Unlocking Morphological and Genetic Diversity in Pigeonpea [Cajanus cajan (L.)] Accessions for Crop Improvement

Pigeonpea [Cajanus cajan (L.) Millsp] is an important legume crop widely cultivated in Africa and Asia in diverse environments. It is a diploid (2n = 2X = 22) crop with a genome size of 833.07 Mbp. It belongs to the family Leguminosae and sub-family Papilionoideae. Cajanus cajan is the only domesticated species among Cajanea family. It is a crucial crop in the semi-arid tropics, cultivated across 24 countries on approximately 6.03 million hectares, yielding about 5.3 million tons annually. India dominates this landscape, accounting for 82.20 per cent of the cultivated area (5.01 million hectares) and 77.60 per cent of the total production (4.3 million tons). Other significant contributors to pigeonpea production include Myanmar, Malawi, Kenya and Tanzania, each contributing over 2 per cent. Within India, pigeonpea is grown in 25 states, covering an area of 5 million hectares and producing 4.3 million tons, resulting in a productivity rate of 861.2 kg per hectare FAO, (2023). Key states for pigeonpea cultivation include Karnataka (0.89 million hectares) Telangana (0.30 million hectares), Uttar Pradesh (0.29 million hectares), Gujarat (0.24 million hectares), Jharkhand (0.23 million hectares) andhra Pradesh (0.24 million hectares), Madhya Pradesh (0.25 million hectares) and Odisha (0.12 million hectares). Karnataka is the leading producer with an output of 9.48 lakh tons, followed closely by Maharashtra with 8.75 lakh tons of pigeonpea production (Indiastat, 2023).
       
Morphological traits play a pivotal role in determining yield in pigeonpea. Key morphological traits such as plant vigor, which is directly proportional to biomass production and stress tolerance are crucial. Semi-spreading types are lodging resistant and typically exhibit higher yields. Additionally, seed shape often correlates with seed size and seed weight. Understanding the relationship between morphological traits and yield is essential for the continued development of pigeonpea varieties that meet diverse needs. Furthermore, a major concern in improving pigeonpea crops is the limited genetic foundation of contemporary cultivars. Consequently, the anticipated genetic advances in pigeonpea output have not been fully realized. Genes with beneficial features found in genebanks can be utilized to create desirable genetic variation and enhance resilience to stressors induced by climate change (Díez  et al., 2018). Therefore, it is crucial to explore genebanks for new germplasm to employ in pigeonpea breeding initiatives, aiming to increase cultivar productivity and climate change resilience.
       
The degree of genetic variability and diversity resulting from the many traits accessible to breeders to create desirable variations determines the effectiveness of breeding programmes in any given crop (Govindaraj et al., 2020). Furthermore, genetic diversity studies offer an information on target trait availability and variability for the effectiveness of breeding programmes by highlighting the disparities among accessions (Mohammadi and Prasanna, 2003). Finding out the extent of genetic diversity present in the various germplasm lines is therefore essential. To gather crucial data for pigeonpea crop improvement, the current study was carried out to evaluate the morphological and genetic diversity in the pigeonpea accessions.

The field experiment was carried out during kharif 2022 at Zonal Agricultural Research Station (ZARS) Kalaburagi, which is located at a latitude of 17^o30’ (N), 76^o81’ Longitude (E) and at an altitude of 443.88 meters above mean sea level and it comes under agro-climatic zone-2 (North-eastern Dry Zone of Karnataka state). A total of 261 pigeonpea accessions (Table S1) obtained from National Genebank of ICAR-National Bureau of Plant Genetic Resource (NBPGR), New Delhi including three checks PT-012, BSMR-736 and Asha were sown in Augmented Block Design (ABD) consisting of 27 blocks. The accessions were sown in 3-meter length of 2 rows each with a row to row and plant to plant spacing of 90 and 20cm respectively. Standard agronomic practices were followed and plant protection measures were taken as and when required by following the recommended package of practices (Anonymous, 2017).


       
At specific stage, the morphological traits were noted, the plant vigour observed and classified into poor (1), good (2) and very good (3) based on visual scoring. Growth habits were observed and grouped into erect and compact (1) semi spreading (2), spreading (3), trailing (4) and others (99). Determinate (1) semi-determinate (2) Indeterminate (3) and others (99) were the classes for plant habit trait. Green (1) sun red (2) purple (3) dark purple (4) and others (99) were the classes of stem color. Flower color observed and grouped into light (1) light yellow (2) yellow (3) orange yellow (4) and others (99). Streak patterns were observed and grouped as sparse streaks (3) medium streaks (5) dense streak (7) uniform coverage of second color and others (99). Seed traits such as seed color grouped into white (1), cream (2), Orange (3), light brown (4), reddish brown (5), light grey (6), grey (7), purple (8), dark purple (9) dark grey (10) and others (99), seed shape in to oval (1), globular (2), square (3), elongate (4) and others (99). and seed eye width for all the lines were observed and scored into narrow (3), medium (5), wide (7) and others (99) (Table S2). Quantitative traits were recorded in 5 random plants from two rows of each accession, Viz., Days to 50 per cent flowering, plant height, primary branches, secondary branches, pod bearing length, number of seeds per pod, number of pods per plant, days to physiological maturity, seed yield and seed weight. The qualitative traits include plant vigor, growth habit, plant habit, seed eye width, seed color and seed shape. The analysis of variance (ANOVA) was carried out for all the quantitative traits. The data was analyzed using R software version 2023.12.1.

The ANOVA results indicated that the mean sum of square for genotypes was highly significant (P≤0.01) for all the traits (Table 1). Based on D² values, the accessions were grouped into seven clusters using Tocher’s method given by (Rao, 1952). Of the seven clusters, cluster three was found to be largest with 87 accessions. Cluster four with 61 accessions. Cluster one, two, five, six and seven have 54, 27, 5, 21 and 5 accessions respectively. The existence of genetic variability in these traits were also reported by (Tuntun et al., 2022; Kumara  et al., 2013; Basavaraj et al., 2023).
 


Variability parameters for quantitative traits
 
Significant variations were observed in the mean, range and coefficient of variations (Table 2). For the days to 50 per cent flowering, the range was from 77 to 188 days with a mean of 122 days. Days to physiological maturity ranged between 127.17 to 232.17 days with an average of 174.69 days. The mean plant height was 168.60 cm with a range of 84.14 to 213.65. The number of seeds per pod and the number of pods per plant showed mean values of 3.33 and 103.5, with ranges of 2.08 to 4.52 and 6.59 to 398.16, respectively. Seed yield ranged from 1.18 g to 76.34 g with a mean value of 17.05 g, while seed weight showed a mean value of 8.29 g with a range of 5.93 g to 18.93 g. Similarly, substantial variation was observed in most of the traits. Box plot analysis compared trait distribution between exotic and indigenous accessions. On an average, days to maturity, secondary branch number, plant height and seed weight were higher in exotic collections (ECs), while primary branch number, pod length and seed yield showed higher average performance in indigenous collections (ICs) (Fig 1). The major steps in crop improvement are assessing the variability for desired traits and their utilization in breeding programs. (Kumar et al., 2015; Tuntun et al., 2022). The wide range of variability obtained was attributable to the diverse collection assessed in the study.




       
To identify the amount of genetic diversity, present in the experimental material the cluster analysis has been done, these clusters represent existence of diversity between the set of accessions. In current study none of the accessions belongs to solitary cluster, the accessions congregated into a cluster which exhibit narrow range of genetic among them while, broad range of variability was recorded between clusters. The generation of such clusters may be due to total isolation arresting the gene flow or rigorous natural or human selection for diverse adaptive complexes. The clusters generated are presented in Table 3, Fig 2.




       
Significant genetic diversity has also been found by previous researchers in the pigeonpea materials (Pushpavalli et al., 2017). The experimental material in the current study exhibited significant genetic diversity, suggesting that it could be a valuable genetic resource for choosing diverse parents which are having higher genetic distance within the cluster for a hybridization programme that aims to isolate desirable segregants for key characteristics such as seed yield and related traits.
 
Correlation studies and principal component analysis
 
Days to 50 per cent flowering (r = -0.25, P≤0.001) and days to physiological maturity (r = -0.26, P≤0.001) have shown significant negative association with seed yield. Number of pods per plant (r = 0.50, P≤0.001) had a significant positive association with seed yield indicating the more the number of pods per plant will increase the seed yield. The number of seeds per pod (r = 0.28, P≤0.001) had a significant positive association with seed yield. Primary branches have shown a significant positive (r = 0.28, P≤ 0.001) association with seed yield. Whereas secondary branches have shown a positive (r = 0.18, P≤0.05) association with pod bearing length and seed yield. Plant height had shown a significant positive (r = 0.29, P≤0.001) association with seed yield (Fig 3). The strong correlation among some of the traits, such as days to 50% flowering and days to maturity and pods per plant, showed that sufficient weightage has to be given while exercising selection for yield. 


       
The significant positive association shown by the traits (Number of seeds per pod, primary and secondary branches and plant height) can be used for multiple trait selection. Here the days to 50% flowering and days to physiological maturity have shown negative correlation with seed yield. Similar results were reported by (Saroj et al., 2013) (Vanniarajan et al., 2023; Bhadru et al., 2010). In converse, a negative correlation between seed weight and seed yield has also been reported previously (Hemavathy et al., 2017). The significant relationship between days to 50% flowering, days to physiological maturity, plant height, number of seeds per pod, number of pods per plant and seed yield is useful for selection for high seed yield. Direct selection for these traits would result in yield improvement.
 
Principal component analysis (PCA) of trait variation in pigeonpea germplasm accessions
 
PCA revealed the association among different traits and their contribution towards variability. The first three PCA components provided a realistic summary of the data and explained 64.29% of total variation. The first principal component (PC1) accounted for 30.05% of the total variation, whereas PC2 and PC3 accounted for 22.11% and 12.13 % variance respectively (Table 4, Fig 4). The days to 50% flowering and days to physiological maturity and seed weight were the highest and positive contributors (With contributions of 0.211, 0.209 and 0.079) on PC1. Seed yield was the only positive contributor (0.046) on the PC2. Traits like Days to 50% flowering, plant height, days to physiological maturity and seed weight were negatively correlated with PC2 exhibiting negative (-0.594, -0.351, -0.597 and- 0.148) PC scores on PC2. Number of seeds per pod, number of pods per plant seed yield and seed weight were the positive contributors (0.582, 0086, 0.236 and 0.683) to the phenotypic variation on PC3. PCA enabled the identification of important traits with high variability amount the accessions. The traits which have exhibited high contribution of principal components can be used for selection. Similar results were reported previously (Nyirenda  et al., 2020;  Mohan et al., 2021).
 
 



Qualitative traits characterization in pigeonpea germplasm accessions
 
The frequency distribution of the entire set was non-normal and varied among traits. In certain cases, a particular trait predominated, while it was dispersed in others. For instance, the trait of plant vigor exhibited good plant vigor in most cases. Among the 258 genotypes, 186 accessions were found to have good plant vigor, while 57 accessions displayed very good plant vigor. The remaining accessions exhibited poor plant vigor. Semi-spreading growth habits were found in 174 accessions, while the rest, 84 accessions, were of the erect and compact type. Concerning plant habit trait, most accessions displayed an indeterminate nature, with only 3 genotypes found to be determinate. Regarding seed color, the majority of accessions (144) exhibited a reddish-brown color, followed by 29 with a light brown color, 5 genotypes with a purple color and the remaining accessions displaying mixed colors. Seed shape was categorized into oval (230), globular (16) and square (12) in this study, with the majority of accessions having an oval seed shape. Seed eye width was found to be medium in 128 accessions, narrow in 120 accessions and wide in 10 accessions (Fig 6).



Identification of trait-specific pigeonpea accessions
 
Superior trait specific accessions IC73961, IC73952, IC73975 and EC843239 for yield and related traits were identified from this study and they are depicted in Fig 5. The identified accessions could be tested in multi-locations and seasons to confirm their performance and then can be used as a potential donor for crop improvement.

The present study involved the characterization of 261 pigeonpea accessions based on various qualitative and quantitative traits. Cluster analysis was employed to assess and elucidate the genetic diversity among the accessions. Correlation and principal component analysis (PCA) revealed associations among various morphological and yield-related traits, highlighting their contribution to the observed genetic diversity. This study also enabled the identification of trait-specific accessions. Based on per se performance, genotypes IC73883, IC73961, IC73952, IC73975 and EC843239 were identified as superior for yield and associated traits. These promising accessions can serve as valuable donors in pigeonpea breeding programs and varietal development.

Authors thank the National Bureau of Plant Genetic Resource (NBPGR), New Delhi for providing seed materials and funding the CRP-AB pigeonpea project through Indian Institute of Pulses Research Institute (IIPR), Kanpur. 

The authors declare that they have no conflicts of interest relevant to the content of this article