Banca de QUALIFICAÇÃO: Marcos Corbellini

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
DISCENTE : Marcos Corbellini
DATA : 26/04/2022
HORA: 08:00
LOCAL: Videoconferência
TÍTULO:

GEOGRAPHIC ADAPTABILITY OF SOYBEAN TO BRAZIL'S SOJÍCOLA MACROREGION 4

PALAVRAS-CHAVES:

Regression-Kriging; Environmental covariates; Geostatistics

PÁGINAS: 18
GRANDE ÁREA: Ciências Agrárias
ÁREA: Agronomia
RESUMO:

Brazil is the largest producer of soybeans, with more than 30% of the world production in the 2019/20 crop, 

being the main oilseed cultivated in the world. Currently, soybean production in the country covers practically

 all regions, resulting in high environmental diversity for cultivation. The environment has a great influence 

on the phenotypic behavior of the species, especially through factors such as: water availability, temperature, 

photoperiod and altitude. Multi-environmental experiments associated with geostatistical techniques, with the 

help of environmental variables, can support the understanding of this complex interaction genotype, environment 

and adaptive limits. We can say that the most expensive and laborious phase within a breeding program is the 

evaluation of genotypes in different environments, thus limiting the size of the breeding program to its 

experimental evaluation capacity. Studying adaptability and stability contributes to the identification of 

genotypes with predictable behavior that undergo few changes according to environmental variations, 

ensuring the selection of materials with better stability and predictability of productivity within the target 

region. Thus, the objective of the present study is to understand the adaptation of soybean cultivars in

 the Sojícola Macroregion 4 of Brazil through the spatialization of productivity, in order to know the adaptive 

geographic limits. Information from yield trials, from the Syngenta Seeds soybean breeding program, 

conducted in 40 locations belonging to the Sojícola Macroregion 4, from the 2018/2019, 2019/2020 and 

2020/2021 crop years will be used. The experimental design adopted will be complete randomized blocks, 

in three replications, with a set of 30 genotypes. The data will be submitted to the adjustment of means and 

productivity prediction, as well as to obtain the genotypic and environmental effects. After adjusting the model

 and obtaining the genotypic effects and adjusted means, the Regression-Kriging method will be applied.

MEMBROS DA BANCA:
Presidente - 131995001 - CELICE ALEXANDRE SILVA