Unveiling variability in F₃ pigeonpea populations for crop improvement

Introduction

Pigeon pea (Cajanus cajan) is the sixth most important edible legume crop worldwide, valued for its adaptability, rapid growth, and resilience in semi-arid tropical regions (Abebe, 2022; Emefiene et al., 2014) [1,11] . It is a short-lived perennial, often cultivated as an annual, with a deep root system that enhances drought tolerance and soil stability. Globally, India is the largest producer, accounting for nearly 70% of the cultivated area, followed by Myanmar, Malawi, Tanzania, and Kenya (Emefiene et al., 2014) [11] . In India, red gram (pigeon pea) covered 40.42 lakh hectares in 2023-24, slightly lower than 40.68 lakh hectares in 2022-23. The major producing states include Karnataka (13.37 lakh ha), Maharashtra (11.11 lakh ha), Uttar Pradesh (3.50 lakh ha), Andhra Pradesh (2.32 lakh ha), Gujarat (2.27 lakh ha), and Jharkhand (1.85 lakh ha). National production during 2023-24 was projected at 33.85 lakh tonnes (ANGRAU, 2023-24) [2] . These figures highlight the crop's central role in Indian agriculture, particularly in semi-arid zones. It is rich in protein (22.3%), carbohydrates (57.6%), minerals (3.5%), fiber (1.5%), and energy (335 kcal/100 g), with key micronutrients like Ca (73 mg), P (304 mg), and Fe (5.8 mg/100 g), making it vital in protein-deficient regions (DPD, n.d.; Abebe, 2022) [1] . Entire plants are used for food, fodder, fuelwood, and green manure, while improving soil fertility through nitrogen fixation and erosion control (Rana & Kaushik, 2018; CGIAR, 2019; Choudhary et al., 2011; Vartapetian & Jackson, 1997) [6,8,20,30] . Economically, it supports flour, noodles, biscuits, and bread industries (Fatokimi & Tanimonure, 2021) [12] , and medicinally it is linked to anti-inflammatory, antibacterial, antioxidant, anticarcinogenic, and antidiabetic properties in traditional systems (Emefiene et al., 2014; Abebe, 2022) [1,11] . India is not self-sufficient in pigeon pea because its domestic demand consistently exceeds national production, creating a persistent reliance on imports to meet consumption needs, as highlighted by Legume Research, which notes that "although India is the largest producer of pulses in the world, its domestic demand outstrips domestic production and the shortfall is met from imports" (Singh et al., 2022) [28] . This continual supply deficit underscores the urgent need to develop high-yielding and stable pigeon pea varieties to enhance productivity and move the country toward long-term self-reliance. Given the crop's cross-pollinated nature (20-70%) and its diploid chromosome number (2n = 22), pigeon pea possesses substantial genetic diversity that can be effectively exploited in breeding programs (Mallikarjuna et al., 2014) [16] . In this context, the present study on variability in the F₃ population aims to assess the extent of variability among segregating lines, analyze the association between yield and key yield-attributing traits, and identify promising lines that can be advanced for the development of superior, high-yielding cultivars.

Materials and Methods

The present study on Variability studies in F3 population of Pigeon pea [Cajanus cajan (L.) Millspaugh] was conducted during the 2023 cropping season at the Department of Genetics and Plant Breeding experimental farm, Nagaland University, SAS, Medziphema Campus, located at 305 m above sea level under subtropical climatic conditions. Sixteen breeding lines along with two check varieties from the AICRP (Pigeonpea) program were evaluated in a randomized block design with two replications, maintaining 60 cm × 20 cm spacing. Standard land preparation and sowing practices were followed, and intercultural operations were carried out as per recommended guidelines. Observations were recorded on five randomly selected plants per replication for quantitative traits such as plant height, number of branches, flowering and maturity duration, pod and seed attributes, and seed yield, along with qualitative traits including stem colour, growth habit, flower colour, pod form, seed shape, and seed coat characteristics. The plot means were subjected to analysis of variance, estimation of genetic parameters, correlation studies, and path coefficient analysis to assess variability and trait associations with yield. During the crop period, temperatures ranged from a maximum of 36.9°C to a minimum of 8.2°C, relative humidity varied between 97% and 42%, and rainfall fluctuated from 123.6 mm to negligible levels. Meteorological data were obtained from ICAR, Jharnapani.

Results and discussions

The results and discussion section provides a detailed account of the variability, heritability, genetic advance, correlation, and path coefficient effects observed among the pigeon pea genotypes studied.

Qualitative traits

Eleven qualitative traits were studied across breeding lines and check varieties. Stem colour was predominantly green, with NUPPC-29D showing minor segregation (11% purple). All lines exhibited erect growth habit and indeterminate flowering. Base flower colour showed wide segregation, ranging from uniform yellow in checks (PA-291, UPAS-120, NUPPC-32D) to mixtures of yellow, red, ivory, and light yellow in breeding lines. Pod colour was largely mixed, though several lines segregated into purple and green types. Pod form was mostly cylindrical, with varying proportions of flat pods in segregating lines. Seed shape ranged from oval (uniform in checks) to square, globular, and elongate in breeding lines. Base seed colour was predominantly light brown, with cream variants in some lines and dark purple restricted to NUPPC-29D. Seed colour pattern varied from plain (uniform in checks) to mottled and speckled in segregating lines. Leaflet shape was lanceolate in checks, while breeding lines showed segregation into broad and narrow elliptical forms. Overall, check varieties remained uniform, whereas breeding lines exhibited segregation for most qualitative traits, confirming variability within the F₃ population.

ANOVA

The analysis of variance showed clear and significant differences across all quantitative traits, confirming wide genetic variability in the F₃ pigeonpea population. Days to 50% flowering ranged from 98 to 149 days, while days to maturity varied between 151 and 271 days, indicating both early and late maturing types. Plant height ranged from 207 cm to 337 cm, reflecting variation in plant stature. Branching traits also showed diversity, with primary branches per plant ranging from 12 to 29 and secondary branches per plant from 4 to 59. Pod bearing length varied between 71 cm and 154 cm, while pods per cluster ranged from 2.2 to 3.7. The number of pods per plant ranged from 127 to 363, and seeds per pod varied between 4.2 and 5.3. Seed traits showed further variability, with 100-seed weight ranging from 10.7 g to 14 g, and seed yield per plant ranging from 21 g to 103 g. Overall, the presence of such variation across flowering, maturity, plant stature, branching, pod traits, seed size, and yield highlights the importance of these characters in selection and breeding programs aimed at developing high-yielding pigeonpea varieties.

Quantitative traits

Genetic Parameters

The study revealed that phenotypic variance was consistently higher than genotypic variance, underscoring the role of environmental factors in trait expression. Traits such as number of pods per plant and secondary branches per plant showed the widest variability, a trend also emphasized by Rangare et al. (2013) and Rekha et al.

(2013) [22,24] . In contrast, number of seeds per pod exhibited (2019) [13,18] . The study revealed high GCV and PCV for traits like secondary branches per plant, seed yield, and number of pods per plant, suggesting strong genetic variability and potential for selection, as earlier emphasized by Bhadru (2010) [4] . Moderate values were observed for traits such as flowering time and pod-bearing length, consistent with the findings of Rangare et al. (2013) and Rekha et al. (2013) [22,24] . In contrast, plant height, seeds per pod, and seed weight showed low variability, a pattern also noted by Meena et al.

(2017) [17] . For several traits, GCV values were close to PCV values, indicating minimal environmental influence and high heritability, whereas traits with larger differences were more environmentally sensitive, a conclusion reinforced by Hemavathy et al. (2019) [13] . Collectively, these findings highlight the scope for exploiting genetic variability in crop improvement.

Broad sense heritability and Genetic advance

Heritability and genetic advance are important indicators for plant breeders, as they show how much of trait variation is genetic and how much improvement can be expected through selection. In this study, most traits showed high heritability (>60%), except pods per cluster (43.97%) and seeds per pod (40.50% [7,15,22,25,27] . In contrast, plant height and test weight showed high heritability but low genetic advance, suggesting complex inheritance and non-additive gene effects, as also noted by Arshad et al. (2003) [3] . Overall, traits under additive control can be effectively improved through selection, while traits with complex inheritance may require alternative breeding approaches.

Correlation studies

The analysis included computation of simple correlation coefficients at both phenotypic and genotypic levels for nine characters, with significance tested at the 5% and 1% levels. Seed yield per plant showed a significant positive association with pod bearing length, number of pods per plant, and number of seeds per pod, and the correlations were stronger at the genotypic level, suggesting that these traits are largely governed by genetic factors. Pod bearing length and number of pods per plant emerged as the most important yield-contributing traits, which agrees with the findings of Sawant et al. (2009) and Bhadru (2010) [4,26] , while the positive association of seeds per pod with yield was also reported by Jogendra (2018). These results indicate that selection for pod bearing length, pods per plant, and seeds per pod would be effective in developing high-yielding pigeon pea genotypes.

Path coefficient Analysis

Path coefficient analysis revealed that number of pods per plant exerted the highest positive direct effect on seed yield, followed by pod bearing length and seeds per pod, which agrees with earlier findings in pigeon pea by Saroj et al.

(2013) and Ramesh et al. (2017) [19,25] . Pods per cluster, days to maturity, primary branches per plant, and days to 50% flowering also showed positive direct contributions, consistent with reports by Devi et al. (2012) and Rao et al.

(2013) [10,23] . Positive indirect effects were mainly expressed through number of pods per plant, with pod bearing length and seeds per pod contributing substantially via this pathway, as observed by Birhan et al. (2013) [5] . Overall, the study highlights number of pods per plant and pod bearing length as the most important yield-contributing traits, both directly and indirectly, suggesting that selection for these characters would be effective in improving pigeon pea yield.

Conclusion

Significant variability was observed among the genotypes, with pod bearing length, number of pods per plant, and number of seeds per pod identified as the most important characters for yield improvement. Among the lines evaluated, NUPPC-30A was the best performer, showing high values in traits positively correlated with seed yield, followed by NUPPC-32C and NUPPC-29C, which also recorded high pod numbers, pod bearing length, and seed yield. NUPPC-31C exhibited the least days to 50% flowering and maturity, making it a potential genotype for use in breeding programs.

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