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A Nonparametric Analysis for Stability of Wheat Genotypes Tested in Southern Punjab, Pakistan

Mariam Hameed, Syed Haider Shah, Hadi Hassan Khan


The objective of our study is to investigate the relationship amongst nonparametric stability statistics. Genotype environment interaction (G × EI) of eighteen genotypes wheat, tested at seven locations was interpreted by non-parametric measures. Different nonparametric measures for (G×EI) on the grain yield data of eighteen wheat’s genotypes were selected from NUWYT in the year 2016-17 in Pakistan. The experiments were conducted in Randomized Completely Block Design (RCBD) and were replicated twice at each location. The nonparametric steps were used to attain improvement for G×EI at (P < 0.01) which recommended the various interaction of the wheat’s genotype to be tested in each environment. Rank correlation by Spearman was applied to calculate the relationship amongst the stability of statistics with (PCA) biplot. The results of (PCA) and correlation analysis of nonparametric stability measures indicate to select stable and highly yield genotype by using Si1, Si2, Si3 and Si6 (Huehn, 1979), the NPi1, NPi2, NPi3 and NPi4 (Thennarasu.1995) and rank sum (Kang’s 1988).  G16, G1 and G5, were found to be the most stable genotypes and G10 was unstable


(G × EI) Genotype Environment Interaction, (PCA) Principal Component Analysis, ANOVA, Multi Environment Trial, Graphical

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