Advances of Vis/NIRS and imaging techniques assisted by AI for tea processing.

IF 8.8 1区农林科学 Q1 FOOD SCIENCE & TECHNOLOGY

Critical reviews in food science and nutrition Pub Date : 2025-03-07 DOI:10.1080/10408398.2025.2474183

Dengshan Li, Quansheng Chen, Qin Ouyang, Zhonghua Liu

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引用次数: 0

Abstract

Tea is one of the most popular drinks due to its distinct flavor and numerous health benefits. The quality of tea is closely related to production processing. Human sensory evaluation is the conventional method for quality monitoring in tea processing. However, this method is subjective and susceptible to environmental influences. Therefore, visible/near-infrared spectroscopy (Vis/NIRS) and hyperspectral imaging (HSI) techniques offer great potential due to their rapid detection speed, nondestructive, low cost, and simple operations. Artificial intelligence (AI) is one of the most promising methodological approaches for spectral analysis and decision-making of automated production. Vis/NIRS and HSI techniques assisted by AI further promote the progress of quality monitoring in tea processing. This paper reviewed the updated applications of Vis/NIRS and HSI techniques assisted by AI for quality monitoring in tea processing from 2019 to 2025. In particular, the tea production process, theories of Vis/NIRS and HSI techniques, and AI algorithms in spectral analysis are briefly introduced. Furthermore, the recent applications of Vis/NIRS and HSI techniques assisted by AI in tea processing quality monitoring are summarized and discussed. Finally, the challenges and future trends of Vis/NIRS and HSI techniques associated with their practical application in the tea industry are presented.

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人工智能辅助茶叶加工的可见光/近红外成像技术研究进展。

茶叶因其独特的风味和众多的健康益处而成为最受欢迎的饮品之一。茶叶的质量与生产加工密切相关。人的感官评价是茶叶加工过程中质量监测的传统方法。然而，这种方法主观性强，易受环境影响。因此，可见光/近红外光谱（Vis/NIRS）和高光谱成像（HSI）技术因其检测速度快、无损、成本低、操作简单等优点而具有巨大潜力。人工智能（AI）是光谱分析和自动化生产决策最有前途的方法之一。在人工智能的辅助下，可见光/近红外光谱和恒星光谱技术进一步推动了茶叶加工质量监测的进步。本文回顾了2019年至2025年人工智能辅助的Vis/NIRS和HSI技术在茶叶加工质量监测中的最新应用。其中，简要介绍了茶叶的生产过程、Vis/NIRS和HSI技术的理论以及光谱分析中的人工智能算法。此外，还总结并讨论了近期人工智能辅助下的可见光/近红外和声像图技术在茶叶加工质量监测中的应用。最后，介绍了 Vis/NIRS 和 HSI 技术在茶叶行业实际应用中面临的挑战和未来趋势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Critical reviews in food science and nutrition 工程技术-食品科技

CiteScore

22.60

自引率

4.90%

发文量

600

审稿时长

7.5 months

期刊介绍： Critical Reviews in Food Science and Nutrition serves as an authoritative outlet for critical perspectives on contemporary technology, food science, and human nutrition. With a specific focus on issues of national significance, particularly for food scientists, nutritionists, and health professionals, the journal delves into nutrition, functional foods, food safety, and food science and technology. Research areas span diverse topics such as diet and disease, antioxidants, allergenicity, microbiological concerns, flavor chemistry, nutrient roles and bioavailability, pesticides, toxic chemicals and regulation, risk assessment, food safety, and emerging food products, ingredients, and technologies.