Genomic and pedigree‐based predictive ability for quality traits in tea (Camellia sinensis (L.) O. Kuntze)

Genetic improvement of quality traits in tea ( Camellia sinensis (L.) O. Kuntze) through conventional breeding methods has been limited, because tea quality is a difficult and expensive trait to measure. Genomic selection (GS) is suitable for predicting such complex traits, as it uses genome wide ma...

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Veröffentlicht in:	Euphytica 2021-03, Vol.217 (3), Article 32
Hauptverfasser:	Lubanga, Nelson, Massawe, Festo, Mayes, Sean
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian analysis Biomedical and Life Sciences Biotechnology Breeding Breeding methods Caffeine Camellia sinensis Epicatechin Genetic improvement Genomes Genomics Genotypes Genotyping Heritability Hilbert space Life Sciences Magnetic resonance spectroscopy Markers Mathematical models Model accuracy NMR NMR spectroscopy Nuclear magnetic resonance Pedigree Plant Genetics and Genomics Plant Pathology Plant Physiology Plant Sciences Population number Prediction models Regression analysis Tea Theanine Training
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