August 15, 2025Open Access

Combining phenomic and genomic selection for pea breeding improvement

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Analysis evaluates phenomic selection's effectiveness for yield-related traits in peas, suggesting improvements when combined with genomic methods.

Phenomic selection accurately predicts yield and seed protein content in pea breeding programs, enhancing genetic gain.
Data indicates the integrative model notably outperforms univariate approaches in predicting complex traits.
Assessment across twelve environments reveals spatial and temporal variations in predictive accuracy, with integrative models consistently excelling.
The approach provides a strategic tool for responding to growing environmental variability challenges in agriculture.

Klein et al. (2025) studied this question.

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August 15, 2025Open Access

View Full Paper

Ask AI

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Authors

Analysis evaluates phenomic selection's effectiveness for yield-related traits in peas, suggesting improvements when combined with genomic methods.

Phenomic selection accurately predicts yield and seed protein content in pea breeding programs, enhancing genetic gain.
Data indicates the integrative model notably outperforms univariate approaches in predicting complex traits.
Assessment across twelve environments reveals spatial and temporal variations in predictive accuracy, with integrative models consistently excelling.
The approach provides a strategic tool for responding to growing environmental variability challenges in agriculture.

Klein et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark