Year: 2022 | Month: March | Volume 15 | Issue 1

G×E Effects Elucidated by AMMI, BLUP and Non-parametric Measures of Wheat Genotypes Evaluated in NEPZ

Ajay Verma Gyanendra Pratap Singh


Highly significant variations due to G×E interactions, environments and genotypes had been observed AMMI analysis. Values of IPCA’s in the AMMI analysis indicate stability or adaptability of genotypes. G11, G1 selected by IPCA-1 and G1, G2 as per IPCA-2. Utilizing 60.6% of G×E interactions ASV identified G1, G7 and ASV1 settled for (G1, G7) genotypes. Nearly 97.8% of variations exploited by MASV1 pointed for G9, G2 whereas MASV judged G9, G8 genotypes. BLUP based HMGV RPGV HMRPGV measures identified G11 & G3. Consistent yield of G2, G3 wheat genotypes supported by the least values of standard deviation and CV measures. Biplot analysis of studied measures observed that two significant PC’s has accounted for 65.8% of the total variation with respective percent share of 40.4% & 25.5% respectively. Si2 , Si4 , Si1 , Si3 , NPi(3) , IPC5 contributed more in PC1 whereas for PC2 contributors were BLGM, RPGV, HMGV, HMRPGV NPi(2), NPi(3), NPi(4) . High degree of positive relationship expressed by NPi(2) NPi(3), NPi(4) with MASV, MASV1. Measures Si1 to Si7 clubbed with standard deviation, CV along with NPi(1). No association of ASV & ASV1 observed with NPi(2) NPi(3) , NPi(4). Clustering pattern seen BLUP based measures in separate cluster while NPi(2) seen with Si1 to Si7 along with standard deviation and CV measures.

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  • AMMI, BLUP, Non parametric composite measures, Biplot analysis

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