Heterotic group classification and heterosis prediction in recombinant maize inbred lines

For grain yield heterosis in maize, it is concluded that: (1) HSGCA is the most suitable method for heterotic group classification; (2) GD is a robust molecular predictor of heterosis; and (3) the predictive power of GD is maximized within the Tropical × Reid inter-group heterotic pattern, which offers a clear framework for future breeding programs. © 2026 Society of Chemical Industry.

Authors

Institutions

Publication Details

Journal
Journal of the Science of Food and Agriculture
Published
2026-02-01
DOI
https://doi.org/10.1002/jsfa.70490
Primary Topic
Genetic Mapping and Diversity in Plants and Animals
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Heterotic group classification and heterosis prediction in recombinant maize inbred lines

XingFu Yin, Ranjan Kumar Shaw, Ruijia Guo, Fuyan Jiang et al.
Journal of the Science of Food and Agriculture
Genetic Mapping and Diversity in Plants and Animals
article

Heterotic group classification and heterosis prediction in recombinant maize inbred lines

XingFu Yin, Ranjan Kumar Shaw, Ruijia Guo, Fuyan Jiang, Xingming Fan, Jiachen Sun, Babar Ijaz, Yuanqu Ma
article en

Abstract

For grain yield heterosis in maize, it is concluded that: (1) HSGCA is the most suitable method for heterotic group classification; (2) GD is a robust molecular predictor of heterosis; and (3) the predictive power of GD is maximized within the Tropical × Reid inter-group heterotic pattern, which offers a clear framework for future breeding programs. © 2026 Society of Chemical Industry.

Journal of the Science of Food and Agriculture
Yunnan Agricultural University (CN), Yunnan Academy of Agricultural Sciences (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 66%
Genetic Mapping and Diversity in Plants and Animals
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.