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oapen-20.500.12657-615242024-03-27T14:14:33Z Digital phenotyping and genotype-to-phenotype (G2P) models to predict complex traits in cereal crops Virlet, Nicolas Lyra, Danilo H. Hawkesford, Malcolm J. Phenomics field phenotyping G2P modelling envirotyping breeding thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TV Agriculture and farming::TVK Agronomy and crop production thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TV Agriculture and farming::TVF Sustainable agriculture thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PST Botany and plant sciences The revolution in digital phenotyping combined with the new layers of omics and envirotyping tools offers great promise to improve selection and accelerate genetic gains for crop improvement. This chapter examines the latest methods involving digital phenotyping tools to predict complex traits in cereals crops. The chapter has two parts. In the first part, entitled “Digital phenotyping as a tool to support breeding programs”, the secondary phenotypes measured by high-throughput plant phenotyping that are potentially useful for breeding are reviewed. In the second part, “Implementing complex G2P models in breeding programs”, the integration of data from digital phenotyping into genotype to phenotype (G2P) models to improve the prediction of complex traits using genomic information is discussed. The current status of statistical models to incorporate secondary traits in univariate and multivariate models, as well as how to better handle longitudinal (for example light interception, biomass accumulation, canopy height) traits, is reviewed. 2023-02-27T12:21:45Z 2023-02-27T12:21:45Z 2022 chapter ONIX_20230227_9781801463126_36 9781801463126 https://library.oapen.org/handle/20.500.12657/61524 eng Burleigh Dodds Series in Agricultural Science application/pdf Attribution 4.0 International 9781801463126_web.pdf Burleigh Dodds Science Publishing Burleigh Dodds Science Publishing 10.19103/AS.2022.0102.12 10.19103/AS.2022.0102.12 9f8f6c63-e2ae-40b8-8aac-316abb377d6a 7c1b4f65-1bfe-4cea-9a5b-326d0b422637 9781801463126 Burleigh Dodds Science Publishing 40 Cambridge [...] Rothamsted Research Rothamsted open access
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The revolution in digital phenotyping combined with the new layers of omics and envirotyping tools offers great promise to improve selection and accelerate genetic gains for crop improvement. This chapter examines the latest methods involving digital phenotyping tools to predict complex traits in cereals crops. The chapter has two parts. In the first part, entitled “Digital phenotyping as a tool to support breeding programs”, the secondary phenotypes measured by high-throughput plant phenotyping that are potentially useful for breeding are reviewed. In the second part, “Implementing complex G2P models in breeding programs”, the integration of data from digital phenotyping into genotype to phenotype (G2P) models to improve the prediction of complex traits using genomic information is discussed. The current status of statistical models to incorporate secondary traits in univariate and multivariate models, as well as how to better handle longitudinal (for example light interception, biomass accumulation, canopy height) traits, is reviewed.
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