MANIPULATING ORGANIC AMENDMENTS TO IMPROVE POTATO PRODUCTIVITY
AND SOIL QUALITY
By
Ninh Thai Hoang

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
Crop and Soil Sciences
2011

ABSTRACT
MANIPULATING ORGANIC AMENDMENTS TO IMPROVE POTATO PRODUCTIVITY
AND SOIL QUALITY
By
Ninh Thai Hoang
Organic amendments are well-known for increasing crop production and improving soil
quality. This study was designed to examine organic amendment effects on potato systems in
Montcalm County, Michigan. In the first chapter, I investigated the effects of poultry compost
application and cover crops in different potato rotations on yield and soil quality by establishing
a laboratory experiment on soils collected in 2006. In the second chapter, I organized a field
experiment at the Montcalm Research Farm to examine the effects of poultry compost
application rates and timing on potato yields and soil quality in 2009 and 2010. The result from
-1

the first study showed that compost applications at a low rate (5.6 Mg ha ) significantly
increased potato yield in a potato-snap bean system both with and without rye cover and
promoted soil microbial activity and soil characteristics. Additionally, clover cover crop
significantly increased N in the light fraction as well as soil microbial activity in a potato-wheat
system. In the second experiment, the compost applications were consistent across 2 years in
increasing potato yield and also increasing soil pH, inorganic N, microbial biomass and enzyme
activities. Scab incidence was negatively correlated to soil aggregate size > 1000 µm, net N
mineralization, soil C&N, and cellobiohydrolase, glucosidase, and acid phosphatase activities.
However, scab reduction was followed with high rates of compost application in the first year
but not in second year. These results suggest that the combination of a low rate of compost with
rye cover in potato-snap bean system will improve potato yields and soil quality.

Dedicated to my parents who inspired my thinking and encouraged me to overcome
all the challenges

iii

ACKNOWLEDGEMENTS

First, I would like to thank Dr. Stuart Grandy, my major advisor, for the opportunity to
work on his project, his useful instructions, and for patience during editing and revising. Without
his dedication and support, I would not have been able to finish this master’s degree. I am also
grateful to my committee members, Dr. Sieglinde Snapp and Dr. Jianjun Hao, for their guidance
and support. I am thankful for 2 years of support from the project “Agricultural Scientific
Technology (AST)”, funded by collaboration between the Vietnam Ministry of Agricultural and
Rural Development (MARD) and Asia Development Bank (ADB). Also, my thanks go out to the
Potato Industry Commission for providing support for my project.
I also would like to thank Dr. Kyle Wickings for his kindness in guiding me through the
soil analysis methods. Many thanks to Dr. Grandy’s lab group, who helped me out with soil
collection and lab work. I would like to thank Bruce Sackett and Dr. David Douches and his
team for helping with potato harvesting at Montcalm Research Farm and potato grading at MSU.
Thanks also to Bill Widdicombe for help with corn harvesting. I would like to thank David Weed
and Steve Hamilton’s lab for help using the TOC instrument. Thanks to Wei Wang and Juan
Munoz for help with statistical analyses. Thanks to all other MSU’s professors and friends for
advanced information and idea exchange from classes. I would like to acknowledge Jesse
Sadowsky for the useful discussions and sharing thoughts about research. I also would like to
thank my friends at the Bower-Coop house where I lived. My gratitude also extends to
Vietnamese friends from the Association of Vietnamese Scholars and Students (AVSS) at MSU
for the good times after work during my stay in East Lansing. Lastly, I would like to thank my
parents and sister for their love and support, and to friends and colleagues in Vietnam who
encouraged me during my 3 years studying.
iv

TABLE OF CONTENTS

LIST OF TABLES ......................................................................................................................... vi
LIST OF FIGURES ..................................................................................................................... viii
CHAPTER 1: Integrating alternative potato cropping systems with manure additions to improve
soil quality and yields ..................................................................................................................... 1
1. Introduction ............................................................................................................................. 2
2. Materials and methods ............................................................................................................ 4
2.1. Site description and experimental design ........................................................................ 4
2.2. Aggregate stability ........................................................................................................... 7
2.3. Soil pH ............................................................................................................................. 8
2.4. Soil C and N ..................................................................................................................... 8
2.5. C and N turnover.............................................................................................................. 9
2.6. Determination of enzyme activity.................................................................................. 10
2.7. Statistical analysis .......................................................................................................... 10
3. Results ................................................................................................................................... 11
3.1. Soil characteristics ......................................................................................................... 11
3.2. Potato yield and common scab incidence ...................................................................... 13
4. Discussion ............................................................................................................................. 14
4.1. The effect of organic amendments on potato yield and quality ..................................... 14
4.2. The effect of organic amendments on soil biological processes.................................... 16
4.3. Relationship of soil biological processes to potato yield. .............................................. 18
5. Conclusion ............................................................................................................................ 19
REFERENCES ......................................................................................................................... 31
CHAPTER 2: Effect of application rates and timing of poultry compost amendment on potato
and soil quality .............................................................................................................................. 37
1. Introduction ........................................................................................................................... 38
2. Materials and methods .......................................................................................................... 40
2.1. Experimental site............................................................................................................ 41
2.2. Analytical methods ........................................................................................................ 43
3. Result .................................................................................................................................... 48
3.1. Potato systems................................................................................................................ 48
3.2. Corn systems .................................................................................................................. 55
3.3. Environmental conditions .............................................................................................. 57
4. Discussion ............................................................................................................................. 57
4.1. Effect of poultry compost application rates on potato quality ....................................... 57
4.2. Management of poultry compost application rates and timing on corn yield................ 59
4.3. Effect of poultry compost application rates on soil quality management...................... 60
4.4. Effect of timing of poultry compost application on soil quality management .............. 61
5. Conclusion ............................................................................................................................ 62
REFERENCES ....................................................................................................................... 102
v

LIST OF TABLES

Table 1.1. Cropping system description. ...................................................................................... 20
Table 1.2. C, N pools and C/N ratio in the research systems ....................................................... 21
Table 1.3. Enzyme activities associated with different cropping system management practices . 22
Table 1.4. Enzyme ratio in the potato systems ............................................................................. 23
Table 1.5. Pearson’s correlation coefficient (r) between total potato yield, scab incidence, CO 2
respiration of 145d, enzyme activity at 157d and other soil characteristics. ................................ 24
Table 1.6. Temperature and precipitation in the research site in 2005 and 2006. ........................ 24
Table 1.7. Overall ANOVA of the soil characteristics ................................................................. 25
Table 2.1. Poultry manure amendment rates for potato in 2009 and corn in 2010 in Phase 1. .... 64
Table 2.2. Field operation dates of 2 studied phases. ................................................................... 65
Table 2.3. Substrate, fluorescing agent and their molarity for enzyme assay .............................. 66
Table 2.4. Soil pH in the potato systems ..................................................................................... 67
Table 2.5. Inorganic N of potato soil in 2009: Phase 1 ................................................................ 68
Table 2.6. Inorganic N of potato 2010: Phase 2 ........................................................................... 69
Table 2.7. Microbial biomass C in the potato soil over the growing seaso n 2009/Phase 1 and
2010/Phase 2 ................................................................................................................................. 70
Table 2.8. Microbial biomass N in the potato soil over the growing seaso n 2009/Phase 1 and
2010/Phase 2 ................................................................................................................................. 71
Table 2.9. β-1,4-glucosidase activity of potato soil over the growing season 2009/Phase 1 and
2010/Phase 2 ................................................................................................................................ 72
Table 2.10. β-1,4-N-acetyl glucosaminidase activity of potato soil over the growing seaso n
2009/Phase 1 and 2010/Phase 2 .................................................................................................... 73
Table 2.11. Acid phosphatase activity of potato soil over the growing seaso n 2009/Phase 1 and
2010/Phase 2 ................................................................................................................................. 74
Table 2.12. Tyrosine amino peptidase activity of potato soil over the growing season 2009/Phase
1 and 2010/Phase 2 ....................................................................................................................... 75
vi

Table 2.13. Phenol oxidase activity of potato soil over the growing season 2009/Phase 1 and
2010/Phase 2 ................................................................................................................................. 76
Table 2.14. Overall ANOVA of repeated measure for potato soil characteristics in 2 phases
(2009 and 2010). ........................................................................................................................... 77
Table 2.15. Pearson’s correlation coefficients (r) between seasonal means of variables in the
potato soil 2009/Phase 1 and 2010/Phase 2 .................................................................................. 78
Table 2.16. Soil pH of corn soil 2010/Phase 1. ............................................................................ 79
Table 2.17. Inorganic N in corn soil 2010/Phase 1. ...................................................................... 80
Table 2.18. Microbial biomass in corn soil 2010/Phase 1 ............................................................ 81
Table 2.19. Enzyme activities in corn soil 2010/Phase 1. ............................................................ 82
Table 2.20. Pearsons’ correlation coefficients (r) between seasonal mean of variables in the corn
soil in 2010.................................................................................................................................... 83
Table 2.21. Overall ANOVA of repeated measure for corn soil characteristics 2010/Phase 1. ... 84
Table 2.22. Irrigation water that was added into the research field in the growing season 2009
and 2010. ....................................................................................................................................... 85

vii

LIST OF FIGURES

Figure 1.1. Soil pH in the potato systems ..................................................................................... 26
Figure 1.2. Net N mineralization in the potato systems................................................................ 27
Figure 1.3. Cumulative CO 2-C produced in the first 30 days of incubation and for and next 115
days. .............................................................................................................................................. 28
Figure 1.4. Potato yield in 2005 and 2006 .................................................................................... 29
Figure 1.5. Potato scab in 2005 and 2006 in the potato systems. ................................................. 30
Figure 2.1. Experimental design and location. ............................................................................. 86
Figure 2.2. Potato yields in 2009 and 2010 at Montcalm Research Farm. ................................... 87
Figure 2.3. Common scab severity in potato ................................................................................ 88
Figure 2.4. Average of soil pH in 2009 and 2010......................................................................... 89
-

Figure 2.5. Average of NO 3 -N in potato soil in 2009 and 2010 ................................................. 90
+

Figure 2.6. Average of NH4 -N in potato soil in 2009 and 2010 ................................................. 91
Figure 2.7. Seasonal average of microbial biomass in potato soil in 2009 and 2010 ................... 92
Figure 2.8. Seasonal average of hydrolytic enzyme activity in the potato systems in 2009 ........ 93
Figure 2.9. Hydrolytic enzyme activity in the potato systems in 2010......................................... 94
Figure 2.10. Phenol oxidase in the potato soil in 2009 and 2010 ................................................. 95
Figure 2.11. Principal component analysis for potato quality and soil character istics in the potato
system in 2009 and 2010............................................................................................................... 96
Figure 2.12. Corn yield in 2010/Phase 1....................................................................................... 97
Figure 2.13. Daily average temperature at Montcalm Research Farm in 2009 and 2010. ........... 98
Figure 2.14. Daily rainfall at Montcalm Research Farm in 2009 and 2010 ................................. 99
Figure 2.15. Average soil moisture in the potato systems during the growing season in
2009/Phase 1 and 2010/Phase 2. ................................................................................................. 100
Figure 2.16. Average soil moisture in the corn systems in 2010/Phase 1 .................................. 101

viii

CHAPTER 1
Integrating alternative potato cropping systems with manure additions to improve soil quality
and yields

Abstract
The use of compost, cover crops and crop rotations has long been known as an effective
tool for reducing environmental impact while also improving soil quality and increasing crop
productivity. In this study, the effect of applying compost, an economical carbon input, at a low
-1

rate (5.6 Mg ha ) in combination with cover crop and crop rotation in a potato farm was
evaluated as a strategy to increase potato yield and improve biological characteristics of sandy
soil in Michigan. The trial, which was part of a long-term ecological research study, was a twoyear rotation of potato with six different treatments; these included potato-snap bean and potatowheat systems integrating with a rye or red clover cover crop and poultry compost application.
The soils were collected after compost application but before potato planting in 2006, air-dried,
and kept at room temperature and humidity until analysis. The results of a laboratory incubation
experiment indicated that compost application, even at the low rate, had a significant impact on
potato yield and soil microbial activity. Rye cover crop increased potato yield in 2005 but not in
2006. Scab incidence was negatively correlated to soil aggregate size > 1000 µm, net N
mineralization, soil C & N, C in light fraction organic matter, cellobiohydrolase, β-1,4glucosidase, and acid phosphatase. Both compost application and presence of a cover crop
increased C and N mineralization. Red clover significantly increased microbial activity and N in
the light fraction. The overall results suggested the use of a potato-bean rotation with a rye cover
crop and compost application as an optimal system for Michigan potato growers.
1

1. Introduction
Michigan grows about 17,000 ha of potatoes (Solanum tuberosum L.) annually, more
than any other vegetable crop (MDA, 2009). Michigan’s potato industry faces many production
and environmental challenges such as declining soil organic matter concentrations, depressed
soil biological activity, and intense pressure from diseases such as stem canker, black scurf, and
common scab (Hao et al., 2009; Po et al., 2009; Larkin et al., 2010). These challenges are
common to other potato- growing regions as well, where declines in soil structural stability,
organic matter concentrations, productivity and severe disease problems have been frequently
reported (Grandy et al., 2002; Rees et al., 2002; Carter et al., 2003).
Organic matter applications (e.g. compost and manure) and crop rotation are known to
promote soil microbial activity and increase plant productivity (Acosta-Martínez et al., 2007;
Larkin, 2008) and can alter the soil physical environment by promoting aggregation and reducing
bulk density (Celik et al., 2004; Hemmat et al., 2010). Javier et al. (2007) suggested that
measuring soil attributes such as these indicators will advance understanding of the relationships
between management, soil properties, and plant disease. For example, soil enzymes that function
as microbial catalysts for decomposing and transforming organic matter (Sinsabaugh et al.,
2008) were considered an indicator of microbial nutrient demand (Allison, 2005), and have been
frequently correlated with total microbial activity (Sinsabaugh et al., 2002; Caldwell, 2005).
Bonanomi et al. (2010) found that disease suppression often increased during decomposition and
suggested that this may be related to microbial activity during organic matter decomposition.
Lozano et al. (2009) also suggested that compost decomposition may stimulate competitive
interactions that suppress disease.
2

Potato common scab, caused by multiple species of Streptomyces, with S. scabies being
dominant, is a common tuber disease of potatoes worldwide (Wanner, 2004; Loria et al., 2006).
Stretomyces scabies can have a significant impact on marketable yield by causing corky lesions
on the tuber surface (Hao et al., 2009; Wanner and Haynes, 2009) and is a long-term production
challenge because the pathogen can survive in the soil and plant debris for more than 10 years
(Conn and Lazarovits, 1999). These species can survive in the soil even under extreme
environments such as high temperature and a wide range of moisture conditions, and can
produce a phytotoxin, thaxtomin, which inhibits biosynthesis of cellulose (Wach et al., 2005;
Loria et al., 2008). To date, many studies seeking controls for common scab in potato systems
have been focused on cultural practices such as changing soil pH or using crop rotation;
however, these methods are not effective in preventing the high crop losses observed in many
regions (Loria et al., 2006). Breeding scab-resistant potato varieties could prove effective but so
far has not been achieved.
Recently, producers in Michigan and elsewhere have begun experimenting with crop
rotations and organic amendments such as compost and manure to improve soil biological
activity (Snapp et al., 2007), and recent research points to possible links between soil
management, biological activity, disease suppression, and crop yield (Bailey and Lazarovits,
2003; Larkin and Honeycutt, 2006; Larkin, 2008). For example, Conn and Lazarovits (1999)
found that the use of chicken and swine manure resulted in a significant decline in potato
common scab. Larkin (2008) observed that using crop rotation with b iological amendments and
compost application can decrease soilborne disease and increase potato yields. Carter et al
(2003) found that potato crops rotated with red clover significantly reduced common scab
infection compared to other cover crops such as ryegrass and barley. Griffin et al (2009) also

3

observed that rotating potatoes with cover crops such as red clover and ryegrass affected soilborne disease: red clover in particular suppressed both Rhizoctonia and common scab in potato.
Crop rotation may also be beneficial for improving soil structure, increasing organic matter, and
providing resilience to potato cropping systems (Carter et al., 2009), in contrast to continuous
cropping with a single host plant, which can deplete soil resources and lead to problems with
soil-borne pathogens (Janvier et al., 2007).
There remain many challenges to using organic amendments and crop rotations to
improve soil quality, increase yield and suppress disease. Firstly, the effects of organic
amendments on plant diseases are often inconsistent. Organic matters with the same inputs
sometimes suppress pathogens and reduce plant disease, but other times have the opposite effect
(Bonanomi et al., 2010). Furthermore, using compost and crop rotations can be expensive, timeconsuming, and labor- intensive. One way to minimize the expense of organic amendments is to
use very low application rates; however, many studies to date have used very high rates that are
not economical for most growers (Grandy et al., 1998; García-Gil et al., 2000; Abbasi et al.,
2002; Hargreaves et al., 2008). To reduce the cost associated with organic matter additions,
Snapp et al. (2003) recommended combining compost use with cover crops. In Michigan, potato
growers are widely interested in using organic amendments to enhance soil biology and have
determined that application rates below ~5.6 Mg ha

-1

are economical. My overall objective was

to determine the effect of low rates of compost amendment in combination with different crop
rotations and cover crops on soil biological processes and potato yields and quality.

2. Materials and methods
2.1. Site description and experimental design
4

The field experiment took place in a sandy loam soil at the Montcalm Potato Research
º

º

Farm, Montcalm County, Michigan, USA (Longitude: 85 10’ 32”, Latitude 43 21’ 12”). My
study occurred during the second phase of a long-term research project begun in 2001. The
research was divided into two phases with Phase 1 started in 2001 and Phase 2 was started in
2002. The main cropping systems were two-year rotations alternating one year of potato with
one year of snap bean or wheat. These systems were integrated with rye and red clover winter
cover crops and compost resulting in six different treatment systems relevant to our region
(Table 1.1). The first treatment was potato with bare soil for winter in the first year followed by
snap bean with bare soil for winter in the second year. The second treatment was potato with rye
cover for winter in the first year then snap bean with rye cover for the second year. The third
treatment was potato with bare soil for winter in the first year and snap bean with bare soil for
winter in the second year and compost application before potato planting. The forth treatment
was potato with rye cover in the first year and snap bean with rye cover in the second year and
compost application before potato planting. The fifth treatment was potato with wheat cover for
winter in the first year and wheat with rye cover for winter in the second year. The last treatment
was potato with wheat cover for winter in the first year and wheat with red clover for winter
cover in the second year. All the treatments were established in a randomized complete block
design with four replications, a design which allows for the examination of the effects of
compost and cover cropping, and their interaction, in a widely used rotation (potato-bean) with
extensive external inputs and low soil organic matter concentrations. The design also permits a
comparison of the potato-bean rotation to an alternative rotation (potato-wheat). This alternative
rotation is used by some Michigan potato growers and replaces snap beans with a crop tha t
enriches the soil with more residual C that has a higher C:N ratio and lower turnover time than
5

beans. The compost consisted of decomposed poultry manure (C: 50%, N: 4%, P 2O 5: 3%, K 2O:
-1

2%, and Ca: 8%) and was applied on 16 May 2006, before potato planting at a rate of 5.6 Mg ha .
The C:N ratio of the compost was 12, the lignin content in compost was 4.2%, and the cellulose
was 22.1%.
Snowden cultivar potato tubers were cut into pieces of approximately 56 g each and
planted on 1 June 2006 at a space of 30.5 cm within row and 86 cm between rows. Each plots
was rectangular, measured 5.5 by 16.7 m and contained six rows of potatoes (Nyiraneza and
Snapp, 2007; Po et al., 2009). Additional urea fertilizer was applied multiple to soils at planting,
hilling, and tuberization to maintain available N at 224 kg ha

-1

for all the treatments. Thus, N

credits were calculated based on the amount of available N in compost and decomposed N from
cover crops (Nyiraneza and Snapp, 2007; Po et al., 2009). For instance, decomposed N from rye
-1

was about 11 kg N ha , from red clover was about 30 kg N ha

-1

and from compost was about 45

-1

kg N ha . Therefore, the inorganic N amounts added were 224 kg N ha
-1

kg N ha

-1

for potato-bean; 213

for potato-bean with rye and potato-wheat with rye; 179 kg N ha

with compost; 168 kg N ha

-1

-1

for potato-bean with rye and compost; and 194 kg N ha

potato-wheat with clover. Potassium (K 2O) was added at a rate of 201 kg ha
and an additional 38 kg P ha

for potato-bean

-1

-1

-1

for

before planting

was added at planting as starter fertilizer (P 2O5).

Soil samples were collected at 0-20 cm depth just before potato planting on 1 June 2006.
All the soils were air dried at room temperature. Potato plants were killed on 14 Sept 2006 using
TM

Matrix

(Rimsulfuron) at 0.98 L ha

-1

(0.25 L ha

6

-1

TM

a.i.) and Poast

(Sethoxydim) at 1.23 L

-1

ha

(0.55 L ha

-1

a.i.) and harvested on 15 Oct 2006 using a one-row harvester. Potatoes were

harvested from two 1.5 m middle sections of each row in each plot to determine tuber yield, in
the same areas that were designated earlier in the season and used to conduct plant population
counts. Specific gravity (weight- in-air/weight-in-water method) was determined on harvested
tubers. Tubers were graded based on USDA market classes: U.S #1 diameter > 5.1 cm; size Bs
diameter < 5.1 cm; tubers with external physiological deformities were placed in a defect
category.
Potato scab was assessed using previously published protocols used at our experimental
site (Snapp et al., 2007). According to this method, the presence or absence of scab incidence
was assessed on all tubers from one harvested row. If the tubers had visible scab that covered
more than 50 % of the tuber (which would reduce marketability), the weight of those severely
infected potatoes was divided by the total weight of all harvested tubers, allowing the percentage
of severe scab incidence to be expressed by weight.
The potato yield and scab incidence from phase one of the rotation in 2005 was also
collected to compare with the potato yield and scab incidence in 2006. In 2005, poultry compost
was applied on 17 May 2005 and potatoes were planted on 25 May 2005. Potato vine desiccant
was applied on 30 Aug 2005 and potato was harvested on 20 Sept 2005. Temperature and
rainfall in 2005 and 2006 for the studied area were collected from the Entrican Station website at
http://enviroweather.msu.edu.

2.2. Aggregate stability
Water stable aggregates were determined by wet sieving (Robertson et al., 1999; Grandy
et al., 2007b) through three different sieves, 1000 µm, 250 µm, and 53 µm resulting in four
7

aggregates size classes: < 53 µm, 53 - 250 µm, 250 - 1000 µm, and > 1000 µm. Aggregates were
wetted before sieving by placing 30 g of air-dried soil on a 125 mm paper filter paper (Whatman
#1) in a Petri dish. Filter paper and soil were gradually wetted with about 30 mL H2O using a
pipette. Samples then were covered with parafilm to eliminate evaporation and kept at room
temperature for 24 h to permit capillary wetting of the soil. After wetting, soil was first placed on
a 1000 µm sieve in water for 3 min before the sieve was slowly moved up and down 3 cm 15
times for 1 min. All the soil that passed through the 1000 µm sieve was carefully transferred to
the 250 µm sieve and sieved again. The same procedure was repeated with the 53 µm sieve. The
º

soil remaining in each sieve was collected, dried at 60 C and weighed.
Sand contents were determined by dispersing the soil in each aggregate size class with
0.5 % sodium hexametaphosphate on a shaker table for 24 h at 200 rpm. The samples were then
sieved to pass through a 53 µm sieve. The sand was collected, dried and weighed and the sand
free aggregate mass was calculated as follows: (aggregate - sand)/ (total soil - sand)*100.

2.3. Soil pH
Soil pH was determined in water by using a 1:2 w/v ratio according to Robertson et al
(1999). Briefly, 15 g of soil was weighed and mixed with 30 mL DI H2O. The slurry was stirred
for 1 min and settled for 30 min before measuring pH using a probe (SevenEasy pH Mettler
Toledo, Switzerland).

2.4. Soil C and N

8

Light fraction soil organic matter (LF) was determined b y using density separation
methods (Robertson et al., 1999; Grandy et al., 2007a). Twenty grams of air dried soil were
weighed into a 50 mL centrifuge tube with 45 mL of sodium polytungstate (NaPT) at a density
3

of 1.7 g/cm . The samples were capped and shaken for 30 min on a shaker table at 200 rpm
before centrifuging for 20 min at 5000 rpm. LF was aspirated from the surface of the samples
using a vaccum pump and subsequently rinsed with deionized water (approximately 400 mL)
º

and dried at 60 C for 48 h. Total C and N in both soil and LF were determined by combustion in
an elemental analyzer (Elemental Combustion System – Costech Instruments).

2.5. C and N turnover
A laboratory incubation experiment was designed to determine potential soil respiration
rates, N mineralization rates, and associated enzyme activities. Twenty grams of soil were
placed into 60 mL serum vials and moistened to 60 % water holding capacity with soil moisture
contents determined and monitored gravimetrically throughout the experiment. Water was
periodically added to individual vials to maintain a constant moisture content. Vials were capped
º

with a rubber septum and incubated in the dark at 25 C. Two identical sets of vials were
established for all the samples. One set was used to determine CO 2 flux and, at the end of the
experiment, enzyme activity. The other set was destructively sampled after 30 d for
determination of enzyme activity and N mineralization rates. Every 2-3 d for 145 d, all vials
were opened for ~30 min to release accumulated CO 2. CO 2 flux ( µg CO 2-C/g soil/day) was
determined by taking a 1 mL sample of headspace three times over 60 min (0, 30 and 60 min)
and measuring CO 2 on an infrared gas analyzer (LICOR-820). N mineralization rates were
9

+

-

determined by measuring the difference in soil NH4 and NO 3 concentrations at the beginning
of the incubation and after 30 d (Robertson et al., 1999). Inorganic N was extracted by shaking
10 g of soil in 50 mL of KCl 1M for 30 min and then determined colorimetrically using an
autoanalyzer (Lachat Instruments, Milwaukee, WI).

2.6. Determination of enzyme activity
The activity of five extracellular soil enzymes was examined after 30 and 157 d using
previously described methods (Grandy et al., 2007a; Saiya-Cork et al., 2002): β-1,4-N-acetyl
glucosaminidase (NAG), cellobiohydrolase (CBH), β-1,4-glucosidase (BG), acid phosphatase
(PHOS), and phenol oxidase (PHENOX). One gram of soil was homogenized in 125 mL sodium
acetate 50 mM buffer at pH = 6 (to reflect the average pH of all the soil samples). The
suspension was continually stirred and 200 µL aliquots were transferred by pipette into the
appropriate column of a 96-well microplate. Buffer and different substrates were added
appropriately following the method described in Saiya-Cork et al (2002) and Grandy et al (2007)
°

prior to incubation in the dark at 15 C before analysis in a fluorometer. NAG, BG, CBH, and
PHOS were analyzed fluorometrically (Fluoroskan Ascent, Thermo Scientific, Hudson, NH),
while PHENOX was analyzed using colorimetric methods in a spectrophotometer (Multiskan
Ascent, Thermo Scientific, Hudson, NH).

2.7. Statistical analysis
Statistical analysis was performed using a randomized complete block design one way
analysis of variance (ANOVA) in a mixed model using SAS (Version 9.2, SAS Institute, 2008).
Assumptions of normality were analyzed by PROC UNIVARIATE and equality of variance of
10

residuals was checked by Levene’s test. Log transformation was applied if necessary to meet the
assumptions of normality and equality of variance for the response variables. Comparison
between treatment means was determined by using Fisher’s protected LSD at p < 0.05 where
treatment was the fixed factor and block was the random factor. The relationships between
variables were performed by Pearson’s correlation coefficient (r) matrices using the SAS model
at p < 0.05.

3. Results
3.1. Soil characteristics
Compost application significantly increased soil pH from 6.10 in potato-bean treatment to
6.43 in potato-bean with compost and 6.51 in potato-bean with compost and rye cover crop
(Figure 1.1). The soil pH in the potato-bean with rye cover was 6.20, which was not different
from the pH in the potato-bean. There was no difference in soil pH among potato-wheat with rye
cover, potato-wheat with red clover cover and potato-bean treatments.
Compost applications and cover crop use did not influence the proportion of sand- free
aggregates between treatments. Sand- free aggregates in the 1000-4000 µm size class (µ = 21.2
%) were dominant in all treatments, followed by the 250-1000 µm size class (µ = 5.9 %) and the
53-250 µm ( µ = 2.3 %) size class.
There were no significant effects of organic management on total soil C and N. The total
-1

soil C ranged from 6.9 - 10.0 g C kg

-1

soil and total soil N ranged from 0.59 - 0.88 g N kg

soil

(Table 1.2). The concentration of C in the LF (Light Fraction) in potato-wheat with clover
systems was significantly lower than in potato-bean, potato-bean with compost, and potato-bean
with compost and rye cover crop. In contrast, the concentration of N in LF in potato-wheat with
11

rye was lower than in potato-bean with compost. There was no difference among ecosystems in
the amount of LF C in the soil but the LF N in potato-wheat with clover cover crop soils was
significantly higher than in the remaining systems, which did not differ from each other (p <
0.05). In contrast, there was no difference in the ratio of LF N to total soil N among treatments
but there were significant differences in the ratio of LF C to total soil C (Table 1.2); this ratio
was higher in potato-wheat with clover cover (p < 0.05) than in the other treatments, which were
not different from each other. There was no difference in soil C:N ratio (ranging from 10.6 to
13.3) and LF C:N ratio (ranging from 21.0 to 24.4) among systems.
Net N mineralization potential in potato-bean with compost, potato-bean with rye cover
and compost, potato-bean with rye cover, and potato-wheat with clover cover were significantly
higher than in potato-bean treatment but were not significantly different from each other. The net
N mineralization in the potato-bean with rye cover and compost was double that in the potatobean treatment. Only the potato-wheat with rye cover was not different from potato-bean
treatment (Figure 1.2).
Carbon mineralization rates differed among treatments (Figure 1.3). The respiration rates
in the potato-bean with compost were significantly higher than in the potato-bean at both 0-30 d
and 0-145 d. Similarly, the respiration rate in potato-wheat with clover cover crop system was
significant higher than in the potato-wheat with rye system (p < 0.05). The potato-bean with rye
cover was not different from potato-bean with rye cover and compost addition in both periods.
The rates of CO 2 production for both periods were highly related to each other (r = 0.94). The C
mineralized after 145 d in the treatment with compost application was approximately 20 % of
total soil C; in other treatments mineralized C composed 9 to 15 % of total soil C.

12

There were no treatment effects on soil enzyme activities at 30 d and 157 d of incubation,
although there was an overall trend (p < 0.1) towards higher activity at 30 d (Table 1.3). There
was also a trend (p < 0.1) of higher NAG (chitinase) activity in compost treatments than in
treatments without compost, and higher activity in the potato-wheat rotation with clover cover
-1 -1

than in the potato-wheat rotation with rye cover crop. BG activity was 49 - 88 nmol h

g

dried

-1 -1

soil and 45 - 80 nmol h g dried soil at 30 d and at 157 d, respectively. Similarly, CBH ranged
-1 -1

from 11 - 24 and 8 - 22 nmol h

g dried soil and PHOS ranged 150 - 349 and 102 - 167 nmol

-1 -1

h

g dried soil in 30 d and 157 d, respectively.

3.2. Potato yield and common scab incidence
-1

-1

Both the total yield (41.2 Mg ha ) and yield of US No.1 (37.4 Mg ha ) in potato-bean
with rye and compost application was significantly higher than the other treatments in 2005
(Figure 1.4). Yields in potato-bean with compost were not different from potato yields in potatobean with rye cover crop but both of them were still higher than yields in the potato-bean system.
Potato yields in potato-wheat with rye and potato-wheat with clover were lower than the potatobean system and did not significantly differ from each other.
The total yields and yields of US No.1-rated potatoes were higher in 2006 in the compost
treatments than in potato-bean treatment (Figure 1.4). The total yield in potato-bean with
compost was 33.6 Mg ha

-1

-1

and in potato-bean with compost and rye cover was 34.2 Mg ha ,
-1

which were almost double the yield of potato-bean system (18.2 Mg ha ). The rye cover crop
did not influence potato yield in potato-bean systems. Potato-wheat with rye cover and potato13

wheat with clover cover crop did not differ from potato-bean. There was no difference in yields
of potatoes of size B among treatments.
The treatment effect of scab incidence was not significant among the systems in both
years, ranging from 70.0 to 90.2 % in 2005 and from 35.2 to 74.2 % in 2006 (Figure 1.5).

4. Discussion
4.1. The effect of organic amendments on potato yield and quality
The total potato yield and yield of size US No.1 demonstrated that relatively small
-1

applications of poultry manure compost (5.6 Mg ha ) can increase potato productivity. Compost
application increased the yield of size US No.1 in potato-bean system by 20% in 2005 and 100%
in 2006, and potato-bean with rye system by 25% in 2005 and 110% in 2006. The yields in 2006
were higher than previously reported for the potato-bean system. Po et al. (2009) reported
comparable yields in potato-bean system of 29.3, 22.7, 31.4, and 25.6 Mg ha

-1

in 2001, 2002,

2003, and 2004, respectively. They reported the highest yields in the potato-wheat with clover
system and in the potato-bean with rye and hairy vetch system in 2003; these systems yielded
about 40 % more than the potato-bean system. In contrast, the present study found that yields in
potato-wheat with rye and potato-wheat with clover were either lower than (in 2005) or not
different from (in 2006) potato-bean.
Compost application significantly increased potato yields in both 2005 and 2006.
However, potato yields in all of the treatments in 2006 were lower than in 2005. Potato yields are
affected by a wide range of biophysical factors including climate, soil physical and chemical
characteristics, moisture, insects, and diseases. The higher yield in 2005 may be explained by the
higher temperature that year relative to 2006 (Table 1.6). Additionally, the rainfall and number
14

of rainy days in 2006 was higher than in 2005; high soil water content can limit the availability
of soil nutrients to plants which could account for the decreased potato yields observed in this
year.
Cover crops influenced potato yield in 2005: the yield was higher with the presence of
rye in potato-bean and potato-bean with compost systems. The difference between potato yie lds
in 2005 and in 2006 suggested influences of other factors on potato yield. Po et al (2009) did not
find any effect of rye cover in the potato-bean system from 2001 to 2004 and suggested that this
may be because of differences in environmental conditions. The warmer temperature in 2005
may have provided better conditions for rye cover decomposition and the recovery of cover-crop
derived N.
There was no scab reduction among the organic amendment treatments in both 2005 and
2006. Similar to previous studies (Hao et al, 2009), there was no correlation between common
scab and potato yields, indicating that common scab did not affect potato yields. However, scab
incidence in 2006 was lower than in 2005. Compost and cover crop can impact soilborne disease
by altering soil microbial communities as a consequence of changing soil physical and chemical
properties (Sarrantonio and Gallandt, 2003; Larkin et al., 2010). However, results have been
mixed and organic amendments sometimes reduce certain diseases but increase others (Bailey
and Lazarovits, 2003). Similar to the difference in potato yield, the difference of scab incidence
between the two years may be explained by the difference of climate condition between the two
years. The rainfall in 2006 was higher and more regular than in 2005 (Table 1.6), which may
have increased the decomposition rate and microbial activity and reduced the S. scabies
population.

15

4.2. The effect of organic amendments on soil biological processes
Compost application and cover crops are very important sources of soil C and N in potato
systems. The compost in this study provided about 224 kg N ha

-1

for the system and about 2.8

-1

Mg C ha C substrate for soil microbes. C mineralization rate has been used to indicate the
potential turnover of organic matter and C sequestration (Wright et al., 2008). Microbial activity,
as approximated by respiration rate was higher when compost and clover cover crop were used
in the potato systems (Figure 1.3). The C loss from mineralization after 157 d in the compost
treatments was very high at 20% of total soil C; in the potato-wheat with clover system it was
intermediate at 12%, and was lowest in the potato-wheat with rye system at 9%. These results are
similar to those of Fortuna et al (2003) who found losses in total organic soil C of about 10% in
1994 and 8% in 1998. The soil was sampled before potato planting but after compost application;
the addition of this new compost likely contributed greatly to the labile C pool. Rye cover crops
also seemed to increase the labile C pool, as similar amounts of CO 2 were released in potatobean with rye and potato-bean with rye and compost systems. Similar amounts of CO2 were
released in potato-bean and potato-wheat with rye cover systems; however, the potato-wheat
with rye system released less CO2 than potato-wheat with clover, suggesting that legume cover
crops stimulate soil microbial activity much more than bare soil, or rye or wheat cover.
The use of rotations with cover crop and compost management also increases total soil N
and minimizes the loss of N leaching (Fortuna et al., 2003) because it enhances the amount and
quality of residue input (Po et al., 2009; Larkin, 2010). The net N mineralization is an important
indicator of soil quality and is frequently positively related to organic matter decomposition
processes (Bardgett, 2005). The net N mineralization in potato-bean system was lower than in all
16

other systems except potato-wheat with rye (Figure 1.2) indicating that N turnover ca n be
increased by the use of compost as well as by the use of rye in a potato-bean system and clover
in a potato-wheat system. This may be explained by the phenomenon that cropping systems with
diverse residue inputs often have higher net N mineralization rates. For example, Sanchez et al
(2001) demonstrated that N mineralization in a corn-corn-soybean-wheat rotation with red clover
interseeded into wheat and corn and dairy manure application mineralized 70% more N than corn
monoculture receiving only inorganic fertilizers. Our results indicated that the potato-bean with
rye and compost mineralized almost 100% more N than potato-bean systems after 30 d.
The red clover cover crop also significantly increased N in the light fraction to two times
-

that of potato-wheat with rye cover. Although rye cover crops capture NO 3 during the winter
and recycle it for the next crop season (Shrestha and Ladha, 2002), legumes often provide more
N and support microbial activity that can significantly increase yield (Po et al., 2009). Residues
from legume cover crops typically have a lower C:N ratio (~14:1) and more soluble compounds
than the residue from rye cover, which has a higher lignin concentration (Sanchez et al., 2001;
Bardgett, 2005). I did not find any influence of legume cover crop on soil C:N ratio and LF C:N
ratio but legumes did influence the proportion of LF C relative to total C (Table 1.2), indicating a
significant impact of legumes on the labile forms of C and N in so ils.
Organic amendments provide carbon compounds as energy sources for microbial
metabolism (Joergensen et al., 2010) and can change the mode of interaction among soil
microbial communities (Yin et al., 2011). In turn, microbial communities produce extracellular
enzymes that play a very important role in organic matter decomposition processes (Wallenstein
and Weintraub, 2008); some extracellular enzyme activities such as BG, PHOS, and NAG are
reported to be positively correlated with plant disease suppression (Bonanomi et al., 2010).
17

Laudicina et al (2010) demonstrated that enzyme activities were significantly increased by
compost addition. In my study, enzyme activities were positively correlated to one another, but
they were not affected by organic amendments. All the enzyme activities in this study were also
correlated with net N mineralization and all except PHOS were associated with CO 2 respiration.
The ratio of C:N-degrading enzymes can provide a fundamental understanding of
microbial community response to changing nutrient resources (Caldwell, 2005), and can help
describe microbial investment into resource allocation. Thus, changes in enzyme potentials and
their ratios in response to C and nutrient additions can be used as indicators of changes in
resource allocation strategies of the microbial biomass. For example, Sinsabaugh et al (2008)
calculated the activity ratio ln(BG):ln(LAP+NAG):ln(PHOS) as the convergence of C:N:P
acquisition potentials. Similarly, I calculated the ratio of (BG+CBH):NAG:PHOS as an indicator
of C:N:P acquisition potential and found that the ratio was 6:1:11. The higher ratios NAG:PHOS,
BG:PHOS, and CBH:PHOS at 157 d in the potato-bean with rye and compost (Table 1.4) than in
other treatments indicated a change in microbial investment into C and P containing enzymes
later in the incubation. The difference of these enzyme ratios after a long-term incubation
indicated the potential response of soil microbial community to different organic compound
structures.

4.3. Relationship of soil biological processes to potato yield
Soil quality is an important predictor of crop yield because it provides an integrated view
of different soil characteristics (Stine and Weil, 2002; Snapp and Morrone, 2008). The potato
yield, in general, was higher in compost treatments and positively correlated to soil pH.
However, with the exception of a negative correlation to PHOS, it was not correlated to other
18

soil characteristics and enzyme activities (Table 1.5). Potatoes grow well in soil with a wide
range of pH but most of the potato production in United States is grown in alkaline soil
(Thornton et al., 2006). This suggests that the high potato yield in our study was associated with
high soil pH resulting from compost application.

5. Conclusion
In the present study, we found that a low rate of compost application significantly
increased potato yield. Clover cover crop significantly increased N in the light fraction and
promoted soil microbial activity but resulted in the same potato yield in 2006 as rye cover crop.
However, rye cover had a significant impact on potato yield in 2005. Potato yield was highly
correlated to soil pH but in a small range. Both compost and cover crop applications significantly
increased C and N mineralization in the soil. Scab incidence was not reduced in the presence of
compost and cover crop and was not correlated to po tato yield and pH in a small range. Scab
incidence was negatively correlated to soil aggregate size > 1000 µm, net N mineralization, soil
C andN, cellobiohydrolase, glucosidase, and acid phosphatase.

19

Table 1.1. Cropping system description.
Treatment
Cropping systems*
Compost addition**
PB
Potato-bare, Snap bean-bare
PBR
Potato-rye, Snap bean-Rye
PBCom
Potato-bare, Snap bean-bare
Poultry compost
PBRCom
Potato-rye, Snap bean-rye
Poultry compost
PWR
Potato-wheat, Wheat-rye
PWCl
Potato-wheat, Wheat-red clover
* These systems were 2 years rotation started in 2002. Soil samples were taken in 2006, before
potato planting. Main crops are presented in bold font.
** The compost was added every other year before potato planting.

20

Table 1.2. C, N pools and C/N ratio in the research systems *
Treatment**

Soil C

Soil N

PB
PBR
PBCom
PBRCom
PWR
PWCl

g kg
6.87 (2.3)
8.39 (2.9)
7.65 (1.7)
8.15 (2.5)
8.30 (0.8)
10.1 (2.6)

-1

Treatment

LF C

LF N
-1

soil
g kg
0.59 (0.27)
357 (5.6)a
0.72 (0.20) 343 (14.5)ab
0.78 (0.20) 361 (26.9)a
0.68 (0.21) 360 (20.4)a
0.63 (0.01) 341 (28.0)ab
0.88 (0.20) 327 (16.8)b

LF C:soil C

LF N:soil N

LF
15.9 (1.4)ab
16.0 (1.9)ab
17.3 (1.6)a
15.7 (3.1)ab
14.0 (0.8)b
15.1 (2.2)ab
Soil C:N

LF C

LF N
-1

g kg
1.19 (0.27)
1.62 (0.56)
1.51 (0.15)
1.66 (0.54)
1.41 (0.20)
2.58 (0.20)

soil

0.053 (0.01)b
0.070 (0.018)b
0.072 (0.005)b
0.066 (0.015)b
0.059 (0.01)b
0.126 (0.007)a

LF C:N

%
PB
18.5 (1.78)b
11.1 (2.32)
12.8 (1.3)
22.6 (1.6)
PBR
19.1 (1.32)b
9.9 (0.62)
11.2 (0.7)
21.8 (3.7)
PBCom
20.9 (1.86)b
10.7 (2.20)
10.6 (1.8)
21.0 (1.5)
PBRCom
20.0 (1.87)b
11.1 (1.97)
12.5 (0.9)
23.6 (4.9)
PWR
17.0 (1.67)b
9.3 (1.49)
13.3 (1.3)
24.4 (1.9)
PWCl
28.6 (4.04)a
15.9 (2.44)
11.3 (0.6)
22.1 (4.1)
* Means with the same letters were not significantly different from each other (Mean ± SE, p <
0.05).
**See Table 1.1 for detail of treatment abbreviations. LF: Light fraction

21

Table 1.3. Enzyme activities* associated with different cropping system management practices
Treatment**
At 30 d
PB
PBR
PBCom
PBRCom
PWR
PWCl
At 157 d
PB
PBR
PBCom
PBRCom
PWR
PWCl

NAG

BG

CBH

PHOS

8.5 (2.2)
16.7 (2.4)
12.7 (2.7)
17.2 (4.0)
13.2 (1.6)
23.5 (6.7)

48.8 (19.0)
69.8 (12.1)
61.6 (14.6)
75.0 (16.9)
50.5 (3.3)
88.3 (26.7)

16.2 (6.2)
18.9 (4.3)
19.5 (6.2)
23.6 (7.4)
10.9 (0.8)
21.1 (7.2)

148.9 (64.3)
213.3 (62.9)
171.3 (73.1)
169.2(61.0)
153.9 (16.6)
287.9 (86.6)

8.2 (1.8)
9.9 (1.2)
10.8 (2.9)
15.9 (3.3)
10.8 (0.9)
18.5 (3.4)

45.4 (15.4)
48.2 (5.4)
56.4 (15.1)
79.7 (20.1)
45.6 (2.6)
76.8 (20.8)

7.9 (3.7)
10.9 (1.6)
12.1 (5.0)
21.4 (6.2)
9.9 (0.8)
22.0 (9.6)

113.6 (39.7)
119.3 (33.1)
102.1 (25.6)
119.2 (60.1)
106.9 (9.8)
166.9 (41.1)

-1 -1

* Mean ± SE, nmol h g
**See Table 1.1 for detail of treatment abbreviations. NAG: β-1,4-N-acetyl glucosaminidase;
BG: β-1,4-glucosidase, CBH: cellobiohydrolase, PHOS: acid phosphatase.

22

Table 1.4. Enzyme* ratio in the potato systems
Treatment*
CBH/NAG
BG/NAG
NAG/PHOS
BG/PHOS
CBH/PHOS
CBH/BG
At 30 d
PB
1.82 (0.24)a
5.49 (0.79)
0.06 (0.01)
0.34 (0.02)
0.11 (0.01)
0.33 (0.01)a
PBR
1.14 (0.21)bc
4.26 (0.58)
0.09 (0.02)
0.36 (0.03)
0.09 (0.01)
0.26 (0.02)abc
PBCom
1.45 (0.17)ab
4.82 (0.12)
0.09 (0.01)
0.43 (0.05)
0.13 (0.02)
0.30 (0.04)ab
PBRCom
1.31 (0.19)abc
4.59 (0.53)
0.10 (0.03)
0.44 (0.08)
0.12 (0.02)
0.29 (0.04)abc
PWR
0.86 (0.09)c
3.91 (0.28)
0.09 (0.01)
0.34 (0.03)
0.07 (0.01)
0.22 (0.02)c
PWCl
0.90 (0.17)c
3.78 (0.36)
0.08 (0.01)
0.31 (0.03)
0.07 (0.01)
0.23 (0.02)bc
At 157 d
PB
0.87 (0.21)
5.28 (0.60)
0.08 (0.01)b
0.40 (0.03)b
0.06 (0.01)b
0.16 (0.02)b
PBR
1.08 (0.08)
4.86 (0.17)
0.1 (0.02)b
0.47 (0.08)b
0.11 (0.02)b
0.22 (0.01)ab
PBCom
1.02 (0.12)
5.22 (0.05)
0.1 (0.003)b
0.55 (0.01)b
0.11 (0.01)b
0.20 (0.02)ab
PBRCom
1.31 (0.16)
4.93 (0.39)
0.20 (0.05)a
0.91 (0.18)a
0.23 (0.04)a
0.26 (0.01)a
PWR
0.94 (0.11)
4.34 (0.48)
0.10 (0.01)b
0.44 (0.04)b
0.09 (0.01)b
0.22 (0.01)ab
PWCl
1.06 (0.24)
4.00 (0.36)
0.12 (0.01)b
0.45 (0.02)b
0.12 (0.02)b
0.26 (0.04)a
* See Table 1.1 and 1.3 for treatment and enzyme abbreviations. Means with the same letters were not significantly different from
each other (p < 0.05).

23

Table 1.5. Pearson’s correlation coefficient (r)* between total potato yield, scab incidence, CO 2 respiration of 145 d, enzyme activity
at 157 d and other soil characteristics.
Yield Scab
pH Large
Med Small Net N Soil N Soil C LF C LF N
BG
CO2 NAG CBH
Scab
0.14
pH
0.65
0.02
Large
-0.29 -0.50 -0.28
Med
-0.12 0.06 -0.19 -0.35
Small
-0.05 -0.35
0.23
0.06
0.16
Net N
0.04 -0.38
0.15
0.66
0.02
0.44
Soil N
-0.33 -0.50 -0.20
0.84 -0.11
0.39
0.76
Soil C
-0.34 -0.61 -0.32
0.87
0.01
0.38
0.74
0.92
LF C
-0.31 -0.40 -0.37
0.70
0.11
0.34
0.72
0.79
0.83
LF N
-0.33 -0.24 -0.38
0.62
0.05
0.16
0.64
0.66
0.67
0.94
0.27 -0.26
0.54
0.39 -0.27
0.36
0.75
0.56
0.40
0.40
0.36
CO2
NAG
-0.19 -0.31 -0.04
0.74 -0.09
0.10
0.73
0.69
0.70
0.68
0.67
0.45
CBH
-0.10 -0.55
0.08
0.81 -0.08
0.34
0.84
0.82
0.83
0.67
0.55
0.56
0.88
BG
-0.16 -0.48
0.02
0.84 -0.09
0.29
0.84
0.84
0.83
0.71
0.61
0.55
0.91
0.99
PHOS
-0.42 -0.58 -0.31
0.90 -0.02
0.31
0.76
0.93
0.96
0.83
0.71
0.40
0.78
0.88
0.90
* Bold letters indicate p < 0.05. Abbreviations: Large: aggregate size 1000-4000 µm, Med: size 250 - 1000 µm, Small: size 53 - 250
µm. See Table 1.3 for enzyme abbreviations.

24

Table 1.6. Temperature and precipitation in the research site in 2005 and 2006.
Growing season*

Average daily temperature
Total rainfall
Number of rainy days
º
C
mm
2005
18.9
337.6
48
2006
17.7
422.7
67
* The climate data was collected from http://enviroweather.msu.edu for the potato growing
season (15 May to 15 Oct) in 2005 and in 2006.

24

Table 1.7. Overall ANOVA of the soil characteristics
Soil characteristics
pH
Net N mineralization *
Total soil N*
Total soil C*
Soil C:N
Light fraction N, mg/kg soil
Light fraction C, mg/kg soil
LF C/ soil C, %
LF N/ soil N, %
CO2_30day*
CO2_145 days*
Light fraction
Aggregate > 1000µm
Aggregate 250 – 1000µm
Aggregate 53 - 250µm
NAG 30d, activity g-1 soil
CBH 30d, activity g-1 soil
BG 30d, activity g-1 soil
PHOS 30d, activity g-1 soil
NAG 157d, activity g-1 soil
CBH 157d, activity g-1 soil *
BG 157d, activity g-1 soil
PHOS 157d, activity g-1 soil
(CBH+BG):NAG 30d
(CBH+BG):NAG 157d
(CBH+BG):PHOS 30d
(CBH+BG):PHOS 157d
NAG:PHOS 30d
NAG:PHOS 157d
* values are log-transformed

Overall F value p value
8.59
0.0007
1.46
0.2648
0.44
0.8144
0.30
0.9040
0.91
0.5029
4.80
0.0092
1.67
0.2076
4.37
0.0131
1.68
0.2049
4.86
0.0088
5.91
0.0039
2.69
0.0661
0.38
0.8532
0.59
0.7059
0.85
0.5347
2.08
0.1290
0.59
0.7082
0.79
0.5767
0.67
0.6553
2.42
0.0882
1.69
0.2006
1.10
0.4026
0.40
0.8430
3.77
0.0225
1.07
0.4178
3.19
0.0427
8.26
0.0008
1.21
0.3566
4.10
0.0167

25

a

a

b
b

b

b

Figure 1.1. Soil pH in the potato systems (Mean ± SE). Means with the same letter were not
significantly different (p < 0.05). Abbreviations of treatments were shown in Table 1.1

26

a
ab

ab

ab
bc

c

-1

-1

Figure 1.2. Net N mineralization in the potato systems (Mean ± SE, mg N kg day ). Means
with the same letter were not significantly different (p < 0.05). See Table 1.1 for description of
treatment abbreviations.

27

B

A

A

A

a

a

ab

A

ab
b

b
b

B

a

a

a
b

a

Figure 1.3. Cumulative CO 2-C (Mean ± SE, p < 0.05) produced in the first 30 days of incubation
and after an additional 115 days. Means for the same time period with the same letter were not
significantly different (p < 0.05). The upper case letters indicate the differences of total
cumulative CO 2-C over the 145 d incubation. Treatment abbreviations were given in Table 1.1.

28

a
C

B

B

A

D

D

c

b

b

a

d

d

B

B

A

A

B

B

b

b

a

a

b

b

b

Figure 1.4. Potato yield in 2005 (a) and in 2006 (b) (Mean ± SE, p < 0.05). Size Bs: tuber
diameter < 5.1 cm; US No.1: tuber diameter > 5.1 cm. Means for the same tuber size with the
same letters were not significantly different (p < 0.05). Upper case letters indicated differences
among treatments in total yield. Abbreviations of treatments were shown in Table 1.1.

29

a

b

Figure 1.5. Potato scab in 2005 (a) and 2006 (b) in the potato systems. Abbreviations of
treatments were shown in Table 1.1

30

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31

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36

CHAPTER 2
Effect of application rates and timing of poultry compost amendment on potato and soil quality

Abstract
Compost amendment is an efficient method to improve soil biological characteristics,
reduce environmental impacts and decrease cost of crop production. However, few studies have
been undertaken to optimize the contribution of compost in order to achieve maximal crop yield
and income. In this study, I examined the effect of poultry compost amendment rate and timing
on soil biological characteristics and potato yield. Thus, I set up a field experiment in Montcalm
Research Farm, Michigan with five treatments and five replicates in randomized complete block
design. The experiment was designed with two phases. In the first phase, potato was planted in
2009 and corn planted in 2010; in the second phase, potato was planted in 2010. Soil samples
were collected multiple times during growing seasons to examine soil biological characteristics.
The result showed that both the application rates and timing of compost amendment influenced
potato and corn yield and soil characteristics such as soil organic matter, water holding capacity,
inorganic N, microbial biomass and enzyme activity. The higher rates of poultry compost
application increased potato yield consistently in both 2009 and 2010. However, scab incidence
was reduced following the increase of compost amendment in 2009 but not in 2010, when there
was a lower scab incidence across all treatments. The common scab incidence was negatively
correlated to soil characteristics in 2009 but not in 2010. I also found that poultry compost
amendment at high rates significantly increased soil pH, inorganic N, microbial biomass and
enzyme activities in both phases 2009 and 2010. However, while a high rate of compost

37

increases C sequestration, it tends to be less economical for farmers. The application of 1.7 ton C
-1

ha per year was recommended to improve soil quality and maintain high crop yield.

1. Introduction
Limited availability of land and economic pressure has lead to an alteration of growing
practices in the Michigan Potato Industry. Growers are using more fertilizers and other inputs in
an effort to increase potato productivity (Sharifi et al., 2009). However, uptake of N from these
inputs is limited since potato root systems are very fibrous and shallow and Michigan potatoes
are often grown in sandy soil with high leaching potential (Peralta and Stockle, 2002).
Indigenous soil N sources derived from the turnover of soil organic matter and crop residues are
generally not adequate to support optimum potato production, especially in the sandy soils
typically used for MI potato production (Zebarth et al., 2005). Therefore, potato growers tend to
use high rates of N fertilizers to ensure an adequate supply (Prunty and Greenland, 1997).
However, the increasing use of N fertilizers has raised concerns over N losses to the environment
(Zielke and Christenson, 1986; Bardgett, 2005; Xu et al., 2010). In potato cropping systems,
nitrate leaching and nitrous oxide emissions (Zebarth et al., 2005) have been reported. For
example, Honisch et al (2002) reported a correlation of nitrate leached in wells and river water
with potato cultivation. Munoz-Arboleda et al (2008) also demonstrated that fertilization at
potato planting significantly increased nitrate content in ground water. The recommended N rates
for sandy potato soils varies from 135 to 200 kg N ha

-1

(Ziadi et al., 2011) and N recovery in

potato systems has been reported to range from 30 to 70 % (Zvomuya et al., 2003).
Potatoes can be grown in a wide range of soil conditions (Thornton et al., 2008).
However, soil is only considered suitable for crop growth if it is able to maintain biological
38

diversity and a high capacity for nutrient cycling (Van Bruggen and Semenov, 2000; Nelson et
al., 2009). Recently, intensive cropping systems with two-year rotations of high- value crops are
becoming more popular in the Great Lakes area (Sharifi et al., 2009; Larkin et al., 2011). These
potato rotations are generally characterized by intensive tillage with low crop-residue inputs
(Grandy et al., 2002). This two- year rotation may significantly reduce soilborne diseases and
produce higher-quality potatoes than continuous potato systems (Specht and Leach, 1987;
Honeycutt et al., 1996).
Soil texture is a key factor for potato management because it determines water
availability and infiltration rates, which directly affect potato root systems and growth.
Inadequate water availability in the soil can increase common scab infection while excessive
water can reduce tuber yield and quality, facilitate the leaching of nutrients out of the root zone,
and increase disease incidence (Powelson and Rowe, 2008). Potatoes have very fine and
branching root systems that are susceptible to soil compaction and tillage. In Michigan, potatoes
are grown in soils that have relatively low cation exchange capacity, low water holding capacity,
high infiltration rates and high nutrient-leaching potential (Stark and Westermann, 2008).
The use of fresh manure has been reported to increase the incidence of common scab o n
potato tubers (Bailey and Lazarovits, 2003) but these results are variable and opposite results
have been reported (Conn and Lazarovits, 1999). Both compost and manure amendment improve
soil physical properties such as soil organic matter and water holding capacity, and increase plant
productivity (Christensen and Johnston, 1997; Van Herk et al., 2004; Munoz et al., 2008) and
may reduce plant soilborne disease (Bailey and Lazarovits 2003; Bonanomi et al., 2010).
Termorshuizen et al (2006) studied 120 bioassays including 18 composts and 7 pathosystems
and found that 54 % of the treatments resulted in significant disease suppression, 43 % had no

39

effect on disease and 3 % resulted in increasing disease. Using compost can also provide more
organic matter and biomass for the soil than other soil amendment methods such as crop rotation
(Grandy et al., 2002; Collins et al., 2006), and a recent metanalysis with 120 comparisons
indicates that the use of compost or manure amendments increases microbial biomass C by an
average of 38% (Kallenbach and Grandy, in review).
Organic amendments have been studied widely as a strategy to reduce diseases and
improve crop productivity and soil quality. For example, in a study in potato cropping systems,
Porter et al (1999) reported that organic amendments in combination with irrigation improved
both yield and soil properties. One way that organic amendments may increase yields is by
suppressing disease. The mechanism of disease suppression is not well known but may include
competition between beneficial organisms and pathogens for resources, production of antibiotics
or toxic substances, enzyme activity or hyperparasitism, and the induction of systemicallyacquired resistance in host plants (Hoitink et al., 1997; Kinkel, 2008).
In the first chapter of this thesis, I found that compost application greatly improved soil
quality and potato yield. In that research, I found that a low rate of poultry manure compost
application in combination with rye cover crop and different rotation potato-wheat with red
clover increased potato yields and soil microbial activity. In order to develop better predictions
about the optimum rate of manure application, in this study I applied multiple rates of poultry
compost to the potato system and also examined the effect of application frequency. The overall
objective of this study was to examine the effect of compost rates and timing on soil biological
characteristics and potato quality.

2. Materials and methods

40

2.1. Experimental site
The experiment was carried out at the Michigan State University Potato Research Farm,
º

º

in Montcalm County, Michigan (43 21 ’13” N and 85 10’33” W). The experimental design was
a randomized complete block with 5 treatments and 5 replicates (Figure 2.1). Experimental plots
were rectangles of 3.5 m in width and 7.6 m in length. The experiment was set up for two phases.
The first phase started with potato planted in 2009 and then corn planting in 2010. The second
phase started with potato planting in 2010, which was the final year of the study.
Phase 1: Poultry compost (N: 4 %, P2O5 : 3 %, K 2O: 2 %, and Ca: 8 %) supplied from
Herbruck Poultry Ranch (MI 48881), one of the primary suppliers to the Michigan potato
industry, was applied on 20 May 2009 before potato planting. The five rates of poultry compost
-1

-1

were 0, 1.7, 3.4, 6.8, and13.6 ton C ha . Only the treatment that received 1.7 ton C ha

in 2009

received the same amount in 2010. This allowed me to compare this treatment to the one that
-1

received 3.4 ton C ha

in 2009 but none in 2010 in order to examine the effect of timing of

poultry compost on crop productivity and soil quality.
Snowden potato was planted on 22 May 2009. Urea was applied three times to provide
and balance nitrogen in all the systems. At planting, urea was applied on all plots at a rate of 16
-1

kg N ha . The second urea application occurred on 24 Jun 2009 at a rate of 67 kg N ha
control (Ctrl), T1 and T2; and 30 kg N ha

-1

-1

for

for T3 (abbreviations of treatments were given in

Table 2.1). Urea was applied a third time on 9 Jul 2009 at a rate of 67 kg N ha
kg N ha

-1

-1

for Ctrl and 33

for T1. Potato tubers were harvested on 15 Oct 2009. Rye was used as a winter cover

crop in all treatments and received urea applied at a rate of 35 kg N ha
41

-1

at planting.

For the second year in the same plots, compost was applied at 1.7 ton ha

-1

to T1 only on

23 Apr 2010. Then corn (Great Lakes 404163VT3) was planted on 10 May 2010 for all the plots
-1

with NPK fertilizer applied on the same day at a rate of (22 - 11 - 11) kg (N-P2O5-K2O) ha .
Urea was applied again on 5 Jul 2010 at 76 kg N ha

-1

for T1, and 110 kg N ha

-1

for Ctrl, T2, T3,

and T4.
Phase 2: Poultry compost was applied on 27 Apr 2010 with the same rates in the first
year/Phase 1 (Table 2.1). Snowden potato was planted on 20 May 2010 and NPK fertilizer was
-1

applied at a rate of (67-24-42) kg (N-P2O5-K2O) ha . Urea was applied again at 67 kg N ha
for Ctrl, T1, T2 and 30 kg N ha

-1

-1

for T3 on 21 Jun 2010 to balance N for all the treatments.

Potato tubers were harvested on 19 Oct 2010.
In Phase 1 of our experiment, there were a total of 12 sampling times in 2009 (potato)
and three sampling times in 2010 (corn). In Phase 2, soil samples were taken four times over the
potato growing season in 2010. Soil samples were taken to a depth of 15 cm with a 2-cm
diameter corer. Twelve replicate samples were taken within each plot. Each of the twelve
samples was taken at a distance of ~15 cm from a plant in order to capture soil biological and
nutrient cycling processes occurring in the vicinity of the root zone. The twelve samples were
combined to form a composite sample representative of the entire plot. Soil samples were
immediately put into a cooler in the field until they were brought to the lab and put in a
º

refrigerator at 4 C. All the soil samples were homogenized by passing through a 2 mm or 4 mm
sieve depending on the soil moisture status before analysis. All soil biological analyses were

42

carried out within one week from sampling date in the following order: enzyme activity first,
then microbial biomass, then inorganic N, and finally soil pH.

2.2. Analytical methods
Potato yield and scab incidence assessment
Potatoes in Phase 1 plots were harvested on 15 Oct 2009 and in Phase 2 plots on 19 Oct
2010. Potatoes in non-plots (NP), which did not receive compost or fertilizers (Figure 2.1), were
also harvested as a reference for comparing potato yield with no management. Potato plants were
-1

killed about one month before harvest using Reglone Desiccant at 2.3 L ha . The middle 2 rows
of each plot were harvested using a one-row potato harvester (Jerry Johnston of Vestaburg
Michigan) to determine tuber yield and assess common scab incidence. Tubers were graded and
weighed according to USDA market classes: oversize > 8.3 cm; A = 5.1 - 8.3 cm; B < 5.1 cm.
US No.1 is sum of oversize and A potatoes.
Common scab incidence was assessed based on potato surface damage (Driscoll et al.,
2009). According to this method, potato common scab was rated at the same time potatoes were
graded. The scab incidence was assessed on a scale of 0 to 5 where 0 was no common scab
infection, 3 was intermediate infection with the scab lesions covering 25 to 50 % of the surface
area and pitted lesions of one cm depth covering less than 5 % of the surface area, and 5 was the
most severe, with lesions covering more than 50 % of surface area, pitted lesions of more than
1cm depth covering more than 25 % of the surface area.
Corn in Phase 1 was harvested from the two middle rows of each plot on 2 Nov 2010
using a one-row corn harvester (John Deere). I also harvested corn in the NP plots in all the
blocks.
43

Soil pH and moisture
Soil pH was determined in water with a soil:water ratio of 1:2 w/v according to
Robertson et al (1999). Briefly, 15 g of soil was weighed and mixed with 30 mL DI H2O. The
slurry was stirred for one minute and allowed to settle for 30 min before measuring pH using a
pH meter (SevenEasy pH Mettler Toledo, Switzerland). Gravimetric soil moisture content was
º

determined after drying field- moist soil in a 65 C oven for about 48 hours.

Inorganic nitrogen
Ten grams of fresh soil were weighed into a 125 mL flask and then nitrate- and
ammonium-extracted in 50 mL of 1M KCl for 30 min on a shaker table. The solution was
º

filtered through 125 mm filter paper (Whatman #1) and stored at 4 C. The nitrate and
-

ammonium analyses were carried out within one month after extraction. N itrate nitrogen (NO 3 N) concentration in the extracted solution was determined using a modification of the method
-

-

described by Doane and Horwath (2003). This assay uses vanadium to reduce NO 3 to NO 2 ,
which reacts with sulfanilamide and N-1-naphthyl-ethylenediamine dihydrochloride to form a
pink color that is analyzed by a spectrophotometer. Briefly, the sample solution and KNO 3
standard solution were pipetted into 96 well clear microplates (Fisher Scientific, USA).
-

Concentration and volume of samples and standard were adjusted appropriately to the NO 3 -N
concentration in each set of samples. Twenty samples with four analytical replicates each were
run on each plate. Eight standard samples ranging from 0 to 10 ppm were loaded into each plate
44

with two replicates per standard. The saturated vanadium solution was prepared by mixing 1 g
VaCL3 with 150 mL of 1M HCl. The working assay solution consisted of 25 mL of saturated
vanadium solution, 200 mL H2O, 1.65 mL of 2 % w/v sulfanilamide in 1 M HCl, and 1.65 mL of
0.2 % w/v N-(1-naphthyl)-ethylenediamine dihydrochloride in DI water. The bottle head spaces
were purged with N2 gas for 30 sec and capped quickly to minimize vanadium oxidization.
Vanadium assay solution was added to the sample solution using a multichannel pipettor. The
samples were incubated at room temperature for 8 - 10 h before measuring nitrate concentration
by a spectrophotometer at λ = 540 nm (Multiskan Ascent, Thermo Scientific, Hudson, NH).
+

Ammonium (NH4 -N) was measured by modifying the method described by Sinsabaugh
et al (2000). The principle of this assay is to use salicylate and cyanurate to react with
ammonium, forming a green color which is measured on a spectrophotometer. The samples and
-

standard solutions were prepared as in the NO3 -N assay. Salicilate solution was prepared by
dissolving one packet of Ammonia Salicilate Reagent Powder Pillows in 5 mL DI H2O and 40
µL was pipetted into each well using a multichannel pipettor. Following this, 40 µL cyanurate
solution was added to each well. The samples were incubated in room temperature for 30 min
+

before determining the NH4 -N concentration in a microplate spectrophotometer (Multiskan
Ascent, Thermo Scientific, Hudson, NH) at λ = 630 nm.

Microbial biomass C and N
Microbial biomass C and N were measured according to the fumigation/extraction
method (Brookes et al., 1985; Beck et al., 1997; Robertson et al., 1999). Fifteen g of soil was
45

weighed into a 50 mL beaker and brought to 50 % water- holding capacity before placing into a
desiccator. Another beaker containing 50 mL of ethanol- free chloroform and boiling chips were
placed in the middle of the desiccator. The dessicator was lined with wet paper towels to
maintain humidity. Air in the desiccator was evacuated until the chloroform boiled. The
chloroform was maintained at boil for 3 min and then vented. The procedure was repeated 3
times, omitting venting after the final sequence. Samples were subsequently kept in the dark at
room temperature to fumigate for 24 h. Chloroform was removed from dessicators, the air was
released, and a vacuum was applied six times to completely remove residual chloroform. After
vaccuming, the soil samples were transferred to a 125 mL flask and extracted with 60 mL of
0.5M K2SO4. The sample solutions were shaken on a shaker table at 200 rpm for 1 h and filtered
(Whatman #5, 125 mm). A subset of non-fumigated control samples were weighed into 125 mL
o

flasks and extracted. The extracts were stored at -20 C before analyzing for total dissolved
organic C and total N with a TOC analyzer (Shimadzu, model TOC-VCPH with a TNM-1
nitrogen module attached). Microbial biomass C (MBC) was calculated as EC/kEC where EC is
the chloroform labile C pool, determined as the difference between fumigated and non- fumigated
samples, and kEC is a soil- specific value estimated as 0.45 (Beck et al., 1997). Microbial
biomass N (MBN) was calculated using the same approach but with a value of 0.54 (Brookes et
al., 1985).

Enzyme activity
The enzyme assay followed previously-described protocols (Saiya-Cork et al., 2002;
Grandy et al., 2007). Enzyme activities were determined within 24-48 h after soil sampling. One
g of soil and 125 mL of 50 mM sodium acetate buffer were combined in a 140 mL plastic bottle .
46

The pH of sodium acetate buffer was adjusted to the average soil pH of all the samples (6.5)
using HCl 0.1M. The solution was homogenized for 30 sec and assays were run using 96-well
microplates. Black plates (Greiner Bio-one) were used for hydrolytic enzyme and clear plates
(Fisher Scientific) for phenol oxidase. The first three columns contained control and standard
samples, the next three sets of three columns (4, 5, 6; 7, 8, 9; and 10, 11, 12) were used for three
other soil samples. The amount of 200 µL of soil slurry were added to each well of one column
of another black plate as a control. The molarity of standards and substrates for each appropriate
enzyme is shown in Table 2.3. For hydrolytic enzymes, 250 µL buffer solution was added to
column 1 and 200 µL to columns 2 and 3; for oxidative enxymes, 250 µL was added to column 1
and 200 µL to column 2. For the enzymes β-1,4-glucosidase (BG), β-1,4-N-acetylglucosaminidase (NAG), and acid phosphatase (PHOS), 50 µL of 4- methylumbelliferone (MUB)
was pipetted into columns 2, 4, 7 and 10 in all plates; for the enzyme tyrosine amino peptidase
(TAP), 50 µL of 7-amino-4-methylcoumarin (MC) was added to the same columns. For
hydrolytic enzymes, 50 µL of each substrate was pipetted into columns 3, 5, 6, 8, 9, 11, 12 for
each plate. For phenol oxidase (PHENOX), 50 µL buffer was added to columns 4, 7, 10 and 50
µL L-3,4-dihydroxyphenylalanine (L-DOPA) to columns 2, 5, 6, 8, 9, 11, 12. After adding the
o

substrate, all the plates were incubated in a 15 C incubator. BG and PHOS were incubated for
about 1.5-2 h, NAG for about 2-2.5 h, TAP for about 5-6 h, and PHENOX for about 24 h. After
incubation, 10 µL NaOH 1M was added to each well across all the columns to stop the reaction
of the hydrolytic enzymes. The hydrolytic enzyme activities were measured by a fluorometric
analyzer (Fluoroskan Ascent, Thermo Scientific, Hudson, NH) and PHENOX was measured
using colorimetric methods in a spectrophotometer (Multiskan Ascent, Thermo Scientific,
Hudson, NH).
47

Statistical analysis
Statistical analyses of amendment effects were carried out with a repeated measure
analysis of variance (ANOVA) using Proc mixed in SAS (SAS version 9.2, SAS Institute 2008).
A one-way ANOVA was also used to examine seasonal averages for each data set. Assumptions
of normality and equal variance of residuals were examined by Proc univariate in SAS and log
transformations were used if necessary to meet these assumptions. The best fit model was chosen
based on the AIC values for the unequal variance structure models. Where ANOVA indicated
significant differences, Fisher’s protected LSD (α = 0.05) was used to separate treatment means.
Pearson’s correlation coefficients were calculated to examine relationships among parameters.
Principal component analysis (PCA) was used to visualize the linear integrated relationship
among potato yield, common scab and other soil characteristics with compost treatment.

3. Result
3.1. Potato systems
Potato yield and common scab incidence
Compost application had a significant effect on potato productivity. Both the total potato
-1

-1

yield and potato yield of grade US No.1 in T3 (6.8 ton C ha ) and T4 (13.6 ton C ha ) in 2009
were significantly higher than in Ctrl (Figure 2.2). The total potato yield and US No.1 yield in T1
-1

-1

(1.7 ton C ha ) and T2 (3.4 ton C ha ) were not different from in Ctrl. The potato yield of these
sizes in all the compost treatments and Ctrl were significantly higher than in the NP (non-plot)
treatment, which produced the highest amount of size B potato yield. In 2010, the total potato
yield and US No.1 yield in all the compost treatments were significantly higher than in Ctrl and
48

in NP. T4 produced the highest total potato yield in all the systems. T3 and T4 also produced
more overweight potatoes than other treatments. The potato yields in Ctrl and NP were similar in
2010. There was no difference in B grade potato yield between any of the systems in 2010.
In 2009, the incidence of common scab in the Ctrl treatment did not differ from that of T1
and T2, but was significantly higher than that of T3 and T4 (Figure 2.3). Scab incidence in T4
was significantly lower than in T1 and T2. The scab incidence in the NP treatment did not differ
from the scab incidence in Ctrl treatment, but was significantly higher than that of all the
compost treatments. In 2010, the scab incidence was generally lower than in 2009 and there were
no differences between treatments. The scab incidence in 2009 was negatively correlated to soil
moisture, pH, inorganic N, MBN, and TAP; in 2010, the scab incidence was not correlated with
any soil characteristics.

Soil pH
In 2009, the seasonal average of soil pH in all the compost treatments were significantly
higher than in Ctrl (Figure 2.4). The higher rate of compost in T3 and T4 also significantly raised
pH compared to other treatments throughout the growing season (Table 2.4). In 2010, the
average soil pH over the growing season in T1 was similar to the soil pH in the Ctrl treatment
but the soil pH of all the remaining compost treatments was significantly higher than in Ctrl. The
soil pH in T3 and T4 was significantly higher than the soil pH in T2 but they were not different
from each other. In all treatments, the soil pH generally decreased in the middle of the season
and increased by the end of the season (Table 2.4).

Inorganic nitrogen

49

-

The seasonal average of NO 3 -N concentration in potato soil in 2009 was not different
-1

between Ctrl and T1, in which compost was applied at the rate of 1.7 ton C ha (Figure 2.5).
-

However, at higher rates of compost application in T2, T3, and T4, NO 3 -N contents were
-

significantly higher than in Ctrl. NO 3 -N in T4 was higher than in T2 and T3, which did not
-

differ from one another. No treatment effect on NO 3 -N was found on the first sampling date, 2
June 2009, or the last sampling date, 26 Nov 2009 (Table 2.5). At all the other measurement
dates, the treatment effect was significant and in almost all of these days, the higher compost
-

-

applications increased the NO 3 -N content in the soil. The NO 3 -N content in first sampling date,
-

-1

which was 2 weeks after composting, was similar in all the treatments ( µ=34.2 mg NO 3 -N kg
-

soil). Relative to the first sampling date, the NO 3 -N on the second sampling date (18 Jun 2009)
was reduced about 6 times in Ctrl and T1 and 4 times in T2 but increased 1.5 times in T3 and
nearly maintained in T4 (Table 2.5). All the treatments peaked on 16 Jul 2009 and then declined
-

over time until the end of the season, when the mean of all the treatments was 3.7 mg NO 3 -N
-1

kg

soil.
-

In 2010, the compost applications in T2, T3 and T4 significantly increased NO3 -N
-

(Figure 2.5). There was no difference between the seasonal average of NO 3 -N in T1 and Ctrl but
-

the seasonal averages of NO3 -N in T2, T3, and T4 were significantly higher than in Ctrl.
Treatment effects were significant at p < 0.0001 at all dates over the growing season except on 5

50

-

July (p < 0.0001). On 12 Aug, all the compost treatments increased NO 3 -N in the soil and the
next day, only T2, T3, and T4 had that effect.
+

The lowest NH4 -N content was in Ctrl treatment and the highest content was in T4
+

treatment, which was about 4- fold higher than in Ctrl (Figure 2.6). The NH4 -N contents in all
the compost treatments were significantly higher than in the Ctrl treatment. On the first sampling
+

+

-1

day in 2009 (Table 2.5), the lowest NH4 -N concentration was in Ctrl (20.3 mg NH4 -N kg )
+

-1

and the highest value was in T4 (150.9 mg NH4 -N kg ). Only NH4-N in T1 was not different
+

from that in Ctrl. On the second sampling day, 18 June 2009, the NH4 -N content in Ctrl and T1
+

was similar to the first sampling date but the NH4 -N contents in T2, T3, and T4 treatments were
+

significantly lower than on the first sampling day. On 16 July 2009, the NH4 -N contents were
+

notably lower than earlier sampling dates (Table 2.5). NH4 -N remained low after 16 July.
+

The average NH4 -N contents across all treatments in 2010 were different from the
+

+

average NH4 -N contents in 2009. In 2010, the NH4 -N content in T4 was higher than in the
+

remaining treatments, which did not differ from one another. NH4 -N contents were not
+

consistent across dates (Table 2.6). Similar to 2009, NH4 -N concentrations in 2010 declined in
July.

Microbial biomass

51

There were significant differences in microbial biomass between treatments when data
were averaged over the growing season (Figure 2.7). MBC in T2, T3, and T4 was higher than in
Ctrl while MBC in T1 was similar to MBC in Ctrl. All five measurements of MBC in 2009
showed a significant treatment effect (Table 2.7). In 2010, the seasonal average s of MBC in T1
and Ctrl did not differ and were lower than the other treatments (Figure 2.7). Only three
measurements were taken in 2010 but each of these exhibited a strong treatment effect (p <
0.0001) and showed that higher amendment application rates generally increased MBC (Table
2.7). T4 always had the highest MBC on all dates sampled.
The seasonal average of MBN in 2009 was different among the treatments (Figure 2.7).
MBN in T2, T3, and T4 were significantly higher than in Ctrl. MBN in T3 and T4 did not differ,
and was about a fold higher than MBN in Ctrl. MBN in T1 was similar to MBN in Ctrl. There
was variation amongst dates in treatment effects on MBN. For example, on the first and the last
dates, MBN in T4 was not different from in Ctrl (Table 2.8) but at three other dates MBN was
higher in T4. In 2010, the seasonal average of MBN was positively related to amendment
application rate (Figure 2.7). The MBN values of T1 and T2 did not differ from one another, or
from Ctrl on 12 Aug 2010; however, on the next measurement, 14 Sep 2010, MBN in all the
compost treatments were higher than in Ctrl (Table 2.8).

Enzyme activities
In 2009, average BG activities in T2 and T4 were significantly higher than in Ctrl (Figure
2.8). The BG activities in the potato soils in 2009 were inconsistent across the dates (Table 2.9).
For example, on 16 Jul 2009, BG in T2 and T4 were higher than in Ctrl and in T1. At the next
measurement on 29 Jul 2009, only BG in T2 was higher than in Ctrl. In 2010, the seasonal

52

average of BG activity in T4 was higher than BG activity in T1, T2, and T3 but similar to that of
Ctrl (Figure 2.9). The compost application rate did not affect BG activity in the potato soil in
2010 at the 2 first dates, but on 12 Aug 2010 and 14 Sep 2010, BG in T4 was not different from
Ctrl but was higher than the 3 other compost treatments.
The seasonal average of NAG activity was significantly affected by compost application
rates (Figure 2.8). NAG activities in T2, T3 and T4 were significantly higher than in Ctrl and
were higher in T2 and T4 than in T1 and T3. On 2 Jun 2009, compost treatment had a strong
effect on NAG activity in the potato systems (Table 2.10). NAG activity in T4 was three times
higher than in Ctrl. The compost rates showed strong effects again on 13 Aug 2009 when NAG
activity in all the compost treatments was higher than in Ctrl. There was a treatment effect on
only one of the four last measurement dates, 13 Oct 2009: NAG in T2 and T4 were higher than
in Ctrl. Seasonal mean NAG activities in 2010 were similar to those in 2009 (Figure 2.9). All of
the dates had similar results in that NAG activities in T3 and T4 were higher than in Ctrl and
typically those in T1 and T2 were similar to those in Ctrl, except on 1 June 2010.
Average PHOS activity in T2 was higher than in all the remaining treatments in 2009
-1 -1

(Figure 2.8). PHOS content in T2 was 111.0 nmol h g , almost two times higher than in Ctrl
and T3. The differences of PHOS content between treatments were not consistent across the
dates (Table 2.11). Average annual PHOS activities in 2010 were not different among treatments
(Figure 2.9). However, on 1 Jun 2010, PHOS activity in T1 was higher than in Ctrl, and on 5 Jul,
PHOS activity in T3 was significantly lower than in all the remaining treatments. There was no
treatment effect in the two final measurements.
The seasonal averages of TAP activities in all the compost treatments were significantly
higher than in the Ctrl (Figure 2.8), and TAP activity in T2, T3, and T4 was higher than in T1.
53

There was no treatment effect on TAP activity in the first two measurements (Table 2.12). The
-1 -1

mean of TAP activity in all treatments on 18 Jun 2009 was about 12 nmol h g soil and was
reduced by about half on 1 Jul 2009. On 16 Jul, 13 Aug 2009, 24 Aug 2009, and 13 Oct 2009
TAP activities in the compost treatments were significantly higher than in Ctrl. In 2010 as in
2009, TAP activities were higher in all compost treatments than in Ctrl (Figure 2.9). Compost
effects were apparent at all the dates except the first (Table 2.12).
In 2009, average PHENOX activities in Ctrl and T1 were higher than in T3, and higher in
T4 than in T2 and T3 (Figure 2.10). On 2 Jun 2009 (Table 2.13), PHENOX activity in Ctrl was
significantly higher than in the compost treatments. There was no subsequent treatment effect
until 13 Aug 2009, when PHENOX activity in Ctrl was similar to T1 but higher than T2 and T3.
In 2010, average PHENOX activity in Ctrl was higher than in T1, T2, and T3 (Figure 2.10). The
treatment effect was significant only on 14 Sep 2010 (Table 2.13).

Principal components analysis
Principal component analysis of all the variables in 2009 showed that the treatments
receiving compost strongly separated from the Ctrl. This was based on soil biological and
chemical metrics, which were higher in the organically amended treatments, high scab incidence
in the Ctrl treatment (Figure 2.11). In 2010, soil biological characteristics distinguished T4 from
the other treatments. Pearson’s correlation coefficients between variables for all the plots also
indicated that potato yield in 2009 was negatively correlated to common scab and positively
correlated to pH, microbial biomass C&N, and TAP enzyme activity (Table 2.15). The potato
-

yield in 2010 was positively correlated to pH, NO 3 -N, microbial biomass C&N, and NAG and

54

TAP enzyme activities, and negatively correlated to PHENOX enzyme activity; there was no
correlation with common scab.

3.2. Corn systems
Corn yield
Although the compost application was made in 2009, it still influenced corn yield in 2010
(Figure 2.12). The corn yield was highest in T4 (14.1 Mg ha

-1

) and lowest in Ctrl (11.8 Mg ha-

1

). Corn yield was higher than Ctrl in all treatments except T3 and all of those were significantly

higher than in NP. Corn yield in T1 was not different from T2, T3 and T4, and the yield in T4
was significantly higher than in T2 and T3. Corn yield was significantly correlated to soil
moisture, and microbial biomass C and N and negatively correlated to ammonium (Table 2.20).

Soil properties
The poultry compost applied in 2009 still had a significant effect on soil pH in 2010.
Averaged over the growing season, the soil pH in Ctrl was 6.31, significantly lower than in all
-

compost treatments (Table 2.16). Averaged over the growing season, NO 3 -N in T1 was
significantly higher than in the other treatments (Table 2.17). There was no difference between
-

-

NO3 -N in T3 and T4 but they were significantly higher than NO 3 -N in T2, which was not
-

+

different from the NO 3 -N content in Ctrl treatment. On average, the NH4 -N contents in Ctrl
+

and T3 were higher than the NH4 -N contents in the remaining treatments (Table 2.17). In
-

+

contrast with NO 3 -N, no any effect of compost application on NH4 -N was observed in the first

55

measurement on 24 May 2010; however, by the end of the season, the treatments with the higher
+

rate of compost (T3 and T4) had higher NH4 -N in the soil.

Microbial biomass
The MBC in corn soil was significantly affected by the poultry compost applied a year
before. The seasonal average of MBC in each of the compost treatments was higher than in Ctrl
(Table 2.18). On 24 May 2010, MBC in T2, T3, and T4 was similar and higher than in Ctrl,
which did not differ from T1. On 19 Jul 2010, the amount of MBC in T1 was significantly
-1

increased from 51.2 to 136.8 mg kg while the amount of MBC in T2, T3 and T4 remained
about the same as on 24 May 2010. By the end of the season, although MBC in all the treatments
had decreased, levels in compost treatments were higher than in the control. For MBN, the
seasonal averages in all compost treatments were also higher than in Ctrl. This trend was the
same for all dates except 24 May 2010, on which MBN level in T1 was similar to Ctrl. Similarly
to the results for MBC, MBN in the soil did not increase with additional compost in the T1
treatment.

Enzyme activities
There were no treatment main effects or treatment by time interactions for BG or NAG
(Table 2.21). Averaged over the season, TAP activity in T1, T2 and T4 was not different from
Ctrl which was higher than in T3 (Table 2.19). In the first measurement, the TAP content in Ctrl
was significantly higher than any of the compost treatments; on the next sample date the TAP
contents in Ctrl and T3 were similar, and were lower than T1, T2, and T4. There was no
treatment effect on TAP activity at the end of the season. The seasonal average of PHOS content
56

in T3 was lower than in Ctrl, T1 and T2. PHOS activity in T2 did not differ from T1, and was
higher than in T3 and T4. PHENOX was measured only once in the beginning of the season and
did not show any treatment effect (Table 2.19).

3.3. Environmental conditions
The daily average temperature was collected near the research site from 20 April to 20
Oct in 2009 and 2010. The temperature in 2010 was significantly higher than in 2009 (p < 0.05),
especially during 20 May to 20 July (Figure 2.13).
Total precipitation (Figure 2.14) during the growing season in 2009 (445 mm) was higher
than in 2010 (373 mm). However, the higher rainfall in 2009 was driven by a few large
precipitation events; in fact, the median rainfall in 2009 (3.0mm) was lower than median rainfall
in 2010 (4.6 mm) and the numbers of rainy days was the same for both years (65 days). In both
years, fields were irrigated six times; however more water was applied in 2010 leading to a
higher amount of irrigation water used that year (Table 2.22).
Compost application significantly affected soil moisture in the potato system in 2009 but
not in 2010 (Figure 2.15). In 2009, the soil moisture in T2 and T4 was higher than in Ctrl. In the
corn soil in 2010, the moisture content in T4 was significantly higher than the other treatments,
which were similar to each other (Figure 2.16).

4. Discussion
4.1. Effect of poultry compost application rates on potato quality
The fundamental challenge of potato cultivation is to maximize yield and reduce diseases
below economic thresholds, and to maintain high soil quality. In this study, poultry compost

57

application significantly increased potato yield. Higher rates of compost produced higher potato
yields and especially increased the number of US No.1 tubers. A net benefit analysis estimated
that a minimum yield increase of 3 Mg ha-1 in US No. 1 tubers would be necessary to support
farmer adoption of organic inputs among Michigan potato producers (Labarta et al., 2002).
Snapp et al (2003) stated that poultry compost applied with a reduced fertilizer rate could
-1

significantly increase potato yield from 3.4 to 6.8 Mg ha . This result demonstrated that
compost at a rate of 1.7, 3.4, 6.8, and 13.4 Mg C ha
1.99, 1.44, 6.96, and 5.79 Mg ha

-1

-1

increased the yield of US No.1 potatoes by
-1

in 2009 and by 5.08, 6.25, 7.77, and 10.2 Mg ha

in 2010,

respectively. This increased yield is possibly explained by the increase in leaf area index when
compost is added (Larkin et al., 2011). Moreover, the combination of inorganic fertilizers with
compost application may have maximized N use efficiency (Sikora and Enkiri, 2000; Nyiraneza
and Snapp, 2007). For instance, Carter et al (2004) found that the compost in combination with
-1

N application could maximize the potato yield to 39 Mg ha .
Environmental conditions such as temperature and soil moisture can be the factors that
affect potato yield. For example, in a study adding compost to potato systems in sandy soil in
Prince Edward Island, Carter (2007) found that the increase of soil organic C was associated with
an increase of soil moisture content and water-holding capacity, and resulted in higher potato
yields. Because the Ctrl system did not receive compost and therefore had lower water-holding
capacity, a short period of water deficit could reduce potato yields and quality (Gregory and
Simmonds, 1992; Carter, 2007). Irrigation in combination with a more regular rainfall in 2010
and higher temperatures, likely account for the overall higher yields in 2010 than in 2009.

58

Environmental changes associated with poultry compost may have also influenced
common scab. For example, Larkin et al (2011) found that common scab in potato systems with
irrigation was increased by 10 to 50% compared to systems without irrigation. Other studies
have found the opposite result: irrigation tended to reduce common scab (Lapwood, 1973; Davis
et al., 1976). Many studies on common scab suppression have focused on cultural controls and
resistant cultivars (Loria et al., 2006) but few have focused on using compost application. I
found that compost amendment substantially changed the soil environment and soil biological
activity by increasing soil water holding capacity, tuber yield, and microbial activity. Potato
responses to amendments may also depend upon the chemical characteristics of the amendment.
Saison et al (2006) stated that the effect of compost amendment on soilborne disease was mostly
affected by the characteristics of the compost used. My results indicated that the rates of compost
application significantly changed the soil microbial biomass and certain types of enzyme
activities in the soil. This could explain the reduction of common scab in 2009 ; however, the
difference in common scab between 2009 and 2010 is more likely due to different environmental
conditions such as temperature or rainfall.

4.2. Management of poultry compost application rates and timing on corn yield
High rates of compost application could increase yields and improve environmental
conditions but are not considered economical by potato growers (Evanylo et al., 2008).
Researchers need to determine the lower rate that preserves efficacy, and how frequently
compost should be applied. The compost application in this study occurred once but in some
instances there were still effects on the corn yield in the next year. In 2010, the additional
application of 1.7 ton C ha

-1

in T1, which provided the same amount of compost in T2 after two

59

years (but with a different frequency of application), increased corn yield to equal that of T2.
Crop yield may not benefit from low rates of compost in a short tern but may be increased by the
accrual of nutrients supplied by multiple applications of compost (Evanylo et al., 2008). The
plots treated with poultry compost preserved more of the inorganic N that was applied, thereby
increasing N availability for corn growth (Munoz et al., 2008; Bowden et al., 2010). Smiciklas et
al (2008) suggested that the optimal compost application rates for the corn-soybean systems
were about 22.4 to 44.8 Mg ha

-1

but that rate may not be economical and may result in excessive

P-loading. Our result also indicated that there was no difference of corn yield between T1 (3.4
-1

Mg C ha

-1

in total) and T4 (13.4 Mg C ha ). This suggested that timing of compost application

should be considered to minimize costs for growers.

4.3. Effect of poultry compost application rates on soil quality management
Management to maintain and improve soil quality is very important and is a difficult task
in potato systems. High rates of poultry compost application in this study significantly enhanced
soil biological characteristics and nutrient availability. This occurred because the poultry
compost increased soil organic matter, which in turn increased water holding capacity,
particulate organic matter C and N, nutrient levels and biomass (Grandy et al., 2002; Larkin et
al., 2011). Thus, it provided N-bearing compounds and organic matter that promoted soil
biological processes (Grandy et al., 2009). The acquisition of nutrients by microbes from soil
organic matter has often been determined by the availability of nutrients in the soil (Caldwell,
2005; Moorhead and Sinsabaugh, 2006). Grandy et al (2009) indicated that BG, NAG and Lleucine aminopeptidase (LAP) were highly correlated to the abundance of N-bearing compounds.
This was also similar to our result that BG, NAG, and TAP were tied to substrate availability
60

from poultry compost in potato systems. Microbial biomass and inorganic N also increased
following compost application. There was no correlation between PHOS and MBC, N, or
inorganic N, probably because PHOS can be produced by a wide range of taxa in both acid- and
alkaline-active forms (Sinsabaugh et al., 2008).
Sufficient N management is essential to maximize crop production; meanwhile, excessive
-

fertilization will increase the costs of production and the risks of NO 3 -N leaching and NH3
volatilization. Compost application increases soil organic matter and microbial biomass, and
therefore helps to reduce N loss from leaching and runoff and increase N recovery. Although N
was balanced in all the systems, inorganic N contents in the treatments receiving higher rates of
compost were nevertheless significantly higher than in the Ctrl treatment during the growing
seasons. The management of combining compost with N fertilizers was reported to improve soil
physical and chemical properties and provide environmental benefits (Evanylo et al., 2008).
Nyiraneza and Snapp (2007) also demonstrated that using a combination of poultry compost and
N fertilizer increased N availability in potato systems. The sole use of inorganic N can reduce
MBC in the soil (Peacock et al., 2001, Lupwayi et al., 2005) while the integration of fertilizers
with organic application usually increases MBN and has negligible or no effect on MBC (LimonOrtega et al., 2009).

4.4. Effect of timing of poultry compost application on soil quality management
-1

Carter et al (2004) stated that an annual compost application rate of 2-3 Mg C ha

was

the minimum amount needed to maintain soil organic matter levels in potato systems in sandy
loam soil for a rotation cycle. In another study of potato rotations in the same area (Angers et al.,
1999), the systems with C input higher than 2.4 Mg C ha
61

-1

-1

yr were found to have the capacity

of maintaining organic matter levels in the soil. In this study, the rate of 1.7 Mg C ha

-1

applied

in the first year was probably not high enough to have an effect. For example, seasonal averages
of MBC and MBN in T1 were not different from T2 in the potato system in 2009; however, in
the corn system in 2010, they were significantly lower in T1 than in T2. This could be explained
by the disturbance of the compost addition in T1 on soil microbial community in 2010. Hadas
and Portnoy (1997) demonstrated that only 9 % of the total organic N was mineralized from
-

compost decomposition after 33 weeks. Examining NO 3 -N contents in these systems, I found
-

that though there was no difference in 2009, in 2010 the seasonal average of NO 3 -N in T1 was
significantly increased to a level higher than in T4. This can be explained by the N recovery
capability of poultry compost addition in increasing the high corn yield in T1.
Compost mineralization processes are greatly affected by N content in compost, C/N
ratio, soil texture, pH and climate. Some studies have found that only a portion of N inputs were
mineralized in the first year following application (Scherer et al., 1996; Brandt et al., 1999).
However, other studies also demonstrated that little to no N availability remained in the second
year due to nutrient loss during composting (Mahimairaja et al., 1995; Warman and Cooper,
2000; Muñoz et al., 2008). Therefore, in the long-term use of compost application, integrating N
supply with the residual N mineralized from compost in the following years is a very important
component of managing soil quality and improving crop production.

5. Conclusion
This study was conducted to examine the effect of poultry compost amendment in terms
of application rates and timing on plant yields and soil quality. Regardless of application rate and

62

timing, compost amendment increased potato and corn yield and soil characteristics such as soil
organic matter, water holding capacity, inorganic N, microbial biomass and enzyme activity. In
-1

chapter 1, compost application at a low and economical rate (5.6 Mg ha ) combined with rye
cover crop significantly increased potato yield and soil microbial activity. In this study, higher
rates of poultry compost application resulted in increased potato yields in both 2009 and 2010.
However, the effect of compost application on scab incidence was not consistent: there was a
treatment effect in 2009 but not in 2010, when there was an overall reduction of scab. The
common scab incidence was also found to be negatively correlated with soil characteristics in
2009 but not in 2010.
In examining the effect of high rates of compost application on soil quality, I also found
that poultry compost significantly increased soil pH, inorganic N, microbial biomass and enzyme
activities in both phases 2009 and 2010. These effects of compost application carried over to the
second year in corn soil. However, although applying compost at a high rate increases C
sequestration, it tends to be less economical for farmers. Therefore, dividing the poultry compost
application into two smaller applications of 1.7 ton C ha

-1

each year for two years was

recommended in this study in order to improve soil quality and crop yield without burdening
farmers financially.
Overall, poultry compost application greatly increased both potato and corn yields and
improved soil biological characteristics. The optimal combination of application rates and timing
of compost need to be further examined in order to determine the best long term management
practices for using organic amendments to improve potato productivity.

63

Table 2.1. Poultry manure amendment rates for potato in 2009 and corn in 2010 in Phase 1.
Rate of compost amendment
Rate of compost amendment
-1
-1
in 2009, ton C ha *
in 2010, ton C ha
Ctrl
0
0
T1
1.7
1.7
T2
3.4
0
T3
6.8
0
T4
13.6
0
* Manure application rate for Phase 2 in 2010 was repeated as in Phase 1 in 2009.
Treatment

64

Table 2.2. Field operation dates of the two study phases.
Operations

Dates*

Phase 1
Phase 2
2009
Potato
Compost application
20 May
Planting
22 May
Fertilizer application No.1
22 May
Fertilizer application No.2
24 June
Fertilizer application No.3
9 July
Vine kill for potato
18 September
Harvest
15 October
2010
Corn
Potato
Compost application
23 April
27 April
Planting
10 May
20 May
Fertilizer application No.1
10 May
20 May
Fertilizer application No.2
5 July
21 June
Vine kill for potato
17 September
Harvest
2 November
19 October
* Phase 1 began in 2009 and Phase 2 began in 2010. In 2009, soil samples were collected 12
times in Phase 1 every two weeks during the growing season. In 2010, soil samples were
collected three times for Phase 1 and four times for Phase 2 over the growing season.

65

Table 2.3. Substrate/fluorescing agents and the molarity of each used in the enzyme assay
Substrate/ Fluorescing agent

Chemical formula

4-methylumbelliferone (MUB)
7-amino-4-methylcoumarin
(MC)
4-Methylumbelliferyl β-Dglucopyranoside
4-Methylumbelliferyl phosphate
4-Methylumbelliferyl N-acetylβ-D-glucosaminide
L-Tyrosine 7-amido-4methylcoumarin
L-3,4-dihydroxyphenylalanine

Enzyme

C10 H8 O3
C10 H9 NO2

Molarity
used (mM)
0.01
0.01

C16 H18O8

β-glucosidase

0.2

C10 H9 O6 P
C18 H21NO8 .H2O

Acid phosphatase
β-1,4-D-acetyl
glucosaminidase
Tyrosine amino
peptidase
Phenol oxidase

0.2
0.2

C19 H18N2 O4
C9 H11 NO4

66

0.1
25

Table 2.4. Soil pH in the potato systems *
Phase 1 - potato 2009
Trt
29 Jul 2009
13 Aug 2009
9 Sep 2009
Ctrl
5.69 (0.04)d
5.84 (0.07)c
5.90 (0.07)c
T1
6.39 (0.06)b
5.82 (0.09)c
6.13 (0.03)b
T2
6.02 (0.07)c
5.73 (0.10)c
6.19 (0.08)b
T3
6.58 (0.06)b
6.32 (0.03)b
6.47 (0.10)a
T4
6.89 (0.15)a
6.57 (0.07)a
6.64 (0.01)a
p value
< 0.0001
< 0.0001
< 0.0001
Phase 2 - potato 2010
1 Jun 2010
5 Jul 2010
Ctrl
5.87 (0.17)b
5.32 (0.10)c
T1
5.82 (0.15)b
5.45 (0.15)c
T2
6.07 (0.16)b
5.83 (0.19)b
T3
6.46 (0.09)a
6.11 (0.08)a
T4
6.51 (0.16)a
6.05 (0.10)ab
p value
< 0.0005
< 0.0001
* Means (±SE) with different letters differ significantly (p < 0.05).

67

13 Oct 2009
5.98 (0.04)c
6.55 (0.04)b
6.57 (0.11)b
6.95 (0.10)a
7.07 (0.08)a
< 0.0001
14 Sep 2010
6.32 (0.14)b
6.32 (0.13)b
6.48 (0.23)b
7.08 (0.09)a
7.05 (0.10)a
< 0.0001

Table 2.5. Inorganic N in potato soil in 2009/Phase 1 *.
-

NO3 -N
Ctrl
T1
T2
T3
T4
p value
+
NH4 -N

2 Jun
2009
30.0
(5.56)
36.0
(5.17)
32.6
(6.60)
32.8
(4.14)
39.8
(8.85)
ns

18 Jun
2009
5.78
(0.80)b
5.72
(0.43)b
8.06
(0.88)b
53.3
(12.4)a
30.5
(7.09)a
< 0.0001

1 Jul
2009
5.05
(0.51)c
8.42
(1.53)b
16.8
(1.55)a
23.3
(5.30)a
17.1
(1.44)a
< 0.0001

16 Jul
2009
38.2
(5.93)b
38.3
(5.62)b
54.6
(7.79)b
48.2
(10.6)b
87.0
(10.0)a
0.0034

29 Jul
2009
17.2
(2.42)c
20.5
(3.19)c
31.6
(3.33)ab
24.9
(2.85)bc
44.3
(8.89)a
0.0036

24 Aug
2009
5.58
(0.44)b
6.07
(0.54)b
9.44
(1.74)a
7.69
(1.00)ab
9.25
(0.52)a
0.0286

9 Sep
2009
10.9
(1.14)c
12.2
(1.08)bc
14.9
(1.01)ab
8.80
(0.87)d
15.6
(1.69)a
< 0.0001

23 Sep
2009
15.7
(1.71)b
16.4
(2.28)b
20.4
(1.74)ab
17.9
(1.48)b
26.1
(1.09)a
0.0094

13 Oct
2009
1.91
(0.25)c
2.36
(0.30)c
4.44
(0.74)b
6.08
(0.58)ab
6.48
(0.73)a
< 0.0001

26 Nov
2009
3.15
(0.17)
3.20
(0.49)
4.65
(0.61)
3.57
(0.38)
4.03
(0.73)
ns

2 Jun
18 Jun
16 Jul
29 Jul
13 Aug
24 Aug
9 Sep
23 Sep
13 Oct
26 Nov
2009
2009
2009
2009
2009
2009
2009
2009
2009
2009
Ctrl
20.3
17.8
0.71
0.53
1.03
1.40
1.42
0.87
1.04
0.76
(7.63)d
(4.99)c
(0.06)c
(0.09)d
(0.06)c
(0.07)b
(0.24)
(0.05)b
(0.11)bc
(0.14)
T1
48.9
46.1
1.69
0.62
1.27
1.52
1.31
1.04
0.88
0.79
(10.6)cd (11.4)ab
(0.11)b
(0.06)cd
(0.08)bc
(0.03)b
(0.18)
(0.05)b
(0.07)c
(0.10)
T2
70.3
18.1
1.77
0.76
1.73
1.78
1.22
0.69
1.05
0.68
(20.1)bc
(3.87)c
(0.17)b
(0.08)bc
(0.22)b
(0.06)ab
(0.05)
(0.12)b
(0.10)bc
(0.03)
T3
102.1
36.9
1.38
0.93
1.78
1.95
1.28
1.39
1.30
1.03
(14.89)b (5.32)bc
(0.19)b
(0.03)b
(0.14)b
(0.14)a
(0.21)
(0.15)a
(0.08)ab
(0.08)
T4
150.9
59.2
2.35
1.82
2.64
2.15
1.37
1.67
1.58
0.80
(10.6)a
(7.76)a
(0.11)a
(0.07)a
(0.29)a
(0.23)a
(0.11)
(0.20)a
(0.13)a
(0.08)
p value
0.0003
0.0154
0.0001
0.0001
0.0001
0.0013
ns
0.0002
0.0012
ns
-1
* Mean±SE (mg N kg soil) Means with the same letters did not differ significantly (p < 0.05). Abbreviation: ns – not significant.

68

Table 2.6. Inorganic N of potato 2010/Phase 2 *
-

NO3 -N
Ctrl
T1
T2
T3
T4
p value

1 Jun 2010
18.8 (2.40)d
25.1 (1.57)cd
34.2 (2.03)bc
44.6 (5.23)b
90.0 (7.29)a
< 0.0001

5 Jul 2010
26.2 (2.54)
31.2 (1.84)
31.5 (4.13)
30.2 (2.02)
35.7 (8.31)
ns

12 Aug 2010
4.50 (0.21)c
7.05 (0.74)b
7.74 (0.70)b
7.08 (0.60)b
13.0 (2.84)a
< 0.0001

14 Sep 2010
8.60 (1.40)c
13.3 (1.52)c
22.2 (2.76)b
27.5 (2.40)a
29.7 (3.38)a
< 0.0001



NH4 -N
1 Jun 2010
5 Jul 2010
12 Aug 2010
14 Sep 2010
Ctrl
26.4 (4.03)bc
3.81 (0.41)a
1.04 (0.16)a
0.47 (0.06)ab
T1
25.3 (3.52)bc
4.05 (0.43)a
0.41 (0.03)b
0.33 (0.03)b
T2
23.4 (1.77)c
3.26 (1.12)a
0.52 (0.03)b
0.43 (0.05)ab
T3
34.4 (4.05)b
1.39 (0.21)b
0.49 (0.02)b
0.55 (0.09)a
T4
51.2 (3.49)a
1.08 (0.11)b
1.69 (0.46)a
0.70 (0.15)a
p value
0.0012
0.0027
0.0005
0.0417
-1
* Mean±SE (mg N kg soil). Means with the same letter did not significantly differ (p < 0.05).
Abbreviation: ns – not significant

69

Table 2.7. Microbial biomass C in the potato soil over the growing season 2009/Phase 1 and
2010/Phase 2 *
Potato 2009 – Phase 1
1 Jul 2009
29 Jul 2009 13 Aug 2009
9 Sep 2009
26 Nov 2009
Ctrl
45.1 (4.83)bc 155.5 (8.75)ab 134.3 (11.2)b
70.7 (10.6)c 103.6 (15.0)b
T1
37.8 (7.86)c
205.5 (23.0)a 139.5 (15.8)b
69.0 (20.0)c
110.1 (5.2)b
T2
32.8 (6.96)c 169.5 (33.9)ab 215.5 (18.0)a 84.9 (20.2)bc 132.5 (3.2)ab
T3
61.3 (8.67)b
203.7 (19.4)a 119.1 (18.9)b 134.0 (20.9)ab 141.8 (12.6)a
T4
128.4 (15.3)a
119.6 (12.3)b 206.9 (20.4)a 148.6 (24.1)a
55.7 (10.8)c
p value
< 0.0001
0.0275
0.0009
0.0150
< 0.0001
Potato 2010 – Phase 2
11 Jun 2010
12 Aug 2010 14 Sep 2010
Ctrl
69.6 (4.52)d
79.6 (7.34)c
73.3 (5.64)c
T1
67.3 (9.61)d
74.4 (7.82)c
76.9 (2.29)c
T2
127.6 (6.98)c
95.0 (9.28)bc 83.8 (6.56)bc
T3
155.2 (12.1)b
118.1 (13.1)b
95.4 (5.08)b
T4
193.5 (9.92)a
176.9 (9.23)a 137.7 (10.1)a
p value
< 0.0001
< 0.0001
< 0.0001
-1
* Mean ±SE (mg kg soil). Means with different letters were significantly different at p < 0.05.

70

Table 2.8. Microbial biomass N in potato soil over the growing season 2009/Phase 1 and
2010/Phase 2*
Potato 2009 – Phase 1
1 Jul 2009
29 Jul 2009
13 Aug 2009
9 Sep 2009
26 Nov 2009
Ctrl
18.1 (3.63)bc
18.1 (1.56)b
19.3 (2.73)b
9.75 (1.29)c
16.6 (1.88)c
T1
11.9 (2.96)c
21.9 (3.81)b
28.3 (1.78)b 17.7 (3.85)bc 17.5 (1.10)bc
T2
25.9 (7.75)ab
24.7 (7.69)b
19.7 (2.04)b 16.9 (4.86)bc 21.7 (1.42)ab
T3
34.9 (4.38)a
37.2 (5.91)a
19.8 (5.29)b
35.0 (4.08)a
26.1 (1.88)a
T4
23.7 (3.89)ab
46.9 (5.97)a
46.2 (1.72)a 23.5 (4.73)ab 21.1 (3.40)abc
p value
0.0125
0.0030
0.0001
0.0082
0.0167
Potato 2010 – Phase 2
12 Aug 2010
14 Sep 2010
Ctrl
12.8 (0.71)c
11.7 (0.98)d
T1
16.7 (1.07)c
18.6 (0.72)bc
T2
16.6 (1.13)bc
16.5 (2.27)c
T3
20.8 (2.61)b
21.3 (1.88)b
T4
32.2 (1.01)a
35.4 (1.01)a
p value
< 0.0001
< 0.0001
-1
* Mean ±SE (mg kg soil). Means with different letters were significantly different at p < 0.05.

71

Table 2.9. β-1,4-glucosidase activity of potato soil over the growing season 2009/Phase 1 and 2010/Phase 2 *
Potato 2009 – Phase 1
2 Jun
2009
Ctrl
20.4
(2.55)c
T1
55.8
(5.44)b
T2
74.3
(6.16)a
T3
75.3
(7.37)a
T4
81.9
(7.51)a
p value
< 0.0001
Potato 2010 – Phase 2

18 Jun
2009
49.3
(8.87)
49.7
(12.89)
60.4
(9.01)
43.9
(10.6)
32.6
(7.78)

1 Jul
2009
30.2
(5.46)
33.1
(8.88)
37.9
(6.20)
20.3
(4.35)
36.7
(8.06)

16 Jul
2009
48.1
(8.57)b
45.9
(6.31)b
80.2a
(12.4)
51.1
(12.6)b
83.0
(7.76)a

29 Jul
2009
61.3
(7.24)b
68.5
(9.88)b
105.6
(13.5)a
52.54
(5.92)b
68.1
(9.87)b

ns

ns

0.0150

0.0136

13 Aug
2009
58.1
(6.24)c
61.5
(7.36)bc
76.7
(4.23)ab
66.2
(3.10)bc
84.4
(6.25)a

24 Aug
2009
32.5c
(3.99)
47.5b
(5.51)
68.2
(5.52)a
62.9
(3.21)a
64.3
(3.74)a

9 Sep
2009
45.3
(4.42)ab
38.7
(2.70)b
52.4
(7.41)a
48.7
(1.80)ab
57.0
(2.01)a

23 Sep
2009
36.0
(3.51)c
34.0
(5.79)c
74.2
(9.64)a
55.4
(4.58)b
39.2c
(3.10)

13 Oct
2009
35.4
(7.00)c
46.4
(6.60)bc
70.4
(11.9)a
39.4
(9.07)c
69.7
(5.35)ab

26 Nov
2009
22.8
(1.97)b
21.4
(1.62)b
30.3
(3.52)a
18.6
(0.63)b
30.5
(1.85)a

0.0171 < 0.0001

0.0458

0.0002

0.0120

0.0010

1 Jun 2010
5 Jul 2010
12 Aug 2010
14 Sep 2010
Ctrl
26.3 (0.62)
25.7 (1.41)
40.9 (2.88)ab
42.2 (1.84)ab
T1
28.5 (2.33)
25.8 (1.89)
33.8 (2.02)c
35.9 (3.30)bc
T2
30.9 (1.53)
29.5 (4.03)
35.2 (1.47)bc
33.6 (2.28)c
T3
29.3 (2.56)
24.7 (0.76)
35.4 (3.05)bc
34.9 (1.40)c
T4
28.1 (2.37)
31.0 (1.84)
44.1 (2.11)a
42.8 (2.18)a
p value
ns
ns
0.0047
0.0059
-1 -1
* Mean±SE (nmol h g soil). Means with different letters were significantly different (p < 0.05).

72

Table 2.10. β-1,4-N-acetyl glucosaminidase activity of potato soil over the growing season 2009/Phase 1
Potato 2009 – Phase 1
2 Jun
18 Jun
1 Jul
16 Jul
29 Jul 13 Aug
24 Aug
9 Sep
2009
2009
2009
2009
2009
2009
2009
2009
Ctrl
14.3
23.1
13.5
22.8
28.7
30.9
9.49
20.2
(3.29)c
(2.58)
(1.47) (2.09)bc
(2.46)b
(1.93)c
(2.01)c
(1.47)
T1
27.5
30.6
17.8
20.2
31.4
39.6
11.0
23.5
(2.72)b
(4.44)
(2.77)
(2.98)c
(3.61)b
(4.26)b (1.46)bc
(3.25)
T2
34.1
36.3
23.1
38.5
49.0
40.4
16.0
23.5
(4.66)ab
(2.72)
(4.19)
(6.25)a
(6.62)a
(2.09)b (1.36)ab
(3.51)
T3
36.7
20.8
14.0
27.2
32.0
40.6
19.3
23.7
(2.79)ab
(1.63)
(2.92) (7.45)abc
(3.61)b
(1.62)b
(0.95)a
(2.68)
T4
42.2
35.6
18.5
35.2
36.9
58.7
17.2
31.6
(2.76)a
(7.83)
(1.44) (3.87)ab
(3.19)b
(2.08)a
(2.29)a
(5.22)
p value
< 0.0001
ns
ns
0.0389
0.0319 < 0.0001
0.0034
ns
Potato 2010 – Phase 2
1 Jun 2010
5 Jul 2010
12 Aug 2010
14 Sep 2010
Ctrl
8.6 (0.29)d
10.5 (0.90)c
15.7 (0.81)c
13.0 (0.80)c
T1
12.9 (1.33)bc
9.6 (0.67)c
15.3 (1.62)c
14.5 (0.84)c
T2
11.1 (1.00)cd
11.9 (1.03)bc
16.5 (1.76)bc
15.0 (1.05)c
T3
15.6 (1.17)b
15.0 (1.34)b
19.1 (1.91)b
22.1 (1.30)b
T4
23.0 (1.97)a
19.8 (2.72)a
30.3 (0.85)a
29.8 (2.94)a
p value
< 0.0001
< 0.0001
< 0.0001
< 0.0001
-1 -1
* Mean±SE (nmol h g soil). Means with different letters were significantly different (p < 0.05).

73

and 2010/Phase 2*
23 Sep
2009
11.9
(0.91)
11.1
(1.31)
11.9
(0.86)
11.8
(0.62)
13.1
(1.67)
ns

13 Oct
2009
18.1
(2.75)c
23.1
(4.42)bc
32.1
(4.54)a
18.6
(4.74)c
28.6
(1.61)ab
0.0400

26 Nov
2009
12.9
(0.80)
13.1
(1.12)
14.1
(0.72)
11.9
(1.62)
15.6
(1.98)
ns

Table 2.11. Acid phosphatase activity of potato soil over the growing season 2009 /Phase 1 and 2010/Phase 2*
Potato 2009 – Phase 1
18 Jun
1 Jul
16 Jul
29 Jul
13 Aug
24 Aug
9 Sep
23 Sep
2009
2009
2009
2009
2009
2009
2009
2009
Ctrl
72.6
50.4
93.6
68.8
92.7
63.1
48.9
49.7
(7.38)a
(6.00)a
(7.94)
(6.02)b
(12.9)
(12.5)c
(11.0)c
(4.83)b
T1
37.6
49.7
88.7
57.8
94.5
94.8
91.1
64.7
(6.60)bc
(11.8)a
(14.2)
(10.3)b
(19.6)
(12.2)b
(7.62)ab
(9.15)b
T2
64.1
60.6
117
124
161
168
131
149
(12.4)ab
(14.8)a
(20.3)
(14.7)a
(18.5)
(11.9)a
(11.2)a
(26.0)a
T3
36.1
17.9
60.4
57.9
110
93.2
84.6
80.0
(2.22)bc
(0.75)b
(12.8)
(10.2)b
(9.55)
(6.82)b
(5.16)b
(22.8)b
T4
34.5
57.2
88.9
46.9
130
120
91.8
54.3
(10.4)c
(11.6)a
(18.1)
(10.7)b
(18.6)
(6.64)ab
(9.87)ab
(11.9)b
p value
0.0022 < 0.0001
ns
0.0007
ns
0.0023
0.0012
0.0003
Potato 2010 – Phase 2
1 Jun 2010
5 Jul 2010
12 Aug 2010
14 Sep 2010
Ctrl
51.6 (6.97)bc
50.4 (5.83)a
166 (26.0)
138 (13.0)
T1
71.2 (6.04)a
53.4 (8.27)a
152 (21.1)
161 (24.7)
T2
67.6 (9.67)ab
67.4 (6.57)a
146 (24.7)
167 (28.7)
T3
65.8 (6.55)ab
20.3 (4.70)b
137 (16.6)
143 (25.9)
T4
41.1 (4.65)c
62.3 (7.23)a
172 (41.1)
187 (46.2)
p value
0.0047
0.0007
ns
ns
-1 -1
* Mean±SE (nmol h g soil). Means with different letters were significantly different (p < 0.05).

74

13 Oct
2009
23.1
(7.05)c
51.4
(9.74)ab
87.9
(12.4)a
31.3
(6.43)bc
50.1
(8.03)ab
< 0.0001

26 Nov
2009
12.1
(1.16)
14.5
(1.64)
22.3
(1.79)
13.8
(2.91)
18.2
(3.97)
ns

Table 2.12. Tyrosine amino peptidase activity of potato soil over the growing season 2009 /Phase 1 and 2010/Phase 2 *
Potato 2009 – Phase 1
18 Jun
1 Jul
16 Jul
29 Jul 2
13 Aug
24 Aug
9 Sep
23 Sep
13 Oct
2009
2009
2009
009
2009
2009
2009
2009
2009
Ctrl
11.1
5.79
2.50
10.4
10.5
5.36
12.0
2.98
5.07
(1.93)
(1.14)
(0.18)c
(1.69)
(1.01)d
(0.78)d
(1.35)
(0.22)b
(1.32)b
T1
6.97
4.41
14.21
14.7
19.5
10.6
10.1
2.82
8.24
(0.93)
(1.18)
(2.93)b
(2.62)
(1.07)c
(0.83)c
(0.99)
(0.14)b
(0.53)ab
T2
15.2
8.33
23.4
19.8
24.4
18.1
13.0
3.90
13.5
(2.89)
(2.47)
(3.09)a
(4.32)
(0.94)b
(1.40)a
(2.10)
(0.47)ab
(2.50)a
T3
12.1
3.08
25.5
19.2
24.1
12.8
13.4
3.96
9.94
(3.52)
(0.74)
(3.02)a
(3.41)
(1.40)b
(0.46)bc
(1.56)
(0.67)ab
(2.56)a
T4
14.5
7.70
23.4
20.3
33.8
15.1
14.9
5.23
15.0
(4.11)
(1.64)
(2.84)a
(4.88)
(2.34)a
(1.28)ab
(1.03)
(0.63)a
(1.74)a
p value
ns
ns
< 0.0001
ns < 0.0001 < 0.0001
ns
0.0111
0.0037
Potato 2010 – Phase 2
1 Jun 2010
5 Jul 2010
12 Aug 2010
14 Sep 2010
Ctrl
5.20 (0.67)
3.69 (0.32)d
10.7 (1.05)d
9.24 (0.63)c
T1
6.22 (0.50) 4.51 (0.47)cd
14.7 (0.66)c 10.6 (0.52)bc
T2
6.67 (1.15) 6.73 (1.44)ab
15.1 (1.11)c
9.83 (0.48)c
T3
8.27 (1.12) 5.50 (1.12)bc
20.1 (1.13)b
12.9 (1.28)b
T4
8.17 (0.67)
10.8 (0.77)a
26.4 (1.04)a
15.9 (0.98)a
p value
ns
0.0002
< 0.0001
< 0.0001
-1 -1

* Mean±SE (nmol h g soil). Means with different letters were significantly different (p < 0.05).

75

26 Nov
2009
3.09
(0.69)
2.31
(0.17)
3.74
(0.86)
3.27
(0.24)
3.76
(0.46)
ns

Table 2.13. Phenol oxidase activity of potato soil over the growing season 2009/Phase 1 and 2010/Phase 2*
Potato 2009 – Phase 1
2 Jun
18 Jun
1 Jul
29 Jul
13 Aug
24 Aug
23 Sep
2009
2009
2009
2009
2009
2009
2009
Ctrl
1.07 (0.11)a 0.59 (0.19) 0.76 (0.18) 1.30 (0.12)
1.27 (0.09)a 1.12 (0.11) 1.24 (0.11)b
T1
0.45 (0.03)bc 0.66 (0.12) 0.77 (0.08) 1.23 (0.14)
1.15 (0.12)ab 0.89 (0.08) 1.66 (0.23)b
T2
0.47 (0.07)b 0.84 (0.08) 0.75 (0.11) 1.26 (0.14)
0.92 (0.09)bc 0.89 (0.08) 0.82 (0.13)c
T3
0.19 (0.07)c 0.66 (0.09) 0.61 (0.16) 1.05 (0.29)
0.80 (0.06)c 0.85 (0.03) 0.92 (0.07)bc
T4
0.47 (0.09)b 0.82 (0.09) 0.81 (0.17) 1.29 (0.08) 0.95 (0.02)abc 0.94 (0.05) 2.05 (0.06)a
p value
< 0.0001
ns
ns
ns
0.0071
ns
< 0.0001
Potato 2010 – Phase 2
1 Jun 2010
5 Jul 2010
14 Sep 2010
Ctrl
0.50
0.32
0.80a
T1
0.36
0.32
0.46abc
T2
0.39
0.19
0.41bc
T3
0.23
0.46
0.38c
T4
0.42
0.30
0.62ab
p value
ns
ns
0.0191
-1 -1
* Mean±SE (µmol h g soil). Means with different letters were significantly different (p < 0.05).

76

26 Nov
2009
0.82 (0.07)b
0.62 (0.13)b
0.66 (0.14)bc
0.28 (0.05)c
1.71 (0.25)a
< 0.0001

Table 2.14. Overall repeated measures ANOVA of potato soil characteristics in both phases in 2009 and 2010.
Potato 2009 – Phase 1
-

+

NO3 -N* NH4 -N*
pH
MBC
MBN*
BG
NAG*
PHOS*
TAP*
PHENOX
Trt
< 0.0001 < 0.0001 < 0.0001
0.0181 < 0.0001
0.0023
0.0006
0.0010 < 0.0001
0.0006
Date
< 0.0001 < 0.0001 < 0.0001 < 0.0001
0.0035 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001
Trt*date
< 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001
Potato 2010 – Phase 2
NO3 -N* NH4 -N*
pH
MBC
MBN*
BG
NAG*
PHOS
TAP
PHENOX
Trt
< 0.0001 < 0.0001
0.0054 < 0.0001
< 0.0001
0.0275
< 0.0001
0.0132
< 0.0001
0.1722
Date
< 0.0001 < 0.0001 < 0.0001 < 0.0001
0.6095
< 0.0001
< 0.0001 < 0.0001 < 0.0001
0.0076
Trt*date
0.0114 < 0.0001 < 0.0001 < 0.0001
0.6324
0.0313
0.0402
0.0002
< 0.0001
0.2642
* Logarithmic transformation. Abbreviations: MBC: microbial biomass C, MBN, microbial biomass N, BG: β-1,4-glucosidase, NAG:
β-1,4-N-acetyl glucosaminidase, PHOS: acid phosphatase, TAP: tyrosine amino peptidase, PHENOX: phenol oxidase.

77

Table 2.15. Pearson’s correlation coefficients (r) between seasonal means of variables in potato soil in 2009/Phase 1 and 2010/Phase 2*
Potato 2009/Phase 1
Scab
W%
pH
NO3

+
NH4

Total yield
-0.56
0.39
0.52
0.22
0.26
0.62
0.50
0.35
0.33
0.45
-0.01
0.10

MBC
MBN
BG
NAG
TAP
PHOS
PHENOX
Potato 2010/Phase 2
Total Yield
Scab
0.14
W
-0.17
pH
0.54
0.53
NO3
+
NH4

Scab

W%

pH

-0.43
-0.51
-0.47

0.33
0.66
0.42
0.48
0.51
0.77
0.72
0.77
0.65
0.16

0.87
0.64
0.78
0.28
0.51
0.68
-0.19
0.01

+

NH4

MBC

MBN

BG

NAG

TAP

PHOS

0.68

-0.48
-0.32
-0.59
-0.17
-0.39
-0.45
-0.11
-0.28

-

NO3

Scab

W%

-0.18
0.30
-0.15

0.35
-0.12
MBC
0.53
-0.01
MBN
0.61
0.07
BG
-0.03
0.04
NAG
0.46
-0.04
TAP
0.53
0.05
PHOS
-0.22
-0.27
PHENOX
-0.45
0.13
* The bold numbers indicate significance

-0.03
0.38

pH

0.82
0.42
0.74
0.47
0.64
0.74
0.23
-0.04
-

0.48
0.70
0.32
0.54
0.66
-0.05
0.13
+

NO3

NH4

0.57
0.53
0.51
0.72
0.13
-0.06
MBC

0.29
0.46
0.65
0.03
0.12
MBN

0.87
0.80
0.76
-0.09
BG

0.89
0.62
-0.06
NAG

0.52
-0.07
TAP

-0.11
PHOS

0.46

0.19
0.32
0.75
0.34
0.62
0.91
0.73
0.32
0.61
0.82
0.69
0.91
0.36
0.24
0.35
0.38
0.49
0.41
0.43
0.89
0.76
0.91
0.42
0.62
0.85
0.66
0.92
0.52
-0.58
0.31
0.21
0.19
0.11
-0.33
-0.08
0.16
-0.02
at p < 0.05. See Table 2.14 for abbreviations.
78

0.50
0.87
0.91
0.10
-0.02

0.49
0.42
0.16
0.31

0.89
0.37
0.05

0.19
-0.16

0.32

Table 2.16. Soil pH of corn soil 2010/Phase 1*.
24 May 2010
19 Jul 2010
29 Sep 2010
Ctrl
6.34 (0.02)c
5.79 (0.15)c
6.81 (0.10)d
T1
6.37 (0.07)c
6.14 (0.07)b
7.09 (0.12)bc
T2
6.59 (0.09)b
6.19 (0.11)b
7.06 (0.07)cd
T3
7.05 (0.06)a
6.40 (0.09)ab
7.34 (0.08)ab
T4
6.93 (0.07)a
6.53 (0.10)a
7.46 (0.05)a
0.0021
0.0005
p value
< 0.0001
* Means with different letters are significantly different (p < 0.05).

79

Average
6.31 (0.08)c
6.53 (0.07)b
6.61 (0.07)b
6.93 (0.06)a
6.97 (0.05)a
< 0.0001

Table 2.17. Inorganic N in corn soil 2010/Phase 1*.
-

NO3 -N
Trt
Ctrl
T1
T2
T3
T4
p value

24 May 2010
4.56 (0.28)c
11.8 (0.82)a
5.77 (0.58)bc
6.10 (0.95)b
7.05 (0.34)b
< 0.0001

19 Jul 2010
4.69 (0.47)bc
4.56 (0.42)bc
3.53 (0.45)c
6.74 (0.71)a
6.05 (0.63)ab
0.0107

29 Sep 2010
2.57 (0.22)c
3.56 (0.50)ab
3.40 (0.35)b
4.24 (0.46)ab
4.44 (0.30)a
0.0076

Average
3.92 (0.20)c
6.81 (0.44)a
4.30 (0.18)c
5.65 (0.54)b
5.82 (0.17)b
< 0.0001

24 May 2010
19 Jul 2010
29 Sep 2010
Ctrl
0.64 (0.04)
4.88 (0.73)a
0.24 (0.02)b
T1
0.70 (0.05)
1.69 (0.14)b
0.32 (0.05)ab
T2
0.69 (0.03)
1.41 (0.09)b
0.24 (0.01)b
T3
0.77 (0.02)
4.30 (0.51)a
0.39 (0.08)a
T4
0.79 (0.06)
2.47 (0.93)b
0.38 (0.04)a
p value
ns
0.0002
0.0362
* Means with different letters are significantly different (p < 0.05).

Average
1.93 (0.24)a
0.90 (0.05)b
0.78 (0.03)b
1.82 (0.17)a
1.08 (0.27)b
< 0.0001

+

NH4 -N

80

Table 2.18. Microbial biomass in corn soil 2010/Phase 1*
Microbial biomass C
29 Sep 2010
60.9 (3.99)d
77.7 (4.98)bc
86.5 (4.02)ab
73.1 (1.88)c
94.1 (5.12)a
0.0001

Average
68.0 (2.96)d
88.5 (3.51)c
122.2 (8.04)a
108.4 (4.00)b
127.9 (4.74)a
< 0.0001

24 May 2010
19 Jul 2010
29 Sep 2010
Ctrl
13.0 (0.71)b
17.4 (1.41)b
8.3 (0.62)d
T1
12.6 (2.48)b
23.5 (1.34)a
12.1 (1.11)c
T2
22.6 (2.47)a
25.3 (2.75)a
14.9 (0.67)ab
T3
21.9 (2.80)a
24.3 (1.85)a
13.2 (0.38)bc
T4
27.1 (0.99)a
27.2 (1.82)a
16.2 (0.54)a
p value
0.0012
0.0471
< 0.0001
* Means with different letters are significantly different (p < 0.05).

Average
13.5 (0.81)c
16.8 (1.43)b
21.0 (1.19)a
19.8 (0.87)ab
22.9 (0.96)a
0.0001

Ctrl
T1
T2
T3
T4
p value
Microbial biomass N

24 May 2010
51.2 (9.3)b
51.2 (12.4)b
139.1 (16.1)a
123.8 (5.7)a
132.4 (10.1)a
< 0.0001

19 Jul 2010
91.9 (4.69)c
136.8 (8.28)ab
140.9 (9.53)ab
128.3 (7.04)b
157.4 (7.22)a
< 0.0001

81

Table 2.19. Enzyme activities* in corn soil, 2010/Phase 1.
-1 -1

β-1,4-glucosidase (BG), nmol h g soil
24 May 2010
Ctrl
54.9 (6.38)
T1
49.8 (5.15)
T2
62.1 (6.78)
T3
50.7 (5.10)
T4
49.1 (6.93)
p value
ns

19 Jul 2010
65.0 (4.78)
61.9 (3.67)
72.7 (3.62)
60.0 (4.80)
71.7 (5.31)
ns

29 Sep 2010
35.0 (3.38)
34.7 (4.23)
41.9 (1.81)
38.7 (1.92)
37.9 (2.70)
ns

Average
51.6 (4.80)
48.8 (3.16)
58.9 (3.62)
49.8 (3.26)
52.9 (2.87)
ns

29 Sep 2010
13.8 (0.71)b
14.3 (1.73)b
16.3 (1.29)ab
17.5 (0.73)a
18.2 (1.31)a
0.0146

Average
20.3 (1.62)
21.5 (1.26)
22.8 (1.38)
18.6 (1.15)
22.0 (1.12)
ns

29 Sep 2010
10.1 (0.74)
10.9 (0.97)
11.5 (0.20)
9.5 (0.43)
12.7 (0.45)
ns

Average
13.7 (0.81)ab
12.2 (0.50)bc
14.3 (0.45)a
11.9 (0.59)c
12.4 (0.20)bc
0.0282

29 Sep 2010
122 (9.3)ab
119 (10.6)abc
145 (8.9)a
95 (7.4)c
107 (8.0)bc
0.0083

Average
138 (14.4)ab
127 (7.5)ab
154 (11.1)a
90 (8.1)c
112 (11.7)bc
0.0077

-1 -1

β-1,4-N-acetyl glucosaminidase (NAG), nmol h g soil
24 May 2010
19 Jul 2010
Ctrl
22.6 (2.70)
24.5 (2.04)bc
T1
21.2 (2.93)
29.1 (1.88)ab
T2
22.1 (2.53)
29.9 (2.31)a
T3
15.8 (1.76)
22.5 (1.54)c
T4
18.5 (3.31)
29.4 (2.39)ab
p value
ns
0.0230
-1 -1

Tyrosine amino peptidase (TAP), nmol h g soil
24 May 2010
19 Jul 2010
Ctrl
17.6 (1.79)a
13.3 (0.95)c
T1
10.0 (0.86)bc
15.6 (0.88)b
T2
13.1 (1.32)b
18.3 (0.66)a
T3
11.1 (1.32)bc
15.1 (0.57)bc
T4
7.6 (1.11)c
17.0 (0.41)ab
p value
0.0001
0.0017
-1 -1
Acid phosphatase (PHOS), nmol h g soil
24 May 2010
19 Jul 2010
Ctrl
124 (18.8)
167 (17.3)ab
T1
98 (12.6)
165 (14.4)ab
T2
127 (18.6)
189 (10.2)a
T3
83 (14.5)
92 (7.3)c
T4
87 (23.6)
141 (12.6)b
p value
ns
0.0004
-1 -1

Phenol oxidase (PHENOX), µmol h g soil
24 May 2010
Ctrl
0.65 (0.08)
T1
0.49 (0.08)
T2
0.64 (0.10)
T3
0.35 (0.12)
T4
0.62 (0.13)
p value
ns
* Means with different letters are significantly different (p < 0.05).

82

Table 2.20. Pearson’s correlation coefficients (r) between seasonal means of variables in corn soil, 2010 *.
Corn yield
pH
W
MBC
MBN
NO3
NH4
pH
0.36
W
0.45
0.37
0.36
0.24
0.32
NO3
-0.53
-0.13
-0.26
-0.14
NH4
MBC
0.51
0.68
0.53
0.22
-0.40
MBN
0.54
0.70
0.62
0.34
-0.34
0.92
BG
0.05
-0.10
0.52
-0.04
-0.21
0.35
0.31
NAG
0.32
-0.15
0.49
0.12
-0.51
0.32
0.31
TAP
0.00
-0.43
0.28
-0.26
-0.09
0.09
0.09
PHOS
0.01
-0.65
0.24
-0.11
-0.18
-0.04
-0.07
PHENOX
-0.11
-0.42
-0.09
-0.56
0.03
-0.29
-0.36
* The bold numbers indicate significance at p < 0.05. See Table 2.14 for abbreviations.

83

BG

NAG

TAP

PHOS

0.79
0.66
0.67
0.17

0.57
0.61
0.15

0.79
0.39

0.33

Table 2.21. Overall repeated measures ANOVA of corn soil characteristics, 2010/Phase 1.
NO3-N*
NH4-N
MBC
MBN*
Trt
0.0001 < 0.0001 < 0.0001 < 0.0001
Date
< 0.0001 < 0.0001 < 0.0001 < 0.0001
Trt*date
< 0.0001
0.0011 < 0.0001
0.6579
* Logarithmic transformation. See Table 2.14 for abbreviations.
pH

84

BG*
0.3699
< 0.0001
0.6503

NAG
0.2127
< 0.0001
0.0665

PHOS
0.0068
< 0.0001
0.0125

TAP PHENOX
0.0327
< 0.0001
< 0.0001
-

Table 2.22. Irrigation water added to the research field during the growing seasons of 2009 and
2010.
Potato 2009/Phase 1

Irrigation, mm

Potato 2010/Phase 2

Irrigation, mm*

25 Jun 2009
1 Jul 2010
19.1
22.9
6 Jul 2009
7 Jul 2010
20.3
25.4
10 Jul 2009
21 Jul 2010
20.3
25.4
18 Jul 2009
29 Jul 2010
25.4
27.9
29 Jul 2009
4 Aug 2010
25.4
27.9
5 Aug 2009
19 Aug 2010
25.4
25.4
Total
Total
135.9
154.9
* The amount of irrigation water applied was the same for potato 2010/Phase 2 and corn
2010/Phase1.

85

Potato compost
phase 1 - 2009

Potato compost
phase 2 - 2010
N

T2

T4

T1
Ctrl

T3

T4

T3

T4

T2

Ctrl

np

Ctrl

T3

np

T1

T3

T4

T1

np

Ctrl

T1

T3

T1

np

Ctrl

T1
T3

T2

T4

Ctrl

T3

T4

np

T1

T2

T2

Ctrl

T2

4T4

T2

Np

T2

np

T3

np

T4

Ctrl

Ctrl

T2

T1

T4

T1

T1

T4

Ctrl

np

T3

np

T2

T3

Figure 2.1. Experimental design and location. Phase 1 started in 2009 and Phase 2 started in
2010. The five treatments were laid out randomly with five blocks (indicated by bold squares) in
a seven-treatments-experiment. Treatment abbreviations were shown in Table 1. Np: non treated
plot (no fertilizers and no compost added). The empty plots were the treatments that were not
used in this study.

86

a
C

B

AB

AB

A

A
a

b

ab

a

ab

b
D

C

BC

BC

A

AB

c

b

ab

ab

a

ab

a

bc

b

bcd

d

cd

C

C

B

B

B

b

ab

ab

A
a
a

b

b
C

C

B

c

c

B

AB

b

ab

A

ab
a

Figure 2.2. Potato yield in 2009 (a) and 2010(b) in Montcalm Research Farm. Potato size Bs: < 5
cm diameter; size As: 5 - 8.3 cm diameter; over weight: > 8.3 cm diameter. T1 – T4: compost
treatments. NP: non treated plot - no compost, no fertilizers added in the growing season. Means
for the same tuber size with the same letter are not significantly different (p < 0.05). The first
row of uppercase letters indicate differences among treatments in total potato yields. The seco nd
row of uppercase letters show differences among treatments in potato yields of size US No.1.

87

a
a

ab

bc

bc

cd

d

b

Figure 2.3. Common scab severity in potato (mean±SE, p < 0.05). (a) Scab incidence in 2009
and (b) Scab incidence in 2010. The disease was assessed after harvesting by rating from 0 to 5
where 0 is no infection; 1 is low infection; 3 is intermediate; and 5 is severe infection.

88

a

a
b
c

c

d

b
a

a

b
c

c

Figure 2.4. Average soil pH. (a) pH in 2009 and (b) pH in 2010 (Mean±SE). Means with
different letters are significantly different (p < 0.05).

89

a
a
b
b
c

c

b
a

b
bc
cd
d

-

-

-1

Figure 2.5. Average NO 3 -N of potato soil in 2009 (a) and 2010 (b). Mean±SE (mg NO 3 -N kg
soil). Means with different letters are significantly different (p < 0.05).

90

a
a
b
c

c

d

b
a
b
b

b

b

+

+

-

Figure 2.6. Average of NH4 -N in potato soil 2009 (a) and 2010 (b) (Mean±SE, mg NH4 -N kg
1

soil). Means with different letters are significantly different (p < 0.05).

91

a
a
ab
c

b
a

a

bc

b
c
d

a

d

a

a

b
c

b

bc

bc

c

d

-1

Figure 2.7. Seasonal average of microbial biomasses in potato soil in 2009 (a) and 2010 (b) (Mean±SE, mg kg soil). Means with
different letters are significantlt different (p < 0.05).

92

a
ab
c

a

a
b

bc

c

c

bc

a

a

ab
b
b

b
b

c

b

d

-1 -1

Figure 2.8. Seasonal average of hydrolytic enzyme activities in potato systems in 2009 (Mean±SE, nmol h g soil). Means with
different letters are significantly different (p < 0.05).

93

a
ab

b

b

a

b
b
cd

c

d

a
b
c
c
d

-1 -1

Figure 2.9. Hydrolytic enzyme activity in the potato systems in 2010 (Mean±SE, nmol h g soil). Means with different letters are
significantly different (p < 0.05).

94

a
ab

a

ab
bc

c

b
a
ab
b

b

b

-1 -1

Figure 2.10. Phenol oxidase in the potato soil in 2009 (a) and 2010 (b) (Mean±SE, µmol h
Means with different letters are significantly different (p < 0.05).

95

g ).

a
PHOS

Component 2 (19.9%)

2

BG

T2

NAG
W

1

TAP

Scab

PHENOX
Ctrl
T1

0

MBC
T4

NH4
MBN
pH
yield

T3

-1

-2

NO3

-1
0
1
Component 1 (68.8%)

2

b
PHENOX
BG

Component 2 (22.1%)

2
Ctrl
1

T4

0

T1
T2
T3

-1

NH4
NAG MBN
NO3
MBC
PHOS
W TAP
Yield
pH

-2
Scab
-2

-1
0
1
2
Component 1 (66.8%)

3

4

Figure 2.11. Principal component analysis for potato quality and soil characteristics in potato
systems in 2009 (a) and 2010 (b). Circles with numbers indicate different sites and arrows
indicate soil characteristics. Data used for the simulation were the average of variables over
growing seasons. See Table 2.14 for abbreviations.

96

ab

b

c

a
bc

d

Figure 2.12. Corn yield in 2010/Phase 1, in which poultry compost was added in 2009
3

-1

(Mean±SE, 10 kg ha ). Additional compost was added to T1 in 2010. NP: non treated plot - no
compost, no fertilizers added. Means with different letters are significantly different (p < 0.05).

97

Figure 2.13. Daily average temperature at Montcalm Research Farm in 2009 and 2010. Data
were collected at Entrican Station, Michigan about 1.5 km east of the research field. The average
º
º
of 6 months from 20 Apr to 20 Oct in 2009 was 15.4 C and in 2010 was 17.5 C (Source:
http://enviroweather.msu.edu).

98

Figure 2.14. Daily rainfall at Montcalm Research Farm in 2009 and 2010. Data were collected at
Entrican Station, Michigan about 1.5 km east of the research field. The total rainfall of 6 months
from 20 April to 20 October of 2009 was 445 mm and of 2010 was 373 mm. The number of
rainy days in 2009 = 2010 = 65 days. (Source: http://enviroweather.msu.edu).

99

a
a

ab
c

bc

b
c

b

Figure 2.15. Average soil moisture in the potato systems over the growing season 2009/Phase 1
(a) and 2010/Phase 2 (b). Means with different letters are significantly different (p < 0.05).

100

a
b

b
b

b

Figure 2.16. Average soil moisture in the corn systems in 2010/Phase 1 (Mean±SE). Means with
different letters are significantly different (p < 0.05).

101

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102

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