Genetic trends and multivariate interrelationships for grain quality of irrigated rice genotypes

For genetic improvement programs, researches with multivariate approaches in rice are fundamental, to define trends, clusters and correlations of agronomic characters that together help selection procedures. This work aimed reveal the performance, trends interrelationships grain quality based on models applied elite lines irrigated rice. The experiment took place 2017/2018 harvest, held at Estação Experimental Terras Baixas (ETB), Embrapa Clima Temperado. study used randomized blocks design, three replications. There were fifteen F6 four control cultivars. Evaluation intrinsic physical attributes aid S21 statistical analyzer, as well yield mill (whole broken grains). Performance analysis variance, parameters Scott Knott cluster test, linear correlation, canonical correlations, via generalized Mahalanobis distance, using Toucher method, addition BIPLOT principal component analysis. results showed PH18502 PH18701 strains presented better performance for studied characters, by univariate demonstrate potential direction multiple point possibility indirect among relevant production chain