Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials

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Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials

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Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials. Retrieved May 24, 2026, from https://4ort.xyz/entity/nonlinear-kernels-dominance-and-envirotyping-data-increase-the-accuracy-of-genome-based-prediction-in-multi-environment-
MLA “Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/nonlinear-kernels-dominance-and-envirotyping-data-increase-the-accuracy-of-genome-based-prediction-in-multi-environment-.
BibTeX @misc{4ortxyz_nonlinear-kernels-dominance-and-envirotyping-data-increase-the-accuracy-of-genome-based-prediction-in-multi-environment-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials}}, year = {2026}, url = {https://4ort.xyz/entity/nonlinear-kernels-dominance-and-envirotyping-data-increase-the-accuracy-of-genome-based-prediction-in-multi-environment-}, note = {Accessed: 2026-05-24}}
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