The present study was carried out to probe
the direct and indirect selection indices in fifteen chickpea (Cicer arietinum
L.) genotypes. The experiment was conducted
at Gram Breeding Research Station, Kallurkot, Pakistan, during Rabi season of
2016-17. Basic analysis of variance revealed that all the genotypes were significantly
different (p?0.01) for all the traits. The path coefficient analysis showed
that the harvest index had greatest direct effect on yield (0.527) which was followed
by number of pods plant-1 (0.498) and 100 seed weight (0.452).
Correlation coefficient studies showed highly significant correlation between
harvest index and yield (0.941) followed by number of pods plant-1
(0.924) and 100 seed weight (0.502) signifying the importance of these traits
for crop improvement. Correlation and path coefficient analysis studies showed
that harvest index, number of pods plant-1 and 100 seed weight have
positive and significant correlation to grain yield coupled with high direct
positive effect. Therefore, these traits may be focused while attempting chickpea
genetic improvement program.
chickpea, direct, indirect indices,
Chickpea is one of the first grain legume crops to be domesticated by
humans in old world (Van der Maesen, 1972).
It is cheap and rich source of protein (20%), along with 60% carbohydrates
and 1.6% fats (Ali and Ahsan, 2012). The crop is being cultivated in more than
30 countries of almost all the continents including Asia, Europe, North America,
South America, Australia and Africa (Mushtaq et al., 2013). Chickpea is the important
rabi pulse crop contributing about 76% share in total pulses production of
Pakistan, occupying > 5 % of the area under rabi crops. But the crop has
been facing from 15-18% decline in production due to erratic trends in amount
and frequency of rainfalls, as the crop’s major share is obtained from Thal
region solely dependent on rain (Pakistan
Economic Survey 2015-16). Irrespective of the fact that the crop ranks
second (after India) in terms of acreage, productivity of the crop on per unit
area basis in Pakistan is far below (276 kg ha-1) than the average world’s production of 952 kg ha-1
(FAO STAT, 2014). Therefore, the evolution of potent cultivars of chickpea is dire
needed to uplift the yield on existing area.
Determination of type and strength of association among various
yield traits and their impact on the final yield is imperative for selection of
suitable germplasm for fruitful breeding programs. For improvement in chickpea
genotypes it is necessary to understand the genetic basis of yield and related
traits. The path coefficient analysis for yield contributing traits will be
helpful in sorting out the most effective plant variable on which the selection
should rely upon.
In most of the biological systems
various traits are interlinked with each other to produce the final phenotype.
The complexity increases with increasing number of factors interlinked in the
system. So identification of the most related and effective parameter for
selection becomes a difficult task for a scientist attempting to improve that
particular system. Under such complexity, the path coefficient analysis helps
to measure the direct and indirect contributions of linked traits towards the
ultimate yield (Singh et al., 1990). Path coefficient analysis quantifies the
impact of various traits directly and indirectly on grain yield (Gull, 1995;
Bakhsh et al., 1998).
Correlation analysis is very helpful in
deciding the most effective selection criteria for improving yield and its contributing
traits (Khan & Qureshi, 2001). Many researchers such as Noor et al. (2003); Farshadfar &
Farshadfar (2008); Atta et al.
(2008); Sharma & Saini (2010) and Ali et al. (2011) emphasized the utility of correlation analysis.
Islam et al. (1984) documented that grain yield is highly and positively
correlated with pods per plant, biomass and secondary branches per plant and gave
emphasis on these parameters as to serve as selection criteria in chickpea. The
correlation among yield and yield attributes has been widely studied (Lokendra
et al. (1999). Saleem et al., 1999; Saleem et al. 2002). and Yucel et al.
(2006) who reported a significant and positive correlation between pods plant-1
and harvest index with grain yield plant-1. Information acquired
from path coefficient analysis and correlation is very useful for a plant breeder
to devise an efficient selection criterion in breeding program aiming at increased
The main focus of the present investigation
was to analyze the mutual relationship in various metric traits and their
direct and indirect influence on the final economic yield (grain yield) through
path coefficient and correlation analysis which could lead as a directional
model for determination of an effective selection criteria to evolve the most
efficient and potent genotypes.
The study for the investigation of
selection criteria in chickpea genotypes using path analysis and correlation
was carried out at Gram Breeding Research Station, Kallurkot, Pakistan, during Rabi
season 2016-17. The experimental material comprised of fifteen chickpea genotypes
including 4 commercial varieties Bhakkar-11, CM-2008, Noor-13 and Bittle-16 and
12 elite strains viz; CH60/10, CH73/10, CH86/10, K010-10, K044-11, K065-11,
CC9899, CH 85/06, DO 80-10, DO 72-11 and DO 88-11). The layout was done in randomized
complete block design (RCBD) with three replications. All experimental plots
comprised of 30 centimeter apart 4 rows of 4 meter length. The seed of
genotypes was sown with the help of dibbler making 10cm apart holes. Two seeds
per hole were sown and later thinned to 1 plant per hole after 10 days of
germination. Insecticide Emamectin @ 200 ml acre-1 was sprayed twice
with an interval of 20 days against pod borer attack during the pod formation
was recorded for number of days taken to flowering (50% ), number of days taken to maturity (90%), plant
height (cm), number of pods plant-1,
100 seed weight (g) and grain yield (Kg ha-1). Harvest index was calculated
as economic yield over total biomass. Analysis of variance was done following Steel et al. (1997) for
the estimation of genetic differences among genotypes for the concerned traits.
Path coefficients analysis was done following Dewey and Lu (1959). While, the genotypic
and phenotypic correlation coefficients were calculated following Singh and