GGE-BIPLOT OF MULTIVARIATE INDEX TO SELECT MAIZE PROGENIES FOR EFFICIENT ASSOCIATION WITH Azospirillum brasiliense1

Abstract

Maize is widely cultivated in Brazil, and nitrogen is a major nutrient for its yield. Azospirillum brasiliense bacteria help in plant nutrient supply; however, maize-Azospirillum symbiosis is not very efficient and requires selection of genotypes with a more efficient association. Multivariate indexes facilitate selection using a single value, and GGE-biplot analysis enables the visualization of the genotype-environment interaction from this value. The present study aimed to select progenies that effectively associate with the bacteria and study the efficiency of progeny selection using a multivariate index observed in the GGE-biplot method. The experiments were conducted in two cities in the state of Mato Grosso do Sul. In a simple 16 × 16 lattice, 256 genotypes were evaluated in the presence and absence of diazotrophic bacteria. PH, SL, SD, FI, HGM, SS, and GY were measured for the construction of a selection index. Genotypes exhibited significant genotype–environment interactions for all evaluated traits, allowing their use in the selection index. High-yield genotypes were not those with the highest selection index values. The traits GY, SD, HGM, SS, SL, and PH contributed the most to the construction of the index. The no-till system may have contributed to the weaker response of maize inoculated with Azospirillum brasiliense. Genotype 96 had the highest values of the characteristics used to calculate the GISI, along with the stability between environments.

Adaptability and stability of corn hybrids for the south of the Amazon biome via GGE biplot

“…The genotypes showed different behaviors in the studied environments with significant GEI (Table 3), due to the environmental characteristics of each site (Table 2). In this sense, the classification of each cultivar may change depending on the environment (Oliveira et al, 2019;Ceccon et al, 2021).…”

“…Therefore, from a plant breeding perspective, identifying superior genotypes for different conditions is a complex task. Thus, it is extremely important to know the nature of these interactions because this phenomenon makes it difficult to recommend varieties adapted to specific environments, as several studies on corn for Brazilian regions have addressed (Cargnelutti Filho & Guadagnin, 2018;Oliveira et al, 2019Oliveira et al, , 2020Ceccon et al, 2021;Shojaei et al, 2022).…”

“…In this sense, the GGE biplot analysis is another useful tool in the plant breeding for the evaluation of genotypes in different environments, and it has been used in stability and adaptability studies on corn (Pagliosa et al, 2015;Kaplan et al, 2017;Oliveira et al, 2019;Božović et al, 2020;Santos et al, 2021).…”