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基于反向传播神经网络的有机绿茶()长期贮藏期间的风味特征、抗氧化能力及贮藏年份判别

The Flavor Characteristics, Antioxidant Capability, and Storage Year Discrimination Based on Backpropagation Neural Network of Organic Green Tea () during Long-Term Storage.

作者信息

Wen Xiaomei, Han Shanjie, Wang Jiahui, Zhang Yanxia, Tan Lining, Chen Chen, Han Baoyu, Wang Mengxin

机构信息

Zhejiang Provincial Key Laboratory of Biometrology and Inspection and Quarantine, College of Life Sciences, China Jiliang University, Hangzhou 310018, China.

Hangzhou Tea & Chrysanthemum Technology, Co., Ltd., Hangzhou 310018, China.

出版信息

Foods. 2024 Feb 29;13(5):753. doi: 10.3390/foods13050753.

Abstract

The storage period of tea is a major factor affecting tea quality. However, the effect of storage years on the non-volatile major functional components and quality of green tea remains largely unknown. In this study, a comparative analysis of organic green teas with varying storage years (1-16 years) was conducted by quantifying 47 functional components, using electronic tongue and chromatic aberration technology, alongside an evaluation of antioxidative capacity. The results indicated a significant negative correlation between the storage years and levels of tea polyphenols, total amino acids, soluble sugars, two phenolic acids, four flavonols, three tea pigments, umami amino acids, and sweet amino acids. The multivariate statistical analysis revealed that 10 functional components were identified as effective in distinguishing organic green teas with different storage years. Electronic tongue technology categorized organic green teas with different storage years into three classes. The backpropagation neural network (BPNN) analysis demonstrated that the classification predictive ability of the model based on the electronic tongue was superior to the one based on color difference values and 10 functional components. The combined analysis of antioxidative activity and functional components suggested that organic green teas with shorter storage periods exhibited stronger abilities to suppress superoxide anion radicals and hydroxyl radicals and reduce iron ions due to the higher content of eight components. Long-term-stored organic green teas, with a higher content of substances like L-serine and theabrownins, demonstrated stronger antioxidative capabilities in clearing both lipid-soluble and water-soluble free radicals. Therefore, this study provided a theoretical basis for the quality assessment of green tea and prediction of green tea storage periods.

摘要

茶叶的储存期是影响茶叶品质的主要因素。然而,储存年份对绿茶非挥发性主要功能成分及品质的影响在很大程度上仍不明确。本研究通过对47种功能成分进行定量分析、运用电子舌和色差技术并评估抗氧化能力,对不同储存年份(1 - 16年)的有机绿茶进行了比较分析。结果表明,储存年份与茶多酚、总氨基酸、可溶性糖、两种酚酸、四种黄酮醇、三种茶色素、鲜味氨基酸和甜味氨基酸的含量呈显著负相关。多元统计分析表明,有10种功能成分可有效区分不同储存年份的有机绿茶。电子舌技术将不同储存年份的有机绿茶分为三类。反向传播神经网络(BPNN)分析表明,基于电子舌的模型分类预测能力优于基于色差值和10种功能成分的模型。抗氧化活性与功能成分的综合分析表明,储存期较短的有机绿茶由于八种成分含量较高,表现出更强的抑制超氧阴离子自由基和羟基自由基以及还原铁离子的能力。长期储存的有机绿茶,由于L - 丝氨酸和茶褐素等物质含量较高,在清除脂溶性和水溶性自由基方面表现出更强的抗氧化能力。因此,本研究为绿茶品质评价和绿茶储存期预测提供了理论依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdfc/10930645/c39d80779d01/foods-13-00753-g001.jpg

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