SciELO - Scientific Electronic Library Online

vol.90 issue1Ash content, carbon and C/N ratio in paricá in function of NPK fertilizationEffectiveness of Arbuscular Mycorrhizal Fungal Isolates from the Land Uses of Amazon Region in Symbiosis with Cowpea author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand




Related links


Anais da Academia Brasileira de Ciências

Print version ISSN 0001-3765On-line version ISSN 1678-2690


SHARIFI, PEYMAN  and  EBADI, ALI AKBAR. Relationships of rice yield and quality based on genotype by trait (GT) biplot. An. Acad. Bras. Ciênc. [online]. 2018, vol.90, n.1, pp.343-356. ISSN 0001-3765.

An experiment was conducted to examine the influencing characters on rice by using 64 rice genotypes, including four local landraces, four released cultivars and 56 mutant lines (M5) derived from these genotypes, with application of the genotype by trait (GT) biplot methodology. The first two principal components (PC1 and PC2) accounted for 46.6% of total variation in 64 genotypes. The polygon view of GT biplot suggested seven sections for 64 genotypes. The vertex G38 had good amounts of grain yield, panicle length, hundred grain weight, internodes length, plant height and fertility percentage. Generally based on vector view it was demonstrated that the selection of high grain yield would be performed via thousand grain weight, panicle weight and number of filled grain per panicle. These traits should be considered simultaneously as effective selection criteria evolving high yielding rice genotypes because of their large contribution to grain yield. The genotypes G2, G4 and G7 could be considered for the developing of desirable progenies in the selection strategy of rice improvement programs. This study revealed GT biplot can graphically display the interrelationships among traits. In conclusion, it is recommended the use of GGE biplot to identify superior genotypes for simultaneous improvement of several traits.

Keywords : Grain yield; polygon view; trait associations; rice; vector view.

        · text in English     · English ( pdf )