Digital phenotyping and genotype-to-phenotype (G2P) models to predict complex traits in cereal crops

• Egile nagusia: Virlet, Nicolas (auth)
• Beste egile batzuk: Lyra, Danilo H. (auth), Hawkesford, Malcolm J. (auth)
• Formatua: Baliabide elektronikoa Liburu kapitulua
• Hizkuntza: ingelesa
• Argitaratua: Cambridge Burleigh Dodds Science Publishing 2022
• Saila: Burleigh Dodds Series in Agricultural Science
• Gaiak: Agronomy & crop production; Sustainable agriculture; Plant physiology; Phenomics; field phenotyping; G2P; modelling; envirotyping; breeding
• Sarrera elektronikoa: OAPEN Library: download the publication; OAPEN Library: description of the publication

Gaia

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.

Deskribapen fisikoa

1 electronic resource (40 p.)

ISBN

AS.2022.0102.12
9781801463126

Sartu

Open Access