ArticleThe plant genome2026
Optimizing genomic predictions in maize using a diversity panel and a multiparental population.
Article in The plant genome, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Optimizing genomic predictions in maize using a diversity panel and a multiparental population.The plant genome · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
Genomic selection allows the prediction of genetic values using SNP markers distributed across the genome. Its effectiveness depends on factors such as trait heritability, genetic similarity between training and validation sets, and population structure. Although results in homogeneous populations have been promising, its application in diverse germplasm remains a challenge. This study evaluates the predictive capacity of genomic best linear unbiased prediction models applied to agronomic and biochemical-structural traits related to stover quality in two maize populations: a diversity panel and a multiparental advanced generation inter-cross (MAGIC) population. Higher heritability was observed in the panel, especially for flowering traits (h
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.