A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea

Area of Science:

• Agricultural Science
• Food Science
• Environmental Science

Background:

• Pu-erh tea quality is influenced by various environmental factors.
• Understanding abiotic stress effects on tea polyphenol content is crucial for quality control.

Purpose of the Study:

• To investigate the impact of abiotic stress on pu-erh tea polyphenol content.
• To identify key environmental factors influencing tea polyphenol levels.
• To develop a predictive model for pu-erh tea polyphenol content.

Main Methods:

• Analysis of tea polyphenol content in relation to environmental factors.
• Utilized LASSO regression to screen significant variables.
• Developed a nomogram model and a visualized prediction system.

Main Results:

• Identified eight factors (altitude, Ni, available Cd, organic matter, N, P, K, alkaline hydrolysis N) influencing polyphenol content.
• A nomogram model using altitude, organic matter, and P achieved AUCs of 0.839 (training) and 0.750 (validation).
• The prediction system demonstrated an accuracy rate of 80.95%.

Conclusions:

• Abiotic factors, particularly altitude, soil organic matter, and phosphorus, significantly affect pu-erh tea polyphenol content.
• The developed nomogram model and prediction system offer a reliable tool for estimating tea polyphenol content.
• This research provides a scientific basis for predicting and improving pu-erh tea quality under environmental stress.