Knowledge about the extent of genotype in environment interaction is helpful for farmers and plant breeders. This because it helps them choose proper strategies agricultural management breeding new cultivars. The main contribution this paper to investigate on environmental using GGE biplot method (Genotype Genotype-by-Environment) ten canola experimental design was a randomized complete block (...

Breeding for novel genotypes with high yield and stability is a crucial objective in agriculture. Environmental factors play significant role determining genotype's response, which commonly known as genotype-by-environment interaction. In this study, multi-environment experiment three replications of twenty-nine pearl millet one year (2019) was conducted at eight locations India. The Additive m...

Our purpose was to determine the value of spring barley (Hordeum vulgare L.) cultivars and lines in terms yield its stability. The GGE biplot analysis competitive cultivar trial data used. Due biplot, relationships between under investigation with environment (years their cultivation) were visualised. mega-environment 2018 2020 most optimal one for yields from cultivars, especially Grace, Amil,...

Six maize hybrids; Khumal Hybrid-2, KML-5(A) × KYM-33, KML-8(A) KWM-91 KWM-93, KWM-92 Super-951 were evaluated in a randomized complete block design (RCBD) with three replications at Bhotechaur (Sindhupalchowk), Mandan Deupur (Kavrepalachowk), and Khumaltar (Lalitpur), Nepal to identify stable superior hybrids. Hybrids found significant (p<0.01) for grain yield. The effects of environment ge...

Yan, W. et Tinker, N. A. 2006. Biplot analysis of multi-environment trial data: Principles and applications. Can. J. Plant Sci. 86: 623–645. Biplot analysis has evolved into an important statistical tool in plant breeding and agricultural research. Here we review the basic principles of biplot analysis and recent developments in its application in analyzing multi-environment trail (MET) data, w...