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

Author:

Tang Ting1,Luo Qing1,Yang Liu1,Gao Changlun1,Ling Caijin2,Wu Weibin1

Affiliation:

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

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

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.

Funder

Guangdong Provincial Special Fund for Modern Agriculture Industry Technology Innovation Teams

Guangdong Digital Smart Agricultural Service Industrial Park

Key Technology Research on Tea Shoot Recognition and Picking Robots

Sichuan Provincial Natural Science Foundation Youth Fund

Publisher

MDPI AG

Subject

Plant Science,Health Professions (miscellaneous),Health (social science),Microbiology,Food Science

Reference130 articles.

1. Research on the Effect Evaluation and Dynamic Mechanism of the Integrated Development of Tea and Tourism Industry;Lin;J. Tea Sci.,2023

2. Studies of the Basic Components and Probiotic Properties of Tea Powder;Zou;Food Res. Dev.,2021

3. Medicinal property, taste, efficacy and prescriptions of tea from the perspective of TCM literature;He;China J. Tradit. Chin. Med. Pharm.,2021

4. Research Advances on Quality Evaluation Methods of Tea Color, Aroma and Taste;Ou;Sci. Technol. Food Ind.,2019

5. Liang, X., Li, L., Han, C., Dong, Y., Xu, F., Lv, Z., Zhang, Y., Qu, Z., Dong, W., and Sun, Y. (2022). Rapid Limit Test of Seven Pesticide Residues in Tea Based on the Combination of TLC and Raman Imaging Microscopy. Molecules, 27.

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3