Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/13/1/25 |
| _version_ | 1797358811011350528 |
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| author | Ting Tang Qing Luo Liu Yang Changlun Gao Caijin Ling Weibin Wu |
| author_facet | Ting Tang Qing Luo Liu Yang Changlun Gao Caijin Ling Weibin Wu |
| author_sort | Ting Tang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T15:07:40Z |
| format | Article |
| id | doaj.art-a484aaba02c44d3b9c080d6e615765be |
| institution | Directory Open Access Journal |
| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-08T15:07:40Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-a484aaba02c44d3b9c080d6e615765be2024-01-10T14:56:37ZengMDPI AGFoods2304-81582023-12-011312510.3390/foods13010025Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral TechnologyTing Tang0Qing Luo1Liu Yang2Changlun Gao3Caijin Ling4Weibin Wu5College of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaTea Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaAs 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.https://www.mdpi.com/2304-8158/13/1/25fresh tea leaveshyperspectral imaging technologyspectroscopyanalytic method |
| spellingShingle | Ting Tang Qing Luo Liu Yang Changlun Gao Caijin Ling Weibin Wu Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology Foods fresh tea leaves hyperspectral imaging technology spectroscopy analytic method |
| title | Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology |
| title_full | Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology |
| title_fullStr | Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology |
| title_full_unstemmed | Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology |
| title_short | Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology |
| title_sort | research review on quality detection of fresh tea leaves based on spectral technology |
| topic | fresh tea leaves hyperspectral imaging technology spectroscopy analytic method |
| url | https://www.mdpi.com/2304-8158/13/1/25 |
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