Adaptability and stability of corn genotypes for baby corn production via GGE biplot and REML

被引：0

作者：

Nascimento, Maxwel Rodrigues ^{[1
]}

Santana, Josefa Grasiela Silva ^{[1
]}

dos Santos, Paulo Ricardo ^{[2
]}

Daher, Rogerio Figueiredo ^{[1
]}

de Souza, Alexandre Gomes ^{[1
]}

Vidal, Ana Kesia Faria ^{[1
]}

Ambrosio, Moises ^{[1
]}

de Melo, Gersia Goncalves ^{[3
]}

机构：

[1] Univ Estadual Norte Fluminense, Ctr Ciencias & Tecnol Agr, Plant Technol Lab, Av Alberto Lamego,2000,Parque Calif, BR-28013602 Campos Dos Goytacazes, RJ, Brazil

[2] Inst Fed Educ Ciencia & Tecnol Amapa, Porto Grande, Amapa, Brazil

[3] Univ Fed Rural Pernambuco, Recife, PE, Brazil

来源：

ACTA SCIENTIARUM-AGRONOMY | 2025年 / 47卷

关键词：

genotype x environment interaction; HMRPGV; ideotype; mixed models; Zea mays L; MEGA-ENVIRONMENT; SOFTWARE; HYBRIDS;

D O I：

10.4025/actasciagron.v47i1.69886

中图分类号：

S3 [农学（农艺学）];

学科分类号：

0901 ;

摘要：

Owing to the interaction between genotype and environment (G x E), selecting and developing high-yielding varieties with strong phenotypic adaptability and stability is paramount. Therefore, this study aimed to determine the efficiency of selection of corn genotypes for baby corn production based on productivity, adaptability, and stability. Eleven corn genotypes were evaluated in six municipalities in the state of Espirito Santo, Brazil in 2019. Superior genotypes were selected using the harmonic mean of the relative performance of the predicted genetic values (HMRPGV) and graphical analysis using the genotype main effect plus G x E (GGE) interaction biplot. Genotypes AG 1051 and BR 106 exhibited the best performance across environments. The HMRPGV method and ideotypes obtained through graphic analysis proved effective in selecting genotypes with high productive potential, responsiveness to environmental changes, and highly predictable behavior in the face of environmental stimuli.

引用

页数：9

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