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INHERITANCE STUDY OF STARCH ACCUMULATION
IN STEMS OF DRY BEANS.

By
Joseph Kassian Mligo

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE
Department of Crop and Soil Science

1983

ABSTRACT
INHERITANCE STUDY.OF STARCH ACCUMULATION IN STEMS
OF DRY BEANS

By

Joseph Kassian Mligo

A study of inheritance of starch accumulation was

undertaken in five crosses of dry beans (Phaseolus vulgaris

 

L.) to get information on whether the differential starch
accumulation in the cultivars was due to genetic causes.

IKI solution as a starch indicator could not estimate
starch levels efficiently in this study. Use of near infra-
red reflectance spectroscopy utilizing Neotec Grain Quality
Analyzer model 41, appeared to be efficient in estimating
stem starch content at 20 days after first flower.

F2 frequency distributions showed a characteristic
of transgressive quantitative inheritance. The broad sense
heritability estimates proved to lie in the intermediate
range with values ranging from 512 to 602. Thus plant
breeders may not have great difficulty in recognizing
genetic differences among parental stocks. However, more
information is needed on the extent to which the genetic

differences observed can be used for selection purposes.

TABLE OF CONTENTS

LIST OF TABLES . . . .'. .

LIST OF FIGURES

INTRODUCTION

LITERATURE REVIEW

EXPERIMENTAL PROCEDURES

A.
B.

C.

Chemical quantification of bean
stem starch .

Calibration of the grain quality
analyzer for estimation of starch
content in dry beans . .

Genetic studies

RESULTS AND DISCUSSION

A.

E.

Relationship between stem starch
quantification and IKI starch
scores in dry bean cultivars

Calibration of grain quality analyzer .

for starch concentration estimation in
dry beans .

Variation among parents . .
Evaluation of segregating and non-
segregating populations for percentage
stem starch of dry bean crosses .

Low x high crosses
High x high crosses
Low x low crosses
Midparent values

Heritability estimates

GENERAL DISCUSSION .

APPENDICES

LITERATURE CITED .

iii

Page
iii
iv

18
18
23

26
30

30

35
37

39

39
44

48
50
53
57
61

Table

10.

LIST OF TABLES

Stem percentage starch as quantitatively
detenmined and the respective IKI scores of
five dry bean cultivars . .

Mean and ranges of percentage stem.starch
content 20 days after first flower of the
ten dry bean cultivars grown in 1981

Frequency distributions for stem percentage
starch content 20 days after first flower in
parents, and F2 generations in a cross
between Redkloud and Michigan 41228

Frequency distributions for stem percentage
starch content 20 days after first flower in
parents, F1 and F2 generations in a cross
between Seafarer and ICA Pijao

Frequency distributions for stem percentage
starch content 20 days after first flower in
parents and F2 generations in a cross between
ICA Pijao and Seafarer

Frequency distributions for stem percentage
starch content 20 days after first flower in
parents, and'Fz generations in a cross
between Brgzil-Z and Redkloud

Frequency distributions for stem percentage
starch content 20 days after first flower in
parents and F2 generations in a cross between
Michigan 41228 and Swedish Brown

Frequency distributions for stem percentage
starch content 20 days after first flower
in parents and F generations in a cross
between Seafarer and 61356

Comparison between parents (P1 P2), mid-
parent (MP) and F2 values for1 the dry bean
stem starch content 20 days after first
flower in five dry bean crosses

Broad sense heritability (BSH) estimates
for stem starch content for F2 progeny of
three dry bean crosses . . . . . .

iv

Page

33

38

40

41

42

43

45

47

49

52

Appendix

Page
1. Multiple linear regression analysis

for K-values for calibration of

the Neotec Grain Quality Analyzer

(model 41) using Hal Stat 4 program 57

LIST OF FIGURES

Figure A Page

1. Starch standard curve used for the estimation
of percentage stem starch based upon standard
quantitative chemical methods . . . . . . . . . 22
2. Relationship between IKI starch scores and

percent starch as determined quantitatively
at 20 days after first flower in the stems of
dry bean cultivars . . . . . . . . . . . . . 31

vi

INTRODUCTION

 

Although many plants store carbohydrate in the form
of sucrose, still a great number deposit their reserve
carbohydrate in the form of larger, more complex, and more
insoluble molecules, the polysaccharides. Starch, in parti-
cular, serves as the reserve carbohydrate of a great number
of plant species and is formed in such organs as leaves, stems,
tubers, roots and seeds, where it is deposited during conditions
favorable to photosynthesis.

In recent years, studies performed in dry beans at
Michigan State University have been concerned with cultivar
differences in carbohydrate partitioning as associated with
yield and the remobilization of stored starch in the plant
parts under stress conditions. In general, crop growth
and yield are controlled by many environmental factors.
These include light, CO2 supply, temperature, water supply
and nutrients, to name a few, which interact with the genet-
ically determined physiological and biochemical systems of
the plant. Complex control mechanisms have evolved to en-
able the plant to maintain a large degree of stability when
external conditions change. If changes prevent the growth
or yield from reaching the genetic potential of a plant
then the limiting factor constitutes a stress. Thus the

ability of a plant to remobilize accumulated starch under

stress conditions, as it has been found in dry beans
(Adams et a1 1981), such as under reduced photosynthesis,
is believed to be a means by which a plant can maintain
some degree of stability to external changes and hence
sustain a steady rate of pod filling and ultimately a more
stable yield.

Due to the fact that starch accumulation may be
advantageous especially under stress conditions, incorpora-
tion of the ability to accumulate more starch into our
future improved cultivars may lead to more stability of
yield. lThe productioncflfimproved cultivars is dependent
on a breeding system which allows gene exchange, and
existence of heritable variation for the characters to be
improved. If the cultivar differences in starch accumulation
are due to genetic causes then heritable variation in starch
accumulation could be used in a bean breeding program to
incorporate the character into the backgrounds of desirable
cultivars. The genetic basis of differential starch
accumulation in beans or in any other plant is not known.
The development of genotypes with high capability of
accumulating starch will be facilitated by the knowledge
of the inheritance of starch accumulation. Together with
this, methodologies to facilitate selection which are rapid
and accurate are required.

The objectives of this study were:
1” To determine the relationship of starch scores

as determined by iodine potassium iodide starch staining

i(lKI) and starch as quantitatively determined
in the laboratory.

2. To determine whether the Grain Quality
Analyzer (GQA) could be used to measure

starch levels in dry beans.
3. If feasible use the GQA to study the
inheritance pattern of stem starch storage in

common bean (Phaseolus vulgaris).

LITERATURE REVIEW

 

Methodologies used for the Measurement of Carbohydrate

Partitioning in Dry Beans

Methods for studying carbohydrate partitioning
among strains of common beans need to be rapid, reproduc-
ible, accurate and inexpensive (Izquierdo, 1981). There
are many analytical procedures relying on colorimetric
measurements which have been developed for carbohydrate
analysis (sugars and starch) in a number of crops (Gaines,
1971, Smith, 1969; Thivend, et a1. 1966) which could be
‘modified for beans. The drawback of these methods is that
they are not suited for analyzing a large number of samples
as required by plant breeders engaged in a screening program.
Another drawback of these techniques is that they require
considerable skill and they are time consuming and sensi-
tive to slight variation in conditions.

In beans, carbohydrate partitioning has been esti-
mated by using iodine- potassium.- iodide (IKI) starch
indicator solution (Adams, et al 1975). The indicator re-
action depends upon the addition of the triodic ion to
starch, yielding a brilliant blue complex (McCready et
a1 1943; 1970). The method involves treating freshly

cut tissues with several drops of IKI starch indicator

solution and visually ranking the color development
against facsimiles and varying degrees of intensity of
color development observed among cultivars in stems

and roots. This method has been used by other researchers,
successfully, in analyzing waxy pollen mutants. Nilan
(1981) reported that the IKI method permits a single
observer in an eight-hour day to analyze the frequency

of pollen mutants--normal (blue) and waxy (red) -- in a

million pollen grains in Hordeum vulgare.

 

Although the method is rapid it is only semi-
quantitative in respect to the estimation of quantities
of starch. The correlation (r = .85, df = 18) between
IKI-starch scores and igflzizg starch reported by Bousalama
(1977) has not been supported by subsequent studies.
Izquierdo (1981), studying the applicability of IKI-
starch scores and content of total soluble solids (TSS)
for evaluating carbohydrate partitioning in beans, reported
that correlation between IKI - starch scores and T88
contents and quantitatively determined starch were in
moderate but not high agreement. Izquierdo speculated
that the lack of correspondence between IKI - values and
inflzizg starch may have been due to differences in starch
quality among cultivars. He referred to the amounts of
amylose and amylopectin which are the two components of
starch, the ratio of which may vary among cultivars.

Amylopectin is weakly detected with IKI - starch; if a

cultivar were to have more amylopectin the IKI - starch
score readings would be lower when compared to a cultivar
with the same level of total starch but with starch stored
primarily in the form of amylase. At present there is no
information about the quality of stem or root starch among
cultivars of dry beans.

In order to circumvent such possibilities and still
have a rapid and reliable technique, the use of a near-
infrared light reflectance (NIR) instrument to estimate
percent starch needs to be explored. The NIR instrument
such as the grain quality analyzer (GQA) is extremely
simple to operate and requires a minimum of laboratory
space (Hymowitz et al 1974). The grain analyzer does not
directly measure chemical components of samples; it must
be calibrated against standards. After calibration,
samples in a powdered form are placed in a glass covered
cup then fed into the instrument from.which one can
estimate the percentage of constituent being analyzed.
Although the GQA will not be as rapid as the IKI starch
score technique relative to chemical starch analytical
methods which could be employed, NIR may prove to have
advantages over the other methods.

NIR techniques have been in use for a long time.
Norris and Hart (1965), investigated the water absorption

bands at 0.76, 0.97, 1.18, 1.45, and 1.94 um for the

spectrophotometric measurement of water in seeds and grains.
These efforts led to the develOpment of a near infrared
reflectance (NIR) technique, which originally aimed at
determining the moisture content of agricultural products,
but later was expanded to the measurement of protein, oil,
starch and other constituents in these products.

Hymowitz et a1 (1974), estimated the protein and oil
content in corn, soybean and oat seeds by NIR using the
grain analyzer manufactured by Dicky - John Corp. These
authors also studied the effect of sample grinding time
on the grain analyzer readings for protein and oil content.
Their most important findings were, a) the high correlation
between the NIR and Kjeldahl data for protein content, and
b) the lack of statistical significance between grinding
time and protein or oil estimates.

Watson et a1 (1977), develOped a regression equa-
tion for protein determination by Kjeldahl and NIR using
five classes of wheat. It was found that the lepe of the
regression equation depended on the wheat class and that
the effect of wheat class on the regression equation was
not related to the particle size distribution.

Williams et a1 (1978), applied the NIR technique
for protein and moisture testing in pulse breeding programs
to improve both yield and quality of pulses in dry and
tropical areas. Pulses were obtained from different research

institutes throughout the world and were analyzed for protein

content by Kjeldahl and were subsequently analyzed by
NIR.using the Neotec Grain Quality Analyzer, model 31.
They found correlation coefficients from 0.89 to 0.96
between Kjeldahl and NIR determination.

Giangiacomo et a1 (1981), employed the NIR technique
to measure the concentration of fructose, glucose, and
sucrose in model systems. Subsequently, measurements were
made to estimate the same sugars in dried apple tissues.
The correlation coefficients of the actual concentrations
versus the predicted values were 0.995, 0.994 and 0.986
for fructose, gluCose and sucrose, respectively, in the
'model systems comprising 20 samples. But when they tried
to use the prediction equations to estimate the sugars in
the dried apple samples, the corresponding correlation
coefficients were 0.70, 0.55 and 0.90 for fructose, glucose,
and sucrose, respectively.

Izquierdo (1981), using GQA-41, estimated the nitro-
gen content of several dried tissues of been plants (seed,
podwall, leafblade, petiole, stem and root) with correlation
coefficients ranging from 0.873 to 0.973, between Kjeldahl
and NIR.

The accuracy of NIR depends on the successful com-
pletion of the following:

1) Selection of a representative set of samples from the
population.
2) Accurate laboratory analysis of the quality parameters

of interest.

3) Accurate NIR data.
4) Appropriate wavelengths for the whole population.

The following are the chief sources of error in near
infrared reflectance testing:
i) Selection of calibration samples
ii) Accuracy of standard chemical analysis used in
calibration or monitoring.
iii) Homogeneity of ground sample.
iv) Moisture status of the sample.
v) Sample storage.
vi) Uneven or inconsistent loading of cell

Although according to literature reviewed, most work
with NIR instrumentation has been with the estimation of
protein and oil, it would appear that if all the above is
achieved there is a possibility of being able to measure
the starch content accurately and to be able to select
different genotypes for use in the study of inheritance of

starch accumulation in dry beans.

Genotypic Differences in Starch Accumulation and Contribution
of Vegetative Carbon Reserves to Grain Yield.

The possibility of genotypic variation in starch
accumulation in dry beans has been reported by Martinez
et a1 (1975). In their study they found differences in
the amount and type of reserves stored in stems of two navy

bean cultivars. Whereas Nep-2 accumulated moderate to large

10

amounts of starch through the growing season. Seafarer
accumulated little. In their study, the starch status

was estimated qualitatively by the iodine-potassium iodide
(IKI) starch indicator solution. The intensity of the blue
color produced with IKI solution was an indication of
presence or absence of starch as described in the previous
section.

In a later study, starch levels in bean stems and
roots as measured quantitatively (Bousalama, 1977) were
found to correlate with IKI scores with a correlation co-
efficient of 0.85 (df = 18). According to this study, IKI
scores are sufficiently accurate to show relative differences
of the starch content among dry bean cultivars.

In a further study of cultivar differences in starch
accumulation, Adams et a1 (1978) reported that the starch
in roots and stems varied significantly among cultivars of
dry beans. The range extended from undetectable amounts
to abundant starch. Also, starch varied significantly with
stage of development and a decline was noted as seed filling
was completed. Although these researchers found significant
stage by cultivar interactions in both root and stems the
starch scores were high, starting at 502 first flower
through mid-pod filling and declining when seed filling
was completed. This indicates that around mid-pod filling
most cultivars have maximum expression of starch accumula-

tion in the stems and roots. This would seem then to be

11

the right stage for starch analysis in order to detect
differences among genotypes.

In the study of patterns of partitioning and re-
mobilization of non-structural carbohydrates hicommon
bean and other selected grain legumes, Kabonyi (1981)
observed that Redkote, Nep-Z, Swedish Brown and Black
Turtle Soup (BTS) often appeared as the most important
starch storers of the common bean group. Seafarer was
grouped as a low starch storer.

Adams et a1 (1978) found no clear pattern of relation-
ship between starch accumulation in stems and roots and
yield. They suggested that if there was any functional
relationship, this might be expressed in a special environ-
ment such as stress. This suggestion was validated by
studies conducted by Adams et a1 (1980) who studied
cultivar differences in starch accumulation in relation
to their ability to withstand a shading stress. In this
study they found that Nep-2 which stores high levels of
starch in the plant parts yielded more under shading stress
condition during the reproductive phase than Sanilac which
stores relatively little starch. Yields were not signifi-
cantly different under no stress condition. They attributed
the high yield under stress to differential ability to
store starch in plant parts and remobilization of the stored
starch reserves. Nep-2 was able to utilize its starch

reserves for seed filling to compensate for the reduced

12

photosynthesis under stress, while Sanilac with little
reserves did not have much to remobilize, hence a reduc-
tion in yield.

These findings appear to be supported by other
studies of the same nature in corn and rice in which
stored carbohydrates appeared to be able to support the
grain growth of corn and rice at almost normal rate (Duncan
et a1, 1965). In these studies the opinion was offered that
the stored carbohydrates can serve as a buffer to support
normal grain growth despite fluctuations of weather.

Studies on wheat (Judel et al, 1982) have also shown
that the depletion of non-structural carbohydrates at
maturity was of much higher order in the culms and leaves
of shaded plants while these parts in the control plants
still contained a quantity of non-structural carbohydrates
which amounted to about 102 of the grain weight. This indi-
cates that stress conditions increase the contribution of
carbohydrate reserves to grain yield.

There is also evidence which indicates that high
temperature (Spiertz, 1977) or drought stress (Bidinger
et al, 1977 and Gallanger et al, 1976) during the grain
filling stage increases the relative contribution of vege-
tative carbon reserves to grain yield in wheat.

Although cultivars have been shown to vary in the
amounts of carbon reserves stored, changes in the amounts

of carbon reserves have been reported to be affected by

13

changes in seasons. Kabonyi (1981), using IKI - starch
scores, observed genotypic and environmental differences
with seasons in partitioning of non-structural carbohydrates
in dry beans.

Thomas et a1 (1982) studied the seasonal changes in
non-structural carbohydrate levels of wheat and oats grown
in a semiarid environment. They reported that the green-
leaf carbohydrate levels were relatively stable throughout
the growing season and did not fluctuate in response to
seasonal rainfall. Carbohydrates accumulated in the stems
to a maximum of 25 to 482 (of the dry weight) at about
anthesis and declined toward maturity. But, although similar
trends were found in both years of their experiments, stem
carbohydrate concentrations differed. Thus, while the stem
water soluble carbohydrates (WSC) concentration of Pitic
‘stems did not exceed 15% during 1978, in 1979 they reached
352. The percentage of non-structural carbohydrates in
the same wheat variety differed from 30% in 1978 to 50%
in 1979. Thus it appears changes in seasons have a tremen-
dous effect on the concentrations of the carbon reserves.

Reasoning from the findings of Gallagher et a1 (1976)
who presented indirect evidence, based on vegetative dry .
weight losses, that field-grown wheat may derive more
than 502 of the grain yield from pre-anthesis assimilates
if subjected to drought stress, Thomas et a1 (1982) specu-
lated that at least 20% of the yield may arise from

vegatative reserves in semiarid environments during dry

14

years. They came up with a suggestion which is similar

to that already given by Adams et al (1978) in dry beans,
that awh’eat cultivar such as 'Pitic,‘ 'which accumulates

large amounts of stem carbohydrates during the period around
anthesis may have an advantage if subjected to drought
stress during the grain filling stage.

From.the literature reviewed it suggests that culti-
vars with the ability to accumulate high levels of carbon
reserves in the plant parts have an advantage over those
which do not have the ability to accumulate more carbon
reserves, especially when a condition of stress subsequently
ensues. .The incorporation of this character into future
cultivars may improve yield stability. The genotypic vari-
ability in starch accumulation among dry bean cultivars
suggests that it could be possible to select for this
character if it is ascertained that much of the variation

is due to genetic causes.

Genetic Control of Starch Content.

 

Though great differences in the degree of stem starch
content occur among common bean cultivars, hardly any informa-
tion has been published on the genetic control of starch
content of the stems. Most of the genetic studies of starch
accumulation have been done on the seeds and tubers. And
much effort has been devoted to the ratio of amylose to
amylopectin.

Salisbury and Ross (1969) reported that the amylose

content is genetically controlled and some waxy varieties

of cereal grains have only amlepectin in their starch.

The inheritance of waxy grains is controlled by a recessive
gene, and only those homozygous for the gene produce amylose-
free starch. They also reported that in a few other plants
the starch is composed almost completely of amylose (e.g.
wrinkled peas).

Akazawa (1976) reported also that it has long been
recognized that the ratio between amylose and amylopectin
contents in the plant is determined by genetic constitution.
Thus, because of the potential industrial use of amylose,
plant geneticists and breeders have attempted to develop
mutants of higher amylose content. Several high amylose
starches are known, such as those which occur in amylomaize
and in wrinkles peas. In such cases the amylose content
ranges from 50 to 80% (Akazawa, 1976).

At Washington State University, numerous mutants
at the waxy locus in barley have been induced primarily
to: 1) probe a particular locus in barley through inter-
allellic recombination and intragenic mapping, and sub-
sequently biochemical analysis of the mutant proteins,

2) understand pathways of starch synthesis, and 3) pro-
vide variants of starch content (amylose/amylopectin
ratios) for possible livestock nutritive value (Nilan et
a1, 1981). From their findings with starch content,
they reported that UDP-glucose glucosyltransferase has

involved determining the anylose/amylopectin ratio. This

16

emphasizes the genetic control of the starch content.
Preliminary results of these researchers showed that

the 3352 mutants lack detectable amounts of amylose as
determined by amperometric titration. Also, analysis of
'mutants for soluble and bound starch synthetase activity,
suggested that the 3351 mutants have a lower level of
bound starch synthetase activity than the parental line,
'Septoe,‘ used in the study, while having approximately
normal levels of soluble starch synthetase activity.

Work done by Nelson and Tsai (1964) has shown that
maize EEEZ mutants contained about one-tenth the level of
bound starch synthetase activity as compared to normal
maize. Nelson et al (1978) showed that this activity
could be accounted for by the presence of a second bound
starch synthetase having a higher affinity for substrate.

As seen from the literature review on the genetic
control of starch content, it appears that the studies on
the genetics of starch content have been based on the
amylose and amylopectin contents. There is no report
where the authors treat starch accumulation as a trait
without considering its components: and it appears that
amylose content is controlled by a dominant gene and
amylopectin content is recessively controlled. Neverthe-
less, one could speculate that any differences among
cultivars in starch content, no matter what fraction of
starch is the more abundant, would be due to genetic

effects. Moreover, the differences in the tissue studied

17

would not be expected to make any appreciable difference.
Studies thus far performed on seeds, tuber and pollen

grains have led to the same conclusions.

EXPERIMENTAL PROCEDURES

A. Chemical Quantification of Bean Stem Starch:

This experiment was performed as part of a series
of experiments aimed at elucidating information on the
relationship between the IKI starch staining technique
and starch quantification in the laboratory in order to
compare techniques for starch estimation in dry bean stems.

Five dry bean cultivars, Seafarer (determinate),
Redkloud (determinate), Michigan 41228 (indeterminate),
Swedish Brown (determinate) and the breeding line 61356
(indeterminate), were used in this experiment. The culti-
vars differed in starch accumulation capability as esti-
mated in an earlier experiment using IKI as a starch
indicator (Adams, et a1, 1978).

The cultivars were grown in one row plots at
East Lansing Michigan during the summer of 1981 and
two row plots in 1982. In 1981 the rows were 50 cm apart
and plants spaced at 15 cm within rows. Two replications
were used. Because of poor accessibility to the plants
during sampling in 1981, row spacing was increased to 1.0
meter in 1982 to facilitate access to the plants.

The growing point of each plant was removed by pinch-

ing when the growing point was just visible after the

18

19

primary leaves had develoPed. This induced two branches
to form in the axil of the two primary leaves. Starch
accumulation measurements were made on one of the branches
while the other was left for producing seeds. Date of
flowering was recorded for each plant and sampling for
starch storage started 20 days after flowering, on an
individual plant basis. Ten plants were sampled in each
plot.

Sampling involved cutting one branch in the second
internode region of the branch. Leaves and petioles were
removed from the stems and the stems were cut into lengths
sufficiently short to fit into sample bags. The samples
were placed in plastic boxes containing dry ice for
immediate stoppage of respiratory enzymes. The slant
cut ends of the stem samples cut from the second internode
of the stems were scored for starch with the IKI starch
indicator technique in a field laboratory. Two to three
drops of the IKI starch indicator solution, made by dis-
solving 0.3 g iodine and 1.5 potassium iodide in 100 ml.
water, were applied to freshly cut section of the stem
tissue. The amount of starch was rated on a five-point
scale, one (least) to five (most). A color photograph
containing a series of IKI - stained cross sections of
stem tissues evaluated and taken from bean strains with
varying amounts of stored starch were used for scoring.
The remaining sample was placed back in the paper bag and

stored at -3 C° for several days, then dried.

20

The samples were dried in a convection oven at 100 C°
for one hour then at 65 C° for 72 hours. After drying, the
tissue from each sample was ground to pass through a 40-mesh
screen in a standard Wiley mill and stored in sealed bags
for quantitative starch determination in the laboratory.

Before analyzing for starch, soluble sugars were
extracted from.the samples. Five hundred mg of the oven
dry sample was accurately weighed on an analytical balance
and placed in a 50 ml centrifuge tube. Twenty-five ml
of 802 ethyl alcohol were added to each tube and samples
were shaken in a water bath at 75 C° for 40 minutes. After
centrifugation and discarding the supernatant containing
sugars the pellets were dried at 70 C° for 12 hours, weighed
and saved for starch analysis.

Starch content was determined in each sample by
analyzing a 200 mg sample of dried pellet, following the
procedure of Dekker and Richards (1971). A soluble starch
solution was prepared by suspending 200 mg of oven-dried
pellet in five ml of a 0.5 N sodium.hydroxide solution for
one hour. Starch solubilization proceeded by constantly
vortexing the suspension for five times in one hour in a
water bath maintained at 35 C°. After solubilization, the
solution was neutralized by adding five ml of 0.5 N acetic
acid solution. The solubilized starch was hydrolyzed to
glucose using an enzyme mixture made by combining one ml
of amyloglucosidase (obtained from Rhizopus spp mold), 0.2 m1
alpha-amylase (Type II-A), 0.2 ml beta-amylase (Type I-B).

21

The enzymes were obtained from the Sigma Chemical Company,
St. Louis, Missouri. The incubation of the enzymes in
the starch solution was carried out for one hour by shaking
in a water bath maintained at 55 C°. The gluCose in the
hydrolysate was determined quantitatively by a Glucostat
Reagent-Assay KitR (Sigma no. 510) and absorbance read for
each sample using the blank as the reference point at
450 nm. The starch concentration was calculated by
reference to a standard curve (Figure 1) of soluble starch
(B.D.H.). The concentrations of the soluble starch used
for the standard curve ranged from 0.1 mg/ml to five mg/ml
from which the equation Y = -0.052499 + 15.02647X was ob-
tained and used in the conversion of absorbance readings
into mg of starch per m1. In the equation Y = mg/ml
(starch), and X = absorbance reading.

Starch (mg/ml) was converted to percentage weight
of starch contained in the moisture free tissue (70 C°)
by first getting the amount of starch in the total pellet
then expressing this as percentage of the total tissue
used.

Simple correlation coefficient was calculated
between IKI-starch scores and percentage starch as deter-
mined quantitatively in the laboratory for the five

cultivars.

(ms/ml)

STARCH

5'0

22~

r I .9997

Y I "0524991 + 15.026h7x
39 ' .049(ms/ml)/ ABS.

n 8 10

 

Figure 1.

 

0'1 0-2 0.3

ABSORB A NCE

Starch standard curve used for the calculation
of percent stem starch based upon standard
quantification chemical methods.

23.

B. Calibration of the Grain Quality Analyzer for Estimation

of Starch Content in Dry Bean Stems.

The near-infrared light reflectance instrument
used in this study was the Neotec Grain Quality Analyzer
model 41 (GQA-41) which measures the reflectance of a
finely ground sample at selected wavelengths in the near-
infrared spectrum. The reflected energy is detected by
lead sulfide cells sampling the reflected energy levels
from each of the selected different wavelengths. The signal
output is amplified, channeled through a filter synchronizer
and then processed by microcomputer. In the computation
process, an equation is solved, resulting in a presentation
of readings on a digital readout device.

Before a NIR instrument can be used to predict the
composition of a particular sample, the instrument must
be calibrated. The instrument is used to obtain the reflec-
tance readings of samples with known values which have been
accurately analyzed by the traditional chemical methods
from which coefficients are obtained and used for pre-
diction of the composition of the unknown samples.

In this experiment, 40 stem samples, ground to pass
a 40-mesh screen, and selected from the cultivars used in
the first experiment, were used for the instrument calibra-
tion. The samples were dried at 70 C° and enzymatically
hydrolyzed and percentage starch calculated from the

liberated glucose as described in the above experiment.

24

The percentages of starch of the samples used for cali-
bration ranged from.0.90 to 16 percent.

The remnants of the samples used for enzymatic
hydrolysis were loaded into the Neotec GQA sample holder
which uses a spring-loaded pressure plate to hold the
sample smoothly against a clear glass window. Due to the
small amounts of the samples used, a modification of the
inside of the sample cup was necessary so that small
samples could be loaded and readings recorded. The modi-
fication of the sample cup involved reducing the size of
the cup by fitting in a piece of sponge of one cm thick-
ness inside the sample cup and making a cut along 1.5 cm
radius through the sponge. The cup so modified had a
diameter of three cm and one cm depth as compared to the
normal cup with five cm diameter and one cm depth. This
modification reduced the amount of sample to less than half
the amount required to fill the normal cup.

Reflectance readings were recorded as dRiR for each
sample, where dR is the differential coefficient of a line
tangent to the absorption curve peak and R is the absolute
reflectance. A change in constituent amount results in a
'change in dR, hence the mathematical model of dR/R result:
' ing in information relating to change of constituent.

Percentage starch as estimated by wet chemistry of
each sample together with the dR/R values were entered into
the computer,andaamultiple regression routine using the Hal

Stat 4 program was used to compute the multiplying

25

coefficients K0 to K4 which gave the best fit to the follow-
ing equation for the percentage starch.
Z starch = KO + K1 dR/R1 + szR/R2 + K3dR/R3 + K4dR/R4
where K0 is the intercept of the multilinear regression line.

K1, K2, K3 and K4 are the regression coefficients

at four different wavelengths.

dR is the differential coefficient and R is the

absolute reflectance value at a particular wavelength.

The K-values and the pulse points for starch were
stored in the instrument and 35 samples used for cali-
bration were run and percentage starch recorded. A bias
adjustment was required to make the instrument and labora-
tory readings agree. Bias is defined as the average off-
set calculated from.comparison of instrument and laboratory
results. This was done by adding 0.10 to the K0 because
laboratory values tended to be a little higher than that
estimated using the GQA-41.

Simple linear coefficients between laboratory and
GQA-41 percentage starch and standard error of estimate
(SEE) were calculated. Also, correlation between small

size sample and normal size sample was calculated. This

was done only with those samples which had enough material.

26

C. Genetic Studies:

Ten cultivars were used for the genetic studies of
starch accumulation in dry beans. They were selected
based on the differences in starch accumulation as esti-
mated by the IKI starch indicator technique. They included
three low starch storer cultivars, Seafarer, Michigan 41228,
and Brazil-2; seven high starch storers, Nep-Z, Redkloud,
61356, ICA pijao, Swedish Brown, 791515 and 790780. These
parents were crossed between high and low, low and low and
high by high in the greenhouse in the winter and spring
of 1981 by hand pollination. F1 seeds were advanced to
the F2 generation. When possible, characters under monogenic
control were examined to insure that cross pollination had
occurred.

Parents F1 and F2 seeds were planted in the field in
the summer of 1981 at Michigan State University Crop Science
Farm. Parents and Fl's were planted in single row plots.
The F2 populations were planted in two row plots, 12 meters
long. In all of the populations, rows were 50 cm apart
and plants spaced at 15 cm apart within rows. Parents and
Fz's were grown in a randomized complete block design
with two replications. The number of F1 seeds was insuf-
ficient for a replicated experiment.

In the summer of 1982, ten F3 seeds were planted
from each of the 88 F2 individual plants of the cross
Seafarer x 61356, 36 F2 individual plants of the cross

Seafarer x Redkloud and 25 F2 individuals from the cross

27

Michigan 41228 x Swedish Brown selected for F3 family
performance studies. Together with their parents these
families were grown in single row plots. The design was
the same as that of 1981. But because of the problems
encountered in 1981 in sampling, the row spacing was
increased in 1982 to one meter to allow easy accessibility
to plants to be sampled.

Since the analysis of starch in stems involved
cutting the whole plant, and was thus destructive, seeds
from plant analyzed for starch, were advanced to the next
generation. Hence, there was need to have two branches
from the main stem so that one branch could be cut for
starch analysis at 20 days after first flower and the
other branch left to produce seeds. So the growing tips
of plants were pinched as described in section A, above.
A number of plants could not support the weight of
branches and consequently they broke off and remained
only half-intact. Because of this, a number of plants
were not used for taking samples which led to reduced
numbers of samples per population.

Supplemental sprinkler irrigation was applied as
needed throughout the growing season. Foliage diseases,
physiological disorders and insects were controlled by
application of recommended chemicals. Similar field pro-
cedures were followed in 1981 and 1982.

Analysis of starch content was done on the stems of

28

parents, F1, F2 and F3 individual plants at 20 days after
first flower. This, on average, is the time of linear

seed filling which coincides with the high values of

starch content in the plant parts as reported by Isquierdo
(1981). Sampling and estimation of starch in the field

by IKI starch indicator solution were the same as described
in Section A, above. The remnant tissues were dried, ground
to pass 40 mesh-screen and then analyzed for percentage
starch with the Neotec GQA-41 as described in Section B,
above.

Initial selection of parents was based on the esti-
mation of starch by IKI starch indicator solution. But
because IKI starch scores could not correlate highly with
the quantitatively analyzed starch, subsequently some of
the crosses made as being high by low were in actual fact
low by low as shown by the wet chemistry analysis of the
parents. Thus the F3 families of which their F2 individual
values were selected depending on IKI starch scores, were
not included in the analysis because the crosses turned up
to be of the low by low types. The Neotec GQA-41 showed
a correlation of 0.907 (Df = 33) with the starch content
as analyzed by wet chemistry. Hence the Neotec GQA—41‘
was used to analyze the starch content of stem samples.

Frequency distributions of the percentage starch
were computed for all F2 populations together with their
parents and Fl's.

An estimate of the broad sense heritability in F2

29

generation was obtained using the variances among individual
plants of F2 populations, environmental variance being esti-
mated by the variances among individual plants of the non-

segregating populations, the parents and Fl's.

RESULTS AND DISCUSSION

The results and discussion are presented in five
parts: A) relationship between stem starch quantifica-
tion and IKI-starch scores, B) calibration of GQA-41
(Grain Quality Analyzer model 41) for the estimation of
starch content in dry bean stems, C) variation among
parents in stem starch accumulation, D) evaluation of non-
segregating and segregating populations and E) heritability
estimates of the selected crosses for stem starch accumula-

tion.-

A) Relationship between Stem Starch Quantification and

 

IKI-Starch Scores in Dry Bean Cultivars:

 

This experiment was performed to ascertain whether
IKI-starch scores were sufficiently accurate in estimating
quantities of stem starch in dry bean cultivars. Figure 2
shows the relationship between the stem starch quantifica-
tion and IKI-starch scores at 20 days after first flower.
As seen from figure 2 the two methods are not significantly
correlated. The lack of high correlation between the two
methods stems from.the fact that: one IKI starch score
is represented by several percentage stem starch values as
estimated by the wet chemistry method. This implies that
IKI starch scores do not accurately indicate starch concen-

tration in this experiment.

30

«It‘d» IUln‘thn

 

(I. AB)

1 ST ARCH

  

  

20-0

15-0

104)

Figure 2:

31

Y 8 5.392163 + .520066X
8:2 I 3.89 fiStarch
:- I 0.18 (df I 28) ns.

 

lKl STARCH. SCORES

Relationship betweenIKI starch scores and
percent starch as determined quantitatively

at 20 days after first flower in the stems of
dry bean cultivars.

32

Table 1 shows the percentage stem starch as quanti-
tatively determined and IKI starch scores for 1981 and 1982
seasons for the five dry bean cultivars used in this study.
The percentage stem starch in 1981 was relatively higher as
compared to that of 1982 season. However, although differences
among cultivars in the 1982 season were nonsignificant, the
relative difference among the five cultivars remained the
same in the two years ( r = 0.927). IKI starch scores were
also lower in the 1982 season as compared to that of 1981.
Again, as with percentage stem starch, the relative differences
among cultivars for stem starch estimated using IKI starch
score remained the same in both years. Variation between
seasons was not surprising since carbohydrate partitioning
has been found to be affected by differences in seasons
(Kabonyi, 1981: Thomas et a1, 1982). Another aspect which
might have contributed to low percentage stem starch values
in the 1982 experiment could be due to sampling technique
difference. In the 1982 experiment, due to the bulkness
of the samples, samples could not immediately be placed
into boxes containing dry ice to stop respiratory enzymes.
The samples were taken to the cold room in the Crop Science
Field Laboratory on an hourly basis and it took on average
five hours before the samples were frozen. Hence, there
is a possibility that the respiratory enzymes continued to
degrade starch into sugars before the samples were frozen.

The percentage stem starch obtained for the variety

Michigan 41228 (15.05%) in the 1981 season was not expected

33

Table 1. Stem Percentage starch as quantitatively determined
and the respective IKI starch scores of five dry
bean cultivars.

 

 

1981 1982
Cultivar Quantitatively IKI Quantitatively IKI
Determined Rating Determined Rating
(Z) (Z)

Seafarer 6.26 2.50 4.50 2.00
Redkloud 7.91 4.20 4.47 3.00
Michigan 41228 15.08 2.33 6.98 1.33
Swedish Brown 11.63 4.83 4.99 3.33
61356 4.20 4.00 3.95 3.33
LSD (.05) 5.34 0.22 ns 0.63

 

34

to be this high. This variety had the lowest value with
the IKI starch indicator solution in both years of study
and also it had a low IKI starch score in a previous study
(Adams et a1, 1978). However, Michigan 41228 had the highest
percentage stem starch with the wet chemistry method in
this study (Table 1). One might be led to speculate that
since the IKI starch indicator solution is only sensitive
to amylose, perhaps this variety (Michigan 41228) has stem
starch content in appreciable amounts of amylopectin which
is only weakly detected by IKI starch indicator solution.
However, the highly variable response of this cultivar
to IKI starch scores and laboratory starch analysis requires
further investigation.

According to the results of this experiment, IKI
starch scores could not be used for the estimation of
starch content of the stems at 20 days after flowering for
the inheritance studies of differential starch accumulation
in stems of dry bean cultivars. A quantitative method
easier and more rapid than laboratory chemical analysis
had to be employed. The results of a search for this method

are presented in the following section.

35

B) Calibration of Grain Quality Analyzer (GQA) for Starch

Concentration Estimation in Dry Bean Stems:

Infrared reflectance spectroscopy [Neotec Grain
Quality Analyzer (GQA-41)] was explored to see whether it
could be used to estimate stem starch levels in dry bean
cultivars. The instrument was calibrated by running
a multiple regression analysis, using Hal Stat 4 program,
of the wet chemistry laboratory values and the first deriva-
tive of the reflectance values (dR) from the calibration
samples read at four different pulse point settings.

The pulse points used were provided by the Neotec Company
obtained from starch absorption bands. Starch has a peak
at 2.10 um and Rotolo (1979) has pointed out that this
peak which is provided by filter 4 can be used to determine
the starch content of samples. The four pulse points pro-
vided by the company were 603 (P1), 639 (P2), 926 (P3)

and 970 (P4). Product button 4 was used for the instru-
ment calibration. Product button 4 is used for starch
detection (Rotolo, 1979) and readings were recorded at the
manual setting. The multiple regression analysis provided
a set of K-values to be entered into the GQA-41 for

the prediction of starch content of the bean stem samples.
The K-values obtained for K0 through K4 were 7.082,
-1002.939, -3355.376, —184.759 and -5225.007, respectively,

with a coefficient of determination of .7313. These K-values

36

were entered into the GQA, then the remnant samples used
for calibration were read on the GQA as unknowns for veri-
fication of calibration. The GQA readings of the 35
calibration samples corresponded closely to the laboratory
analyzed values with a coefficient of linear correlation
of 0.907 and a standard error computed as variation from
the regression line of 1.42% starch.

The modification of the sample cup to accommodate
small sample size did not affect the GQA readings. There
was a very close relationship between the GQA readings
using the normal sample cup size and the modified sample
cup (r = .986). This indicated that the modified sample
cup was sufficiently adequate to hold the samples for the
estimation of starch content in the dry bean stems. These
findings agree with those of Hymowitz et a1 (1974) who found
no difference in percentage protein or oil in the meals
between normal sample cup and the cup fitted with a false
bottom which reduced by half the meal required to fill the
cup.

Based on the data presented here, the GQA was used
for the prediction of starch levels in dry bean stems for
the selection of parents to be used in the study of inheri-
tance of differential starch accumulation hidry bean stems.
Although these findings were for stems, the applicability
of GQA to other tissues will be straight forward provided
appropriate samples are available for development of cali-

bration curves.

37

C) Variation Among Parents

Significant differences for percentage stem starch
at 20 days after first flower as estimated by the GQA-41
were observed among the ten parents evaluated in the 1981
growing season (Table 2). Michigan 41228 with 11.61% stem
starch ranked the highest and 791515 with 7.07% stem starch
ranked the lowest. This suggests that at 20 days after
first flower cultivars could show differences in ability
to store starch, hence evaluation of segregating populations
for their ability to store starch in stems at 20 days after
first flower will render it possible to observe differences
between individuals.

From these results parents were ranked as either high
or low starch storers. Parents with percentage stem.starch
above 10% were ranked as high and those with percentage
stem starch below 9% were ranked as low starch storers.
Hence Michigan 41228 (11.61%), ICIA Pijao (11.47%), Swedish
Brown (10.82%) and Brazil-2 (10.40%) were ranked as high
starch storers while 61356 (8.56%), Redkloud (8.45%) and
Seafarer (7.47%) were ranked as low starch storers and
Nep-2 (9.28%) was in the medium range. Therefore crosses of
high x high, low x high, and low x low between those parents
were studied for the inheritance of differential stem
starch accumulation ability and the results are discussed

below.

38

Table 2. ‘Mean, ranges, standard deviation and coefficients
of variation of percentage stem starch content
20 days after first flower of the ten dry bean
cultivars grown in 1981.

 

Cultivar Mean Range N s I C.V.

 

Michigan 41228 11.61 8.81-13.86 8 1.91 16.50
ICIA Pijao 11.47 9.31-13.18 13 1.40 12.20
Swedish Brown 10.82 7.98-13.89 15 2.02 18.67
Brazil-2 10.47 7.22-14.33 12 1.79 17.10
790780 10.33 6.95-13.92 13 1.96 18.97
Nap-2 9.28 4 69-11.70 12 1.98 21.33
61356 8.56 4.80-11.37 16 2.12 24.76
Redkloud 8.45 6.71-10.68 13 1.06 12.54
Seafarer 7.47 6.40-9.17 9 0.89 11.91
791515 7.07 4.01-9.18 12 1.81 25.60
LSD (.05) 1.18

 

39

D) Evaluation of Segregating and Non-segregating Populations

for Percentage Stem.Starch of Dry Bean Crosses

 

Low x High Crosses:

 

Table 3 shows the frequency distributions for percent-
age stem starch in parents F1 and F2 generations for the
cross between Redkloud (low parent) and Michigan 41228 (high
parent). The mean of the F1 was between the parental values
but tending towards the parent with high starch content
indicating possible expression of dominant genes for high
starch content.

Despite the very few individuals available for
analysis in this cross, F2 variations was continuous and
extended beyond the ranges of parents indicating transgressive
segregation had occurred. Starch values of about 66% of
the F2 individuals approached the parent with high percentage
stem starch, which agreed with the F1 analysis and suggested
that dominance was involved in trait expression. The cross
between Seafarer (low) and ICIA Pijao (high) had a similar
distribution (Table 4). This may indicate that the low and
high starch storer parents used in these crosses of low
x high have similar allelic content for the expression of
stem starch storage. This can also be supported by the
results of a cross between ICA Pijao (high) and Seafarer
(low) which is a reciprocal cross in terms of high and
low parents. This also had a similar distribution (Table 5)
as low x high crosses. Therefore, there appear to be no

reciprocal effects.

40

amch w. mnmacoaow
mHOSmH H:

cumnHHVCnHOSm mom mama monomsnmmm manna: nonnmSn No cmxm mmnmn MHNmn
mmnmdnm. mH use m» omamnmnwoau w: m OHOmm umnzmms wmQWHocm use Sworwmm:

 

 

HHNNm.
onmm emanmNm Ha N mnmnou

omseemneose m.e m.e 8.8 m.o 6.8 Ho.e He.e H~.o eu.m He.m s x mm
wmarHoca H u u H H Hw m.bu H.Hw
Abosv
Sworwmma bHNNm H H H H N N m HH.mo w.oo
Amwmrv
NH H H H N H o Ho.N¢ b.~¢
mN H H u N m N u N w No Ho.uo ¢.Nw
ZeauwmnmSn Ho.o~

 

41

HmuHm b. wflmncmdow cwmnnwocnwoSm mou mama mmHannmmm mnmnn: 005nm3n No Umwm mmnmn.wwfimn
mHosmH H3 mmHmSHm. mH mam mN omdmnmnwonm U m OHOmm omnzmmn mommmumfi mam Ho>

wwumo.

onmm omnnmnm H: N mnmno:

 

nonmnmnwoam #.m. m.¢ ¢.m u.m m.o ©.m D M mm

mmmmmeme w e N H e e.ee o.me

Abosv

Hn>.weumo u Hm HH.bu H.0m

Amwmwv

mH H H m Ho.Hm N.p~

m» H N m m Ho Ho mo o.wo b.wp
m.eu

.zHaumeman

42

Hmch m. mfimncm50% UHmnnwuanOSm mou mnma_pmHomunmmm mnmfinr nonnmdn No Umwm >mnmd mHHmn
wHozmH H5 memanm mam aw omSmHmnHodw w: m OHOmm umnSmmD Ho> wwgmo mad mommmnofl.

nHmmm nonnoflm Ha wmnnmdnmmm mnmun:

 

 

88888888688 8.8 8.8 8.8 8.8 8.8 88.8 88.8 88.8 88.8 s x m8
88> 88886 8 8 8 8 8 88 88.88 8.88
Amwmrv

mommmumn u w m H o 8.88 o.mo
3.9.88 .

88 8 8 8 8 88 8 8 8 8 88 8.88 8.88

zHQummHmsn 0.88

 

43

amuHm a. muoncm50< cwmnnwucnwosm mon mnma wannmSnmmm manner nounmsn no Guam mmnmn arm MHNmn mHozmn

H: mundane. mH man u» mmnmnmnwoam H3 m oNOmm cmntmms meNHHnN mam wmarHoca.

onmm omanmnm H: N mnmno:

 

 

anamnmnHosm H.m N.a u.m a.¢ m.m a.o 8.m m.a e.o Ho.a HH.¢ HN.¢ Hu.m H>.m 3 N mN
wnmNHHuN H H a H a HH Ho.88 w.~c
Amwmrv

8888.888 8 8 . 8 8 8 88 8.88 8.88
Arozv

mH N H H H a N H HN Ho.mb m.bo
mm H H H a w 8 b m m o H N mo o.mm m.H¢
zHaummHmsn c.8u

 

44

In the cross between Brazil-2 (high) and Redkloud
(low), the F1 mean value was slightly but not significantly
higher than the high parent (Table 6). There may be
therefore some degree of heterosis expressed in the F1
of this cross. This was also observed in the growth of
the F1 plants of this cross. By visual observations, the
plants in this cross showed a high vigor in growth and had
very large leaves as compared to their parents. So the
heterosis in stem starch content could be a reflection of
high leaf area which would imply a higher source of photo-

synthates for transformation into starch.

High x High Cross:

 

The cross involving parents which were both high in
percentage stem.starch was that between Michigan 41228
and Swedish Brown. The difference between the cultivars in
percentage stem starch was not significant. The F2 was
variable (Table 7). One thing observed in this cross was
that, whereas the crosses of low x high or high x low
parents indicated the F1 and F2 values tending towards the
parent with high percentage stem starch, the situation in
this cross was rather quite different. About 73% of the
F2 individuals had starch values tending towards low values.
Since the cross does not involve a low parent, the varia-
tion observed would suggest that the parents used were genet-
ically different. That is, they do not have the same allelic

content for starch accumulation expression and this might have

45

HmuHm 8. MHmQCmdnw uHmnnwuanodm mow mnma monomSnmmm mnmfior nonnmdn No Umwm mmnmd mHHmn mHosmH

H5 memSHm mam wN GmSmnmnwonm Ms m OHOmm umnSmms Sworwmms bHNNm mam mamawmr wHozs.

OHmmm nmsnmnm H5 N mnmunr

 

88864888688 8.8 8.8 8.8 8.8 8.8 8.8 8.8 8.8 88.8 88.8 88.8 88.8 8 a 88

38688888 88888 8 8 8 8 8 8 8 88.88 8.88

Amwmwv

mSmaHmr wHozd H N u u H N w Hm Ho.mN b.om

Amwmrv

88 8 8 8 8 8 8 8 8 8 8 8 8 88 8.88 8.88
88.88

ZHQumemdn

 

46

led to combinations that gave values in F2 generation which
were beyond either parent. In other words, this indicates
a probable transgressive segregation towards low values

of percentage stem starch.

Low x Low Cross:

 

Table 8 shows the frequency distributions for the
percentage stem starch in the parents and F2 generations
of the cross of low x low type between Seafarer and 61356.
In this cross the F2 generation was less variable. In fact,
it was even less variable than one of the parents. The low
variability observed in this cross may not be strange be-
cause not much variability is expected from such a cross
especially if the two parents have the same genes for the
expression of stem starch accumulation ability. A closer
look at the distribution of the F2 reveals observations
which are rather intriguing. The mean of the F2 generation
is well below that of either parent, an observation not
expected. The possibility of parents differing genetically
for genes controlling starch accumulation should not be

ruled out.

Summary of the Three Types of Crosses:

Starch accumulation is a complex character and it
appears to be inherited in a quantitative manner. The
recovery of both the parental types within the size of
the F2 populations studied, as well as the range of F2

segregates beyond both the parental ranges in Redkloud (low)

'47

amva m. mnmacmsow uwmnueuanoSm mow mama wmnomsnmmm mnmdor nonnmSn No swam mmnmu mwnmn
.mHOSmH H: wmnmsnm mad m omdmumnwonm H5 m nHOmm unnamo: mmmmmdmn mum onmm.

N

nHmmm omnnmnm H5 N mnmflnr

 

88888888688 8.8 8.8 8.8 8.8 8.8 8.8 8.8 8.8 8.8 8.8 88.8 88.8 8 a m8

mmmmmHmH u o 8.mN o.mo

Arosv

88888 8 8 8 8 8 88 8.88 8.88

Afiosv

88 8 88 88 88 88 88 88 888 8.88 8.88
8.88

SwaimemSH

 

48

x Michigan 41228 (high) and Brazil-2 (high) x Redkloud (low)
indicated that these parents had manh genes in common. How-
ever, it appeared probable that some parent combinations
differed in some genes conditioning stem starch accumulation.
Thus, plus and minus gene effects conditioning stem starch
accumulation in different parents permitted a complementary
type of gene action in the F2 segregates. This explains the
indicated transgressive segregation observed in the F2 of
the low x high and high x low crosses. In contrast, the
transgressive segregation observed in crosses of the low x
low and high x high cannot be explained by complementary
tyep of gene action alone: since most of the segregates
tended to be towafds the low side of starch values it

could probably be due to other genic interactions.

Midparents Values:

 

Midparent values when compared to their respective
F2 values may in general indicate the type of gene action
prevailing for the character of interest. Comparison between
parental, midparent and F2 values of percentage stem starch
in the five dry bean crosses is presented in Table 9. In
general crosses involving parents with low and high propor-
tion of percentage stem starch produced F2 populations with
the mean values which were not significantly different from
their respective midparent values. This would suggest a
preponderance of additive gene action. However, this was not

clearly evident for crosses involving high by high and low

'\

49

 

 

 

 

Table 9. Comparison between Parental (P1, P2) Midparent (MP)
and F2 Values for the Dry Bean Stem Starch Content 20
Days after First Flower in five Dry Bean Crosses.
Z starch
Cross P1 P2 MP F2
Brazil-Z/
Redkloud 10.46 8.43 9.45 9.66
Redkloud]
Mich 41228 8.43 11.60 10.02 10.76
Seafarer/
ICA Pijao 7.52 11.48 9.50 9.29
Mich 41228/
Swedish Brown 11.60 10.78 10.89 7.43*'
Seafarer/61356 7.52 8.56 8.04 4.35*

 

*F2 values significantly different from their respective MP

values at the .05 probability level.

50

by low parents. In these types of crosses the F2 values
-were significantly different from.their respective midparent
values. In both type of crosses the F2 values were towards
the low starch values. This indicates a negative departure
from.midparent value which may be due to genic interaction.
Hence, as discussed above, this indicates some parent
combinations in this study do not have the same allelic con-

tent for genes conditioning stem starch accumulation.

E) Heritability Estimates:

 

Effective selection of desired genotypes when condi-
tioned by quantitative inheritance usually is difficult in
segregating generations if the heritability is low. Hence,
it may become desirable to determine genotypic variance in a
segregating population in order to estimate the magnitude
of the heritable fraction.

In this study, heritability of percentage stem starch
is used in the broad sense and indicates the extent to which
expression of the percentage stem starch is under genic
control. The heritability for percentage stem.starch was
calculated as the percent genotypic variance of the total
F2 variance. Table 10 shows the heritability estimates for
percentage stem starch for one high by low and two low by
high crosses. In all three crosses the heritability estimates
proved to lie in the intermediate range. The values ranged
from.51 to 60%. These heritability values indicated that

some of the differences observed in the dry bean genotypes

51

for stem.starch accumulation levels were due to genetic
influence. Plant breeders should have no great difficulty
in recognizing genetic differences among parental stocks.
However, more information is needed on the extent to which
the genetic differences observed can be used for selection
purposes. That is, heritability in the narrow sense must

be determined. This can be calculated from the regression
of F3 values into F2 values in which the heritability is
largely due to additive genetic effects transmitted from
parent to progeny such as F2 - F3. It was not possible in
the present study to get information concerning narrow sense
heritability of percentage stem starch from the regression
of F3 family values into respective F2 values due to mis-
classification of parents selected for that study by the use

of IKI solution as a starch indicator.

52

Table 10. Broad Sense Heritability (BSH) estimates for stem
starch content for the F2 progeny of three dry
bean crosses.

 

 

Cross Heritability (BSH)
Brazil-2 x Redkloud .60
Redkloud x Michigan 41228 .51

Seafarer x ICA Pijao .60

 

GENERAL DISCUSSION

As far as techniques for estimation of starch content
in dry bean stem are concerned, it appeared that the IKI
solution as starch indicator cannot estimate starch levels
efficiently. Since IKI apparently is sensitive to only one
component of starch - the amylose, the status of starch
quality in beans needs to be pursued so that efficient
techniques for estimation of starch content can be employed.
Use of the near infrared reflectance spectroscopy utilizing
Grain Quality Analyzer (GQA-41) appeared to be efficient in
estimating starch content, at least as compared to the IKI
starch score system, but it lacked the rapidity of the
IKI starch score system.

From the inheritance studies of stem starch accumulation
it was found that frequency distributions for all the segre-
gating generations were continuous and serve to indicate that
quantitative inheritance is important in determining differ-
ences in starch accumulation levels in the stems of dry
bean cultivars at least for the populations studied. Trans-
gressive segregation was indicated in both directions of low
and high starch values. It is concluded that the parents
probably differed in relatively few genes, with sufficient
plus and minus gene effects present to account for trans-

gressive segregation on all the three types of crosses

53

54

since all parental ranges and beyond were recovered in F2
populations. _

Although major genes were not detected, the moderately
_ high broad sense heritability values obtained indicated that
‘at least the stem starch content is genetically controlled,
and more information is required on how much of this heri-
tability can be used to identify desirable lines in a culti-
var development program. The low x high and high x low
crosses indicated that a substantial fractional variability
of stem starch accumulation was additive in nature. Although
results of crosses between low x low and high x high were
rather intriguing, the nature of inheritance of stem starch
accumulation as revealed in the current study suggests the
use of recurrent selection as means of concentrating favor-
able alleles in a breeding pOpulation.

As noted in a previous section, the study of starch
accumulation is a rather complex subject. The accumulation
of stem carbohydrates as a whole results from a phase differ-
ence between the ability of the plant to produce carbohydrate
and the requirement for it (assimilate sinks). Thus, al-
though cultivars have been reported to show differential
starch accumulation in stems and roots, some of these differ-
ences, in addition to genetic reasons, could be due to
differences in the sink size. That is, if a cultivar has more
pods much of the starch or stem carbohydrates will be reallo-
cated to seedfilling. On the other hand, presence of fewer pods

(small sink size), will mean much of the stem carbohydrates

55

will remain unallocated. Hence, accumulation in this case
will be due to slower removal of photosynthate from the
production or storage sites by translocation. WOrse still,
these differences can occur within a plant depending on what
section of a plant is sampled. waterseuzal, (1980) reported
a decline in concentration of starch in the middle and
upper sections of bean stems where most of the pods concen-
trated, whereas the concentration was raised in the lower
sections of stems with few pods as pod fill proceeded. This
emphasizes the consistency of the section of the plant that
is sampled for study.

On the contrary, some varieties may not divert their
nonstructural carbohydrate in storage to the reproductive
organs because their leaf photosynthetic rate increases to
match or else to exceed seed sink demand. Peet et a1, (1977)
showed that the leaf photosynthetic rates increased by 132,
408, 873 and 21 percent, from flowering to early pod set
respectively, for Redkote, Redkloud, Swedish Brown, and
Black Turtle Soup. So most of the NSC in storage for these
cultivars might be of use under stress conditions. In fact,
Kabonyi (1981) indicated that Black Turtle Soup appeared
to be the best remobilizer of NSC in a stress situation.

Beevers (1969) discussed the biosynthesis of starch.
There is indication that when provided as uridine diphosphate-
glucose or adenosine diphosphate-glucose units of glucose
are added to pre-existing starch or smaller molecules by

starch synthetases. Starch may also be synthesized directly

.56

from sucrose. Some cultivars may not store NSC in the
form of starch, they may store it in the form of sucrose
or other NSC polysaccharides. The fact that this study
has singled starch accumulation does not mean that other
constituents of NSC are not important. ‘In actual fact,
any form of NSC which would be the abundant carbohydrate
reserve in any cultivar at any stage in the plant's onto-
genetic development might serve as the source of the
carbohydrate to be translocated to needy sinks, either
under stress or normal growth when sink demand exceeds

current photosynthate production.

APPENDIX

57
APPENDIX

Table 1. Multiple linear regression analysis for K—values for
calibration of the neotec Grain Quality Analyzer-
(model 41) using Hal Stat 4 program.

ITLE BEEN STRRCH
LESUILD)FREEJNU.5)DRTIN'SGQR
=R.BS.C:D.BERN STRRCH

FIRST CREE

a - as c .0 BB%ISWRC
1 2 , 3 4 s
-.882458 -.ee4988 .012140 .883310 3.298888

8 t * 09TH INPUT TERMINRTED B? END-OF-DRTR CHRD
NUMEER OF CHEES REED 43 DROPPED 3 END RETRINED 43

SEEN ETHRCH
EIHELE PRECISION FILE OF 43 CRSES END 5 URRS. CRERTED ON DZF/M12f32

NON-

SUM OF MISSING

U99 MINIMUM HHXINUM HEHN SQUHRES ELEMENTS

33 2 -.33? “.333 -.335 .331 43

C 3 .339 .318 .314 .333 43

D 4 .332 .334 .333 .333 43

558% STEEC 5 .393 15.443 5.639 2313.925 43

SEEN STRECH
SINELE PRECISION FILE 0F 43 CRSES END 5 USPS. CRERTED OH DZT/N12f33
IST CRSE RETHINED
R 83 C D BERN STRRC
“.332453 ‘.334933 .312143 .333313 3.293333

HgHEEP OF CRSES REED 43 DROPPED 3 END RETRINED 43

T H B L E H - - STRTISTICS ON TRHNSFORMED URRIRBLES
SUM OF SQURRED
STRNDHRO SUM OF DEUIRTIONS
“R? DEUIHTIOHS SUM SOURRES FROM THE MEHN
1 .3316?3 -.3754 .3302 .3331
2 .0313?2 -.2312 .3313 .3333
3 .332463 .5353 .3382 .3333
4 .333649 .1349 .3334 .3333
3 3.923936 242.4733 2313.9245 646.6756

SIMPLE CORRELHTIONS

UHF: HO .

58

 

 

Appendix Table.1' (Continued)
3?
a 1 1.88888
35 2 .51793 1.88888
8 5 .1282 -.78832 1.88888
8 4 -.333.6 -.42651 -.14842 1.88888
esnw STHRC 5 -.19474 -.63?28 .59688 —.18159 1.88888
1 2 3 4 5
8 as c o BERN STHRC
BERN STRRCH
8885LE Peso MRTRIX FOR 45 cases END 5 URRS. CRERTED 0H 027/M12/82
L3

2 837212 FOR 45 88555 RND 5 URRS. CRERTED on 027/M12"32

SIMPLE CORRELHTIONS OF 3(1) MITH HLL OTHER URRIRBLES.

(THESE URLUES NH? 8E FOUND IN THE XCI)

ROU RND COLUMN OF THE INPUT MRTRIX.)

H as c D BERN STRRC
1 2 5 4 5
1.888888 .517934 .1212? W35 51 -.194?43

PENDENT UHRIRBL E--N(5) BERN STHRC
ROU FOR OUERHLL REGRES SION

sum OF DEG 0F mean
SOUHPES FREEDOM SQURRE F SIG
9529555 CH 4?2.3913 4 118.2228 25.3583 '8.8885
“REJUT ”ERW‘
5=92= 125.73428522 52 .5755
'FiiUT mean.
TD'H- 542.278641?c 42
:5353 IULTIPLE CORP 885 F5 STRHDRPD ERROR
R2 . R ERR 2 R 888 OF ESTIMHTE
45 .2515 .3551 .785 8 .3584 2.1555288
PEGPEEEIOH ‘ STD. ERRORS BETH STD ERRORS
88: COEFFICIENTS OF COEFFICIENTS wEIGHTs 0F BETHE
8 ?.8321332? 3.2663879! 8.88888 8.88888
1 ~1882.9:9828?2 453.?4661891 -.42686 .19525
2 -5555.52&: 5:5 82?.1445 8941 -.91523 .2258:
: 24..5°2:::’:E~ 310. 29512 C- -o11619.13‘e14
4 —5225 .88745255 958.: ?2?932? -.3é4:1 1=2=*

I-J

.Appumndia:

Table 1.

59

(Continued)

 

 

consrawt

83
C
D

L!

9

5(4fJMQ

2.1679
-bolsss
-4.0566

-0 5954
-5.6160

TB

RN 52909 110 ON LFN 00TH
FILE IS NOT OPEN.

.G
R... S

08.HDDRESSB

BERN STRRCH

SINGLE PRECISION FILE 0F

m

22735

4. 699.,
4.7797
16.4553 (0.0005
.555 -
31.5399 (0.0005 -

43 CHSES HHD

SIG one? COEFS

.036 '
.035 -
-.5497

5 URRS.

R E S I D U R L S

BERN STHRC

H I79 '0 0) '4 '3‘ 0| 1‘4 H In) H

yo“

V 8 3(5)

3.2988888
5.2288888
18.2888888
9.2388888
8.6?88888
5.8288888
16.4488888
15.8688888
13.?388888
2.8688888
13.1288888
8.9888888
4.6888888
3.9188888
4.8288888
4.4488888
2.8488888
6.2388888
4.6588888
4.4888888
4.3588888
8.6188888
8.2388888
4.5188888
6.2888888
3.5888888
4.6888888
3.9688888
2.?888888
2.4988888
1.1888888
.7988888
3.3288888
2.2888888
2.8888888
4.9988888
1.8688888
2.3888888
1.1488888
3.9688888

ESTIMRTED V

6.4429739
6.9142518
11.0527812
9.2515501
9.6330161
7.3959583
12.7271453
11.1553600
10.9619794
9.1366152
10.9291641
9.8321335
.0363533
066370
539412
. 326937
’. 121439
.5706205
.642538
5560796
‘- 4?:05'52
.2611323
.4931410
1.9059187
3.3270573
.2.4471251
2.4420625
.986822?
-.9745239
3.3603502

7 a»? '1
H. 2‘dU2°"

2.0224663
3. 385724
5.4175214
2.683172
2.8970701
.74‘4357
3660

‘l H 0‘ '4 m RD
J 560 '0

It.

”I

3'

(050113013313

‘7 7"
u o 9.“.

.3318
.3343

.0961
.6735

VDELETES
.6988

.6975
.6149
.7288
.5032

CRERTED 0N 027/M12/32

V - ESTIMRTED V

-3.1529739
-1.6942518
-.??2?812
-.8215581
-.9638161
-1.5T59583
3.?128547
3.9841488
2.?688286
3.7233848
2.1988359
-.1321835
—4.4863533

-3.3339412

-1.9926937
-.8688394
-1.1321489
-.9286285
-..642538
-2.286£T86
3.7682649
1.7569343
.2438177
-1.7131418
1.5948813
’5‘9427

. ‘35"

.5 23749
.2579375

1.5039773

2.0745299

2.4296499
.0916737

0:9”r?9 ‘5
C Onqu ‘Ih"-‘a.

-1.1335724
-.4275214
-.3231720

-.5970701

“375643-

0"-

o é'21.3:4"3

Page 3

Appendix Table 1.

4x
42

43

fLMEER 0F CRSES REHD

SUN V
242.47000000

sscv‘e
2013.92450888

P889. 0F URRIRTION
EPPLHINED EV COEFS
.73126511
EH8 STRT
PERCY 15.33.82
CRTALOG.E’88.38F38.
88*8L88.5588.JOE38.

FEED? 15.34.01

60

(Continued)

1.1700000
3.2700000
'.3900000

43 DROPPED

SS<V - MESH V)
646.67564136

DURBIN MRTSON
STHTISTIC

.87165575

3.1067735
3.3553736
.9528546

0 END RETRINED 43

SUN RES
.00000000

55 RES
173.78430572

SUM OF SQURRES
(RES - PPEU RES)
151.48003900

-1.9367735
-.5853736
-.0623546

LITERATURE CITED

LITERATURE CITED

Adams, M. W.; J. W. Wiersman and J. Salazar. 1978. Differ-

ences in starch accumulation among dry bean cultivars.
Crop Sci. 18: 155-157.

Reicosky, D.: Garcia, S. and Izquierdo, J. A. Q. 1981.
Differential starch storage in two bean varieties in

relation to their ability to withstand a shading stress.
Bean Improvement Cooperative. 24: 39-41.

Akazawa, T. 1976. Polysaccharides: In Plant Biochemistry.
Ed. by James Bonner and Joseph E. Varner. Third Ed.

Beevers, H. 1969. Metabolic Sinks. pp. 169-180. In J. D.
Eastin, F. A. Haskins, C. Y. Sullivan and C. H. M.
Van Bavel (ed.) Physiological Aspects of Crop Yield.

Bousalama, M. 1977. Accumulation and partitioning of
carbohydrates in two cultivars of navy beans (Phaseolus
vulgaris L.) as influenced by grafting and source-sink
manipulation. M.S. Thesis, Dept. of Crop and Soil
Sciences, Michigan State University.

 

Bidinger, F.; R. B. Musgrave and R. A. Fischer 1977. Contri-
bution of stored pre-enthesis assimilate to grain
yield in wheat and barley. Nature 270: 431-433.

Dekker, R. F. H. and G. N. Richards. 1971. Determination of

starchixlplant material. J. Sci. Food Agric. 22:
441-444.

Duncan, W. G.; A. L. Hatfied, and J. L. Ragland. 1965. The
growth and yield of Corn. 11. Daily growth of corn
kernels.. Agron. J. 57: 221-223.

Gaines, T. P. 1971. Chemical methods of tobacco plant
analysis. University of Georgia. Res. Report
No. 97, Tifton GA.

Giangiacomo, R.; J. B. Magee: G. S. Birth and G. G. Dully.
1981. Predicting concentrations of individual sugars

in dry mixtures by near infrared reflectance spectro-
scopy. J. Food Sci. 46:531.

61

62

Gallanger, J. N.: P. V. Biscoe and B. Hunter. 1976. Effects
of drought on grain growth. Nature. 264: 541-542.

Izquierdo, J. A. Q. 1981. The effect of accumulation and
remobilization of C-assimilate and nitrogen on
abscission, seed development and yield of common
bean (Phaseolus Vul aris L.) with different archi-
tectural forms. PE.D. Dissertation, Dept. of Crop
and Soil Sciences, Michigan State University.

Hymowitz, T., J. W. Dudley, F. I. Collins and C. M. Brown.
1974. Estimation of protein and oil concentrations
in corn,soybean and oat seed by NIR. Crap Sci.

14: 713.

Judel, G. K. and K. Mangel. 1982. Effects of shading on
nonstructural carbohydrates and their turnover in
culms and leaves during the grain filling period of
spring wheat. Crop Sci. 22: 958-962.

Kabonyi, S. 1981. Patterns of partitioning and remobilization
of non-structural carbohydrates in common bean and
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