based on principal component analysis (pca), gge biplot analysis is an effective method to fully assess multienvironmental yield trials (mets). additive main effects and multiplicative interaction (ammi) is an alternative method for assessing phenotypic stability and adaptability. in this research, met data of 14 maize inbred lines were used to perform ammi and gge biplot analyses. these genoty...

the yield performance of 23 barley (hordeum vulgare l.) genotypes in sixteen test environments across a barley growing region of china was evaluated. the experiment was conducted using a randomized complete block design with three replicates, in two cropping seasons (2010-2011, in the south; 2012-2013, in the north). the gge biplot was applied to analyze the data obtained in the multi-environme...

T HE experiment involved 48 pairs of male Holstein fraternal twin calves. Two methods of raising calves were contrasted: (A) High fat (20%) and protein (20%) vealer ration fed from 3 days of age to a market weight of 128 kilograms. (B) The same vealer was fed up to a live weight of 56.7 kg, followed by pelleted grain mixture fed ad libitum and hay offered to a maximum of 0.9 kg per day. Twin pa...

Background: It has long been recognized that bread making quality traits vary considerably as a result of genotype, environment and their interaction. The present study was aimed at determining the effect of cultivar, environment and their interaction on several bread making quality traits as well as to analyze relationship between these traits, Methods: Hundred forty wheat genotypes originated...

A G × E performance (interaction, profile) plot for showing genotype-by-environment data is discussed. Three versions of such a plot are compared: the regular performance plot; the performance plot based on coded data (environment-centered performance plot), in which the environment means of a trait are subtracted from data; and the performance plot based on data standardized in environments (e...