ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2022
Phenomic selection in wheat breeding: identification and optimisation of factors influencing prediction accuracy and comparison to genomic selection.
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Phenomics-assisted sparse testing for potato breeding.Scientific reports · 2026Article
- Comparing statistical 'phenomic prediction' models for remote-sensing-based phenotyping of maize susceptibility to common rust.Plant phenomics (Washington, D.C.) · 2025Article
- Genomic and hyperspectral imaging-based prediction blending enables selection for reduced deoxynivalenol content in wheat grains.G3 (Bethesda, Md.) · 2025Article
- Genomic Prediction in a Self-Fertilized Progenies ofPlants (Basel, Switzerland) · 2025Article
- Genomic and phenomic prediction for soybean seed yield, protein, and oil.The plant genome · 2025Article
- Integrating phenomic selection using single-kernel near-infrared spectroscopy and genomic selection for corn breeding improvement.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Using phenomic selection to predict hybrid values with NIR spectra measured on the parental lines: proof of concept on maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Genomic prediction for yield and malting traits in barley using metabolomic and near-infrared spectra.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Using near-infrared spectroscopy (NIRS) to predict budbreak of the following year.Quantitative plant biology · 2025Article
- Drought-tolerant wheat for enhancing global food security.Functional & integrative genomics · 2024Review
- Quantifying Genetic Parameters for Blackleg Resistance in Rapeseed: A Comparative Study.Plants (Basel, Switzerland) · 2024Article
- Integrating genomics, phenomics, and deep learning improves the predictive ability for Fusarium head blight-related traits in winter wheat.The plant genome · 2024Article
- Feature engineering and parameter tuning: improving phenomic prediction ability in multi-environmental durum wheat breeding trials.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Genomic and phenomic predictions help capture low-effect alleles promoting seed germination in oilseed rape in addition to QTL analyses.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Near-infrared reflectance spectroscopy phenomic prediction can perform similarly to genomic prediction of maize agronomic traits across environments.The plant genome · 2024Article
- Optimizing selection based on BLUPs or BLUEs in multiple sets of genotypes differing in their population parameters.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Using drone-retrieved multispectral data for phenomic selection in potato breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Genomic prediction for agronomic traits in a diverse Flax (Linum usitatissimum L.) germplasm collection.Scientific reports · 2024Article
- Multispectral-derived genotypic similarities from budget cameras allow grain yield prediction and genomic selection augmentation in single and multi-environment scenarios in spring wheat.Molecular breeding : new strategies in plant improvement · 2024Article
- Performance of phenomic selection in rice: Effects of population size and genotype-environment interactions on predictive ability.PloS one · 2024Article
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Authors and funding
9 authors.
Funding
Abstract
key messagePhenomic selection is a promising alternative or complement to genomic selection in wheat breeding. Models combining spectra from different environments maximise the predictive ability of grain yield and heading date of wheat breeding lines. Phenomic selection (PS) is a recent breeding approach similar to genomic selection (GS) except that genotyping is replaced by near-infrared (NIR) spectroscopy. PS can potentially account for non-additive effects and has the major advantage of being low cost and high throughput. Factors influencing GS predictive abilities have been intensively studied, but little is known about PS. We tested and compared the abilities of PS and GS to predict grain yield and heading date from several datasets of bread wheat lines corresponding to the first or second years of trial evaluation from two breeding companies and one research institute in France. We evaluated several factors affecting PS predictive abilities including the possibility of combining spectra collected in different environments. A simple H-BLUP model predicted both traits with prediction ability from 0.26 to 0.62 and with an efficient computation time. Our results showed that the environments in which lines are grown had a crucial impact on predictive ability based on the spectra acquired and was specific to the trait considered. Models combining NIR spectra from different environments were the best PS models and were at least as accurate as GS in most of the datasets. Furthermore, a GH-BLUP model combining genotyping and NIR spectra was the best model of all (prediction ability from 0.31 to 0.73). We demonstrated also that as for GS, the size and the composition of the training set have a crucial impact on predictive ability. PS could therefore replace or complement GS for efficient wheat breeding programs.
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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.