Evaluating Chinese tea varieties through differential analysis of PPO isoenzymes and non-volatile metabolites and construction of adaptability models for black tea

Tea varieties are key factors influencing tea type and flavor quality. However, the key biochemical indicators biochemical indicators associated with tea varietal suitability remain unclear, and the traditional phenol-ammonia ratio is insufficient as an evaluation criterion. Therefore, identifying reliable biochemical markers for evaluating tea varietal suitability is important for optimizing tea processing and product quality. We aimed to identify key biochemical indicators associated with tea varietal suitability for black and green tea processing and to establish a predictive model for evaluating tea varietal adaptability. Molecular biology and targeted metabolomics approaches were used to analyze polyphenol oxidase (PPO) activity, the expression of three PPO isozymes, and the contents of 60 non-volatile metabolites (NVMs) in fresh leaves from 20 representative tea varieties. Variable importance in projection, S-plot, taste active value, and classification analyses were applied to identify key differential indicators. A predictive model for tea varietal suitability was subsequently developed using data preprocessing and regression analysis. Nine key differential biochemical indicators, including epigallocatechin gallate, epicatechin gallate, epigallocatechin, epicatechin, catechin, myricetin-3-O-galactoside, theaflavin-3-3′-di-O-gallate, theanine, and glutamic acid, together with three enzyme-related indicators, namely PPO activity and the expression levels of PPO2 and PPO4, were identified. Tea varieties suitable for black tea exhibited high levels of epigallocatechin gallate, epicatechin gallate, theaflavin-3-3′-di-O-gallate, and PPO activity, particularly PPO4 expression. In contrast, tea varieties suitable for green tea showed high levels of epigallocatechin, epicatechin, theanine, glutamic acid, and myricetin-3-O-galactoside content. A 1DER+MINMAX data preprocessing method and predictive model effectively evaluated tea varietal suitability. This study identified key biochemical indicators associated with tea varietal suitability and established a predictive model for evaluating tea adaptability for black and green tea processing. These findings provide theoretical and technical support for the efficient utilization of fresh leaf leaves and tea product development.