Vol. 8 (1) : January-February 2017 issue
Green Farming Vol. 8 (1) : 16-19 ; January-February, 2017
Principal component analysis of submergence related traits in landraces of rice (Oryza sativa L.)
RAJESH KUMARa1*, NILMANI PRAKASHb2, U.K SINGHa3 and NEERAJ KUMARa4
aDepartment of Plant Breeding and Genetics, bDepartment of Agricultural Biotechnology and Molecular Biology, Rajendra Agricultural University, Pusa – 848 125, Samastipur (Bihar)
Designation : 1,3Asstt. Professor *(rajrau.2007@rediffmail.com), 2,4Research Scholar
Subject : Crop Genetics and Plant Breeding
Paper No. : P-5021
Total Pages : 4
Received : 08 April 2016
Revised accepted : 18 December 2016
First Page
Citation :
RAJESH KUMAR, NILMANI PRAKASH, U.K. SINGH and NEERAJ KUMAR. 2017. Principal component analysis of submergence related traits in landraces of rice (Oryza sativa L.). Green Farming Vol. 8 (1) : 16-19 ; January-February, 2017
ABSTRACT
Genetic diversity was assessed in 184 land races including four checks using principal component analysis to assess the extent and pattern of genetic divergence based on k-mean determination. Principle component analysis (PCA) showed the first four PCs had Eigen value >1.00 and accounted 73.98% of total variation. Rotated component matrix revealed that each principal component is separately loaded with various submergence tolerant related traits.PC1 was constituted by tiller per plant (0.47), panicle length (0.43), fertile tiller per plant (0.40) and survival % (0.37) while PC2 was mainly composed of tolerance score (0.53) therefore, intensive selection procedures can be designed to bring about rapid improvement of submergence tolerance by selecting the lines from PC1, PC2 and PC3 .All 184 land races were grouped into 14 clusters. Cluster II and IV showed high mean for most of the characters indicating land races from these groups can be used for further improvement of traits. 3 D plot based on three top principal components indicated that Pecalo, Houra Kani and S-177 were most divergent land races from Karabonka, Tiebimah and Urarkaruppan which might be utilized effectively in breeding programme for submergence tolerance
Key words :
Eigen value, Genetic diversity, K-Mean clustering, Rice, Tolerance Score, Trait optimization.