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基于光谱技术的鲜茶叶品质检测研究综述

Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology.

作者信息

Tang Ting, Luo Qing, Yang Liu, Gao Changlun, Ling Caijin, Wu Weibin

机构信息

College of Engineering, South China Agricultural University, Guangzhou 510642, China.

Tea Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China.

出版信息

Foods. 2023 Dec 20;13(1):25. doi: 10.3390/foods13010025.

Abstract

As the raw material for tea making, the quality of tea leaves directly affects the quality of finished tea. The quality of fresh tea leaves is mainly assessed by manual judgment or physical and chemical testing of the content of internal components. Physical and chemical methods are more mature, and the test results are more accurate and objective, but traditional chemical methods for measuring the biochemical indexes of tea leaves are time-consuming, labor-costly, complicated, and destructive. With the rapid development of imaging and spectroscopic technology, spectroscopic technology as an emerging technology has been widely used in rapid non-destructive testing of the quality and safety of agricultural products. Due to the existence of spectral information with a low signal-to-noise ratio, high information redundancy, and strong autocorrelation, scholars have conducted a series of studies on spectral data preprocessing. The correlation between spectral data and target data is improved by smoothing noise reduction, correction, extraction of feature bands, and so on, to construct a stable, highly accurate estimation or discrimination model with strong generalization ability. There have been more research papers published on spectroscopic techniques to detect the quality of tea fresh leaves. This study summarizes the principles, analytical methods, and applications of Hyperspectral imaging (HSI) in the nondestructive testing of the quality and safety of fresh tea leaves for the purpose of tracking the latest research advances at home and abroad. At the same time, the principles and applications of other spectroscopic techniques including Near-infrared spectroscopy (NIRS), Mid-infrared spectroscopy (MIRS), Raman spectroscopy (RS), and other spectroscopic techniques for non-destructive testing of quality and safety of fresh tea leaves are also briefly introduced. Finally, in terms of technical obstacles and practical applications, the challenges and development trends of spectral analysis technology in the nondestructive assessment of tea leaf quality are examined.

摘要

作为茶叶制作的原料,茶叶的品质直接影响成品茶的质量。鲜叶的品质主要通过人工判断或对内部成分含量进行理化检测来评定。理化方法较为成熟,检测结果更准确客观,但传统的测定茶叶生化指标的化学方法耗时、费工、复杂且具有破坏性。随着成像和光谱技术的快速发展,光谱技术作为一种新兴技术已广泛应用于农产品质量安全的快速无损检测。由于存在信噪比低、信息冗余度高和自相关性强的光谱信息,学者们对光谱数据预处理进行了一系列研究。通过平滑降噪、校正、特征波段提取等方法提高光谱数据与目标数据之间的相关性,构建具有强泛化能力的稳定、高精度的估计或判别模型。关于利用光谱技术检测鲜叶质量的研究论文已有较多发表。本研究总结了高光谱成像(HSI)在鲜叶质量安全无损检测中的原理、分析方法及应用,旨在追踪国内外最新研究进展。同时,还简要介绍了近红外光谱(NIRS)、中红外光谱(MIRS)、拉曼光谱(RS)等其他光谱技术在鲜叶质量安全无损检测中的原理及应用。最后,从技术障碍和实际应用方面,探讨了光谱分析技术在茶叶品质无损评价中的挑战与发展趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/daa7/10778318/8f6c10e8f14e/foods-13-00025-g001.jpg

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