ArticlePeerJ2024
Assessment of genotype by environment and yield performance of tropical maize hybrids using stability statistics and graphical biplots.
Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Investigating the spatial adaptation for iron and zinc content using AMMI and GGE biplot model in lentil (Lens culinaris L.).BMC plant biology · 2026Article
- Physiological and Biochemical Responses of Two Major Legume Crops to Seed Priming-A Systematic Review.Plants (Basel, Switzerland) · 2026Review
- From Biodiversity to Biocompatibility: Insights from the Special Issue "Analysis and Biological Evaluation of Bioactive Compounds from Natural Sources-Second Edition".Molecules (Basel, Switzerland) · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Enhancing maize grain yield in tropical regions faces significant challenges due to variability in agroclimate, soil conditions, and agroecosystems. Understanding genotype (G) by environment (E) interaction (GEI) in plant breeding is crucial for selecting and developing high-yielding genotypes adapted to diverse environments. Methods: Ten maize hybrids, including eight candidates and two commercial varieties, were evaluated across ten environments in Indonesia using a randomized complete block design with three replications. The GEI effect and yield stability were assessed using stability statistics, additive main effects and multiplicative interaction model (AMMI), and genotype + genotype × environment (GGE) biplot methods. Results and Discussion: Analysis of variance revealed a significant GEI effect, indicating differences in hybrid responses for grain yield (GY), allowing for stability analysis. G01 showed the highest GY based on the best linear unbiased prediction (BLUP) across environments. Correlation analysis indicated strong associations between stability statistics (
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