GENETIC DIVERGENCE AND STUDIES ON BIOACTIVE COMPOUNDS IN CHICKPEA

SUBMITTED TO:-
Dr. T. SRINIVAS
PROFESSOR & HEAD
Dept. Of GENETICS &
PLANT BREEDING
AGRICULTURAL COLLEGE
BAPATLA
SUBMITTED BY:-
T.HARISH VIKRAM
BAM/2020-16
I M.Sc(Ag.)
Dept. Of GENETICS &
PLANT BREEDING
ACHARYA N.G. RANGA AGRICULTURAL UNIVERSITY
AGRICULTURAL COLLEGE BAPATLA
TOPIC:- GENETIC DIVERGENCE AND STUDIES ON BIOACTIVE COMPOUNDS
IN CHICKPEA (Cicer arietinum L.)
COURSE NO:- GP 591
Masters seminar
Department of Genetics and Plant Breeding
Agricultural College, Bapatla
1

Content
Case Studies
Bio active
compounds
Divergence
Introduction
Department of Genetics and Plant Breeding 2

INTRODUCTION
Chickpea (Cicer
arietinum L.) is an
annual, erect, C3, dicot,
self- pollinated crop.
2n=16
Origin :- Western Asia
(Turkey)
Second most important
legume crop widely
grown in more than 50
countries.
Resilient to climate
change
80 gm/capita/day
Contains Malic acid &
Oxalic acid
Other names-
Gram, Bengal gram,
chana

Taxonomy
Hierarchy Name
Domain Eukaryota
Kingdom Plantae
Phylum Spermatophyta
Subphylum Angiospermae
Class Dicotyledonae
Order Fabales
Family Fabaceae
Genus Cicer
Species arietinum

Nutrient Composition
S.NO Component Percentage
1. Protein 18-21%
2. Carbohydrates 50-60%
3. Fat 4-10%
4. Fiber 10-20%

Statistics
PLACE YEAR AREA (M. hectares) PRODUCTION(M. tonnes) PRODUCTIVITY
(Kg/ha)
INDIA
2018-19 6.8 10.90 1127
2019-20 9.94 9.94 1040
A.P
2018-19 0.478 0.243 508
2019-20 0.460 0.560 1218

Constraints
• Sowing time
• Weed infestation
• Improper irrigation
Agronomic
• More energy demand for conversion to proteins
Bio-Chemical
• Low harvest index
• Low sink potential
• Flower drop
Physiological

Pest & Disease
Gram
Caterpillar
Plume
moth
Stem fly Pod borer
Wilt Rust
Ascochyta
blight
Stem rot

Types

Importance of
Divergence
Studies
• The sum total of genetic differences present
among different individuals, genotypes, strains,
clones or populations of a species is called
genetic diversity.
• Genetic diversity is the base for survival of
plants in nature and for crop improvement
• Plays a vital role in cultivar improvement, for
exploitation of variability
• It involves estimation of genetic similarity or
dissimilarity between pairs of entries.

Inclusion of diverse parents in hybridization helps in
isolation of superior recombinants.
Mahalanobis’s D2 statistics is a powerful tool in quantifying the degree of
variability at the genotype level
Principal Componenet Analysis by Edward Jackson, 1991 is the recently
used method.
Grouped into clusters and the clusters with maximum inter cluster distance
are used in breeding programme
Helps us to know the contribution of various characters towards genetic
diversity.

Absolute variability in different characters cannot be the decisive factor
Relative values of phenotypic and genotypic coefficient of variation, therefore
gives an idea about the magnitude of variability present in a population
Estimate of genotypic and phenotypic coefficient of variation, heritability and
expected genetic advance are useful for yield improvement

Importance of
Correlation
coefficient
It is a statistical
measure which is
used to find out the
degree (strength) and
direction of
relationship between
two or more
variables.
It determines the
component characters
on which selection
can be based for
genetic improvement
in yield.
The association of
one or more
characters influenced
by a large number of
genes is elaborated
statistically by
correlation
coefficients.
Genotypic correlation
coefficient provides a
measure of genotypes
conjugation between
characters.

Importance
of Path
Analysis
• The method of partitioning the
correlation into direct and indirect
effects by path coefficients analysis .
• The phenotypic and genotypic paths
are commonly estimated to determine
yield contributing characters.
• It splits the correlation coefficient
into direct & indirect effects and their
respective contribution of each indepe
ndent variable on the dependent
variable.
• To know the direct or indirect effect of
characters on yield

The correlation and path analysis provide information on genetic
association of yield and different yield contributing characters,
which in turn are useful in developing breeding strategies.
Inspite of phenotypic divergence, knowledge of genetic diversity
among the parents with respect to the association characters which
are to be improved is essential.

Bio-active
compounds
Anti-nutritional factors
Phytic acid
Tannins

Phytic acid
• Major source of 'P' in legumes
• Phytate 'P' was 51.2%of total 'P'
• It binds with other nutrients and make them
indigestible
• It forms insoluble complexes with essential
minerals
• Poor mineral bioavailability
• Decreases protein solubility
• Inhibits enzyme activity
• Reduces nutrient digestibility

Uses
Reduced bioavailability, and
their toxicity of heavy metals
In vitro antioxidant properties
Effects are mediated through it's
Fe &Cu chelating properties.

Tannins
• Ability to tan animal skins to produce
leather
• Form insoluble complexes
with carbohydrates and proteins
• Polyphenolic secondary metabolites of
higher plants
Hydrolysable tannins
Condensed tannins

Chickpea type Tannins Content (g/100g)
Desi
Hydrolysable tannins 0.36-0.72
Condensed tannins 0.01-0.09
Kabuli
Hydrolysable tannins 0.12-0.51
Condensed tannins 0.00-0.04

Genetic Diversity
Analysis in Chickpea
(Cicer arietinum L.)
N. R. Thakur et al., (2018)
Case Study I
International Journal of Current Microbiology and Applied Sciences
NAAS Score (2021) : **

Material and Methods
• 100 genotypes of chickpea including 75 desi and 25 kabuli, were grown during Rabi
2016- 2017 using RBD.
• With two replications at the Experimental Farm, Department of GPBR, College of
Agriculture, Latur.
• Data were recorded on five randomly tagged plants for days to 50% flowering, days to
maturity, plant height (cm), number of primary branches, number of secondary branches,
total pods plant-1, total number of seeds plant-1, 100 seed weight (g), seed yield plant-1(g),
and harvest index (%).

• Data were calculated by Mahalanobis D2 statistics (1936) and the
genotypes were grouped into different clusters according to Tocher’s
method as described by Rao.
• Contribution of individual characters towards divergence was estimated
according to the method described by Singh and Choudhary (1979).
• Grouping of variety into various clusters was done and average intra and
inter cluster distance were estimated.

Grouping of 100 chickpea genotypes into 12 clusters by
Tocher’s method

Results &
Discussion
Based on D2 values, 100 genotypes were grouped into twelve
clusters.
The cluster I consisted of maximum 49 genotypes, followed by
Cluster III, cluster VII and cluster IX, which had 16, 12 and 12
genotypes, respectively.
The maximum intra cluster distance was found in cluster IX (7.72)
followed by cluster VIII (6.65), VII (6.52), cluster III (6.14) and
cluster I (5.46).
However, maximum inter cluster distance was noticed between
cluster VII and cluster X (14.95), followed by cluster XI and cluster
XII (14.08), cluster VI and cluster XI (13.43) and cluster II and
cluster XI (13.22). Inter cluster values varied from 2.75 to 14.95.

Average intra &
inter cluster D2 &D
value of 12 clusters
from 100
chickpea genotypes

Cluster mean
performance for 10
characters of 100
chickpea
genotypes

• Whereas, days to 50 % flowering (22.89 %)
followed by 100 seed weight (21.29 %),
total number of seeds per plant (14.16 %) and
plant height (13.80 %) contributed
maximum towards diversity.
• Based on inter cluster distances and per se
performance PG 0749, BCG 79, ICC 5003,
ICC 1058, HK 06-171 and PKV KABULI 4 were
identified for inclusion in
hybridization programme for realizing desirable
transgressive segregates.

Percent
contribution
of 10
characters for
diversity in
chickpea

Clustering by Tochers method
Department of Genetics and Plant Breeding
32

Conclusion
• The above discussion showed wide variation
between clusters.
• The discrimination of genotypes into discrete
clusters suggested presence of high degree of
genetic diversity in the material evaluated.
• Presence of substantial genetic diversity among the
parental material screened in the present study
indicated that this material may serve as good source
for selecting the diverse parents for hybridization
programme aimed at isolating desirable segregants
for seed yield and other important characters.

Principal Component
Analysis of Chickpea
(Cicer arietinum L.) Germplasm
Renuka Shivwanshi (2017)
Case Study II

Material & Methods
• The study pertaining to the evaluation of superior chickpea
genotype using principal component analysis was conducted
in the Seed Breeding Farm, College of Agriculture, JNKVV,
Jabalpur (M.P.) during rabi 2015- 16.
• The experimental material comprised of 434 different
chickpea genotypes evaluated for thirteen quantitative traits,
received from NBPGR New Delhi sown in augmented block
design.
• Each plot comprised of 30 rows of 4.0 m length, row to row
distance of 30 cm and plant to plant distance is 8-10 cm.

PCA is a well-known method of dimension reduction that can be used to reduce a
large set of variables to a small set that still contains most of the information in
the large set.
The present investigation was aimed to evaluate the germplasm of chickpea for
identify and rank important traits and genotype on the basis of principal
component analysis before taking up hybridization programme for evolving
better hybrid in chickpea.

Results &
Discussion
• Selection of genotypes and traits based on
Principal Component analysis. Out of thirteen
PCS’s identified first 8 PC accounted for
77.68% of the total variation. The PC1
explained 26.57 % of total variation.
• While PC2, PC3, PC4, PC5, PC6, PC7 and
PC8 exhibited 13.58%, 8.45%, 6.54%, 5.48%,
6.03, 4.37 and 3.66% variability, respectively.
• Genotype IC 84037 was commonly found in
PC 1, PC3, PC 6 and PC7 followed by IC
84037 in PC 1, PC 3, PC 6 and PC 7, IC 83812
in PC 1, PC 2, PC 3, and PC 7, IC 83372 in PC
1, PC 3, PC 5, and PC 7, IC83592 in PC 1, PC
4, PC 5 and PC 7, similar type of genotypes on
a common principal component permitting to
designate them as seed yield factors

Screen plot constructed based on thirteen principal component and
their Eigen values

PC values of rotation component matrix for thirteen variables of chickpea

Rotated component matrix

Traits having
highest values
in each PC

Conclusion
• These genotypes may further be utilized in breeding programs for improving seed yield these genotypes
can be considered an ideotype breeding material for selection of traits viz more total number of seed per
plant, more effective pods per plant and high biological yield per plant and further utilization in precise
breeding program.
• The maximum PC value was found in genotype IC 84037 (9.79) followed by, IC 83812(8.46), EC
489919(7.70), IC 83387 (6.42), IC 83813 (6.24).
• This result has been suggested that these genotypes would be of practical value to chickpea breeders in
identifying the genotype with desired trait for utilization in breeding program for genetic improvement.

Correlation Studies and Path
Coefficient Analysis in
Chickpea
(Cicer arietinum L.)
J. K. Dawane (2020)
Case Study III

Materials
and
Methods
The present investigation on chickpea for correlation and
path analysis was conducted at Agricultural Research
Station, Badnapur, during Rabi season of 2017-18.
The experimental materials used for study consisted of 43
genotypes of chickpea
Out of which 25 genotypes were obtained from ICRISAT,
Hyderabad, 15 genotypes from the A.R.S. Badnapur and
three standard checks using RBD.
Two rows of four meter length for a genotype
Five randomly selected plants of each replication

• Spacing : 45×10cm
• Days to 50% flowering, days to maturity, plant height, number of 1o
branches, number of 2o branches per plants, number of pods per plant,
number of seeds per pods, number of pods per plant, harvest index,100
seed weight & seed yield.
• The genotypic co-variance was calculated as per Johnson et al., (1955).
To establish a cause and effect relationship the partitioning of genotypic
and phenotypic correlation coefficient was done into direct and indirect
effects by path analysis as suggested by Dewey and Lu (1959) and
developed by Wright (1921)

Results &
Discussion
Correlation coefficients
Studies showed that the traits viz. harvest index, number of
pods per plant, 100 seed weight, number of seeds per pod
and plant height exhibited positive and highly significant
genotypic correlation with seed yield.
This indicates that the simultaneous improvement of these
characters through selection.
Hence, the selection of genotypes based on these characters
as selection criterion would be helpful in improving the
seed yield potential of chickpea.

Estimation of phenotypic (above diagonal) correlation coefficients in
chickpea

Diagram showing the genotypic correlation in yield and its component characters of Chickpea

Path analysis
In path coefficient analysis the characters, number of pods per plant, harvest
index, 100 seed weight, number of seeds per pod, plant height and number
of secondary branches per plant had positive direct effect on seed yield in
decreasing order of magnitude.
Among all the components number of pods per plant exhibited the highest
direct effect on seed yield followed by harvest index, 100 seed weight, days
to maturity, number of seeds per pod, number of secondary branches per
plant, while number of primary branches per plant, plant height and days to
50 % flowering, recorded negative direct effect at phenotypic level.
At genotypic level pods per plant exhibited the highest positive direct effect
on seed yield followed by number of seeds per pod, 100 seed weight, days
to maturity, harvest index, number of secondary branches per plant.

Direct and indirect effect of yield and its component characters on
grain yield at genotypic level

Direct and indirect effect of yield and its component
characters on grain yield at phenotypic level

Conclusion Correlation studies showed that the traits like harvest index,
number of pods per plant, 100 seed weight, number of seeds
per pod and plant height exhibited positive and highly
significant genotypic correlation with seed yield.
Path coefficient analysis indicated that the characters like
number of primary branches per plant, plant height and days
to 50 % flowering exhibited negative direct effect on seed
yield per plant.
Hence, the selection of genotypes based on these characters
as selection criterion would be helpful in improving the
seed yield potential of chickpea.

Biochemical diversity evaluation
in chickpea accessions employing
mini-core collection
Sameer Suresh Bhagyawant (2018)
Case Study IV
Physiology and Molecular Biology of Plants
NAAS Score (2021):-8.01

Material
• Two hundred and fifteen mini-core accessions of chickpea (C. arietinum L.)
were used for analysis .
• Out of which four accessions were Indian national checks.
• The mature and dry seed material was obtained from ICRISAT, Hyderabad,
under MTA understanding.
• Seeds were grind in a grinder and obtained seed powder was first defatted
using chilled acetone and air dried.
• Analysis was performed under ambient conditions of temperature and
humidity

Methods
COMPONENT METHOD
Total protein Fan & Sosulski
Total amino acid Moore & Stein
Tannin Schandrel
Phytic acid Wilcox
Total flavonoids khoo
Total phenolics Swain & Hillis

Results
&
Discussion • The seeds of chickpea provide an exceptional source of dietary
proteins and is one of the important legumes.
• The available germplasm of cultivated chickpea is deficient in desired
biochemical signatures.
• To identify new sources of variations for breeding, reduced subsets of
germplasm such as mini-core collection can be explored as an
effective resource.
• The spectrum of diversity was documented for total protein (4.60–
33.90%), total free amino acids (0.092–9.33 mg/g), phytic acid
(0.009–4.06 mg/g), tannin (0.232–189.63 mg/g), total phenolics
(0.15–0.81 mg/g), total flavonoids (0.04–1.57 mg/g)

Multivariate principal
component analysis of
215 mini-core chickpea
accessions based on
evaluated parameters

Single seed
representation
of 215
chickpea mini-
core accessions

UPGMA
Dendrogram

Conclusion
• Chickpea is a good source of protein, free
amino acid, vitamins, mineral.
• The principal component analysis revealed
association of chickpea higher protein
content to the lower level of total phenolics
and flavonoid contents.
• The dendrogram obtained by unweighted
pair group method using arithmetic average
cluster analysis grouped the chickpea
accessions into two major clusters.
• There are no cultivars with all required
biochemical parameters.

GENETIC DIVERGENCE AND STUDIES ON BIOACTIVE COMPOUNDS IN CHICKPEA

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