Your browser doesn't support javascript.
loading
Development of a novel green tea quality roadmap and the complex sensory-associated characteristics exploration using rapid near-infrared spectroscopy technology.
Zuo, Yamin; Tan, Gaohao; Xiang, Di; Chen, Ling; Wang, Jiao; Zhang, Shengsheng; Bai, Zhiwen; Wu, Qing.
Afiliación
  • Zuo Y; School of Basic Medical Sciences, Hubei Key Laboratory of Wudang Local Chinese Medicine Research, Hubei University of Medicine, 30 Renmin South Rd, Shiyan, Hubei 442000, China; Guizhou Key Laboratory for Information System of Mountainous Areas and Protection of Ecological Environment, Guizhou Normal
  • Tan G; Guizhou Key Laboratory for Information System of Mountainous Areas and Protection of Ecological Environment, Guizhou Normal University, 116 Baoshan North Rd, Guiyang, Guizhou 550001, China.
  • Xiang D; The Yunnan Tea Chamber of Commerce, Panlong District, Kunming, Yunnan 650051, China.
  • Chen L; The Department of Tea, Guizhou Vocational College of Agriculture, 3 Huangshi Rd, Qingzhen, Guizhou 551400, China.
  • Wang J; Guizhou Key Laboratory for Information System of Mountainous Areas and Protection of Ecological Environment, Guizhou Normal University, 116 Baoshan North Rd, Guiyang, Guizhou 550001, China.
  • Zhang S; Guizhou Key Laboratory for Information System of Mountainous Areas and Protection of Ecological Environment, Guizhou Normal University, 116 Baoshan North Rd, Guiyang, Guizhou 550001, China.
  • Bai Z; The Guizhou Gui Tea (Group) Co. Ltd, Huaxi District, Guiyang, Guizhou 550001, China. Electronic address: 20170529@hbmu.edu.cn.
  • Wu Q; Guizhou Key Laboratory for Information System of Mountainous Areas and Protection of Ecological Environment, Guizhou Normal University, 116 Baoshan North Rd, Guiyang, Guizhou 550001, China; Innovation Laboratory, the Third Experiment Middle School in Guiyang, Guiyang, Guizhou 550001, China. Electron
Spectrochim Acta A Mol Biomol Spectrosc ; 258: 119847, 2021 Sep 05.
Article en En | MEDLINE | ID: mdl-33940571
Nondestructive instrumental identification of the green tea quality instead of professional human panel tests is highly desired for industrial application recently. The special flavor is a key quality-trait that influence consumer preference. However, flavonoids, as well as sensory-associated compounds, which play a critical role in the quality-traits profile of green tea samples have been poorly investigated. In this study, we were proposing an objective and accurate near infrared spectroscopy (NIRS) profile to support quality control within the entire green tea sensory evaluation chain, the complexity of green tea samples' sensory analysis was performed by two complementary methods: the standard calculation and the novel NIRS roadmap coupled with chemometrics. The green tea samples' physical quality, gustatory index, and nutritional index were measured respectively, which taking into consideration the gustatory evaluation of green tea for five commercially representative overall quality ("very bad", "bad", "regular", "good" and "excellent"). Our findings highlight the underexplored role of NIRS in chemical-to-sensory relationships and its widespread importance and utility in green tea quality improvement. Collectively, the comprehensive characterization of sensory-associated attribution allowed the identification of a wide array of spectrometric features, mostly related to moisture, soluble solids (SS), tea polyphenol (TPP), epigallocatechin gallate (EGCG), epicatechin (EC) and tea polysaccharide (TPS), which can be used as putative biomarkers to rapidly evaluate the green tea flavor variations related to rank differences. Otherwise, the NIRS' data were split into the calibration (n = 80) and prediction (n = 40) set independently, which showed high correlation coefficient with Rp-values of 0.9024, 0.9020 in physical and total cup quality, respectively. In this research, we demonstrated that NIRS was an easily-generated strategy and able to close the loop to feedback into the process for advanced process control. However, the established models should be improved by more green tea samples from different regions.
Asunto(s)
Palabras clave

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Té / Catequina Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Spectrochim Acta A Mol Biomol Spectrosc Año: 2021 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Té / Catequina Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Spectrochim Acta A Mol Biomol Spectrosc Año: 2021 Tipo del documento: Article