Correlation and Path Analysis Studies in Mungbean [Vigna radiata (L.) Wilczek] under Arid Environment of Western Rajasthan

Mungbean [Vigna radiata (L.) Wilczek; 2n=22], belonging to the family Fabaceae and sub-family Papilionaceae, is a self-pollinating diploid grain legume. It is an important multipurpose pulse crop extensively cultivated in arid, semi-arid and sub-tropics. It can be grown in various crop rotation practices because of its short-duration nature, wider adaptability, low water requirement and photo insensitiveness (Singh et al., 2015).
 
Mungbean is an essential dietary component in India. It is the cheapest source of protein and provides nutritional security to vegetarians. It is also consumed in the preparation of other food products like Papad, Namkeen, Mangori, Dal vada, etc. Mung Ki Dal Ki Khichadi made with mungbean Dal and rice is easily digestible and therefore always recommended by doctors for sick people (Sharma, 2016).
 
India is the principal producer of mungbean in the world with an annual production of 3.17 million tonnes from an area of 5.5 million hectares with productivity of 570 kg/ha. The Mungbean alone accounts for 10% of production and 16% of the area for all pulses. In India, it is mainly grown in Rajasthan, Madhya Pradesh, Maharashtra, Karnataka, Uttar Pradesh, Bihar, Tamil Nadu, Gujarat, Haryana, Punjab and Andhra Pradesh (Anonymous, 2022a). Rajasthan occupies the first position in the area and production of mungbean in India. In Rajasthan, it is cultivated on 25.60 lakh hectare area with the production of 9.05 lakh tonne and productivity of 354 kg/ha. Major mungbean growing districts of Rajasthan are Nagaur, Jodhpur, Churu, Pali, Jaipur, Ajmer, Jalor and Tonk (Anonymous, 2022b).
 
Though India is a leading producer of green gram in the world its productivity is very low as compared to its potential production. Therefore, there is great scope for its improvement by developing high-yielding, disease and pest resistance varieties with improved nutritional value. Development of high-yielding cultivars requires knowledge of the existing genetic variation and also the extent of association among yield contributing characters.
 
Yield is a complex dependent character and is contributed by several components. Correlation coefficient analysis is a statistical technique that measures the degree and association between two or more variables. Estimates of the correlation coefficient are useful in identifying the component traits that can be used for yield improvement of mungbean. Correlation studies simply measure the association of yield and yield attributes and do not give the actual dependence of yield on the correlated characters. Path coefficient analysis provides a thorough understanding of the contribution of various characters by partitioning the correlation coefficient into components of direct and indirect effects (Wright, 1921), which helps the breeder in determining the yield components. To accumulate the optimum contribution of yield-contributing characters, it is essential to know the association of various characters along with path coefficients (Bhutia et al., 2016). Path coefficient analysis is an effective method to determine the direct and indirect causes of association and also permits to examine the specific forces acting to produce a given correlation.
 
Therefore, in the present study, an effort has been made to generate information on the association of yield with its different component measures through correlation and path analysis so that an appropriate selection strategy can be formulated for evolving suitable genotypes of mungbean for arid zones.

The present investigation was carried out at the Experimental farm, Department of Genetics and Plant Breeding, College of Agriculture, Swami Keshwanand Rajasthan Agricultural University, Bikaner during Kharif, 2017-18. The experimental material consisting of 79 genotypes procured from NBPGR, Regional Station, Jodhpur; Rajasthan Agricultural Research Institute, Durgapura, Jaipur; Agricultural Research Station, Sriganganagar and Agricultural Research Station, Mandor, Jodhpur is given in Table 1. The germplasm of mungbean was evaluated in randomized block design with three replications accommodating 3 meters long two rows per replication at 30 cm spacing under sprinkler irrigated situation. All recommended agronomic practices were adopted to raise a healthy crop. Observations recorded for 11 characters viz., days to 50 per cent flowering, days to maturity, plant height, number of branches per plant, number of pods per plant, number of seeds per pod, pod length, 100-seed weight, biological yield per plant, seed yield per plant and harvest index. The data on days to 50 per cent flowering and days to maturity were recorded on plot basis, while five randomly selected plants from each of the entries were selected for recording the remaining observations.


 
Analysis of variance was calculated by the method suggested by Panse and Sukhatme (1985). Phenotypic and genotypic correlation coefficients were worked out as per the procedure outlined by Burton and Devane (1953) and Johnson et al., (1955). Direct and indirect effects of component traits on grain yield were worked out using the correlation coefficient of various traits as suggested by Wright (1921) and elaborated by Dewey and Lu (1959). 

The analysis of variance (Table 2) revealed significant differences among seventy-nine diverse genotypes for all eleven characters studied indicating the presence of significant variability in the materials thereby justifying the selection of the experimental materials. The phenotypic and genotypic correlation among the yield and yield components in mungbean are presented in Table 3. A significant correlation of characters suggested that there is much scope for direct and indirect selection for further improvement. In general, the estimates of genotypic correlation coefficient were higher than their corresponding phenotypic ones thereby suggesting inherent association among the characters studied. In the present investigation, seed yield per plant had significant and positive correlation with number of pods per plant, biological yield per plant, harvest index, number of seeds per pod and pod length at phenotypic level. Therefore, selection for seed yield per plant may be done by taking biological yield per plant, number of pods per plant, harvest index, number of seeds per pod and pod length into account. These characteristics may be emphasized for the mungbean breeding programme. Significantly positive correlation in seed yield per plant with number of seeds per pod and number of pods per plant have earlier been reported by Bisht et al., (2014) and Bhutia et al., (2016); Choudhary et al., (2016) for biological yield per plant. Significantly positive correlation in seed yield per plant with harvest index was earlier reported by Gadakh et al., (2013); Katiyar et al., (2015); Jadhav et al., (2019) and Gaur et al., (2021).

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The phenotypic correlation coefficient of days to 50 per cent flowering, days to maturity, plant height and number of branches per plant with seed yield per plant was found significantly negative which suggests its use in breeding programme for earliness and dwarfness. Significantly negatively correlation in seed yield per plant and for 50 per cent flowering, plant height and number of branches per plant was earlier reported by Khanpara et al., (2012) and Bisht et al., (2014). Significantly negatively correlation in seed yield per plant and days to maturity was earlier reported by Khanpara et al., (2012).
 
Path coefficient analysis was carried out by taking seed yield as a dependent variable to partition the correlation coefficient into direct and indirect effects to determine the contribution of different characters toward the seed yield. The result of present investigation on path coefficient analysis is presented in Table 4 revealed that direct and positive effect on seed yield per plant was observed for characters like biological yield per plant, harvest index, number of pods per plant, pod length, number of seeds per pod, plant height, 100 seed weight, days to 50 per cent flowering, respectively. Therefore, selection based on these component traits would results improvement in seed yield of mungbean.

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Direct positive effect on seed yield through biological yield and harvest index was earlier reported by Gadakh et al., (2013) and Choudhary et al., (2016); for number of pods per plant, number of seeds per pod, pod length, plant height and 100- seed weight was earlier reported by Bhutia et al., (2016), Choudhary et al., (2016) and Dhunde et al., (2021) in mungbean.
 
Days to maturity and number of branches per plant had negative direct effect on seed yield per plant; similar findings were reported by Kumar et al., (2004) and Choudhary et al., (2016) in mungbean.
 
The low value of residual effect at phenotypic (0.1723) and genotypic (0.1620) levels indicates that the characters studied in the present investigation had major contribution towards seed yield and therefore, other remaining characters have little contribution towards seed yield in mungbean.
 
Hence, the present study reveals that number of pods per plant, biological yield per plant, harvest index, number of seeds per pod, 100-seed weight and pod length are important agronomic traits as they have directly contributed towards seed yield; plant height and days to 50 per cent flowering also had direct effect on seed yield. Therefore, selection based on these component traits would results improvement in seed yield of mungbean.

In the light of above findings, it may be concluded that improvement in the characters like number of pods per plant, biological yield per plant, harvest index, number of seeds per pod, 100-seed weight, plant height, pod length, days to maturity and number of branches per plant will help in improving the seed yield in mungbean directly. Therefore, these characters should be considered for yield improvement in the mungbean breeding programme.

I am extremely grateful to Prof. (Dr.) N.K. Sharma, ADR (Seed), SKRAU, Biakner; Prof. (Dr.) A.K. Sharma, Head (GPB), SKRAU, Biakner for best guidance and support. I am also extremely grateful to Dr. OmVeer Singh, Principal Scientist and Officer-In-Charge, NBPGR, RS, Jodhpur; Prof. (Dr.) B.R. Chaudhary, Hon’ble Vice-Chancellor, Agriculture University; Prof. (Dr.) O.P. Khedar, O/I, MULLARP, RARI, Durgapura, Jaipur and Prof. (Dr.) Vijay Prakash, ARS, Sriganganagar for providing valuable research material for my experimentation. I am also grateful to Ravindra, Mukesh, Devendra and Smrutishree Sahoo for technical support.

All authors declare that they have no conflicts of interest.