Int.J.Curr.Microbiol.App.Sci (2017) 6(10): 166-173 166 Original Research Article https://doi.org/10.20546/ijcmas.2017.610.021 Principal Component Analysis of Chickpea (Cicer arietinum L.) Germplasm Renuka Shivwanshi * and Anita Babbar Department of Plant Breeding and Genetics, College of Agriculture, J.N.K.V.V. Jabalpur, (M.P.) 482004, India *Corresponding author ABSTRACT Introduction Chickpea is a cool season legume crop and is grown in several countries worldwide as a food source. Chickpea is the third most important food legume crop and India is the largest producer contributing to 65% of world’s chickpea production: it imports chickpea from other countries. However the ever-increasing demand for this legume crop; it is essential to improve the production and area under cultivation. The area under chickpea cultivation decreased due to lack of high yielding varieties and susceptibility to insects and diseases (Hameed et al., 2009). The yield of chickpea can be improved by selection of superior genotypes which is directly related with the seed yield and utilize these genotypes exclusively in breeding programs to enhance grain yield. Yield is a complex trait which is affected by several factors and environment hence a well-known technique was introduce known as principal component analysis which identified and prioritizes the important traits to minimise the number of traits for effective selection. PCA is a standard tool in modern data analysis because it is a simple, non-parametric method International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 10 (2017) pp. 166-173 Journal homepage: http://www.ijcmas.com In order to define selection criteria 434 chickpea genotypes were evaluated under rain-fed conditions during 2015-16 rabi season. Selection of genotypes and traits based on Principal Component analysis. Out of thirteen PCS’s identified first 8 PC accounted for 77.68% of the total variation. The PC1 explained 26.57 % of total variation. While PC2, PC3, PC4, PC5, PC6, PC7 and PC8 exhibited 13.58%, 8.45%, 6.54%, 5.48%, 6.03, 4.37 and 3.66% variability, respectively. Genotype IC 84037 was commonly found in PC 1, PC3, PC 6 and PC7 followed by IC 84037 in PC 1, PC 3, PC 6 and PC 7, IC 83812 in PC 1, PC 2, PC 3, and PC 7, IC 83372 in PC 1, PC 3, PC 5, and PC 7, IC83592 in PC 1, PC 4, PC 5 and PC 7, similar type of genotypes on a common principal component permitting to designate them as seed yield factors. These genotypes may further be utilized in breeding programmes for improving seed yield these genotypes can be considered an ideotype breeding material for selection of traits viz more total number of seed per plant, more effective pods per plant and high biological yield per plant and further utilization in precise breeding programme. The maximum PC value was found in genotype IC 84037 (9.79) followed by, IC 83812(8.46), EC 489919(7.70), IC 83387 (6.42), IC 83813 (6.24). This result has been suggested that these genotypes would be of practical value to chickpea breeders in identifying the genotype with desired trait for utilization in breeding program for genetic improvement. Keywords Chickpea, Eigen value, Principal component Analysis. Accepted: 04 September 2017 Available Online: 10 October 2017 Article Info