham, MA, USA) in 80% acidified methanol (pH = 2.0) and centrifuged at 5,000 x g. The
extraction was dried using a rotory evaporator, and the remaining water portion was lyophilized.
The lyophilized material was dissolved with acidified methanol to a specific concentration (5 g
fresh wt./ml). Insoluble material was then further extracted with ethyl acetate and centrifuged at
5,000 x g. This extraction was then dried down and dissolved in acidified methanol as described
above. Methanolic extracts (5 mg of fresh weight tissue per μl) from ripe fruits of ‘Elliott’ and
‘Jersey’ before and 4 days after inoculation with C. acutatum conidia were loaded onto a 250-µm
cellulose thin layer chromatography (TLC) plate (Analtech Inc., Newark, DE) (50 µl per sample)
and compounds were separated with butanol:acetic acid:water (4:1:5 top phase). Plates were
allowed to dry overnight and then sprayed with an aqueous conidial suspension of C. acutatum
6

(10 conidia/ml). Plates were incubated at room temperature (22 to 24°C) for 60 hours in a 100%
relative humidity chamber and subsequently stained using the gas phase created from iodine
crystals. Areas of inhibition of fungal growth were measured. On a replicate plate, those areas
were removed, dissolved in methanol, and scanned with a UV/Vis spectrophotometer (200 to 600
nm) (Figure C.1).
Since no significant differences were observed between inoculated and uninoculated
‘Elliott’ extracts, further extractions were conducted on fresh, non-inoculated fruit. An exhaustive
extraction with water, methanol, and ethyl acetate from fresh whole fruits was used (Figure C.2).
As described above fresh tissue was homogenized for 5 min with a Sorvall tissue homogenizer in
water (pH = 2.0) and centrifuged at 5,000 x g. The residue was then further extracted in methanol
92

and centrifuged at 5,000 x g. Then the residue was further extracted with ethyl acetate and
centrifuged at 5,000 x g. All fractions were dried using a rotory evaporator or lyophilized and
stored at -20°C for bioassays. Initial screenings on PDA plates (described below) indicated that
the methanolic extract had the most biological activity. Then, a second extraction with methanol
was used on lyophilized ripe fruits of ‘Elliott’ and ‘Jersey’ (Figure C.3). Residue from the second
extraction was further extracted with ethyl acetate. Methanol-soluble and -insoluble fractions were
obtained by stirring the dried methanolic extract in methanol. Anthocyanin and non-anthocyanin
flavonoid fractions were obtained from the methanolic extract by standard laboratory protocols
(163).

Antimicrobial screening of extracts and in vivo activity of the methanol-soluble fractions
6

For the bioassay, 400-µl aliquots of an aqueous suspension of 10 conidia/ml were applied
to the entire surface of full-strength potato dextrose agar plates and allowed to dry. Extracts and
fractions were screened for antimicrobial activity by applying extracts dissolved in dimethyl
sulfoxide (DMSO) directly onto the media (10-µl droplets) at various concentrations (1000, 500,
250, 125, 63, 31, and 16 µg). Plates were incubated without parafilm for 48 hours at 25°C in the
dark and monitored for the inhibition of C. acutatum microconidiation. Extracts or fractions were
considered biologically active if microconidiation was absent. Each extract or fraction was tested
at least twice and all experiments had at least 2 replicates. For in vivo inhibition, the methanolsoluble fraction was dissolved in water at varying concentrations and ‘Jersey’ fruits were
pretreated by immersing fruit in the extract prior to inoculation with C. acutatum using five

93

replicates and 10 fruits per replicate. Fruits were incubated at 100% relative humidity, and disease
incidence was rated at 12 days post inoculation

Identification and quantification of flavonoids
Anthocyanins and non-anthocyanin flavonoids were separated on a 150 x 4.6-mm
Symmetry Shield C18 column with a 5-µm particle size (Waters Corporation, Milford, MA, USA)
at a flow rate of 0.5 ml/min and a column temperature of 25°C using a 2695 Separator Module,
with a photodiode array (PDA) detector (#2996) and a Micromass ZQ mass spectrometer (Waters
Corporation). To obtain anthocyanins, compounds were eluted with a gradient of 10% formate and
1% formic acid in acetonitrile at a flow rate of 0.5 ml/min over a 55-minute period with a gradient
from 5% to 35% acetonitrile. The PDA and MS detectors scanned ions (250-750 m/z in positive
ion mode) at 200- to 550-nm wavelengths in order to identify compounds. Compounds were
identified according to Additionally, published research on retention times, masses, and absortion
spectra was used to identify many of the compounds (152). Non-anthocyanin flavonoid
compounds were eluted with a gradient of 1% formate and 1% formic acid in acetonitrile at a flow
rate of 0.5 ml/min over a 40-minute period with a gradient from 10% to 35% acetonitrile. The
PDA detector scanned ions (250 to 750 m/z in positive ion mode with scan time of 0.3 seconds, an
interscan delay of 0.1 seconds and a source temperature of 140°C) at 200 to 550 nm wavelengths
and in order to identify compounds The standards quercetin-3-O-rhamnoside (Sigma-Aldrich, St
Louis, MO, USA) and quercetin-3-O-glucoside (Sigma-Aldrich) were included.
To quantify anthocyanins and non-anthocyanin flavonoids, 5 g of freeze-dried blueberries
per cultivar were extracted separately and standardized to yield equal volumes of extract per gram
of fresh weight (FW) of fruit. For non-anthocyanin flavonoids, anthocyanins were removed prior
94

to quantification using a SepPak C18 cartridge (Waters Corporation) according to standard
protocols (163). Each extract was then analyzed with duplicate injections. The mean peak areas
from the duplicate analyses were used to read the concentration of anthocyanin from the standard
curve. Data were collected for five replicate samples per cultivar and averaged to determine the
quantity of different compounds. For anthocyanins, a wavelength of 520 nm and a standard curve
plot of cyanidin 3-O-glucoside (Polyphenols Laboratories, Sandnes, Norway) were used. For nonanthocyanin flavonoids, a wavelength of 255 nm and a standard curve plot of quercetin-3-Orhamnoside were used.
The identities of non-anthocyanin flavonoid compounds 08F and 09F (Table 4.2) were
further confirmed by using MS/MS. Analysis was accomplished using a QTRAP 3200 mass
spectrometer (Applied Biosystems/MDS Sciex, Foster City, CA, USA) coupled to a UFLC LC20AD system (Shimadzu Corporation, Kyoto, Japan). The mass spectrometer was operated in the
positive ion mode with a TurboIon Spray source. A daughter ion scan was used using the parent
ions 449 (compound 08F) and 493 (compound 09F) with an initial ionization of 20 V and a
collision voltage of 30 V. The other ionization parameters were as follows: curtain gas (psi), 10;
ion source gas 1 12; ion source gas 2 30; source temperature 400°C; entrance potential 10 V;
collision-activated dissociation high; ion spray voltage 5,500 V. The mass spectrometer and the
HPLC system were controlled by Analyst 1.4.2 software (Applied Biosystems/MDS Sciex).

Liquid bioassay of specific extracts
Minimal media consisting of 0.7% KH2PO4, 0.4% KNO3, 0.3% Na2HPO4, 0.1% MgSO4,
0.03% CaCl2, 1.5% BACTO-agar, and 4% D-glucose and 4% D-fructose (5) was used to grow C.

95

acutatum in the presence of various extracts and fractions (50 μg per 100 μl of culture). Extracts
were dissolved in methanol and applied to wells in 96-well culture plates and allowed to dry.
6

Minimal medium (90 μl) was then applied followed by an addition of 10 µl of 10 washed
conidia/ml. Conidia were washed by centrifuging at 500 x g for 5 minutes and re-suspending the
pellet with an equal volume of water 3 times. Cultures were incubated at 25°C in the dark. Growth
was quantified daily using the change in optical density (λ 590 nm) from day 0. Light absorbance
was read with an EL 800 Universal Microplate Reader (BioTek Instruments, Winooski, VT, USA).
Experiments were repeated twice with three replicate wells per treatment.

RESULTS AND DISCUSSION
Extracts and fractions from the resistant cultivar Elliott suppress microconidiation and
blueberry fruit infection by Colletotrichum acutatum
Extracts and fractions from the resistant cultivar Elliott were more effective at inhibiting
microconidiation of C. acutatum on agar plates than the susceptible cultivar Jersey. In particular,
the methanol, methanol-soluble, and non-anthocyanin fractions were the most biologically active
(Table C.1). The non-anthocyanin flavonoid fraction of ‘Elliott’ was the most effective at
inhibiting microconidiation (activity observed at an amount of 125 µg when applied directly to a
microconidiating C. acutatum culture). In the ‘Elliott’ anthocyanin fraction, activity was only
observed at 1000 µg and no activity was observed in the ‘Jersey’ anthocyanin fraction. No activity
was observed in the ethyl acetate extract of either cultivar (Table C.1). Since, the most active
fraction was the methanolic extract of ‘Elliott’ and higher activity was observed in the nonanthocyanin fraction, this indicates that antifungal compounds were soluble in methanol and were
able to be eluted from a SepPak column with ethyl acetate and are therefore non-polar in nature.
96

80

Infected fruit (%)

60

40

20

0

Treatments

Figure 4.1. Anthracnose infection incidence in fruit of the susceptible cultivar Jersey pretreated
with methanol-soluble fractions from ‘Jersey’ and ‘Elliott’ followed by inoculation with
Colletotrichum acutatum. Bars denote the standard error of the mean (n = 5). From left to right:
Negative control = uninoculated fruit with no extract applied, Positive control = inoculated fruit
with no extract applied, J.M.S. = ‘Jersey’ methanol-soluble fraction, and E.M.S. = ‘Elliott’
methanol-soluble fraction.

97

Non-anthocyanin flavonoids appear to be the primary antimicrobial compounds because the most
active fractions always contained non-anthocyanin flavonoids. Previous research has demonstrated
the antimicrobial activity of non-anthocyanin flavonoids against Colletotrichum species, including
methoxylated flavones (6), isoflavonoids (60), and 3-deoxyanthocyanidins (117).
An 88% reduction in anthracnose infection incidence in ‘Jersey’ fruits was observed when they
were pretreated with a 4% solution of the methanol soluble fraction from ‘Elliott’ (containing
mainly anthocyanins and non-anthocyanin flavonoids) (Figure 4.1). A dose response was evident.
Activity was also observed using ‘Jersey’ fractions but it was not as distinct as ‘Elliott’ and the
dose response was not as distinct. This showed that the extracted compounds also had antifungal
activity in planta.

The resistant cultivar Elliott contains more anthocyanins and non-anthocyanin flavonoids
than the susceptible cultivar Jersey
Overall, ‘Elliott’ fruits contained 4.87 mg anthocyanins per gram of freeze-dried tissue of
and ‘Jersey’ fruits contained 3.27 mg of anthocyanins per gram of freeze-dried tissue. However,
‘Jersey’ had a more diverse anthocyanin profile than ‘Elliott’ (Figure 4.2, Table 4.1). Additionally,
anthocyanidins in ‘Elliott’ tended to be glycosylated with arabinose and galactose, and
anthocyanidins in ‘Jersey’ were more commonly glycosylated with glucose. The ratio of the
different anthocyanins to themselves is similar in ‘Jersey’ to other cultivars including; Coville
(98), Blueray (90), and the Vaccinium ashei Rabbiteye cultivar Tifblue (152), whereas 57% of the
anthocyanins in ‘Elliott’ comprised two compounds: malvidin-3-O-galactoside and malvidin-3-Oarabinoside. No acylated anthocyanins were observed in either cultivar.

98

λ = 520 nm

0.8
AU

0.6
0.4
0.2
A

0.0

0.8
AU

0.6
0.4
0.2
0.0
0
B

5

10

15

20

25

30
Minutes

35

40

45

50

55

Figure. 4.2. HPLC chromatograms of anthocyanins from the anthracnose-resistant blueberry
cultivar Elliott (A) and susceptible cultivar Jersey (B) using 10-μl injections at λ = 520 nm.

99

60

Table 4.1. Anthocyanins from the resistant blueberry cultivar Elliott and the susceptible blueberry
cultivar Jersey identified in HPLC/MS analysis and quantified using HPLC/PDA. Compounds
were putatively identified based on previous research, available spectra, standards, retention times
and m/z ratios. Anthocyanins were quantified at a wavelength of 520 nm using a standard curve
plot of cyanidin 3-O-glucoside.

Compound Compound
a
b
ID
Name

RT

(M+H)
m/z
(Total,
aglycone)

c

d

Elliott ± SE
(µg/g)

d

Jersey ± SE
(µg/g)

01A

Delphinidin 3O-galactoside

15.5

465, 303

583.45 ± 83.83

346.10 ± 64.29

02A

Delphinidin 3O-glucoside

18.2

465, 303

31.13 ± 27.27

201.67 ± 45.08

03A

Cyanidin 3-Ogalactoside

20.1

449, 287

106.77 ± 32.64

68.68 ± 28.46

04A

Delphinidin 3O-arabinoside

22.0

435, 303

406.36 ± 66.87

300.88 ± 56.78

05A

Cyanidin 3-Oglucoside

23.6

449, 287

24.56 ± 24.56

42.63 ± 27.61

06A

Petunidin 3-Ogalactoside

24.4

479, 317

443.85 ± 111.96

209.08 ± 44.86

27.5

419, 287

65.94 ± 28.87

198.36 ± 40.08

27.5

479, 317

++

++

07A

08A

Cyanidin 3-Oe

arabinoside
Petunidin 3-Oe

glucoside

09A

Peonidin 3-Ogalactoside

29.8

463, 301

64.54 ± 29.19

37.05 ± 26.34

10A

Petunidin 3-Oarabinoside

32.2

449, 317

256.31 ± 47.46

163.53 ± 40.61

100

Table 4.1 (con’t.).
11A
12A

Malvidin 3-Of

galactoside

Peonidin 3-Oglucoside

f

33.5

493, 331

1330.57 ± 153.76

452.26 ± 68.51

33.5

463, 301

++

++

13A

Malvidin 3-Oglucoside

37.0

493, 331

71.90 ± 30.64

467.01 ± 67.37

14A

Peonidin 3-Oarabinoside

38.3

433, 301

28.87 ± 28.87

24.56 ± 24.56

15A

Malvidin 3-Oarabinoside

39.5

463, 301

1454.57 ± 240.91

763.07 ± 99.66

4868.82

3274.87

Total
a

Compounds are listed in elution order, and A denotes an anthocyanin.

b
c

RT = retention time.

d
e

Compounds were identified based on UV/Vis spectra, m/z ratios, and previous research.

Data are expressed as µg per gram of lyophilized tissue. Fruit tissue contained 79 to 82% water.

Cyanidin-3-O-arabinoside (419/287) coelutes with petunidin-3-O-glucoside (479/317) (27.5 min).

Petunidin-3-O-glucoside predominates.
f

Malvidin-3-O-galactoside (493/331) coelutes with peonidin-3-O-glucoside (463/301) (33.5 min).

Malvidin-3-O-galactoside predominates.

101

0.08

λ = 255 nm

AU

0.06
0.04
0.02
0.00
A
0.08

AU

0.06
0.04
0.02
0.00
B

20

22

24

26

28

30
Minutes

32

34

36

38

40

Figure 4.3. HPLC chromatograms of non-anthocyanin flavonoids from the anthracnose-resistant
blueberry cultivar Elliott (A) and susceptible cultivar Jersey (B) using 10-μl injections at λ 255 nm.
Arrows denote compounds selected for further analysis.

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Table 4.2. Non-anthocyanin flavonoids from the resistant blueberry cultivar Elliott and the
susceptible blueberry cultivar Jersey identified in HPLC/MS analysis and quantified using
HPLC/PDA. Compounds were putatively identified based on previous research, available spectra,
standards, retention times and m/z ratios. Non-anthocyanin flavonoids were quantified at a
wavelength of 255 nm using a standard curve plot of quercetin 3-O-rhamnoside.
d

d

RT

(M+H) m/z
(Total,
aglycone)

Myricetin rutinoside

23.9

627, 319

3.93 ± 0.29

9.72 ± 0.34

02F

Quercetin rutinoside

26.1

611, 303

10.52 ± 0.41

5.38 ± 0.73

03F

Myricetin pentoside

27.0

451, 319

0.29 ± 0.69

0.27 ± 0.88

04F

Myricetin methyl
pentoside

27.6

465, 319

10.61 ± 0.87

5.39 ± 0.64

05F

Quercetin hexoside

28.1

465, 303

16.19 ± 2.29

56.32 ± 10.39

05F

Quercetin 3-O-glucoside

28.3

465, 303

5.18 ± 0.10

0.45 ± 0.74

06F

Quercetin pentoside

30.9

435, 303

14.53 ± 0.90

28.28 ± 0. 01

07F

Quercetin pentoside

31.8

435, 303

30.78 ± 3.25

12.28 ± 0.31

08F

Quercetin 3-Orhamnoside

32.7

449, 303

61.28 ± 7.70

2.11 ± 1.50

09F

Dimethylmyricetin
methyl pentoside

36.5

493, 347

26.54 ± 2.79

1.06 ± 0.74

179.86

123.28

Compound
a
ID

Compound

01F

b

c

Total
a

Jersey ± SE
(µg/g)

Compounds are listed in elution order, and F denotes a non-anthocyanin flavonoid.

b
c

Elliott ± SE
(µg/g)

Compounds were identified based on UV/Vis spectra, m/z ratios, standards and previous research.

RT = retention time.

d

Data is expressed as µg per gram of lyophilized tissue. Fruit tissue contained 79 to 82% water.

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Furthermore, ‘Elliott’ fruits contained more non-anthocyanin flavonoids (0.18 mg/g of
freeze-dried tissue) than ‘Jersey’ (0.12 mg/g of freeze-dried tissue) (Table 4.2). ‘Elliott’ also had a
more diverse chemical profile than ‘Jersey’, and the majority of non-anthocyanin flavonoids in
‘Jersey’ were made up of compound 05F, likely a quercetin hexoside (Figure 4.3). Some specific
non-anthocyanin flavonoids were almost completely exclusive to ‘Elliott’, including compound
08F (61 µg/g of freeze-dried tissue in ‘Elliott’ versus 2 µg/g of freeze-dried tissue in ‘Jersey’) and
compound 09F (27 µg/g of freeze-dried tissue in ‘Elliott’ and 1 µg/g of freeze-dried tissue in
‘Jersey’).
These two compounds were further characterized using MS/MS. Daughter ions for
compound 08F (parent M+H ion 449) included 303, 147 and 129, indicating an aglycone mass
consistent with quercetin and glycosylated with a methyl pentose (Figure 4.4A). Using a standard
and additional UV/Vis information (peaks at 256 and a shoulder at 350 nm) this compound is
likely quercetin-3-O-rhamnoside (Figure 4.4B). Daughter ions for compound 09F (parent M+H ion
493) included 347, 147 and 129, indicating an aglycone mass consistent with a dimethylmyricetin
and glycosylated with a methyl pentose (Figure 4.4A). Additional UV/Vis information yielded
peaks at 256 and a shoulder at 350 nm and taken with them MS data this compound is likely
dimethylmyricetin methyl pentoside (Figure 4.4B). Dimethylmyricetin methyl pentoside or
plausibly Syringetin-rhamnoside which has been reported in Bog bilberries (Vaccinium uliginosum
L.) (109). Given that the two unique compounds in the resistant blueberry cultivar contain a
methylated sugar and the latter compound is methoxylated twice, the chemical contribution to the
resistance response in ‘Elliott’ fruit might be due to the increased fungitoxicity of specific
compounds. Researchers have found that methoxylated flavones can inhibit the growth of
Colletotrichum gloeosporioides from citrus fruits (6). Researchers have also found that

104

303

100

AU

%

0.03

129

0.01

147

A 0

0.02

0.00

B
347

100

AU

%

0.02

129 147

C 0
100

200

D
300
400
500
m/z [M+H]

600

0.01
0.00
250

350
450
Wavelength (nm)

550

Figure 4.4. MS/MS and UV/Vis spectra of two flavonoid compounds unique to the anthracnoseresistant cultivar Elliott. (A) Daughter ions detected when selecting for the parent ion of quercetin
3-O-rhamnoside (compound 08F in Table 4.2). (B) UV/Vis spectrum of quercetin 3-O-rhamnoside
(compound 08F in Table 4.2). (C) Daughter ions detected when selecting for the parent ion of
dimethylmyricetin methyl pentoside (compound 09F in Table 4.2). (D) UV/Vis spectrum of
dimethylmyricetin methyl pentoside (compound 09F in Table 4.2).

105

methyoxylation may also be important in imparting a certain degree of lipophilicity to the
flavonoid and may be required for the compounds to be biologically active (197).

Non-anthocyanin flavonoids suppress the growth of Colletotrichum acutatum in a liquid
medium
In our liquid assay, methanolic extracts of ‘Elliott’ and ‘Jersey’ inhibited the hyphal growth
of C. acutatum at the concentrations tested (50 µg per 100 μl of culture); however, the reduction in
growth was more pronounced with the ‘Elliott’ methanolic extract. The anthocyanin standard
cyanidin-3-O-glucoside increased the overall growth of C. acutatum. Additionally, anthocyanin
fractions from which non-anthocyanin flavonoids were removed also increased the growth of C.
acutatum (Figure 4.5A). This indicates that anthocyanins have little antifungal activity on the
growth of C. acutatum, while they are significantly more abundant in both ‘Elliott’ and ‘Jersey’
tissues than other flavonoids, they do not seem to play a direct role in the resistance response.
However, ‘Elliott’ fruits are known to produce an oxidative burst of H2O2 that is more than two
times greater than in ‘Jersey’ fruits following the inoculation of C. acutatum (125). Therefore, the
main contribution of anthocyanins might be to scavenge reactive oxygen species following
oxidative burst in order to prevent damage to host tissues.
The standards quercetin-3-O-glucoside and quercetin-3-O-rhamnoside decreased the
overall growth of C. acutatum, and the non-anthocyanin flavonoid fractions of ‘Elliott’ and
‘Jersey’ significantly decreased the growth of C. acutatum; the effect was again slightly more
pronounced in the ‘Elliott’ fraction (Figure 4.5B). This result matches our initial biological activity
screenings and demonstrates that the non-anthocyanin flavonoids have the most significant effect
on the growth of C. acutatum. Other researchers have found quercetin-3-O-rhamnoside to be the
106

∆ Optical density (590 nm)

1

A

0.4

Positive control
Cy-gluc
E.M.E.
J.M.E.
E.A.F.
J.A.F.

0.5

0

Positive control
Q-gluc
Q-rham
E.M.E.
J.M.E.
E.N.A.F.
J.N.A.F.

0.2

0

2

4

6 B

0

0

2

4

6

Time (days)

Time (days)

Figure 4.5. Change in the optical density (λ 590 nm) of liquid medium inoculated with conidia of
Colletotrichum acutatum over time in the presence of various fractions (50 μg per 100 μl of
culture) from ripe fruit of the anthracnose-resistant blueberry cultivar Elliott and susceptible
cultivar Jersey. (A) Anthocyanin-containing extracts and fractions from ‘Elliott ‘and ‘Jersey’ as
well as the standard cyanidin 3-O-glucoside. (B) Flavonol-containing extracts and fractions from
‘Elliott’ and ‘Jersey’ as well as the standards quercetin 3-O-glucoside and quercetin 3-Orhamnoside. The positive control denotes the fungus alone in the medium. Bars denote the
standard error of the mean (n = 3). Note , Postive control = methanol only, Cy-gluc = cyanidin 3glucoside, Q-gluc = quercetin-3-O-glucoside, Q-rham = quercetin3-O-rhamnoside, J.M.E. =
‘Jersey’ methanol extract, E.M.E. = ‘Elliott’ methanol extract, E.A.F. = ‘Elliott’ anthocyanin
fraction, J.A.F. = ‘Jersey’ anthocyanin fraction, E.N.A.F. = ‘Elliott’ non-anthocyanin flavonoid
fraction, and J.N.A.F = ‘Jersey’ non-anthocyanin flavonoid fraction.

107

most antimicrobial when compared against other glycosides; interestingly this compound is almost
entirely unique to ‘Elliott’ and may be important in the resistance response (195).
Most of the compounds we identified in these fractions were flavonol glycosides; however,
when exposed to water, flavonoids can oxidize and become deglycosylated. In onions, levels of
quercetin glucosides in dried brown areas were much lower than of the quercetin glucosides in
fleshy areas, whereas levels of the aglycone quercetin were high in dried brown areas. This
suggests that quercetin was formed by deglucosidation and oxidation of quercetin glucosides
(182). Deglycosylation tends to increase the activity of flavonoids (208), and further oxidation can
even lead to the creation of quinones (143) which are antimicrobial against Colletotrichum species
(121).

CONCLUSION
The resistant blueberry cultivar Elliott has more anthocyanins and non-anthocyanin flavonoids
than the susceptible cultivar Jersey, and there are two almost unique flavonoid compounds present.
Anthocyanins do not seem to play a direct role in the resistance response but may play an indirect
one by protecting host tissues from oxidative damage. The non-anthocyanin flavonoid fraction
from the resistant cultivar ‘Elliott’ seems to play a key role in suppressing microconidiation and
reducing growth of C. acutatum. Interestingly, this fraction contains two unique compounds;
quercetin-3-O-rhamnoside, and another flavonol glycoside which may play a more specific role in
the resistance response because of increased biological activity.
Non-anthocyanin flavonoids likely complement other aspects of 'Elliott' fruit rot resistance
that have been previously described, such as higher levels of sugar content (126) and an oxidative

108

burst following initial fungal penetration (125). Further investigation into how this process is
regulated at the molecular level might provide new insight into the interaction.

ACKNOWLEDGEMENTS
I would like to gratefully acknowledge funding from MSU Project GREEEN (Generating
Research and Extension to meet Economic and Environmental Needs). I also would like to thank
Dr. Ray Hammerschmidt for help with developing the liquid bioassay, Dr. Christine Vandervoort
for helping with the chemical separation using HPLC, and Dr. Daniel Jones for helping with the
MS/MS analysis.

109

CHAPTER V: EVALUATION OF SCREENING METHODS AND FRUIT COMPOSITION IN
RELATION TO ANTHRACNOSE FRUIT ROT RESISTANCE IN BLUEBERRIES

Published in the peer-reviewed journal Plant Pathology (Early View - Doi: 10.1111/j.13653059.2011.02541.x)

ABSTRACT
Anthracnose fruit rot is an important disease of blueberries and losses are common in
humid growing regions. Most commercial cultivars are susceptible and the disease is usually
managed with fungicides. However, a few cultivars are considered resistant. The objectives of this
study were to: (1) Compare different inoculation techniques for anthracnose fruit rot resistance
screening, (2) Screen ripe fruit from a range of blueberry cultivars using selected techniques, and
(3) Investigate the role of fruit characteristics in anthracnose fruit rot resistance. The following
inoculation methods were evaluated on ripe fruit of a susceptible and resistant cultivar using a
conidial suspension: spray, droplet, and injection inoculation of whole fruit; and droplet
inoculation of the open surface of cut fruit. All whole-fruit inoculations yielded similar results.
Despite the removal of the epidermis, resistance was also expressed in cut fruit but relatively fewer
conidia were produced. The cut-fruit assay required substantially less time and half the amount of
fruit to accomplish than whole-fruit assays. Detached ripe fruit from 24 cultivars in 2008 and 26
cultivars in 2009 were screened for resistance. Results from the cut-fruit assay correlated best with
published resistance ratings. To determine the possible role of fruit characteristics in resistance,
fruit pH, titratable acidity, sugar content, and firmness were regressed against various fruit rot
resistance measures. Fruit rot resistance was positively correlated with sugar content. On defined

110

media, mycelial growth was restricted as sugar concentration increased and pH decreased,
suggesting that fruit composition may play a role in the resistance phenotype.

INTRODUCTION
Anthracnose fruit rot, caused by the fungus Colletotrichum acutatum J.H. Simmonds, is a
major disease of highbush blueberries (Vaccinium corymbosum L.) in humid growing regions. The
disease is characterized by sunken areas on infected fruit that become covered by salmon-colored
conidial masses. Infections may occur as early as fruit set and remain latent until fruit ripening
(128). Most commercial cultivars are susceptible, and the disease is usually managed with
fungicides (123). The use of resistant cultivars with desirable horticultural characteristics would be
a cost-effective and environmentally safe way of managing fruit rots. One of the difficulties in
breeding for anthracnose fruit rot resistance is the labor and amount of fruit required for sufficient
screening, which requires natural infection or artificial inoculation of fruit. Through a screening
effort that took more than ten years to complete, anthracnose fruit rot resistance profiles have been
generated for the majority of older blueberry cultivars (150). In that study, the authors artificially
inoculated immature fruit on potted plants with multiple strains of C. acutatum and rated disease
incidence once the fruit ripened. Many of the newer cultivars were not included but were screened
for resistance to post-harvest fruit rot in another study that relied on natural field infection rather
than inoculation (84).
Fruit rot resistance may be manifested in two ways, namely reduced infection incidence
(150) and reduced symptom severity or sporulation (201). Not much is known about the
mechanism of anthracnose fruit rot resistance in blueberries. In previous studies, resistance to fruit
infection by C. acutatum was not correlated with resistance to foliar infection (64) or with the

111

production of antimicrobial fruit volatiles (149). Recent studies have shown an active resistance
response in ripe fruit of cv. Elliott leading to a restriction of fungal growth in fruit epidermal and
subepidermal tissues (201). An accumulation of phenolic compounds (201), an oxidative burst
following infection (125), and the presence of putative antifungal compounds (124) are thought to
play a role in anthracnose fruit rot resistance in cv. Elliott.
In our initial studies, ‘Elliot’ had a lower sugar content and higher pH than the susceptible
cultivar Jersey, and we hypothesized that fruit composition may play a role in resistance, either
directly by affecting fungal growth or indirectly by modulating fungal or plant enzyme activity
(124). Fruit composition, i.e. sugar content, pH and titratable acidity, is an important determinant
of flavor and sensory quality of blueberry fruit (42, 84). Ripe blueberries typically contain between
10% and 14% sugar (48% D-glucose, 49% D-fructose, and 3% sucrose) by fresh weight and have
a pH of 2.5 to 3.5, depending on the cultivar and study (42, 84, 120). A better understanding of
how these traits affect resistance to C. acutatum will provide further information about the nature
of the resistance response and aid in the development of resistant cultivars.
Although disease resistance is an objective of many blueberry breeding programs, no
genotypic or phenotypic markers are currently available for rapid screening of blueberry breeding
lines for anthracnose fruit rot resistance. Resistance screening of plants can only be accomplished
when they bear fruit in sufficient quantities for evaluation, usually at 2 to 3 years of age. Relying
on natural field infection is less labor intensive than using artificial inoculation but would require
observations over multiple locations and/or years due to variability between sites and growing
seasons. Furthermore, it would be difficult to compare cultivars directly due to widely varying fruit
maturation dates, chilling requirements, and cold hardiness levels which prevent some cultivars
from being grown in certain locations. Unless anthracnose fruit rot resistance is a specific priority

112

of a breeding program, new cultivars may not be evaluated for anthracnose fruit rot resistance prior
to their release.
The infection process of Colletotrichum spp. on fruits has been studied in a number of plant
pathosystems (36, 131, 159, 206). In general, as fruits start to ripen they become increasingly
susceptible to infection.
During fruit ripening, many physiological changes occur, such as a reduction in fruit
firmness, changes in pH and cell wall composition, and an increase in soluble sugars and
secondary metabolites, such as anthocyanins (20, 164). In avocado, several factors have been
associated with increased fruit susceptibility to infection by Colletotrichum gloeosporioides
(Penz.) Penz. & Sacc. as fruit ripens, including an increase in fruit pH (159) and a decrease in
preformed antimicrobial compounds (155) and pathogenicity factor inhibitors, such as epicatechin
(79). Other studies have shown that ammonia secretion by the fungus increases the pH of host
tissues and is important for pathogenicity on almond (55), apple (157), avocado (157) and tomato
(3, 157). Soluble sugars may also play a role in defense responses during ripening. Guava
cultivars that contained high levels of soluble sugars and ascorbic acid also were the most resistant
to Glomerella cingulata (Stoneman) Spauld. & H. Schrenk (176). In grapes, the accumulation of
antifungal proteins and sugars during fruit ripening is an important defense mechanism against the
fungal pathogens Botrytis cinerea Pers.:Fr. and Guignardia bidwellii (Ellis) Viala & Ravaz (165,
185).
In blueberries, resistance to anthracnose fruit rot is expressed in green as well as in ripe
fruit (125, 201). It is not known whether the same mechanism governs resistance at both
developmental stages. Since immature fruit of all blueberry cultivars is resistant to anthracnose
fruit rot unless physically damaged, our focus is on resistance expressed in ripe fruit. To improve

113

techniques for resistance screening in blueberry breeding and evaluate fruit characteristics as
possible phenotypic markers of resistance, we conducted a study with the following objectives: 1)
Compare different inoculation techniques for anthracnose fruit rot resistance screening, 2) Screen
ripe fruit from a range of blueberry cultivars using selected techniques, and 3) Investigate the role
of fruit characteristics in anthracnose fruit rot resistance. The overall goal of this project is to
facilitate the development of anthracnose fruit rot-resistant blueberry cultivars.

MATERIALS AND METHODS
Plant and fungal material
Ripe blueberry fruit was collected from the Michigan Blueberry Growers Association
(MBG) variety trial field in Grand Junction, MI, USA on 27 July and 7 August in 2008 and 2009
and stored at 4°C for no more than 3 days prior to testing. Approximately 50% of the fruit of
selected cultivars was ripe at the time of harvest. Germplasm types were categorized into five
groups: northern highbush (Vaccinium corymbosum L.), southern highbush (adapted V.
corymbosum with minimal chilling requirement, some crossed with V. darrowi Camp and/or V.
ashei Reade), half high (V. corymbosum × V. angustifolium Ait.), and intermediate (between
southern and northern highbush blueberries in chilling requirement with genetic contributions from
southern highbush) (Table 5.1). The cultivars included in this study are commonly grown in
Michigan and account for more than 95% of the cultivated blueberries in the state (105). A singleconidium isolate of C. acutatum isolated from blueberry fruit in Grand Junction, MI, USA in
August 2006 was used for inoculations. This isolate (CA001) was the most virulent of 25 isolates
in a preliminary test and was used for all experiments. Fungal cultures of C. acutatum were grown
and stored in accordance with Miles et al. (2011). For inoculum production, sporulating cultures
114

were flooded with 3 mL of sterile deionized water (SDW), and conidia were dislodged using a
6

sterilized L-shaped glass rod. Conidia were counted using a hemacytometer, and diluted to 1 x 10
conidia per milliliter with SDW.

Inoculation methods
Ripe fruit of cvs. Elliott (resistant) and Jersey (susceptible) was inoculated with a conidial
6

suspension (10 conidia per milliliter) using four different methods: 1) applying a 10-µL droplet
into the calyx cup, 2) spraying the berries until runoff, 3) injecting 50 µL with a syringe into the
interior of the fruit, and 4) applying a 50-µL droplet to the open surface of a cut fruit. For the cutfruit assay, berries were cut in half longitudinally with a sterile scalpel and placed cut side up.
There were five replicates per cultivar with 5 fruits per replicate. Fruit in all treatments was
incubated on wire mesh screens at 22-24°C and 100% humidity for 10 days post inoculation (dpi),
except cut fruit which was incubated for 3 dpi. After incubation, conidium production was
quantified by placing five inoculated fruit in 5 mL of sterile water and gently inverting the tube for
5 minutes. Conidium concentration per milliliter was determined using a hemacytometer as the
average of three separate counts (Table 5.1).
To further evaluate whole- and cut-fruit inoculation methods, a range of blueberry cultivars
(24 in 2008 and 26 in 2009) was screened for anthracnose fruit rot resistance. Ripe whole fruit
were spray inoculated as described above followed by evaluation of infection incidence
(proportion of fruit infected) and severity (percentage of the fruit surface supporting sporulation)
after 10 days. Cut fruit were drop inoculated and sporulation was measured with a hemacytometer
as the number of conidia produced per fruit half.

115

To determine the utility of spectrophotometry for measuring sporulation, conidia were
harvested from a 4-day-old microconidiating culture of C. acutatum. A dilution series from 1.0 x
5

7

10 to 1 x 10 conidia per ml was used to develop a standard curve for conidium concentration
based on optical density of the conidial suspension. The absorbance was read with an EL 800
Universal Microplate Reader (BioTek Instruments, Winooski, VT, USA) at a wavelength of 590
nm. The actual conidium concentration of each sample was determined microscopically with a
hemacytometer. All measurements were made on triplicate subsamples. The same procedures were
used to quantify the number of conidia produced on cut fruit surfaces of seven blueberry cultivars
(Bluecrop, Blueray, Elliott, Jersey, Liberty, Nelson and Rubel) in 2008. In addition, fruit from an
F-1 population resulting from a cross of cvs. Draper (resistant) and Jewel (susceptible) was used to
validate the spectrophotometric procedure. Plants were grown in Interlachen, FL, USA and fruit
was collected in April and May, 2011 when approximately 50% of the fruit on a bush was ripe.
Fruit was cooled immediately, shipped within three days of the harvest, and inoculated and
evaluated as described above.

Assessment of fruit characteristics
Ripe fruit of different blueberry cultivars was harvested at appropriate times from early
July to late August over 4 years (2005 to 2008) from the MBG variety trial in Grand Junction, MI,
USA. Sugar content, pH, and titratable acidity (TA) were measured in juice extracted from 25
berries per cultivar (five replicates of five berries) that were blended at high speed in a tissue
homogenizer (Ultra Turrax T25; Janke and Kunkel Co., Staufen, Germany). Sugar content was
determined using a handheld refractometer (Westover model RHB-32; Southwest United
Industries, Tulsa, OK, USA). Results are reported as percent sugar content (wt/wt) on a fresh116

weight basis. TA was determined using 10 mL of juice diluted to 100 mL with SDW, titrated with
0.1 N sodium hydroxide to pH 8.2, and expressed as percent citric acid (wt/wt) on a fresh-weight
basis. Fruit firmness was determined on a sample of 50 fruit per cultivar per year using a portable
2

firmness measuring instrument (188). Data were reported as force (newtons/mm ) required to
deform the surface of the fruit. These results represent an expansive data set including more
cultivars and years of data collection than previously reported by (84).

Effect of sugar concentration on mycelial growth in vitro
To determine the effect of sugar concentration on fungal growth, a minimal medium was
utilized as described by (5), consisting of 0.7% KH2PO4, 0.4% KNO3, 0.3% Na2HPO4, 0.1%
MgSO4, 0.03% CaCl2, 1.5% BACTO-agar, and varying concentrations of sugar (ranging from 4
to 20%). The sugar utilized in the media was 100% D-glucose, 100% D-fructose, or a 50/50
mixture of both sugars. The medium was adjusted to a final pH of 6.5 and autoclaved at 121°C and
100 kPA for 30 minutes. Hyphal plugs (~5.5 mm in diameter) were transferred from a 7-day-old
potato dextrose agar (PDA) culture of C. acutatum to Petri plates containing the defined minimal
medium. There were three replicate plates per treatment. Plates were incubated without Parafilm
for 7 days in the dark at 25°C. After incubation, the diameter of each colony was measured in two
perpendicular directions, and the average diameter was calculated after subtracting the diameter of
the initial hyphal plug. The experiment was conducted three times.

117

Effects of pH and sugar concentration on mycelial growth in liquid media
To determine the effects of pH and the interaction of pH and sugar concentration on
mycelial growth, liquid media were used, namely potato dextrose broth containing 0.4% potato
starch and 2% dextrose, and the minimal medium described above containing 4% D-glucose and
4% D-fructose without the addition of agar. Both media were adjusted to a final pH of 2.0, 2.5, 3.0,
3.5, 4.0, 5.0, and 6.5 using dilute hydrochloric acid as measured with an Accumet AB15 pH meter
(Thermo Fisher Scientific, Waltham, MA, USA). The media were sterilized with a 0.45-μ syringe
filter (Millipore, Billerica, MA, USA) and placed in 2.95-mL aliquots in 14-mL polypropylene
Falcon tubes (Becton Dickinson Labware, Franklin Lakes, NJ, USA). A 50-µL conidial suspension
6

(10 conidia/mL) from a 3- to 7-day-old culture was added to each tube and cultures were shaken
at 300 rpm at 22-24°C. After 7 days, the mycelial suspensions were filtered through pre-weighed,
9-cm-diam. Whatman filter paper disks in a Büchner funnel by applying a vacuum. Filter disks
were allowed to air dry for 4 days and the dried mycelium was weighed. To study the interaction
of pH and sugar concentration, the minimal medium as described above was used with sugar
concentrations of 8, 10, 12, 14, and 16% (50/50 D-glucose/D-fructose) at three pH levels (3.0, 4.0,
and 5.5). Each treatment was replicated three times and the experiments were conducted twice.

Statistical analyses
All statistical analyses were performed with the StatGraphics statistical computer program
(StatPoint Inc., Warrenton, VA, USA) and SigmaPlot version 11 (SYSTAT Software, Chicago, IL,
USA). For the different inoculation techniques, the data were statistically analyzed using a paired
Student’s t-test (α = 0.05) after checking for normality and equality of variance. For the cultivar
resistance screening experiments, statistical differences were determined by one-way ANOVA and
118

Fisher’s Protected LSD test (P = 0.05). Since the factor “year” had no significant effect, we pooled
the data from 2008 and 2009 to calculate means and standard errors. For fruit composition
analysis, all experiments were analyzed by ANOVA according to a completely randomized design.
Previously reported resistance ratings using proportion decayed fruit from Polashock et al., (2005)
were utilized for regression analyses. Linear and power (log-log) regressions were run using
SigmaPlot for obtaining P and r values. For investigating the combined effect of pH and sugar, a
two-factor ANOVA was used to analyze main and interaction effects of sugar content and pH (α =
0.05).

RESULTS
Inoculation method does not affect the resistance phenotype
The three whole-fruit inoculation methods (droplet, spray, and injection) resulted in similar
infection phenotypes with abundant sporulation on the fruit surface 10 days after inoculation
6

(Figure 5.1). In each method, ‘Jersey’ fruit yielded similar numbers of conidia (23.2 x 10 to 26.5
6

6

x 10 conidia per milliliter), whereas conidium production was much lower in ‘Elliott’ (2.8 x 10
6

to 4.0 x 10 conidia per milliliter) (Figure 5.2). The variance of the data was highest in the
injection and lowest in the spray inoculation procedure.
In the cut-fruit method, fungal sporulation was evident on the cut fruit surface of both
cultivars after 3 days. However, ‘Jersey’ showed more darkening and maceration of the internal
fruit tissues than ‘Elliott’ (Figure 5.1D and 1I). No significant necrosis or sporulation was
observed in the water control of either cultivar (Figure 5.1E and 1J). Overall, the cut-fruit method
yielded about 10-fold fewer conidia per berry than the whole-fruit inoculation methods, but the

119

A

B

C

D

E

F

G

H

I

J

Figure 5.1. Signs and symptoms of fruit infection by Colletotrichum acutatum on two different
blueberry cultivars, Jersey (A to E), and Elliott (F to J) after inoculation with a conidial suspension
using different techniques, such as applying a 10-µL droplet into the calyx cup (A and F), spraying
the berries until runoff (B and G), injecting 50 µL into the interior of the fruit with a syringe
(needle still visible) (C and H), and applying a 50-µL droplet to the open surface of a cut fruit (D
and I). Fifty microliters of sterile deionized water served as a control in the cut fruit experiments
(E and J). All treatments were incubated for 10 days after inoculation, except the cut-fruit
treatments (3 days).

120

Jersey

6

No. of conidia produced per berry (10 )

40

Elliott

30

20

10

0
Drop

Spray

Syringe

Cut surface

Inoculation methods
Figure 5.2. Conidium production on fruit of blueberry cultivars Jersey and Elliott after inoculation
with a Colletotrichum acutatum conidial suspension using different inoculation methods (applying
a 10-µL droplet into the calyx cup, spraying the berries until runoff, injecting 50 µL into the
interior of the fruit with a syringe, and applying a 50-µL droplet to the open surface of a cut fruit).
All treatments were incubated for 10 days after inoculation, except the cut-fruit treatment (3 days).
Bars denote the standard error of the mean (n = 5 with 10 fruits per replicate).

121

Table 5.1. Anthracnose fruit rot resistance profiles of different blueberry cultivars after artificial
inoculation with Colletotrichum acutatum as measured by infection incidence (proportion of fruit
infected), infection severity (the percentage of the fruit surface supporting sporulation), and
sporulation capacity (number of conidia produced on the cut surface of a half berry). Ripe fruit was
collected from a field planting in Grand Junction, MI, USA in July and August of 2008 and 2009
(n = 10 unless otherwise noted and SE = standard error of the mean).

Cultivar

Sporulation capacity
Infection severity
Germplasm Infection incidence
6
(proportion ± SE) (percentage ± SE) (no. of conidia x 10 ± SE)
a
c
type
(2008 and 2009)
(2009 only)
(2008 and 2009)

Aurora

NHB

0.64 ± 0.05

3.9 ± 0.5

0.56 ± 0.02

Berkeley

NHB

0.92 ± 0.03

8.8 ± 0.8

4.56 ± 0.20

Bluechip

NHB

0.75 ± 0.13

-

d

14.97 ± 3.25

Bluecrop

NHB

0.98 ± 0.02

21.6 ± 2.0

12.30 ± 0.90

Bluehaven

NHB

0.88 ± 0.06

7.7 ± 1.1

0.51 ± 0.07

Bluejay

NHB

0.63 ± 0.04

14.4 ± 3.4

3.12 ± 1.75

Blueray

NHB

1.00 ± 0.00

27.2 ± 3.6

10.81 ± 2.75

Bounty

NHB

0.98 ± 0.02

26.9 ± 2.8

7.60 ± 1.60

Brigitta

NHB

0.66 ± 0.03

7.5 ± 1.7

2.15 ± 0.67

Caroline

NHB

0.65 ± 0.13

d

1.90 ± 1.15

Collins

NHB

0.98 ± 0.01

22.7 ± 2.1

1.68 ± 0.60

Darrow

NHB

0.98 ± 0.01

15.0 ± 2.4

7.62 ± 1.80

Denise

NHB

0.86 ± 0.06

9.6 ± 1.9

3.34 ± 0.65

Draper

NHB x SHB

0.68 ± 0.07

c

8.4 ± 2.3

1.05 ± 0.80

Duke

NHB

0.70 ± 0.04

c

14.9 ± 1.5

7.25 ± 0.60

Earliblue

NHB

0.70 ± 0.04

36.3 ± 6.4

2.87 ± 0.55

Elliott

NHB

0.47 ± 0.06

2.4 ± 0.2

0.29 ± 0.08

b

b

-

122

c
c

Table 5.1 (cont’d.)
Jersey

NHB

0.98 ± 0.02

21.6 ± 1.4

3.35 ± 0.31

Lateblue

NHB

0.50 ± 0.06

d

3.00 ± 0.55

Liberty

NHB

0.52 ± 0.04

4.3 ± 0.75

1.00 ± 0.33

Nelson

NHB

0.70 ± 0.06

d

14.10 ± 5.00

Northblue

HH

0.70 ± 0.07

9.9 ± 0.9

8.04 ± 0.10

Northland

NHB

0.81 ± 0.05

8.9 ± 0.7

0.98 ± 0.48

Rose

NHB

0.57 ± 0.08

6.1 ± 1.3

4.13 ± 1.10

Rubel

NHB

0.98 ± 0.02

14.3 ± 1.3

2.07 ± 0.80

Toro

NHB

0.81 ± 0.04

5.4 ± 0.9

5.62 ± 2.15

b

-

b

-

a

Abbreviations for germplasm type as previously defined in materials and methods. NHB =
northern highbush; SHB = southern highbush; HH = half high (V. corymbosum x V.
angustifolium); NHB x SHB = intermediate.
b
Data were collected only in 2008 and therefore n = 5.
c

Data were collected only in 2009 and therefore n = 5.

d

No data collected.

123

difference between the cultivars was proportionally the same. However, if the cut fruit was
incubated longer than 3 days, significant background infection became apparent, since these were
field-collected berries (data not shown).
A linear regression yielded the best fit for a standard curve of conidium concentration
2

against optical density of an aqueous suspension of C. acutatum conidia from culture (R > 0.99)
(Figure 5.3A). Conidia harvested from inoculated cut fruit surfaces from the Draper x Jewel
2

population in 2011 also showed a strong positive linear correlation with optical density (R =
0.90), although there was an occasional outlier (Figure 5.3B). A linear function also described the
standard curve for conidia from cut fruit surfaces of selected blueberry cultivars in 2008. However
2

the relationship was not as strong as for the previous curves (R = 0.81) (Figure 5.3C).

Fruit resistance results correlate with previously published resistance ratings
The results of screening different blueberry cultivars for anthracnose fruit rot resistance in
the whole- and cut-fruit assays were consistent from 2008 to 2009, as there were no significant
effects of year or cultivar × year. P-values were 0.32 (whole fruit) and 0.51 (cut fruit) for the effect
of year, and 0.13 (whole fruit) and 0.21 (cut fruit) for cultivar × year. Data were therefore reported
as an average of the two years (Table 5.1), except for infection severity which was only rated in
2009. Water controls in the whole-fruit inoculations showed evidence of background infection,
primarily in the susceptible cultivars.
Of the resistance measures evaluated, sporulation capacity in the cut-fruit assay was most
strongly correlated with cultivar resistance ratings published by Polashock et al. (2005)

124

6

No. of conidia per milliliter (10 ) No. of conidia per milliliter (10 ) No. of conidia per milliliter (10 )

6

A

6

B

C

16

2

R = 0.99
12 P < 0.001
8
4
0
16
12

2

R = 0.90
P < 0.001

8
4
0
16
12

2

Bluecrop

R = 0.81
P = 0.006

Nelson
8
Blueray
Liberty
4
Jersey
Elliott
Rubel
0
0.00
0.25
0.50
0.75
Optical density (590 nm)

1.00

Figure 5.3. Relationship between the concentration of an aqueous suspension of Colletotrichum
acutatum conidia and optical density at 590 nm. A) Conidia produced on PDA. B) Conidia from
cut fruit surfaces from a Draper x Jewel F1 population. C) Conidia produced on cut fruit surfaces
of selected blueberry cultivars.
125

Table 5.2. Pearson correlation coefficients (r) and statistical significance (P) for regressions
between different measures of anthracnose fruit rot resistance after artificial inoculation of a range
of blueberry cultivars with Colletotrichum acutatum. Infection incidence (proportion of fruit
infected), infection severity (the percentage of the fruit surface supporting sporulation), sporulation
capacity (number of conidia produced on the cut surface of a half berry) and previously published
resistance ratings (Polashock et al., 2005) were subjected to linear regression. All values were log
transformed prior to regression. R-values in boldface are statistically significant at α < 0.05

Dependent
Variable (Values
from Table 5.1)

Independent Variable

Infection incidence

Infection severity

Sporulation
capacity

Number of
cultivars in
common

r value

P value

Infection severity

22

0.69

< 0.001

Sporulation capacity

26

0.40

0.044

Proportion decayed
(Polashock et al., 2005)

18

0.31

0.208

Sporulation capacity

22

0.63

0.002

Proportion decayed (20)

15

0.64

0.010

Proportion decayed (20)

18

0.86

< 0.001

126

(r = 0.86; P < 0.01). Infection incidence in the whole-fruit assay was positively correlated with
infection severity on whole fruit (r = 0.69, P < 0.01) and sporulation capacity on cut fruit (r = 0.40,
P = 0.04) but only weakly correlated with resistance ratings by Polashock et al. (2005) (r = 0.33, P
= 0.21). Infection severity on whole fruit also was correlated with sporulation capacity on cut fruit
(r = 0.63, P = 0.002) and resistance ratings by Polashock et al. (2005) (r = 0.64, P = 0.01) (Table
5.2).

Anthracnose resistance is correlated with certain fruit characteristics
Average weight per berry ranged from 1.10 g to 3.07 g, sugar content from 10.3% to
13.9%, pH from 2.53 to 3.28, titratable acidity from 0.4% to 1.2%, and fruit firmness from 262 to
2

519 newtons per mm (Table 5.3). Anthracnose fruit rot resistance as measured by sporulation
capacity on cut fruit, infection severity on whole fruit, and proportion decayed from Polashock et
al. (2005) was negatively correlated in a linear fashion with percent soluble sugar in the fruit (r = 0.53, P = 0.02; r = -0.44, P = 0.09; r = -0.62, P < 0.01, respectively), i.e. the higher the sugar
content, the more resistant the fruit. The correlation between infection incidence on whole fruit and
sugar content showed the same trend but was not significant (r = -0.24, P = 0.34). Additionally,
infection severity on whole fruit showed marginally significant negative correlations with berry
weight (r = -0.44, P = 0.09) and titratable acidity (r = -0.45, P = 0.08) (Table 5.4). Correlations
with fruit firmness were not significant (Table 5.4).

Mycelial growth is reduced at high sugar content and low pH
Colonies of C. acutatum grew faster on solid media with D-glucose than with D-fructose
(Figure 5.4D). Growth on the medium with a 50/50 mixture of D-glucose and D-fructose was more
127

Table 5.3. Characteristics of fruit of different blueberry cultivars collected from a field planting in
Grand Junction, MI, USA from 2005 to 2008. Values shown are averages and standard errors over
4 years. Five berries were used per replicate.

a

b

Berry
weight
(g)

Sugar
content
(%)

Titratable Firmness
2c
acidity (%) (N/mm )

Cultivar

Type Years tested

Aurora

NHB 05, 06, 07, 08

Berkeley

NHB

Bluecrop

NHB 05, 06, 07, 08

2.0 ± 0.1

11.2 ± 0.3 2.8 ± 0.1

0.9 ± 0.1 354.6 ± 67.9

Bluegold

NHB 05, 06, 07, 08

1.9 ± 0.2

12.6 ± 0.3 2.8 ± 0.1

1.0 ± 0.1 342.7 ± 66.1

Bluehaven

NHB

1.9 ± 0.3

11.8 ± 0.2 2.7 ± 0.0d 0.8 ± 0.0d 146.2 ± 95.5

Bluejay

NHB 05, 06, 07, 08

1.8 ± 0.1

12.5 ± 0.3 3.0 ± 0.1 0.7 ± 0.0d 299.6 ± 54.5

Blueray

NHB

05, 06, 08

2.3 ± 0.1

10.5 ± 0.8 3.0 ± 0.1

0.7 ± 0.1 365.8 ± 89.3

Bluetta

NHB

05, 06, 08

1.4 ± 0.1

10.4 ± 0.2 2.8 ± 0.1

0.8 ± 0.2 396.8 ± 99.4

Brigitta

NHB 05, 06, 07, 08

2.6 ± 0.3

12.1 ± 0.6 2.8 ± 0.1 0.9 ± 0.0d 463.4 ± 90.1

Chanticleer

NHB

06, 07, 08

3.1 ± 0.2

10.5 ± 0.5 2.8 ± 0.1

Darrow

NHB

05, 06

2.6 ± 0.1

12.2 ± 0.9 2.6 ± 0.0d 1.2 ± 0.0d 519.2 ± 211.7

Draper

X

05, 06, 07, 08

2.2 ± 0.2

12.2 ± 0.9 2.8 ± 0.1

1.1 ± 0.1 519.2 ± 124.6

Duke

NHB 05, 06, 07, 08 1.9 ± 0.0d

10.3 ± 0.2 3.0 ± 0.1

0.7 ± 0.1 572.5 ± 148.6

Earliblue

NHB

Elliott
Jersey

07 only

06, 07

2.0 ± 0.2

13.4 ± 0.5 2.8 ± 0.1 1.1 ± 0.0d 415.6 ± 85.9

2.0

12.3

2.8

0.6

227.7

1.1 ± 0.1 276.4 ± 79.9

1.2 ± 0.0

11.1 ± 0.7 2.9 ± 0.0d 0.7 ± 0.1 361.7 ± 80.9

NHB 05, 06, 07, 08

1.8 ± 0.2

12.9 ± 0.9 2.8 ± 0.1

NHB 05, 06, 07, 08

1.6 ± 0.2

13.4 ± 0.4 3.2 ± 0.2 0.5 ± 0.0d 319.9 ± 64.3

05, 06, 07

d

pH

128

1.1 ± 0.1 341.8 ± 69.7

Table 5.3 (cont’d.)
Jewel

SHB

08 only

2.5

Lateblue

NHB

06, 07, 08

2.1 ± 0.1

12.9 ± 0.5 2.8 ± 0.1

0.9 ± 0.1 167.1 ± 54.6

Legacy

X

05, 06, 07, 08

2.2 ± 0.1

13.2 ± 0.6 3.1 ± 0.1

0.6 ± 0.1 373.2 ± 75.1

Liberty

NHB 05, 06, 07, 08

2.4 ± 0.3

13.3 ± 0.7 2.9 ± 0.1 0.9 ± 0.0d 518.8 ± 114.6

Nelson

NHB 05, 06, 07, 08

2.1 ± 0.3

12.2 ± 0.2 2.8 ± 0.1 1.0 ± 0.0d 318.8 ± 53.4

O’Neal

SHB

06, 08

1.7 ± 0.1

12.5 ± 0.2 3.28 ± 0.4 0.5 ± 0.0d 121.2 ± 89.8

X

05, 06, 07, 08

2.2 ± 0.1

11.3 ± 0.3 2.9 ± 0.1

Patriot

NHB

07 only

2.2

Rubel

NHB

05, 06, 07

1.1 ± 0.1

Sapphire

SHB

08 only

1.8

Spartan

NHB 05, 06, 07, 08

2.3 ± 0.1

11.4 ± 0.1 3.0 ± 0.1 0.6 ± 0.0d 396.2 ± 75.4

Star

SHB

1.5 ± 0.2

10.8 ± 0.4 3.1 ± 0.3

Toro

NHB 05, 06, 07, 08 2.6 ± 0.0d

Ozark Blue

06, 08

11.5

11.9

2.6

2.5

13.9 ± 0.3 2.9 ± 0.1
13.1

3.0

0.7

211.1

0.8 ± 0.1

354.0± 66.5

1.0

310.3

0.9 ± 0.1 424.9 ± 110.2
0.4

262.0

0.6 ± 0.1 161.2 ± 125.5

11.1 ± 0.3 2.8 ± 0.1 0.9 ± 0.0d 374.0 ± 73.2

a

Abbreviations for germplasm type as previously defined. NHB = northern highbush; SHB =
southern highbush; HH = half high (V. corymbosum x V. angustifolium); X = intermediate.
b
To calculate means, 5 berries per replicate (25 in total) were used for each year of study. All
values displayed in the table correspond to the mean of the yearly means.
c
Force required to indent blueberry fruit.
d

Indicates standard error values less than 0.05.

129

Table 5.4. Pearson correlation coefficients (r) for regressions of various measures of anthracnose
fruit rot resistance after artificial inoculation of blueberry fruit with Colletotrichum acutatum
(Table 5.1) against fruit characteristics (Table 5.3). Infection incidence (proportion of fruit
infected), infection severity (percentage of the fruit surface supporting sporulation), sporulation
capacity (number of conidia produced on the cut surface of a half berry) and previously published
resistance ratings (150) were subjected to linear regression against fruit variables. Statistically
significant r-values are indicated in boldface.
Independent variable

Dependent variable

Berry
Weight (g)

Sugar
content (%)

pH

Titratable
acidity
(%)

Firmness
(Newton
per 1
2a
mm )

r-value
Infection incidence

-0.11b

-0.24

0.16

0.28

0.06

Infection severity

-0.44*

-0.44*

0.42

-0.45*

-0.07

0.17

-0.53**

0.10

-0.03

0.03

0.29

-0.62**

-0.30

0.26

0.18

Sporulation capacity
Proportion decayed (150)
a

Force required to indent fruit surface.

b

*Indicates statistical significance at P ≤ 0.10, ** Indicates statistical significance at P ≤ 0.05

130

similar to growth with D-glucose than with D-fructose. However, mycelial growth was reduced to
a similar extent as concentrations of both sugars increased. Average colony diameter was reduced
by 37% and 35%, respectively, as D-glucose and D-fructose concentrations increased from 4% to
20%. On the medium with a 50/50 mixture of D-glucose and D-fructose, the largest reduction in
growth occurred between 12% (Figure 5.4B) and 16% sugar content (Figure 5.4C), reducing
average colony diameter by about 1 cm (Figure 5.4D). In a more detailed experiment using a 50/50
mixture of D-glucose and D-fructose within the physiological range of blueberries, the biggest
reduction in mycelial growth was seen between 11% and 13% sugar content (Figure 5.4E).
When investigating the effect of initial medium pH on mycelial growth of C. acutatum in
liquid media, a similar pattern was observed on both media with slightly more growth in potato
dextrose broth than in the minimal medium. In the latter, mycelial growth was significantly
reduced below an initial pH of 4.0 and no growth had occurred at an initial pH of 2.5 after 7 days
of incubation. In potato dextrose broth, a similar reduction was observed but in this case, no
growth occurred at a pH of 2.0. An initial pH of 4.0 appeared optimal for mycelial growth (Figure
5.5A). If the fungus grew, the pH was modified in the culture to 5.6 to 6.5 by day 7 depending on
the initial pH (data not shown).
The combined effect of initial pH and sugar content in the physiological range of
blueberries showed that the fungus was able to grow under all conditions, but mycelial growth was
most curtailed by high sugar content combined with a low pH (Figure 5.5B). Unfortunately, we
could not test pH levels lower than 3 due to the fungus’ inability to grow at low pH in the minimal
medium, but by extrapolation, mycelial growth would have been even more reduced and in some
cases virtually absent at the more acidic pH levels typical of blueberries, i.e. 2.5 to 3.2 (Table 5.3).

131

Colony diameter (mm)

C

B

A
60

54

50

50

40

46

30

42
2

D

6

10
14
18
Sugar content (%)
D-Glucose

22

9
E

D-Fructose

10

11
12
13
Sugar content (%)

14

15

50/50 D-Glucose/D-Fructose

Figure 5.4. Mycelial growth of Colletotrichum acutatum on minimal medium with different sugar
(50/50 D-glucose/D-fructose) concentrations: 8% (w/v) (A), 12% (w/v) (B), and 16% (w/v) (C)
after 7 days. D) The effect of sugar content in minimal medium on mycelial growth of C. acutatum
after 7 days using D-glucose, D-fructose and a 50/50 D-glucose/D-fructose mixture. E) The effect
of sugar content in minimal medium on mycelial growth of C. acutatum after 7 days using a 50/50
D-glucose/D-fructose mixture in the physiological range for blueberries. In D and E, error bars
denote standard error of the mean.

132

0.05
Potato dextrose broth
Minimal medium

Dry mycelial weight (g)

0.04

0.03

0.02

0.01

0.00
2

A

3

4

5

6

Initial pH

0.04

Dry mycelial weight
0.04 g
0.03 g
0.02 g
0.01 g
0.00 g

0.03

0.02

0.01
0.00

8

5.0

10

4.5

12

4.0
3.5

B

14
3.0 16

Figure
fdsf 5.5.
133

Figure 5.5 (cont’d.). A) The effect of initial pH in potato dextrose broth and minimal medium on
the amount of mycelial growth (dry weight) of Colletotrichum acutatum after 7 days in 3ml
cultures. Initial pH is indicated here since the pH changed as cultures grew. Error bars denote
standard error of the mean. B) The effect of initial pH and sugar content (using a 50/50 Dglucose/D-fructose mixture) on mycelial growth (dry weight) of C. acutatum after 7 days.
Different degrees of shading indicate different mycelial weights, with darker shades indicating less
growth
.

134

At the typical sugar content of ripe blueberries (10.4 to 13.9%; Table 5.3) moderate growth
suppression would be expected.

DISCUSSION
This study represents a broad approach to screening blueberry cultivars for anthracnose
fruit rot resistance, comparing and improving screening methods, and correlating resistance ratings
to a previous study. When we inoculated the susceptible cultivar Jersey and the resistant cultivar
Elliott, the quantity of conidia produced was similar in fruit inoculated by syringe injection
compared to droplet and spray inoculation. We also obtained a difference of similar proportion by
drop-inoculating the open surface of cut fruit. This suggests that anthracnose fruit rot resistance in
‘Elliott’ fruit is expressed not only in the skin but also in the flesh of the blueberry. While
Colletotrichum studies generally do not involve inoculation of wounded or cut fruit because
wounding is not required for infection, similar resistance levels were found in five olive cultivars
whether the fruit was wounded or not prior to inoculation (131). Since the majority of soluble
phenolic compounds in blueberries occur in the epidermal and subepidermal layers of the fruit
peel, e.g., anthocyanins and flavonol glycosides (161), mechanisms other than the presence of
soluble phenolic substances may play a role in the resistance response.
Under natural conditions, infection usually takes place on green fruit followed by a latent
period until the fruit ripens, at which time the infection progresses until most of the fruit is covered
with acervuli (123). Infection incidence tends to increase rapidly during fruit ripening, with later
harvests having poorer fruit quality (128). Due to the labor and space involved in inoculating green
fruit on plants in the field or greenhouse, we chose to inoculate detached ripe fruit collected from
field-grown plants. We compared three different disease evaluations, including disease incidence

135

and severity on whole fruit and sporulation capacity on cut fruit. The whole-fruit inoculations did
not seem to correlate well with the other data sets, which is likely due to background infections as
indicated by the water controls. In our experience it is difficult to avoid background infection in
the field unless plants are grown in dry regions or protected from precipitation. Therefore, using
whole ripe fruit from field-grown plants may not provide accurate resistance ratings. Furthermore,
due to the variation in flowering and ripening times of different cultivars, it is possible that some
escape infection or, conversely, are exposed to higher-than-average doses of inoculum. While an
escape of infection due to timing of flowering or fruit ripening may lead to “field resistance”, this
would not be a reliable indicator of cultivar performance across regions.
The cut-fruit inoculation assay for blueberries showed the strongest correlation with
previously reported anthracnose fruit rot resistance ratings by Polashock et al. (2005) in New
Jersey and appears to be an efficient method for fruit rot resistance screening. Furthermore, due to
the relatively short incubation period, interference from background infections is mostly
eliminated as acervuli from natural infections on the fruit epidermis are not able develop to any
significant extent during the 3-day incubation period. Since local pathogen strains were used in
both studies, the strong correlation suggests that strain variation is not a big issue, and that a
cultivar that is resistant in one region can also be expected to be resistant in another region. It
should be pointed out that Polashock et al. (2005) rated disease incidence (proportion of fruit
decayed) whereas our cut-fruit assay measured the quantity of spores produced per half berry,
which could be interpreted as a measure of disease severity. Disease incidence and severity are
often correlated but not necessarily congruent. In addition to a direct relationship between
inoculum abundance and measures of disease incidence and severity, sporulation and fruit

136

softening must be sufficiently severe to be visible to the naked eye against the dark background of
a blueberry fruit, thereby affecting incidence ratings.
The cut-fruit assay is an improvement over conventional anthracnose fruit rot resistance
screening assays in that testing can be done on younger bushes that produce small amounts of fruit,
facilitating screening earlier in the breeding process. This way, moderately to highly susceptible
genotypes can be excluded before much effort has been expended in their selection and
maintenance. It does not preclude conducting other screening assays at a later stage. Since
microscopic quantification of conidia requires training and is somewhat tedious, a possible
improvement is the use of spectrophotometric methods in quantification of sporulation. We found
a linear correlation between optical density and conidium concentration in several experiments,
with the strongest correlation observed for conidia harvested from culture. Since pigments and
debris released from injured blueberry fruit may affect optical density readings, it is advisable to
develop a standard curve for cut fruit from representative cultivars prior to conducting a largescale screening assay. . While use of optical density for quantifying conidia from cut fruit may be
slightly less accurate, it is more time efficient and requires less training than microscopic
observation.
A positive linear correlation between fruit sugar content and anthracnose fruit rot resistance
suggests that soluble sugars may play a role in the resistance response. However, it most likely is
an additive effect as indicated by the relatively low r values and the fact that some moderately
susceptible cultivars had fairly high soluble sugar concentrations.
Diseases have been classified as high- and low-sugar diseases (88, 191). Low-sugar
diseases are characterized by heightened resistance to pathogens when tissues contain more sugar,
a concept termed “high-sugar resistance” (88, 191). Soluble sugars have been found to repress

137

photosynthetic genes as well as induce a number of defense-related genes and this shift in
expression could contribute to the overall resistance response (87). We found that high sugar
concentrations in artificial media had a negative impact on hyphal growth of C. acutatum,
presumably by increasing osmotic stress. This reduction was more pronounced with D-glucose
than with D-fructose. Our results suggest that internal sugar content in fruit may play a role in
slowing the growth of C. acutatum during the colonization of the fruit and should be investigated
further. Since sugar has been shown to induce the expression of pathogenesis-related proteins in
Arabidopsis thaliana, a similar response may occur in blueberries (187).
It is interesting that we did not see a correlation between pH and anthracnose fruit rot
resistance ratings despite the fact that hyphal growth of C. acutatum was significantly inhibited in
artificial media at pH values between 2.5 and 3.0, which are similar to natural pH levels in ripe
blueberries. Our method of measuring the pH of blueberry fruit was fairly crude, however, in that
it involved the maceration of the entire fruit. By doing so, we might have missed potential pH
variation in different fruit tissues, such as the exocarp and mesocarp (159). Since the epidermis is
the first physical barrier encountered by the pathogen, the specific pH of this tissue may be critical
for the establishment of C. acutatum. Based on other pathosystems, it is likely that the fungus is
able to modify the pH in its immediate surroundings, thereby reducing its effect (55). Modulation
of pH by Colletotrichum spp. has been shown to play an important role in the colonization of other
plant hosts (157). Our observation of a pH change a period of growth by C. acutatum in artificial
media supports this assumption.
The role of berry weight and titratable acidity in fruit rot resistance appears to be limited as
indicated by relatively low correlation coefficients and marginal statistical significance. However,
if the rate of colonization is the same, the fungus would be expected to take longer to colonize

138

large than small berries, which may be manifested in proportionally less surface area colonized in
heavier (larger) berries. Percent titratable acidity may be related to berry size and therefore not be
directly correlated with infection severity. Since no significant correlations were found between
fruit firmness and any of the resistance ratings, it is presumed not to play a role in fruit rot
resistance.
In this study, we have identified a relatively rapid and simple screening assay for
anthracnose fruit rot resistance that can be used early in the selection process of blueberry
germplasm. This would not preclude later screening under greenhouse or field conditions. Relying
on natural infection only may introduce confounding effects of weather and inoculum availability
as flowering and ripening times differ among blueberry cultivars. Artificial inoculation of fruit
with no background infection is most desirable to identify an accurate resistance phenotype.
Despite evidence for the role of sugar content in anthracnose fruit rot resistance, this characteristic
is not suitable as a single marker due to the moderate strength of the correlation. However,
selection for high sugar content may inadvertently yield anthracnose fruit rot-resistant cultivars as
an added benefit. More investigation is required to elucidate the molecular and biochemical
mechanism(s) of anthracnose fruit rot resistance in blueberry in order to identify specific markers
for resistance screening and novel strategies for disease management.

ACKNOWLEDGEMENTS
I would like to gratefully acknowledge funding from Michigan State University Project
GREEEN (Generating Research and Extension to meet Economic and Environmental Needs). I
would also like to thank the Michigan Blueberry Growers Association for allowing access to their

139

blueberry variety planting and Christine Bates and Daniel Svoboda for technical assistance. We
also thank Jerri Gillett and Laura Avila for critical reading of the manuscript.

140

CHAPTER VI: INHERITANCE OF RESISTANCE TO COLLETOTRICHUM ACUTATUM IN
HIGHBUSH BLUEBERRY (VACCINIUM CORYMBOSUM L.) FRUIT

ABSTRACT
Anthracnose fruit rot, caused by Colletotrichum acutatum, is a major disease of
highbush blueberries. The inheritance of fruit rot resistance to C. acutatum was investigated in
crosses of parents with varying susceptibility. Three cultivars with known resistance profiles
(Bluecrop, Elliott, and Jersey) and progeny from sixteen crosses of parents with varying levels of
susceptibility were screened. Fruit of field-grown bushes was inoculated when immature,
harvested when ripe, incubated, rated after 5, 8 and 12 days and area under the disease progress
curve (AUDPC) values were calculated. AUDPC values varied from 117 to 417 in 2010 and 100 to
545 in 2011. These values were then compared with the actual and predicted resistance values
from two previous studies. One study focused on disease incidence and the AUDPC values were
2

2

significantly correlated with our values in 2010 (R = 0.73) and 2011 (R = 0.71). The other study
utilized disease severity and once again the AUDPC values were significantly correlated with our
2

2

values in 2010 (R = 0.63) and 2011 (R = 0.65). These findings have important implications for
anthracnose resistance breeding, and provide strong evidence that anthracnose resistance is highly
heritable in highbush blueberries. Additionally, this research provides benchmark values so future
breeding selections can be evaluated for their resistance to C. acutatum.

INTRODUCTION
Anthracnose fruit rot is caused by the fungus Colletotrichum acutatum. The main
symptom of anthracnose on blueberries is rotting of ripe fruit in the field before harvest and in
141

storage after harvest (128). Infections occur as early as fruit set, but remain latent until fruit
ripening, which complicates detection of the disease. Initially, sunken areas develop on the fruit
surface, followed by the formation of sporulating structures (acervuli) exuding salmon-colored
spores (conidia). This disease can have a severe economic impact, with preharvest losses estimated
at 10% to 20% and post-harvest losses as high as 100% in storage (128). Most blueberry cultivars
are susceptible to anthracnose fruit rot including popular cultivars such as Bluecrop, Bluegold,
Duke, Jersey, Nelson and Ozarkblue. However, several resistant cultivars have been identified,
including Elliott, Brigitta and Legacy, display strong resistance in the field and in laboratory
inoculation studies (63, 126, 150).
The development of alternative management strategies is necessary because anthracnose is
primarily controlled by fungicides (169) at this time. Some of these fungicides are suspected
carcinogens (e.g., chlorothalonil), whereas others are prone to fungicide resistance development
(e.g., azoxystrobin). In all likelihood, more fungicide sprays are used than necessary because of the
difficulty in optimizing spray timing, incorrect disease diagnoses and the possible development of
fungicide resistance.
In other Colletotrichum plant pathosystems, host resistance has been shown to be localized
to a single gene, several genetic loci or a combination of these. In the C. acutatum-strawberry
pathosystem, a single dominant gene (Rca2) has been shown to be responsible for high-level
resistance, and weaker resistance appeared to be quantitative and controlled by a number of minor
genes (50). In the C. acutatum-chili pepper pathosystem, resistance was mapped to a single
recessive gene at the mature green fruit stage and a single dominant gene at the ripe fruit stage
(119). In another species of pepper, resistance to C. capsici has been associated with a single
recessive gene (144). Mapping of host resistance in Phaseolus vulgaris has revealed two

142

independent resistance genes within the same cluster that confer resistance to different strains of C.
lindemuthianum (72). Resistance to C. higginsianum has been shown to be localized to a single
genetic locus RCH1 in the Arabidopsis ecotype Eil-0 (134).
In previous studies, anthracnose fruit rot resistance in blueberries was not significantly
correlated with resistance to foliar infection (64) or the production of antimicrobial fruit volatiles
(149). However, resistance has been associated with different infection strategies by C. acutatum
(201), high levels of reactive oxygen species (125), accumulation of phenolic compounds (124),
antimicrobial compounds (127) and high sugar content of blueberry fruit (126). While we have
information on the relative anthracnose fruit rot resistance of many cultivars based on our own
studies and those of Polashock et al. (2005), the inheritance of resistance in current breeding
programs is largely unknown. Additionally, the heritability of disease resistance is of particular
interest in cultivated highbush blueberries due to decreasing heterozygosity because of increased
interspecific hybridization and the fact that the majority of genetic diversity is derived from only
four wild selections (83). An understanding of how resistance to C. acutatum is inherited is
important in making strategic breeding decisions as well as estimating durability of resistance. The
objectives of this study were to: 1) determine the anthracnose fruit rot susceptibility of daughters
from crosses of parents with varying susceptibility and 2) correlate their susceptibility with actual
and predicted resistance values from previous studies.

MATERIALS AND METHODS
Plant material
Ten to 20 progeny of crosses between parents varying in susceptibility to anthracnose were
selected that were interspersed within two breeding selection blocks located at Michigan State

143

University’s Southwest Michigan Research and Extension Center (Benton Harbor, MI). The
selected families were planted together at 0.7 m spacing within rows and 3 m between rows. The
plantings were established in 2006 and 2008. Parents with varying susceptibility were identified
based on the previous screenings by Polashock et al. (2005) and Miles et al. (2011) (Table 6.1).
The most susceptible cultivars according to the two previous studies are ‘Bluecrop’, ‘Duke’,
‘Jersey’ and ‘Nelson’. While the most consistently resistant cultivars between the studies are
‘Brigitta’ and ‘Elliott’ (Table 6.1). Sixteen crosses were selected, including ‘Aurora’ x ‘Legacy’,
‘Aurora’ x ‘Ozarkblue’, ‘Bluegold’ x ‘Elliott’, ‘Bluegold’ x ‘Nelson’, ‘Brigitta’ x ‘Draper’,
‘Brigitta’ x ‘Duke’ , ‘Brigitta’ x ‘Ozarkblue’, ‘Draper’ x ‘Legacy’, ‘Draper’ x ‘Nelson’, ‘Draper’ x
‘Ozarkblue’, ‘Liberty’ x ‘Legacy’, ‘Liberty’ x ‘Nelson’, ‘Liberty x Ozarkblue’, ‘Nelson’ x
‘Ozarkblue’, ‘Ozarkblue’ x ‘Elliott’, and ‘Ozarkblue’ x ‘Legacy’. Additionally within the field,
three reference cultivars (Bluecrop, Elliott, and Jersey) were present. Twenty individual daughter
plants were selected within each family and the same plants were screened in 2010 and 2011.

Fungal material and inoculation methods
A single-conidium isolate of C. acutatum isolated (#0001) from blueberry fruit in Grand
Junction, MI, USA in August 2006 was used for inoculations. This isolate was the most virulent of
25 isolates in a preliminary test and was in two previous studies (125, 126). Fungal cultures of C.
acutatum were grown and stored in accordance with Miles et al. (2011a). For inoculum
production, sporulating cultures were flooded with 3 mL of sterile deionized water (SDW), and
conidia were dislodged using a sterilized L-shaped glass rod. Conidia were counted using a
6

hemacytometer and diluted to 1 x 10 conidia per milliliter with SDW.

144

Table 6.1. Previous anthracnose fruit rot resistance profiles of blueberry cultivars used in this
study using proportion decayed values (150) and sporulation capacity (126). Both studies used
artificial inoculation, however, Polashock et al. (2005) inoculated green fruit and rated disease
incidence (proportion decayed) and Miles et al. (2011b) inoculated the cut surface of ripe fruit and
rated the quantity of conidia produced on a cut fruit surface (sporulation capacity).

Cultivar
Aurora
Bluecrop
Bluegold
Brigitta
Draper
Duke
Elliott
Jersey
Legacy
Liberty
Nelson
Ozarkblue

Proportion decayed (150)
0.78
0.54
0.18
0.44
0.15
0.38
0.10
0.50
0.55

145

Sporulation capacity
6
(no. of conidia x 10 per berry)
(126)
0.56
12.30
2.15
1.05
7.25
0.29
3.35
1.00
14.10
-

Pea-sized green fruit was inoculated on each daughter plant by using a hand-pump sprayer
and spraying conidial suspensions until run-off, covering the whole plant with a 114-liter, clear
plastic bag for approximately 12 hours overnight. Bags were removed the following morning. In
2010, plants were inoculated on 21 and 22 of June with nighttime temperatures ranging from 20 to
27°C. In 2011, plants were inoculated on 16 and 17 of June when nighttime temperatures ranging
from 15 to 24°C.

Disease rating
Fruit from inoculated plants was harvested in individual pint-sized clamshells when ripe
(fully blue) on four different dates in 2010 (7, 14, 21, and 28 of July) and in 2011 (6, 13, 20, and
27 of July). Fruit were immediately cooled, transported to the laboratory, and placed equidistantly
on wire mesh over a layer of water in covered aluminum pans that acted as humidity chambers,
and incubated for 12 days at 22 to 24 °C. Fruits were then monitored at 5, 8 and 12 days for
incidence of C. acutatum in the various progeny populations and cultivars. Between 25 and 200
fruits were harvested from each individual daughter plant, and the area under the disease progress
curve (AUDPC) was calculated for each individual. AUDPC values were calculated by summing
the area between 5 to 8 days and 8 to 12 days. Due to the fact that plants were small and it was not
always possible to procure enough fruit from each daughter, some families were sampled more
extensively than others.

146

Statistical analyses
Data were analyzed using an unbalanced analysis of variance and least square means
differences by Tukey’s HSD’s multiple range test for mean separation procedures using the
statistical algorithms and GLIMMIX procedure of SAS version 6.04 (SAS Institute, Cary, NC) and
SIGMAPLOT version 11 (SYSTAT Software, San Jose, CA). There was a significant effect of
year (P = 0.008) and therefore the data from 2010 and 2011 were analyzed separately.
Average AUDPC values for each family and cultivar were correlated against the previously
reported resistance ratings using proportion of decayed fruit from Polashock et al. (2005) and
Miles et al. (2011). We correlated the average AUDPC values of the progeny of each family with
the average the previously determined value of the parents (mid-parent value). Expected
midparent values from the two previous studies were compared with the mean AUDPC of each
2

cross family and the R value from this linear correlation was used to estimate heritability.

RESULTS
Daughters of cross families show a wide variation in susceptibility to C. acutatum
Fruit rot caused by C. acutatum significantly increased between 5 and 12 days after
inoculation. The area under the disease progress curve (AUDPC) was decided as the best method
to measure differences in disease incidence among the cross families and cultivars (Figure 6.1).
The analysis of variance showed many statistically significant differences among the cross families
and reference cultivars (P < 0.001 for 2010 and P < 0.001 for 2011). In 2010, AUDPC values
across the families and cultivars averaged 220 and ranged from 117 and 417. In 2011, the average
was 262 and ranged from 100 and 545 (Table 6.2). AUDPC values were highest for

147

0.5
2010
Total proportion decayed

0.4

2011

0.3

0.2

0.1

0.0
5

8

12

Time (days)
Figure. 6.1. The proportion of all blueberry fruit infected over time by Colletotrichum acutatum in
2010 and 2011 at 5, 8 and 12 days post incubation averaged over all of the cross families and
cultivars.

148

Table 6.2. Area under the disease progress (AUDPC) values of the incidence of Colletotrichum
acutatum on various blueberry cultivars and cross families screened by artificial inoculation in
2010 and 2011 at the Southwest Michigan Research and Extension Center (Benton Harbor, MI).
Fruit of 4 to 7-year old bushes were inoculated when immature, harvested when ripe, incubated,
and rated at 5, 8 and 12 days. A statistically significant effect of year (P = 0.008) so data from the
two years was analyzed separately.

a
b

a

Cultivar/Cross

N

Bluecrop
Elliott
Jersey
Aurora x Legacy
Aurora x Ozarkblue
Bluegold x Elliott
Bluegold x Nelson
Brigitta x Draper
Brigitta x Duke
Brigitta x Ozarkblue
Draper x Legacy
Draper x Nelson
Draper x Ozarkblue
Liberty x Legacy
Liberty x Nelson
Liberty x Ozarkblue
Nelson x Ozarkblue
Ozarkblue x Elliott
Ozarkblue x Legacy

5
5
5
14
19
19
19
8
20
20
13
20
13
14
20
11
20
13
19

b

a

2010
417.4 ± 34.8
159.6 ± 20.0
280.8 ± 29.8
117.9 ± 33.0
277.2 ± 25.0
132.0 ± 21.5
342.7 ± 24.1
127.3 ± 50.3
190.1 ± 24.1
163.8 ± 22.1
188.7 ± 26.6
206.4 ± 33.2
226.4 ± 33.1
127.2 ± 18.4
219.7 ± 36.3
242.1 ± 25.5
311.5 ±31.4
192.9 ± 48.7
262.3 ± 20.9

b

N
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg

5
5
5
3
8
16
18
2
20
13
16
12
8
2
12
6
18
0
13

2011
545.2 ± 70.0
138.2 ± 16.1
281.5 ± 22.9
162.4 ± 2.5
148.2 ± 19.4
183.6 ± 21.2
366.3 ± 40.2
186.1 ± 38.9
288.1 ± 26.0
319.2 ± 31.7
138.1 ± 31.7
165.5 ± 29.1
339.0 ± 31.6
99.9 ± 27.9
331.8 ± 47.2
155.7 ± 11.2
440.1 ± 26.5

abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
abcdefg
Abcdefg
Abcdefg
Abcdefg
Abcdefg
Abcdefg
Abcdefg
Abcdefg
Abcdefg
abcdefg

c

Nd
423.6 ± 41.6

abcdefg

N = Number of individual daughter plants per cross family.

Values in columns followed by the same letter are not significantly different according to a
Tukey’s HSD mean separation test (α = 0.05).
c
No data collected.

149

Nelson x Ozarkblue

Bluegold x Elliott

10

2010

A

Frequency

8
6
4
2
0
10

2011

B

Frequency

8
6
4
2
0

AUDPC Range
Figure 6.2. Distribution of anthracnose fruit rot resistance (expressed as area under the disease
progress curves (AUDPC)) in a susceptible x moderate cross (‘Nelson’ x ‘Ozarkblue’) and a
resistant x resistant cross (‘Bluegold’ x ‘Elliott’) in 2010 and 2011. A) ‘Nelson’ x ‘Ozarkblue’ in
2010, B) ‘Nelson’ x ‘Ozarkblue’ in 2011, C) ‘Bluegold’ x ‘Elliott’ in 2010, and D) ‘Bluegold’ x
‘Elliott’ in 2011. Discrete levels were defined every 50 AUDPC values..

150

‘Bluecrop’ (417 in 2010 and 545 in 2011), moderate for ‘Jersey’ (281 in 2010 and 282 in 2011),
and lowest for ‘Elliott’ (160 in 2010 and 138 in 2011). Families with the lowest average AUDPC
values were ‘Aurora’ x ‘Legacy’ (118 in 2010 and 162 in 2011), ‘Bluegold’ x ‘Elliott’ (132 in
2010 and 184 in 2011), ‘Brigitta’ x ‘Draper’ (127 in 2010 and 186 in 2011), ‘Draper’ x ‘Legacy’
(189 in 2010 and 138 in 2011), and ‘Liberty’ x ‘Legacy’ (127 in 2010 and 100 in 2011). Those that
showed relatively high overall AUDPC values included ‘Bluegold’ x ‘Nelson’ (343 in 2010 and
366 in 2011), ‘Draper’ x ‘Ozarkblue’ (226 in 2010 and 339 in 2011), and ‘Nelson’ x ‘Ozarkblue’
(312 in 2010 and 440 in 2011) (Figure 6.2).

Midparent regressions show a correlation between predicted and actual disease resistance
values suggesting heritability of resistance
AUDPC values for families and cultivars were significantly correlated with the values
derived from previous studies of anthracnose resistance including; proportion decayed which
2

2

focuses on disease incidence (R = 0.73, P = 0.001 for 2010, and R = 0.71, P = 0.004 for 2011)
2

(150) (Figure 6.3) and sporulation capacity which focuses on disease severity (R = 0.63, P =
2

0.033 for 2010, and R = 0.65, P = 0.029 for 2011) (126) (Figure 6.4). The predicted midparent
values for the proportion decayed for the various families averaged 0.391 and ranged from 0.310
and 0.525, using the parental values generated by Polashock et al. (2005). The predicted midparent
values for sporulation capacity of the various families averaged 5.36 and ranged between 1.60 and
7.58, based on the parental calculated by Miles et al. (2011).

151

600

2

R = 0.734
500 P = 0.001
AUDPC

Bluecrop
400

BGxN

300

OxLE

200 Elliott
A

Jersey

BRxDU
BGxE

100
600

NxO

OxE
BRxO

2

R = 0.711
500 P = 0.004

Bluecrop
NxO

AUDPC

OxLE
400
BRxO
300

BRxDU

BGxN

Jersey

200
B

100
0.1

Elliott

BGxE
0.3

0.5

0.7

0.9

Proportion decayed (derived from Polashock et al. 2005)
Figure 6.3. Correlation between the average anthracnose fruit rot incidence on various blueberry
cultivars and cross families expressed as area under the disease progress curves (AUDPC) against
actual and predicted proportion decayed values from Polashock et al. (2005) in (A) 2010 and (B)
2011. Abbreviations for parent cultivars: BG = Bluegold; BR = Brigitta; DU = Duke; E = Elliott;
LE = Legacy; N = Nelson; O = Ozarkblue.

152

600

2

R = 0.632
500 P = 0.033
AUDPC

Bluecrop
400
Jersey

300
200 Elliott

A

BRxDR

100
600

2

Bluecrop

R = 0.650
P = 0.029

500
AUDPC

BRxDU

400
Jersey

300

BRxDU

200 BRxDR
B

LIxN
DRxN

100

LIxN
DRxN

Elliott
0

2

4

6

8

10

12

14
6

Sporulation capacity (Number of conidia x 10 )
(derived from Miles et al. 2011)
Figure 6.4. Correlation between the average anthracnose fruit rot incidence on various blueberry
cultivars and cross families expressed as area under the disease progress curves (AUDPC) against
actual and predicted sporulation capacity values from Miles et al. (2011b) in (A) 2010 and (B)
2011. Abbreviations for parent cultivars: BR = Brigitta; DU = Duke; DR = Draper; E = Elliott; LI
= Liberty; N = Nelson.

153

DISCUSSION
There were significant differences in the relative disease susceptibilities of the various
families, as well as between the three reference cultivars. No family or cultivar exhibited complete
resistance; however this was not expected as previous studies have never identified a cultivar that
was immune to anthracnose fruit rot. Additionally, for the three cultivars screened, our results
mirrored two previous studies and identified ‘Bluecrop’ as highly susceptible, ‘Jersey’ as
intermediate, and ‘Elliott’ as highly resistant to anthracnose fruit rot (126, 150). Additionally, the
overall AUDPC values for the families were significantly correlated with the predicted values
based on previous screens of the parents for disease incidence and severity. This suggests that
anthracnose resistance is a highly heritable trait, which is strongly dependent on parental
susceptibility. Furthermore, this inheritance appears to be quantitative in nature, as a continuous
pattern of variability was observed within and between families. We can also make preliminary
estimate of heritability to anthracnose fruit rot resistance in blueberry as ranging between 0.61 to
2

0.73 (H ), which is fairly high. A study on C. graminicola resistance in corn reported values
between 26 and 70% using an ordinary least squares regression (30).
Quantitative resistance to plant pathogens is typically controlled by multiple loci of small
effect and is common in many Colletotrichum pathosystems (30, 50, 73, 89). While this
phenomenon has been documented in many systems it is poorly understood. In strawberry
different modes of inheritance for resistance to anthracnose have been suggested based on the
pathogenicity groups of Colletotrichum (51). Resistance to pathogenicity group 1 is quantitative,
however, a single dominant gene, Rca2, controls the resistance to pathogenicity group 2 although
minor genes may also contribute to this resistance in several cultivars (50).

154

Understanding how resistance is inherited might provide insight into the mechanism of
resistance. Multiple mechanisms of blueberry anthracnose resistance have been identified such as
increased sugar content within the fruit (126), a number of pathogensis related-proteins (125),
antimicrobial compounds (127) and an oxidative burst (125). A variety of defense mechanisms in
other Colletotrichum–plant interactions has been observed, including the production of reactive
oxygen species (25), host-derived cell wall-degrading enzymes (31, 76, 110, 204) and preformed
and induced antifungal compounds (159).
Future work to study segregating populations of specific crosses will make it possible to
identify loci that are involved in anthracnose fruit rot resistance in blueberries. In strawberries
sequenced characterized amplified region (SCAR) markers have been developed for the Rca2 gene
and it has been demonstrated to be highly predictive of anthracnose resistance (114). Identification
of quantitative trait loci (QTL) will be useful for developing a marker-assisted selection protocol,
which will greatly facilitate future screening for anthracnose fruit rot resistance early in the
breeding and selection process.

ACKNOWLEDGEMENTS
I would like to gratefully acknowledge funding from Michigan State University Project
GREEEN (Generating Research and Extension to meet Economic and Environmental Needs). I
would also like to thank Christopher Woelk, Kevin Messing, and Chelsea Reynolds for technical
assistance and Laura Avila for critical reading of the manuscript.

155

CONCLUSIONS AND FUTURE DIRECTIONS

156

Anthracnose fruit caused by Colletotrichum acutatum J. H. Simmonds is the most
important postharvest disease of blueberries (Vaccinium corymbosum). This thesis focused on
three main aspects of this disease; 1) host defense responses, 2) the inheritance of resistance and 3)
the environmental factors that are important in the infection process.
Our investigation of the environmental requirements to C. acutatum infection indicated that
temperature, wetness duration, wetness interruptions and relative humidity have a direct effect on
the development of melanized appressoria and infection of both immature and mature blueberry
fruits by C. acutatum. The relationship between temperature and wetness conforms to previous
studies of Colletotrichum spp. on other fruit crops (130, 168, 206). This research provides useful
information on temperature and wetness requirements for infection of blueberry fruit by C.
acutatum under controlled conditions and this represents the first step towards the development of
a disease prediction model for anthracnose fruit rot in blueberries. Further research is needed to
validate these results under field conditions. In the field, fruit clusters may stay wet longer than an
exposed leaf wetness sensor of a weather station would indicate. This needs to be taken into
account when applying a prediction model.
We also investigated differentially expressed genes in the resistant blueberry cultivar
Elliott, this research represents the first profiling of gene expression in a VacciniumColletotrichum interaction at different stages of the infection process and provides additional
evidence for an active resistance response in ‘Elliott’. We identified differentially expressed ESTs
in ‘Elliott’ versus ‘Jersey’ that were involved in defense, abiotic stimuli and development and
oxidative stress. Our results clearly showed a time delay between inoculation and measurable gene
expression. Consequently, there was a significant lag period before any defense response was
detectable, which would correlate well with previous microscopy studies outlined in Wharton and

157

Schilder (2008). These results add new insight into the host responses of blueberry fruit to
infection by C. acutatum at the molecular level and suggest that pathogen ingress into the host is
required for the activation of resistance. A more detailed investigation of gene expression during
the early stages of infection, including pre-penetration events, will help to pinpoint when the host
first recognizes C. acutatum and initiates the resistance response. Furthermore, chemical analysis
and studies on the genetic inheritance of resistance will complement molecular research in
elucidating the basis of anthracnose fruit rot resistance in blueberries.
Consequently, we looked at antimicrobial compounds present in ripe ‘Elliott’ fruits in
response to C. acutatum, and we found that ‘Elliott’ has more anthocyanins and non-anthocyanin
flavonoids than ‘Jersey’. Anthocyanins do not seem to play a direct role in the resistance response
but may play indirectly protect host tissues from oxidative damage. The non-anthocyanin
flavonoid fraction from ‘Elliott’ plays a key role in suppressing microconidiation and reducing
growth of C. acutatum. This fraction contained two unique flavonol glycosides; quercetin-3-Orhamnoside, and a dimethylmyricetin glycoside which may play a more specific role in the
resistance response because of its increased biological activity. The role of non-anthocyanin
flavonoids in the resistance response likely complements other aspects of ‘Elliott’ fruit rot
resistance that have been previously described, such as, higher levels of sugar content and an
oxidative burst following initial fungal penetration. Further investigation into how these
processes are regulated at the molecular level might provide new insights into the interaction.
In addition to that we investigated screening methods for anthracnose fruit rot resistance
breeding and we have developed a relatively rapid and simple screening assay that can be used
early in the selection process of blueberry germplasm. This would not preclude later screening
under greenhouse or field conditions but would certainly provide an initial resistance profile.

158

Relying on natural infection only may introduce confounding effects of weather and inoculum
availability as flowering and ripening times differ among blueberry cultivars. Artificial inoculation
of fruit with no background infection is most desirable to identify an accurate resistance
phenotype. Despite evidence for the role of sugar content in anthracnose fruit rot resistance, this
characteristic is not suitable as a single marker due to the moderate strength of the correlation.
However, selection for high sugar content may inadvertently yield anthracnose fruit rot-resistant
cultivars as an added benefit. Future investigation is required to elucidate the molecular and
biochemical mechanism(s) of anthracnose fruit rot resistance in blueberry in order to identify
specific markers for resistance screening and novel strategies for disease management.
Lastly, we investigated the inheritance of C. acutatum resistance in highbush blueberries.
There were significant differences in the relative disease susceptibilities of the various cross
families, as well as between the three reference cultivars (Bluecrop, Elliott, and Jersey). No family
or cultivar exhibited complete resistance; however this was not expected as previous studies have
never identified a cultivar that was immune to anthracnose fruit rot. Additionally, the overall
AUDPC values for the families were significantly correlated with the predicted values based on
previous screenings of the parents for disease incidence and severity. This suggests that
anthracnose resistance is a highly heritable trait, meaning that it is strongly dependent on parental
susceptibility. Furthermore, this inheritance appears to be quantitative in nature, as a continuous
pattern of variability was observed within and between families. We can also make preliminary
2

estimates of resistance in blueberry as ranging between 0.61 to 0.73 (H ), which is fairly high.
Future work on segregating populations of specific crosses will make it possible to identify loci
that are involved in anthracnose fruit rot resistance in blueberries. In strawberries SCAR markers
have been developed for such loci and they have been demonstrated to be highly predictive of
159

anthracnose resistance (114). Identification of quantitative trait loci (QTL) will be useful for
developing a marker-assisted selection protocol, which will greatly facilitate future screening for
anthracnose fruit rot resistance early in the breeding and selection process.

160

APPENDICES

161

APPENDIX A. RAW DATA FIGURES FROM CHAPTER II

80

60

40

20
40
30

0
30

20
25

20

10
15

10

Figure A.1. The effect of temperature and wetness duration on the development of melanized
appressoria of Colletotrichum acutatum on parafilm slides. Discrete transitions indicate levels of
melanized appressoria every 20% starting at zero.

162

120

120

80

80

40

40

0
30
A

20
10

40
30
20
10

0
30
B

20
10

40
30
20
10

Figure A.2. The effect of temperature and wetness duration on the infection level of immature (A)
and mature (B) blueberry fruits by Colletotrichum acutatum. Discrete transitions indicate levels of
infected fruit every 20% starting at zero.

163

80

60

40

20

16
14
12
10

0
45

8
40

35

6
30

4

25

20

15

2

Figure A.3. The effect of wetness duration and interrupted wetness periods on the development of
melanized appressoria of Colletotrichum acutatum on parafilm slides. Values are calculated as the
melanized appressoria (%) relative to the no interruption control. Discrete transitions indicate
levels of melanized appressoria every 20% starting at zero.

164

160

160

120

120

80

80

40

16
12

0

45

40
0

8
35

25

4
15

A

16
12
45

8
35

25

4
15

B

Figure A.4. The effect of wetness duration and interrupted wetness periods on the infection level
of immature (A) and mature (B) blueberry fruits by Colletotrichum acutatum. Values are
calculated as the infected fruit (%) relative to the no interruption control. Discrete transitions
indicate levels of infected fruit every 20% starting at zero.

165

80

125

60

100
75

40
20
0
30 28
26 24
A
22

50

100

25
0
30 28
26 24
B
22

80
60
20

100
80
60
20

Figure A.5. The effect of temperature and relative humidity on the development of melanized
appressoria (%) of Colletotrichum acutatum (A), and the infection level of mature blueberry fruits
(B) by C. acutatum. Discrete transitions indicate levels of melanized appressoria every 20%
starting at zero and in mature fruit levels are indicated every 20% starting at zero.

166

APPENDIX B. SUPPLEMENTAL TABLES AND FIGURES FROM CHAPTER III

Table B.1. Characteristics and predicted physiological function of differentially expressed sequence tags (ESTs) from ripe fruit of
highbush blueberry cultivar Elliott versus cultivar Jersey after inoculation with Colletotrichum acutatum. The hypothetical function is
based on homology to sequences in translated nucleotide databases (DDBJ/EMBL/GenBank) using TBLASTX. Some ESTs are likely
of fungal origin based on homology with fungal genes.

ID code

a

Size
b
(bp)

Redundancy

c

Genbank
Accession
No.

Homologous Gene
(BLAST Hit Accession Number)

Homologous
Species

Small subunit ribosomal RNA
(AY157626)
12S small subunit ribosomal RNA
(FJ190616)

Penicillium
expansum
Petriella
setifera

Score

E value

-5

Putative fungal proteins (E values < 1x 10 )
EST02

262

1

GW397253

EST09

251

1

GW397260
-5

-1

-52

209

7.0 x 10

47.3

7.0 x 10

-12

Hypothetical proteins (E values > 1x 10 and < 1x10 )
EST12

215

1

GW397263

Hypothetical protein (AF241472)

290

3

GW397264

Hypothetical protein (AC135360)

122

1

GW397265

EST16

300

1

EST17

183

EST18
EST19

EST13*
EST14

d

Penicillium
waksmanii
Mus musculus

-3

32.2

2.0 x 10

35.9

5.6 x 10

Hypothetical protein (XM001907104) Mus musculus

31.8

1.0 x 10

GW397267

Hypothetical protein (AC135360)

Mus musculus

37.3

2.5 x 10

1

GW397268

Hypothetical protein (AC098883)

40.0

1.5 x 10

319

1

GW397269

34.5

1.6 x 10

137

1

HO762505

Mus musculus
Actinidia
Hypothetical protein (EF530146)
deliciosa
Ricinus
Hypothetical protein (XM002519631)
communis

42.8

2.3 x 10

167

-2
-1
-2
-1
-1
-2

Table B.1. (cont’d.)
-1

a

Unknown (E values > 1 x 10 )
EST15
80
1
EST20
272
1
EST21
99
1
EST22
272
1
EST23
233
1
EST24
63
1
EST25
120
1
EST26
150
1
EST27
273
1
EST28
188
1
EST29
174
1
EST30
290
1
EST31
332
1
EST32
311
1
EST33
322
1
b

GW397266
HO762506
HO762507
HO762508
HO762509
HO762510
HO762511
HO762512
HO762513
HO762514
HO762515
HO762516
HO762517
HO762518
HO762519

No homology
No homology
No homology
No homology
No homology
No homology
No homology
No homology
No homology
No homology
No homology
No homology
No homology
No homology
No homology
c

N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A

d

N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A

N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A

ID code = identification code; bp=number of base pairs; = number of times sequence was recovered; = * denotes ESTs selected
for further study.

168

Elliott

Jersey

1

2

3

4

5

6

7

8

9

10

11

12

13

14

Figure B.1. Optimization of cDNA amplification using various PCR amplification cycles (1530), for C. acutatum-inoculated fruit of blueberry cultivars Jersey (lanes 2-7) and Elliott (lanes 914) (5 µL loaded per well). Lanes 1 and 8, 1-kb+ DNA ladder; lanes 2 and 9, 15 cycles; lanes 3
and 10, 18 cycles; lanes 4 and 11, 21 cycles; lanes 5 and 12, 24 cycles; lanes 6 and 13, 27 cycles;
lanes 7 and 14, 30 cycles. Twenty one cycles was found to be optimal for both libraries and those
products were used for digestion and adapter ligation.

169

Elliott

Jersey

1

2

3

4

5

6

Figure B.2. Restriction enzyme digestion of pooled cDNA libraries of the blueberry cultivars
Jersey and Elliott after inoculation with C. acutatum for the generation of shorter, blunt-end
fragments (necessary for adaptor ligation and subtraction). Lanes 1 and 4, 1-kb+ DNA ladder;
lanes 2 and 5, samples from ‘Jersey’ and ‘Elliott’ before digestion, respectively; lanes 3 and 6,
samples from ‘Jersey’ and ‘Elliott’ after digestion, respectively.

170

1

2

3

4

5

6

7

8

9

10

Figure B.3. Primary (lanes 2-5) and secondary (lanes 7-10) PCR products of pooled cDNA
libraries in subtracted and nonsubtracted samples of blueberry cultivars Elliott and Jersey after
inoculation with C. acutatum. These products were used for the construction of DIG probes and
for cloning of the subtractive libraries for differential screening. Lanes 1 and 6, 1-kb+ DNA
ladder; lanes 2 and 3, ‘Elliott’ and ‘Jersey’ subtracted primary PCR products, respectively; lanes
4 and 5, ‘Elliott’ and ‘Jersey’ nonsubtracted primary PCR products, respectively; lanes 7 and 8,
‘Elliott’ and ‘Jersey’ subtracted secondary PCR products, respectively; lanes 9 and 10, ‘Elliott’
and ‘Jersey’ nonsubtracted secondary PCR products, respectively.

171

APPENDIX C. SUPPLEMENTAL FIGURES FROM CHAPTER IV
Table C.1. Bioactivity of extracts and fractions from the anthracnose-resistant blueberry cultivar
Elliott and susceptible cultivar Jersey as measure by their ability to inhibit microconidiation of
Colletotrichum acutatum on solid media (+ = activity, - = no activity).

Type of extract/fraction

Amount of extract/fraction (μg)

Cultivar

Methanolic

Elliott

1000
+

500
+

250
-

125
-

63
-

31
-

16
-

Ethyl Acetate

Elliott

-

-

-

-

-

-

-

Soluble methanol

Elliott

+

+

+

-

-

-

-

Insoluble methanol

Elliott

+

-

-

-

-

-

-

Anthocyanin

Elliott

+

-

-

-

-

-

-

Non-anthocyanin
flavonoid

Elliott

+

+

+

+

-

-

-

Methanolic

Jersey

+

-

-

-

-

-

-

Ethyl Acetate

Jersey

-

-

-

-

-

-

-

Soluble methanol

Jersey

+

+

-

-

-

-

-

Insoluble methanol

Jersey

-

-

-

-

-

-

-

Anthocyanin

Jersey

-

-

-

-

-

-

-

Non-anthocyanin
flavonoid

Jersey

+

+

+

-

-

-

-

172

1

2

3

4

1.0
0.8

1
2

AU

0.6

3
4

0.4
0.2

A

0.0
200
B

300

400
500
Wavelength (nm)

600

Figure C.1. TLC plate assay showing inhibition of microconidiation of Colletotrichum acutatum
and UV/Vis spectra of methanolic extracts from ripe fruit of the anthracnose-resistant blueberry
cultivar Elliott and susceptible cultivar Jersey. (A) Cellulose TLC plate after inoculation with
conidia of C. acutatum and stained with iodine crystals (gas phase). (B) UV/Vis spectra of the
boxed area in the TLC plate. (Note: 1 = methanolic extract of uninoculated ‘Elliott’ fruit, 2 =
methanolic extract of ‘Elliott’ fruit 4 days after inoculation, 3 = methanolic extract of
uninoculated ‘Jersey’ fruit, and 4 = methanolic extract of ‘Jersey’ fruit 4 days after inoculation.

173

50g of frozen blueberry tissue*
- Grind tissue
- Add 150 ml of H2O
- Lyophilize
Residue

H2O
Extract

- Add 150 ml of MeOH
- Evaporate liquid
Residue

Methanol
Extract

- Add 150 ml of EtAc
- Evaporate liquid
Ethyl Acetate
Extract

Waste

*C. acutatum inoculated and uninoculated blueberry tissue
from ‘Elliott’ and ‘Jersey’ was analyzed.
Figure C.2. Schematic presentation of the extraction procedures for biochemical analysis of
blueberry fruit using fresh fruit material and the solvents water, methanol, and ethyl acetate.

174

50g of lyophilized blueberry tissue*
- Add 150 ml of MeOH
- Evaporate liquid
Methanol
Extract
- Add 20 ml MeOH for 1 min
Residue

- Evaporate liquid
Methanol
Soluble
Fraction

- Add 150 ml of EtAc

Methanol
Insoluble
Fraction

- Evaporate liquid
Ethyl
Acetate
Extract

*C. acutatum inoculated and uninoculated blueberry tissue from
‘Elliott’ and ‘Jersey’ was analyzed.

Waste

Figure C.3. Schematic presentation of the extraction procedures for biochemical analysis of
blueberry fruit using lyophilized fruit material and the solvents methanol, and ethyl acetate.

175

APPENDIX D. PATHOGENICITY OF VARIOUS ISOLATES OF COLLETOTRICHUM
ACUTATUM ON ‘JERSEY’ BLUEBERRIES

Table D.1. Pathogenicity of various isolates of Colletotrichum acutatum on detached fruit of the
susceptible blueberry cultivar Jersey. Isolates were obtained from various hosts including
highbush blueberry (Vaccinium corymbosum), currant (Ribes spp.), cranberry (Vaccinium
macrocarpon), raspberry (Rubus spp.), blackberry (Rubus spp.), strawberry (Fragaria x
ananassa), and grape (Vitis spp.). Ripe ‘Jersey’ fruits were harvested from a field planting in
6

Harrietta, MI in August 2006, spray-inoculated with 10 conidia per ml, incubated at 100%
relative humidity, and rated for incidence of disease 10 days post inoculation (n = 5 and SE =
standard error of the mean).
Isolate
number

Strain ID

Location
(County)

Tissue
type

Host

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21

Cola 103-193
BB 599-81b
BB 599-42f
BB 599-122f
BB 599-72a
BB 599-1b
BB 599-26b
BB 599-143c
BB 599-121c
13-a-a
1c-a
1a-a
4a-a
None
6a
Colac 01-083
6a
4a
1f-b
10b-b
Colsp 02-034b

Berrien
Van Buren
Allegan
Newago
Unknown
Van Buren
Allegan
Muskegon
Newago
Unknown
Unknown
Berrien
Ingham
Kent
Ingham
Unknown
Van Buren
Van Buren
Unknown
Unknown
Ingham

Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit
Fruit

Blueberry
Blueberry
Blueberry
Blueberry
Blueberry
Blueberry
Blueberry
Blueberry
Blueberry
Raspberry
Blackberry
Blackberry
Blackberry
Currant
Cranberry
Cranberry
Cranberry
Cranberry
Raspberry
Raspberry
Raspberry

176

Proportion
decayed ±
SE
0.90 ± 0.06
0.90 ± 0.06
0.70 ± 0.06
0.70 ± 0.06
0.85 ± 0.10
0.70 ± 0.13
0.65 ± 0.17
0.70 ± 0.10
0.75 ± 0.15
0.40 ± 0.08
0.55 ± 0.05
0.15 ± 0.05
0.75 ± 0.05
0.45 ± 0.10
0.70 ± 0.10
0.40 ± 0.08
0.80 ± 0.00
0.60 ± 0.08
0.65 ± 0.10
0.45 ± 0.05
0.50 ± 0.17

Mean
a
separation
abcdefghij
abcdefghij
abcdefghij
abcdefghij
abcdefghij
abcdefghij
abcdefghi
abcdefghij
abcdefghij
abcdefghi
abcdefghi
abcdefghi
abcdefghij
abcdefghi
abcdefghij
abcdefghi
abcdefghij
abcdefghi
abcdefghi
abcdefghi
abcdefghi

Table D.1. (cont’d.)
22
23
24
25
26

a

1a
Colac 03-109
Colac 03-110
Colsp 04-133
0001

Leelanau
Ingham
Ingham
Ingham
Van Buren

Fruit
Fruit
Fruit
Leaf
Fruit

Strawberry
Strawberry
Strawberry
Grape
Blueberry

0.80 ± 0.14
0.40 ± 0.08
0.60 ± 0.08
0.30 ± 0.13
0.95 ± 0.05

abcdefghij
abcdefghi
abcdefghi
abcdefghi
abcdefghij

Values in columns followed by the same letter are not significantly different according to a
Fisher’s LSD mean separation test (α = 0.05).

177

APPENDIX E. SCREENING DAUGHTER BLUEBERRY PLANTS FROM A DRAPER x
JEWEL CROSS FOR RESISTANCE TO COLLETOTRICHUM ACUTATUM

Table E.1. Anthracnose resistance ratings of detached blueberryfruits from several daughters of
a Draper x Jewel cross. Fruits were harvested in Interlachen, FL between 26 April and 12 May in
2011, stored, and shipped overnight to Michigan State University and inoculated with 10

6

spores/ml by spraying (whole fruit assays) or by a 50 µl droplet on a cut fruit surface (cut fruit
assays). Fruits incubated at 100% relative humidity at 22-24°C and rated at 3 days (for cut fruit
assays) or 10 days ( for whole fruit assays). For each daughter 5 fruits were screened per
replicate (25 in total, and n = 5) per type of inoculation.
Cultivar/
Daughter
number
Jewel
1
2
3
4
5
7
9
10
12
13
14
15
16
17
18
19
20
21
22
25

Whole fruit assays
Infection severity
(percentage ± SE)
59.6 ± 12.0
34.8 ± 22.3
26.8 ± 6.8
38.8 ± 6.8
44.4 ± 12.8
47.6 ± 14.3
70.4 ± 21.5
61.0 ± 21.0
33.2 ± 13.3
50.0 ± 30.8
28.5 ± 25.5
26.4 ± 14.6
58.4 ± 33.2
55.3 ± 19.6
16.3 ± 15.5
48.4 ± 27.3
62.8 ± 27.1
40.8 ± 17.5
40.9 ± 27.4
22.6 ± 25.0
70.4 ± 35.0

Cut fruit assays
Sporulation capacity
Optical density
6
(λ
590 nm ± SE)
(no. of conidia x 10 ± SE)
12.8 ± 7.9
0.19 ± 0.10
15.1 ± 19.7
0.24 ± 0.28
2.5 ± 4.1
0.04 ± 0.03
14.1 ± 6.3
0.16 ± 0.09
4.0 ± 7.2
0.06 ± 0.07
1.8 ± 2.1
0.04 ± 0.03
5.8 ± 4.7
0.11 ± 0.05
64.4 ± 11.0
0.48 ± 0.09
1.0 ± 2.4
0.02 ± 0.02
1.5 ± 1.7
0.03 ± 0.02
18.6 ± 8.7
0.24 ± 0.11
2.2 ± 1.5
0.03 ± 0.02
2.1 ± 3.6
0.05 ± 0.03
7.9 ± 8.0
0.10 ± 0.07
1.8 ± 1.6
0.11 ± 0.05
4.5 ± 1.9
0.07 ± 0.01
1.9 ± 2.5
0.04 ± 0.03
11.8 ± 4.5
0.17 ± 0.09
16.2 ± 2.6
0.20 ± 0.01
12.4 ± 12.8
0.14 ± 0.09
1.4 ± 1.5
0.04 ± 0.02
178

Table E.1. (cont’d.)
27
28
30
31
32
33
34
35
37
38
39
40
41
42
43
44
45
48
49
50
51
52
53
54
55
56
58
59
60
61
62
65
66
67
69
72
73
75
76
77
78
79
83

66.4 ± 31.5
36.4 ± 22.7
45.9 ± 14.0
35.6 ± 19.6
54.4 ± 28.5
24.0 ± 17.9
71.2 ± 12.9
38.0 ± 34.4
36.0 ± 29.5
47.6 ± 24.6
48.4 ± 23.5
71.0 ± 19.1
76.4 ± 17.7
26.8 ± 26.0
50.0 ± 10.5
93.2 ± 19.1
42.8 ± 17.8
42.4 ± 30.6
40.8 ± 32.3
54.0 ± 24.7
48.0 ± 27.4
51.6 ± 15.0
46.0 ± 48.2
59.2 ± 26.4
33.2 ± 20.2
46.8 ± 27.0
67.2 ± 24.6
69.3 ± 25.7
52.4 ± 8.6
82.8 ± 22.0
27.2 ± 10.0
51.2 ± 22.5
50.8 ± 21.6
88.8 ± 27.1
37.6 ± 16.6
64.4 ± 21.1
53.6 ± 8.0
58.0 ± 31.5
44.0 ± 11.4
30.8 ± 23.8
42.0 ± 17.0
57.2 ± 8.1
26.0 ± 13.0

3.6 ± 2.3
1.0 ± 1.3
5.1 ± 3.8
2.2 ± 2.6
7.2 ± 3.5
10.5 ± 2.4
7.8 ± 4.3
12.8 ± 13.5
0.4 ± 0.4
41.7 ± 29.0
1.5 ± 1.9
11.5 ± 6.0
4.5 ± 2.2
13.7 ± 9.7
4.7 ± 2.6
19.0 ± 16.6
7.7 ± 4.3
9.8 ± 6.3
16.9 ± 15.8
1.5 ± 2.3
2.6 ± 3.9
26.9 ± 15.4
3.7 ± 4.4
22.0 ± 11.2
4.8 ± 3.7
2.5 ± 1.5
22.6 ± 20.0
8.0 ± 6.6
11.5 ± 6.5
10.0 ± 7.6
10.7 ± 11.0
41.8 ± 14.9
6.8 ± 6.1
11.7 ± 8.7
7.0 ± 1.4
56.7 ± 5.2
5.4 ± 3.1
44.1 ± 11.1
2.1 ± 1.8
1.1 ± 1.9
0.6 ± 0.8
7.2 ± 5.1
2.7 ± 4.7

179

0.06 ± 0.05
0.05 ± 0.04
0.13 ± 0.09
0.25 ± 0.25
0.11 ± 0.04
0.11 ± 0.03
0.09 ± 0.03
0.16 ± 0.11
0.03 ± 0.02
0.35 ± 0.27
0.04 ± 0.03
0.17 ± 0.05
0.07 ± 0.05
0.12 ± 0.08
0.09 ± 0.15
0.14 ± 0.09
0.11 ± 0.05
0.11 ± 0.06
0.20 ± 0.10
0.07 ± 0.03
0.06 ± 0.04
0.27 ± 0.09
0.06 ± 0.05
0.20 ± 0.07
0.10 ± 0.06
0.05 ± 0.02
0.24 ± 0.19
0.09 ± 0.07
0.14 ± 0.04
0.09 ± 0.05
0.16 ± 0.32
0.40 ± 0.13
0.11 ± 0.04
0.19 ± 0.09
0.10 ± 0.07
0.53 ± 0.11
0.14 ± 0.25
0.37 ± 0.10
0.03 ± 0.01
0.03 ± 0.01
0.04 ± 0.04
0.09 ± 0.07
0.06 ± 0.05

Table E.1. (cont’d.)
85
86
87
88
89
90
93
94
99
101

64.0 ± 20.7
29.6 ± 14.3
59.6 ± 27.1
80.8 ± 43.4
46.4 ± 9.7
42.8 ± 14.4
32.0 ± 16.7
58.8 ± 19.1
66.8 ± 19.9
78.8 ± 12.1

34.8 ± 22.3
7.0 ± 5.4
17.4 ± 8.4
5.7 ± 6.6
31.7 ± 14.4
6.2 ± 4.4
15.1 ± 8.8
29.2 ± 8.9
4.2 ± 3.0
20.7 ± 15.3

180

0.32 ± 0.11
0.09 ± 0.02
0.17 ± 0.08
0.09 ± 0.08
0.30 ± 0.12
0.09 ± 0.08
0.15 ± 0.08
0.32 ± 0.07
0.08 ± 0.06
0.20 ± 0.13

Table E.2. Anthracnose resistance ratings of detached blueberryfruits from several daughters of
a Draper x Jewel cross. Fruits were harvested in Corvallis, OR between 20 July and 11 August in
2011, stored, and shipped overnight to Michigan State University and inoculated with 10

6

spores/ml by a 50 µl droplet on a cut fruit surface. Fruits incubated at 100% relative humidity at
22-24°C and rated at 3 days. For each daughter 5 fruits were screened per replicate (25 in total,
and n = 5) per type of inoculation.
Optical density
(λ 590 nm ± SE)
0.07 ± 0.01
0.18 ± 0.01
0.17 ± 0.01
0.12 ± 0.02
0.12 ± 0.04
0.20 ± 0.01
0.11 ± 0.03
0.11 ± 0.01
0.08 ± 0.01
0.12 ± 0.01
0.09 ± 0.01
0.07 ± 0.01
0.18 ± 0.00
0.09 ± 0.01
0.11 ± 0.01
0.17 ± 0.03
0.13 ± 0.01
0.14 ± 0.01
0.17 ± 0.00
0.13 ± 0.01
0.20 ± 0.01
0.10 ± 0.01
0.08 ± 0.01
0.07 ± 0.01
0.12 ± 0.01
0.14 ± 0.03
0.09 ± 0.01
0.13 ± 0.01
0.16 ± 0.01
0.07 ± 0.01
0.09 ± 0.02

Cultivar/Daughter number
Draper
1
8
10
11
13
14
15
16
18
19
20
21
22
24
25
27
28
29
30
31
32
33
34
35
39
40
41
42
43
44
181

Table E.2. (cont’d.)
45
50
54
56
60
61
65
75
77
79
83
85
99

0.10 ± 0.02
0.13 ± 0.02
0.18 ± 0.02
0.13 ± 0.02
0.18 ± 0.01
0.08 ± 0.01
0.30 ± 0.01
0.32 ± 0.02
0.13 ± 0.01
0.10 ± 0.02
0.12 ± 0.01
0.22 ± 0.02
0.09 ± 0.02

182

0.35

Optical density (Table E.2 values)

r = 0.744
0.30

P < 0.001

0.25
0.20
0.15
0.10
0.05

0.0

0.1

0.2

0.3

0.4

0.5

Optical density (Table E.1 values)
Figure E.1. Relationship between the concentration of an aqueous suspension of Colletotrichum
acutatum from anthracnose resistance cut fruit screenings (590 nm) (Table E.1 and E.2 values) of
detached blueberry fruits from several daughters of a Draper x Jewel cross.

183

APPENDIX F. THE ROLE OF ETHYLENE IN BLUEBERRY ANTHRACNOSE FRUIT ROT
RESISTANCE

0.16

Ethylene levels (ppm) per
25g of blueberries

0.14

n=4

0.12
0.10
0.08
0.06
0.04
0.02
0.00

Figure F.1. External differences in ethylene concentration in ‘Elliott’ and ‘Jersey’ fruits after
inoculation of Colletotrichum acutatum or sterile deionized water. Fruits were spray-inoculated
6

with 10 conidia/ml, incubated at 100% relative humidity for 48 hours at 22-24°C, placed in
quart sized mason jars, ethylene concentration was measured using then was measured 2 hours
later using previously described methods (1). Error bars denote standard error of the mean.

184

1.6
Ethylene concentration (ppm)

1.4

n=3

1.2
1.0
0.8
0.6
0.4
0.2
0.0
Elliott

Jersey

Figure F.2. Internal differences in ethylene concentration within ‘Elliott’ and ‘Jersey’ fruits.
Fruits were immersed in a saturated solution of KCl, a vaccum was applied and headspace
analysis was used to measure the concentration of ethylene in accordance with previous methods
(1, 2). Error bars denote standard error of the mean.

185

Ethylene concentration (ppm)

6

No. of conidia produced per berry (10 )

30

n=5

25
20
15
10
5
0

1.2
1.0

n=3

0.8
0.6
0.4
0.2
0.0
0

A

2

4 6 8 10 12 14 16
Time (days)

B

Figure F.3. Effect of ethylene on anthracnose symptom development in ‘Elliott’ and ‘Jersey’
fruits. A) Amount of conidia produced per berry in ‘Elliott’ and ‘Jersey’ fruits in each chamber
(ethylene or air). B) Levels of ethylene in both chambers throughout a 14 day period. Two 30gallon tanks were used to simulate an environment with 1ppm ethylene or air. Fruits were spray6

inoculated with 10 conidia/ml, incubated at 100% relative humidity for 14 days at 22-24°C,
ethylene concentration was measured in accordance with previous methods (1). Closed circles
represent the ethylene chamber, open circles represent the air chamber. Error bars denote
standard error of the mean.

References: (1) S. Jayanty et al. J. Amer. Soc. Hort. 127:998-1005, 2002. (2) L. Sun et al.
Euphytica. 165:55-67, 2009.

186

APPENDIX G. FIRST REPORT OF GRAPE ROOT ROT CAUSED BY ROESLERIA
SUBTERRANEA IN MICHIGAN

Published in the peer-reviewed journal Plant Disease (July 2009, Volume 93, Page 765)

In September of 2008, declining grapevines were observed in two vineyards (Vitis
interspecific hybrids ‘Canada Muscat’ and ‘Chardonel’) in Fennville, MI. Affected vines were
stunted with shortened internodes and yellow leaves; others had dead cordons or were entirely
dead. The grower reported that vines were losing vigor and collapsing during a period of 2 years.
Renewal trunks would collapse during the second season of growth. Several symptomatic vines
showed signs of root decay. On one vine, distinctive fruiting bodies (mazaedia) were apparent on
the roots below the soil line and resembled those of Roesleria subterranea (Weinm.) Redhead
(2,3,4). The mazaedia were 4 to 5 mm tall and 1 mm in diameter with white-to-tan stipes and
powdery, gray-to-greenish hemispherical heads. Ascospores were hyaline to light grayish green,
disk shaped, and 4 to 6 μm in diameter. This fungus, also known as R. hypogaea Thüm & Pass.,
has been previously reported to cause grape root rot, vine decline, and replant problems in North
America and Europe (2,3,4). The fungus was cultured from ascospores on potato dextrose agar
(PDA). Colonies grew slowly (approximately 2 mm per day at 22 to 24°C) and were green in the
center. No spores were produced. DNA was extracted, and internal transcribed spacer (ITS)
sequences obtained by PCR were compared with known sequences using BLASTn (1). Our
isolate had 100% ITS sequence homology to an isolate from Germany, Roesleria subterranea
strain IB (Accession No. EF060304.1). To test for pathogenicity, the fungus was grown in potato
dextrose broth for 14 days at 22 to 24°C. An aqueous suspension (0.1 g of fungus per ml) was
187

prepared by blending mycelia with sterile deionized water (SDW) in a food processor. Five twonode, rooted ‘Chardonnay’ cuttings (45 days old) were placed in the suspension. Five other
cuttings were placed in SDW (control). After 3 h, plants were removed and repotted in fresh
BACTO soil (Michigan Peat Company, Houston, TX) and kept in a growth chamber at 23°C
with a 16/8-h light/dark cycle. After 25 days, inoculated plants were, on average, 63% smaller
with 77% lower fresh-root weight and fewer fine roots than the control plants. The pathogen was
recovered from surface-disinfested roots of all five inoculated plants but not from the control
plants. Cultures appeared similar to the original isolate and their identity was confirmed by ITS
sequencing. To our knowledge, this is the first report of R. subterranea on grapes in Michigan
and the Midwest. This fungus needs to be recognized as a potential cause of vine decline and
replant problems in Midwestern vineyards.

References: (1) S. F. Altschul et al. J. Mol. Biol. 215:403, 1990. (2) W. Gärtel. Page 40 in:
Compendium of Grape Diseases. R. C. Pearson and A. C. Goheen, eds. The American
Phytopathological Society, St. Paul, MN, 1988. (3) M. Kirchmair et al. Mycol. Res. 112:1210,
2009. (4) J. R. Liberato et al. Pest and Diseases Image Library. Online publication, 2009.

188

APPENDIX H. FIRST REPORT OF PYTHIUM STERILUM CAUSING ROOT ROT OF
BLUEBERRY IN THE UNITED STATES

Published in the peer-reviewed journal Plant Disease (May 2011, Volume 95, Page 614)

In September 2009, ~40 declining blueberry plants (Vaccinium corymbosum L. ‘Jersey’)
were observed in a poorly drained area of a 30-year-old field near Fennville, MI. The stunted
bushes had yellow leaves and defoliation; others were completely dead. The grower reported that
the bushes had been declining over several years. Root samples tested positive in a Phytophthora
ELISA test (Agdia Inc., Elkhart IN). Twenty root pieces (2 cm long and 2 to 3 mm in diameter)
were surface disinfested and plated on Rye A agar; five yielded fungal-like colonies that were
subcultured on potato dextrose agar (PDA). One isolate was white and grew slowly (3 to 4
mm/day at 22 to 24°C). Three isolates were white and grew faster (10 to 12 mm/day at 22 to
24°C) in a chrysanthemal pattern. The fifth was a Fusarium sp. DNA of the white colonies was
extracted and the internal transcribed spacer (ITS) region was sequenced using ITS1 (5′TCCGTAGGTGAACCTGCGG-3′) and ITS4 (5′-TCCTCCGCTTATTGATATGC-3′) primers.
The slow-growing morphotype had 99% identity to Phytophthora sp. isolate 92-209C (Accession
No. EU106591) in GenBank but failed to induce symptoms in multiple inoculation tests. The
fast-growing morphotype (Accession No. HQ398249) had 98% identity to Pythium sterilum
UASWS0265 from declining alder stands in Poland (Accession No. DQ525089). Sequencing of
the COXII gene using the FM66/FM58 primer set (3) yielded a product (Accession No.
HQ721468) with 100% identity to P. sterilum GD32a from forest soil in Poland (Accession No.
EF421185). Hyphae were hyaline, coenocytic, and 4 to 7 μm wide with some swellings at the
189

tips (7 to 9 μm wide). No sporangia, oogonia, or antheridia were observed. Mycelium tested
positive in the ELISA test described above. According to Agdia Inc., 10 of 19 tested Pythium
spp. have shown similar cross reactivity. Pythium spp. are known to cause root rot of blueberries
in Oregon (2). In British Columbia, P. sterilum was commonly isolated from roots of declining
blueberry bushes (4). P. sterilum Belbahri & Lefort only reproduces asexually (1). Our isolate
was similar but did not produce sporangia in water or on PDA, V8 juice agar, Rye A agar, or
water agar. Roots of 10 2-month-old ‘Bluecrop’ cuttings were placed in an aqueous suspension
of rinsed mycelium (0.1 g/ml) from 21-day-old cultures grown in V8 broth or in sterile deionized
water (control). After 1 h, plants were potted in peat moss/perlite (2:1) or autoclaved sand (five
each) and placed in a glasshouse at 25°C. After 7 days, inoculated plants in both soil types had
wilted or collapsed with significant necrosis on the roots and primary shoot. Control plants
showed no symptoms. In a similar experiment with 6-month-old plants in sand, symptoms
appeared after 10 to 12 days. The pathogen was recovered from surface-disinfested root and stem
sections of all inoculated plants but not control plants and its identity was confirmed by
sequencing of the ITS region. To our knowledge, this is the first report of P. sterilum on
blueberries in the United States. While this disease appears to be uncommon in Michigan, it is a
potential cause of plant decline, the diagnosis of which may be complicated by cross reactivity in
ELISA testing.

References: (1) L. Belbahri et al. FEMS Microbiol. Lett. 255:209, 2006. (2) D. R. Bryla and R.
G. Linderman. HortScience 43:260, 2008. (3) F. N. Martin. Mycologia 92:711, 2000. (4) S.
Sabaratnam. BC Plant Health Fund Final Report. B.C. Retrieved from
http://www.agf.gov.bc.ca/cropprot/phf_final_report.pdf, 2008.
190

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