Designing an Index for Multi-location Yield Stability Analysis Involving Univariate and Multivariate Methods in Rice (Oryza sativa L.)

Abstract

Under different environmental conditions, crop yields differ primarily due to G and E interactions. The Global Rice Array (GRA-IV) is IRRI's fourth flagship project to identify climate-resilient rice genotypes. Use of Several univariate and multivariate methods can differentiate genotypes based on their behaviour under different environmental conditions. Since genotypes were ranked differently across models, ASR and Yield Stability Index (YSI) were combined in this study. It included 15 rice genotypes (from a collection of global rice arrays IV called the "Antenna Panel"). Experimentation done in five diverse environments in the Northern Tarai region of India. Grain yield over five diverse environments was significantly influenced by genotypes, G (24.51%), environments, E (40.79%), and genotype and environment effects combined (34.69%). G2, G5, G8, G15 and G10 exhibited lowest ASR values. G2 is the most stable high-yielder, concluded on the basis of new stability index calculated by combining the ASR's and YSI values; these superior genotypes can benefit breeding programs in the future. A stable-high yielder can be more accurately predicted with the new stability index.

Keywords:
AMMI, Rice-yield; Multi-environment evaluation; Stability; Non-Parametric; Parametric

HIGHLIGHTS

"Antenna Panels" characterize the changing climate dynamics through the crop’s eye.

New stability index can decipher stability more accurately.