title: High-quality green tea leaf production by artificial cultivation under growth chamber conditions considering amino acids profile.
abstract: The current study focused on the tea plant (Camellia sinensis) as a target for artificial cultivation because of the variation in its components in response to light conditions. We analyzed its sensory quality by multi-marker profiling using multicomponent data based on metabolomics to optimize the conditions of light and the environment during cultivation. From the analysis of high-quality tea samples ranked in a tea contest, the ranking predictive model was created by the partial least squares (PLS) regression analysis to examine the correlation between the amino-acid content (X variables) and the ranking in the tea contest (Y variables). The predictive model revealed that glutamine, arginine, and theanine were the predominant amino acids present in high-ranking teas. Based on this result, we established a cover-culture condition (i.e., a low-light intensity condition) during the later stage of the culture process and obtained artificially cultured tea samples, which were predicted to be high-quality teas. The aim of the current study was to optimize the light conditions for the cultivation of tea plants by performing data analysis of their sensory qualities through multi-marker profiling in order to facilitate the development of high-quality teas by plant factories.
authors.affiliation: Corporate Research and Development Division, Sharp Corporation, 2613-1 Ichinomoto-cho, Tenri, Nara 632-8567, Japan.
authors.forename: Shunsuke
authors.initials: S
authors.lastname: Miyauchi
authors.affiliation: Corporate Research and Development Division, Sharp Corporation, 2613-1 Ichinomoto-cho, Tenri, Nara 632-8567, Japan.
authors.forename: Takayuki
authors.initials: T
authors.lastname: Yuki
authors.affiliation: Corporate Research and Development Division, Sharp Corporation, 2613-1 Ichinomoto-cho, Tenri, Nara 632-8567, Japan.
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Fuji
authors.affiliation: Corporate Research and Development Division, Sharp Corporation, 2613-1 Ichinomoto-cho, Tenri, Nara 632-8567, Japan.
authors.forename: Kunio
authors.initials: K
authors.lastname: Kojima
authors.affiliation: Corporate Research and Development Division, Sharp Corporation, 2613-1 Ichinomoto-cho, Tenri, Nara 632-8567, Japan.
authors.forename: Tsutomu
authors.initials: T
authors.lastname: Yonetani
authors.affiliation: Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan.
authors.forename: Ayako
authors.initials: A
authors.lastname: Tomio
authors.affiliation: Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan.
authors.forename: Takeshi
authors.initials: T
authors.lastname: Bamba
authors.affiliation: Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan. Electronic address: fukusaki@bio.eng.osaka-u.ac.jp.
authors.forename: Eiichiro
authors.initials: E
authors.lastname: Fukusaki
mesh_terms: D000596:Amino Acids / Q000032:analysis* / Q000378:metabolism; D028241:Camellia sinensis / Q000737:chemistry* / Q000254:growth & development* / Q000378:metabolism / Q000528:radiation effects; D005971:Glutamates / Q000032:analysis; D016018:Least-Squares Analysis; D055432:Metabolomics; D010936:Plant Extracts / Q000032:analysis / Q000737:chemistry; D018515:Plant Leaves / Q000737:chemistry / Q000254:growth & development / Q000378:metabolism / Q000528:radiation effects; D013662:Tea / Q000737:chemistry* / Q000592:standards*
chemical_list: D000596:Amino Acids; D005971:Glutamates; D010936:Plant Extracts; D013662:Tea; C026166:theanine
keywords: Camellia sinensis; Metabolomics; Plant factory; Prediction model; Quality of green tea