ArticleThe plant genome2026
Optimizing multi-trait selection for profitability in Illinois wheat using a factor analytic mixed model and an economic selection index.
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.
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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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1 citing paper in PubMed.
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3 authors.
Funding
Abstract
Economic selection indices can improve the efficiency of selection for multiple traits, but they are underutilized in plant breeding due to limited research on the economic values of traits and a lack of well-documented case examples employing economic indices. This study evaluated a genomic-based Smith-Hazel index incorporating empirically derived economic weights for grain yield, test weight, and maturity in soft red winter wheat (Triticum aestivum L.) in Illinois. Economic weights used in the index were estimated using a function describing expected profit considering the predominant cropping system and grain quality pricing scheme of the region. Data from 2995 genotypes, five traits, and 12 environments (2022-2024) were analyzed together with genome-wide marker data using a factor analytic (factor analytic model with k factors [Fak]) model fitted to the environment-by-trait combinations to obtain predictions of breeding value. The optimal multi-trait multi-environment (MTME) model (FA5) explained over 91% of the additive genetic variance and achieved high prediction accuracy (≥0.95). Compared with a single-trait multi-environment (STME) model, use of an MTME model for index selection increased predicted economic return by 3.4% ($120 ha
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