Multi-trait random regression models increase genomic prediction accuracy for a temporal physiological trait derived from high-throughput phenotyping

Research article (PLoS ONE, 2020) · cited 32× · AI/ML
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Multi-trait random regression models increase genomic prediction accuracy for a temporal physiological trait derived from high-throughput phenotyping

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Multi-trait random regression models increase genomic prediction accuracy for a temporal physiological trait derived from high-throughput phenotyping is a scholarly article[1].

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  • Multi-trait random regression models increase genomic prediction accuracy for a temporal physiological trait derived from high-throughput phenotyping's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). Multi-trait random regression models increase genomic prediction accuracy for a temporal physiological trait derived from high-throughput phenotyping. Retrieved May 24, 2026, from https://4ort.xyz/entity/multi-trait-random-regression-models-increase-genomic-prediction-accuracy-for-a-temporal-physiological-trait-derived-fro
MLA “Multi-trait random regression models increase genomic prediction accuracy for a temporal physiological trait derived from high-throughput phenotyping.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/multi-trait-random-regression-models-increase-genomic-prediction-accuracy-for-a-temporal-physiological-trait-derived-fro.
BibTeX @misc{4ortxyz_multi-trait-random-regression-models-increase-genomic-prediction-accuracy-for-a-temporal-physiological-trait-derived-fro_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Multi-trait random regression models increase genomic prediction accuracy for a temporal physiological trait derived from high-throughput phenotyping}}, year = {2026}, url = {https://4ort.xyz/entity/multi-trait-random-regression-models-increase-genomic-prediction-accuracy-for-a-temporal-physiological-trait-derived-fro}, note = {Accessed: 2026-05-24}}
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