Assessment of genetic variability and correlation analysis in pigeon pea (Cajanus cajan L.) for yield and agronomic traits

Introduction

Pigeon pea (Cajanus cajan [L.] Millsp.), also known as red gram or Arhar, is the second most important pulse crop in India after chickpea. It belongs to the family Leguminosae, with a chromosome number of 2n=22. Pigeon pea is an excellent protein source (20-22%) and is primarily consumed as dry split dhal. In 2017-18, India cultivated pigeon pea on 4.42 million hectares, yielding 4.02 million tons, with Madhya Pradesh contributing significantly (647,000 hectares; 897,000 tons; yield: 1,247 kg/ha). The crop is grown as a sole crop or intercrop with cereals and oilseeds across states like Maharashtra, Karnataka, and Madhya Pradesh. Apart from food, pigeon pea serves as feed, fuel, fertilizer (fixing nitrogen), and material for baskets and fences. Despite its high potential yield (2,500-3,000 kg/ha), productivity remains stagnant (~700 kg/ha) due to biotic (e.g., wilt, pod borer) and abiotic (e.g., drought, erratic rainfall) stresses, coupled with limited adoption of improved management practices. Pigeon pea has also suffered a loss of genetic variability due to domestication. Breeding efforts focus on developing stress-resistant, high-yielding genotypes and analyzing genetic parameters like GCV, heritability, and genetic advance. As pulses play a critical role in nutrition and soil health through nitrogen fixation, a holistic approach to develop region-specific varieties and technologies is essential to meet the rising demand, stabilize production, and improve per capita availability.

Materials and Methods

The Experiment was conducted at Agriculture Farm, Nana Ji Deshmukh New Agriculture Campus, Mahatma Gandhi Chitrakoot Gramodaya Vishwavidyalaya, Chitrakoot, Satna to evaluate the thirty two genotypes/varieties under normal soil and rain fed condition. The experiment was laid out fallowing Randomized Block Design (RBD) with three replications The plant to plant distance was maintained 25cm by thinning. Recommended agronomic cultural practices and plant protection measures were adopted to raise a best crop. Observations were recorded for five randomly selected plants from each replication for 10 characters, including days to 50% flowering, days to maturity, plant height (cm), number of primary branches per plant, number of secondary branches per plant, number of pods per plant, seed yield per plant (g), number of seeds per pod, Appropriate variances and covariances were used for calculate phenotypic and genotypic correlation coefficients (Johnson et al., 1955) [3] .

Result and Discussion

Correlation studies

The estimates of correlation coefficients among the 11 characters of pigeon pea genotypes at genotypic and phenotypic levels are given in Table 1 & 2.

In general, genotypic correlations were higher than phenotypic ones in magnitude for all the characters. The character which showed negative association at genotypic level also showed negative association at phenotypic level.

The seed yield kg/ha showed significant and positive correlation with pods/plant (0.701), secondary branches (0.685), 100-seed weight (0.365) and primary branches (0.267) exhibited positive correlation coefficient with seed yield kg/ha at genotypic level. At phenotypic level, seed yield kg/ha exhibited highly significant and positive correlation with pods/plant (0.595), secondary branches (0.573) and 100-seed weight (0.251) exhibited positive correlation coefficient with seed yield kg/ha at phenotypic level. The 100-seed weight showed significant and positive correlation with pods/plant (0.290& 0.218), secondary branches per plant (0.231 and 0.189) both at genotypic and phenotypic level. The days to maturity showed significant and positive correlation with days to 50% flowering (0.728 and 0.572);

The plant height with secondary branches per plant (0.366 and 0.331); no. of pods/plant with secondary branches per plant (0.709 and 0.677) and secondary branches per plant with primary branches (0.263 and 0.216) showed positive correlation at both genotypic and phenotypic level, respectively The seed yield or economic yield is a complex character, which manifests from multiplicative interaction of several other characters that are termed as yield components. The genetic architecture of seed yield in pigeon pea as well as other crops is based on the balance or overall net effect produced by various yield components, interaction with one another. Thus, selection for yield per se alone would not be better as such unless accompanied by the selection for various component characters responsible for conditioning it. Thus, identification of important yield components and information about their association with yield and also with each other are very useful for developing efficient breeding strategy for evolving high yielding varieties. The correlation coefficient measures the degree of association between two variables or characters, which helps in understanding the nature and magnitude of association between yield and its components.

In the present investigation, phenotypic and genotypic correlations were estimated. The direction of phenotypic and genotypic correlations was similar for almost all the characters. In general, genotypic correlations were higher than phenotypic ones in magnitude for all the characters. The character which showed negative association at genotypic level also showed negative association at phenotypic level.

The seed yield kg/ha showed significant and positive correlation with pods/plant, secondary branches, 100-seed weight and primary branches exhibited positive correlation coefficient with seed yield kg/ha at genotypic level. At phenotypic level, seed yield kg/ha exhibited highly significant and positive correlation with pods/plant secondary branches and 100-seed weight exhibited positive correlation coefficient with seed yield kg/ha at phenotypic level.

The strong positive correlation of grain yield with the characters mentioned above has also been reported earlier in pigeon pea. Parveen et al. (2011) [7] for pods per plant, harvest index and clusters per plant with seed yield, and Kumar et al. (1995) [6] for number of branches, number of clusters, number of pods per plant, number of seeds per plant, pod weight,

The 100-seed weight showed significant and positive correlation with pods/plant, secondary branches per plant both at genotypic and phenotypic level. The days to maturity showed significant and positive correlation with days to 50% flowering; The plant height with secondary branches per plant; no. of pods/plant with secondary branches per plant; and secondary branches per plant with primary branches showed positive correlation at both genotypic and phenotypic level, respectively. The strong positive correlation of grain yield with above mentioned four yield components, which were highly correlated with each other, indicates the highly favorable situation for obtaining high response through selection. Therefore, selection practiced for improving these traits individually or simultaneously is likely to bring improvement in order to correlated response. This suggests that selection would be quite effective in improving yield and yield components in pigeon pea, especially in context of germplasm collections evaluated. Positive correlation among the yield components such as those noted above has also been reported by previous workers (Kingshlin and Subbraman, 1999; Sharma et al., 1994; Dhamelia and Pathak, 1994; Patil et al., 1989) [4,9,2,8] and Kumar et al.

(1995) [6] . Baldaniya, et al.(2018) for characters days to 50 percent flowering, days to maturity, plant height, number of branches per plant, number of pods per plant, pod length, number of seeds per pod, 100-seed weight, harvest index and protein content at both genotypic and phenotypic level

Conclusion

The present study highlighted the variability and correlation among different traits in pigeon pea genotypes. Significant genetic variability was observed for important traits such as seed yield, number of pods per plant, and plant height, with moderate to high phenotypic and genotypic coefficients of variation. The strong positive correlation of seed yield with traits like the number of pods per plant, secondary branches, 100-seed weight, and primary branches indicates that these traits are critical yield components. These findings suggest that selection targeting these traits can effectively improve yield in pigeon pea breeding programs. The higher genotypic correlations observed also highlight the genetic potential of the evaluated germplasm for developing highyielding varieties.

References

1. Baldaniya JD, Kale BH, Mungra KS, Patel HN, Lad MD, Chauhan DA. Genetic variability, correlation and path analysis for morphological and quality traits in pigeonpea [Cajanus cajan (L.) Millsp.]. International Journal of Chemical Studies. 2018;6(5):2584-2587.
2. Dhamelia HR, Pathak AR. Correlation studies in segregating generations of pigeonpea. International Chickpea and Pigeonpea Newsletter. 1994;1:30-32.
3. Johnson HW, Robinson HF, Comstock RE. Genotypic and phenotypic correlations in soybean and their implications in selection. Agronomy Journal. 1955;47:477-483.
4. Kingshlin M, Subbaraman N. Character association and component analysis in F3 and full sib progenies of pigeonpea (Cajanus cajan (L.) Millsp.). Crop Research. 1999;18:84-88.
5. Kingshlin M, Subbaraman N, Chandirakala R. Studies of genetic parameters and selection response in biparental progenies of pigeonpea. Crop ResearchHisar. 1998;16:85-88.
6. Kumar SS, Sudharshanam A, Kumar SV, Reddy VN. Correlation and path coefficient analysis in green gram (Vigna radiata). Madras Agricultural Journal. 1995;82(3):160-162.
7. Hepper). International Journal of Applied Biology and Pharmaceutical Technology. 2011;2(3):619-625.
8. Patil HS, Deshmukh RB. Correlation and path analysis in mungbean. Journal of Maharashtra Agricultural Universities. 1988;13(2):183-185.
9. Sharma JD, Gupta VP. Selection parameters in interspecific derivatives of urdbean x mungbean. Indian Journal of Pulses Research. 1994;7(2):174-176.