Quantitative trait association and genetic diversity analysis in chickpea (Cicer arietinum L.) genotypes

Introduction

Chickpea (Cicer arietinum L.) holds a prominent position in global pulse production and serves as a crucial source of protein in human nutrition, particularly in developing countries. The crop's significance extends beyond its nutritional value, encompassing its role in sustainable agriculture through biological nitrogen fixation and soil health improvement. As global demand for protein-rich foods increases and climate challenges intensify, the need for improved chickpea varieties has become increasingly urgent. Genetic improvement in chickpea relies heavily on understanding the extent of genetic variability, heritability and genetic advance of economically important traits. These parameters are fundamental to designing effective breeding strategies and achieving genetic gain through selection (Kumar et al., 2021) [17] . Recent studies involving diverse chickpea germplasm have revealed substantial genetic variation for various agronomic and physiological traits, providing opportunities for crop improvement. Recent advances in genomic tools and technologies have enhanced our understanding of the genetic basis of important traits in chickpea. Assessment of genetic variability, correlation coefficient analysis among diverse genotypes has revealed promising traits such as hundred seed weight, seed per plant and pods per plant were found to be significant for yield. Kumar et al., identified several genotypes with superior performance under drought conditions, exhibiting high heritability for drought tolerance-related traits. Globally, chickpea cultivation spans approximately 17.8 million hectares, producing 17.2 million metric tons annually, with India leading production at 11.4 million tons (FAOSTAT, 2023). In India, Madhya Pradesh, Maharashtra, Rajasthan, and Uttar Pradesh are the top chickpea-producing states, contributing significantly to national production (ICRISAT, 2023). The significant genetic variability observed among 53 genotypes, combined with high heritability and genetic advance for key traits, suggests good prospects for genetic improvement through selection.

Results

Correlation coefficient analysis

Days to 50% flowering (DFF) exhibited a significant positive correlation with days to maturity (0.412). The positive association with days to maturity confirms that later-flowering genotypes tend to have a longer crop duration, a trend consistent with reports by Bakhsh et al.

(1998) [18] and Wahid and Ahmed (1998). The largely nonsignificant relationships with yield components suggest that flowering time alone may not directly govern productivity under the conditions studied. Days to maturity (DM) exhibited a significant negative correlation with pods per plant (-0.332). Non-significant positive associations were recorded with seed yield per plant (0.242), seeds per plant (0.028), seeds per pod (0.130), and 100-seed weight (0.008) consistent with findings of Arora and Kumar and Bakhsh et al. (1998) [18] . Primary branches per plant (PB) showed nonsignificant negative correlations with seed yield per plant (-0.083), plant height (-0.078), and 100-seed weight (-0.204) (1998) [18] . Seeds per pod (SPPOD) exhibited highly significant positive correlations with seed yield per plant (0.591) and seeds per plant (0.770).

The strong interrelationship between seeds per pod and seeds per plant (0.770) indicates that selection for higher seeds per pod simultaneously increases total seed count, as reported by Ozdemir (1996) and Jethwa (1994). 100-seed weight (SW) showed a significant positive correlation with seed yield per plant (0.420) and plant height (0.313). The significant link between seed weight and yield confirms seed size as a reliable selection criterion, consistent with Yadav (1990) and Singh (1997). The negative associations with pod and seed number reflect the classical size number trade-off noted by Mani and Bahl (1990). Seed yield per plant (YPP) is the primary trait of interest and recorded highly significant positive correlations with seeds per plant (0.738) and seeds per pod (0.591). A highly significant positive association was also found with pods per plant (0.480). Significant positive correlations were observed with 100-seed weight (0.420). The results confirm that seeds per plant, seeds per pod, and pods per plant are the most influential contributors to yield, and should be prioritized in selection programmes, in agreement with Singh et al.

(1997), Bakhsh et al. (1998) [18] , and Kumar.

Inter-cluster divergence

The analysis of inter-cluster average K values (

Discussion

The correlation analysis of 53 chickpea genotypes for nine morpho-agronomic traits revealed significant associations governing yield determination. Days to flowering demonstrated a positive correlation with days to maturity (0.412), confirming that late-flowering genotypes possess prolonged crop durations, consistent with contemporary findings by Mohan and Thiyagarajan (2019) [6] , Rahangdale et al., (2023) [10] and Rajput et al., (2023) [9] . However, days to maturity exhibited a weak negative correlation with pods per plant (-0.332), suggesting that extended growing periods alone do not guarantee superior pod production. This contrasts with some breeding programs where selection for late-maturing types resulted in enhanced productivity (Nagar and Karnawat, 2023) [7] . The observed variation in these relationships underscores the genotype-specific nature of phenological trait interactions. Yield component analysis identified seeds per plant as the most reliable yield predictor (0.738), substantiating recent multivariate analyses by Kumar et al. (2025) [4] and Pal (2024) [12] . Seeds per pod demonstrated highly significant interdependence with seeds per plant (0.770) and both traits displayed strong positive association with seed yield (0.591 and 0.738, respectively). Pods per plant showed robust positive correlation with yield (r = 0.480), reinforcing its value as a selection criterion (Lambe et al., 2024). Notably, 100-seed weight maintained significant positive correlation with yield (0.420) despite negative associations with pod and seed numbers, exemplifying the classical size-number trade-off (Akbar et al., 2025) [1] . This trade-off offers strategic flexibility; breeders can simultaneously pursue either seed quality or quantity depending on market preferences and environmental adaptation requirements. Plant height showed significant positive associations with both pods per plant (0.341) and 100-seed weight (0.313), supporting the hypothesis that taller genotypes provide superior pod-bearing framework (Deepa et al., 2023) [2] . Primary branches per plant exhibited negligible correlations with yield components, suggesting compensatory mechanisms operate in yield determination. The cluster analysis identified substantial genetic divergence among the 53 genotypes, with clusters VI and IX showing the maximum inter-cluster distance (6.4736), similar to findings by Shivwanshi and Babbar (2019) [13] , Barela et al., (2022) [8] and Jain et al., (2024) [11] who reported inter-cluster distances of 6.7 in chickpea germplasm. This genetic divergence provides excellent parental combinations for hybridization programmes. Cluster V demonstrated superior mean performance for yield per plant (12.71 g) alongside highest seeds per plant (74.73) and seeds per pod (1.80), identifying this cluster as a valuable source for direct selection or elite parent material, consistent with Singh et al.

(2022) [14] . Integrated selection prioritizing seeds per plant, pods per plant, and plant height would efficiently combine highyielding potential with agronomic suitability for varied environments. The identified genotypic variation and clustering patterns provide breeders with substantial genetic resources for developing superior chickpea cultivars through both direct selection and divergent crossing strategies, potentially improving chickpea productivity in diverse growing regions globally (Dawane et al., 2020) [3] .

References

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