G×E effects elucidated by AMMI, BLUP and non-parametric measures of wheat genotypes evaluated in NEPZ

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. S_i², S_i⁴, S_i¹, S_i³, NP_i⁽³⁾, IPC5 contributed more in PC1 whereas for PC2 contributors were BLGM, RPGV, HMGV, HMRPGV NP_i⁽²⁾, NP_i⁽³⁾, NP_i⁽⁴⁾ . High degree of positive relationship expressed by NP_i⁽²⁾NP_i⁽³⁾, NP_i⁽⁴⁾ with MASV, MASV1. Measures S_i¹ to S_i⁷ clubbed with standard deviation, CV along with NP_i⁽¹⁾. No association of ASV & ASV1 observed with NP_i⁽²⁾NP_i⁽³⁾, NP_i⁽⁴⁾. Clustering pattern seen BLUP based measures in separate cluster while NP_i⁽²⁾ seen with S_i¹ to S_i⁷ along with standard deviation and CV measures.

• Negative correlation of composite non parametric measures with BLUP based measures as well as with AMMI based measures for the present study of wheat genotypes evaluated under late sown conditions. Non parametric measures have been observed less computationally intensive and robust against the outliers.