Barley Genotypes Evaluated under Salinity Conditions by AMMI, BLUP and Non Parametric Measures

Abstract

Highly significant variations due to environments, GxE interactions, and genotypes were observed by AMMI analysis . About 22.3% of the total sum square of variation for yield was due to environments followed by 35% of GxE interactions, whereas genotypes accounted 34.2%. AMMI1 explained a total variation of 54.9%, AMMI2 augmented about 23.7%, 11.8% for AMMI3. First two AMMI components totalled 78.7% of the total variation. Using first two IPCAs in stability analysis could benefits in identification of the stable high yielder genotypes. Dynamic concept of stability explained by ASV1 and ASV measures as both recommended (G6, G5, G12) wheat genotypes. MASV and MASV1considered all significant IPCAs of the AMMI analysis identified same genotypes G6, G5, G12. BLUP based measures BLUP-based simultaneous selections, such as HM identified G3, G4, G1 while values of PRVG favored G4, G3, G1 and HMPRVG settled for G4, G3, G1 genotypes. Non parametric composite measures NP_i⁽¹⁾ toNP_i⁽⁴⁾ found G3, G4, G5 as genotypes of choice for salinity conditions. Biplot analysis observed ASV, ASV1, MASV, MASV1 S_i¹, S_i², S_i³, S_i⁴, ,S_i⁷, accounted more of in first principal component whereas Mean, Average, GM, HM PRVG, HMPRVG, NP_i ^(2), NP_i ⁽³⁾, NP_i were major contributors in PC2. Non parametric measures NP_i⁽²⁾, NP_i⁽³⁾, NP_i⁽⁴⁾ formed one cluster whereas BLUP based measures Mean, GM, HM, PRVG, MHPRVG grouped with average yield of genotypes.