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Meng Q, Zhang J, Li X, Li Y, Shen X, Li Z, Xu M, Yao C, Chu P, Cui YJ, Guo DA. ASAP-MS combined with mass spectrum similarity and binary code for rapid and intelligent authentication of 78 edible flowers. Food Chem 2024; 436:137776. [PMID: 37862980 DOI: 10.1016/j.foodchem.2023.137776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 10/11/2023] [Accepted: 10/14/2023] [Indexed: 10/22/2023]
Abstract
This is the first report to use Atmospheric Pressure Solids Analysis Probe (ASAP) for rapid and intelligent authentication of 78 edible flowers. Mass spectra of 451 batches were collected, with each run for 1-2 min. Experimental raw data was automatically extracted and aligned to create a MS database, based on which flowers were identified by MS similarity scores and rankings. To avoid background interference, top 25 ions of each flower were screened and gathered into an m/z pool containing 292 ions (+) and 399 ions (-). Binary sequence IDs were then generated by automatically assigning "1″ for presence and "0″ for absence, resulting in 78 binary codes. Binary code similarity with 78 IDs was used for authentication. Above two approaches were automatically performed by MATLAB, and compared to k-nearest neighbor model, and samples were all successfully identified (100 %). The proposed method provides a high-throughput authentication approach for large-scale food samples.
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Affiliation(s)
- Qian Meng
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road #501, Shanghai 201203, China; Shanghai University of Traditional Chinese Medicine, Cailun Road 1200, Shanghai 201203, China
| | - Jianqing Zhang
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road #501, Shanghai 201203, China
| | - Xiaolan Li
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road #501, Shanghai 201203, China
| | - Yun Li
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road #501, Shanghai 201203, China
| | - Xuanjing Shen
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road #501, Shanghai 201203, China
| | - Ziqing Li
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road #501, Shanghai 201203, China
| | - Meng Xu
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road #501, Shanghai 201203, China
| | - Changliang Yao
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road #501, Shanghai 201203, China
| | - Pengfei Chu
- Waters Technology (Shanghai) Co., Ltd., Shanghai 201203, China
| | - Ya-Jun Cui
- Shanghai University of Traditional Chinese Medicine, Cailun Road 1200, Shanghai 201203, China.
| | - De-An Guo
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Haike Road #501, Shanghai 201203, China; Shanghai University of Traditional Chinese Medicine, Cailun Road 1200, Shanghai 201203, China.
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Tang T, Luo Q, Yang L, Gao C, Ling C, Wu W. Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology. Foods 2023; 13:25. [PMID: 38201054 PMCID: PMC10778318 DOI: 10.3390/foods13010025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 12/13/2023] [Accepted: 12/18/2023] [Indexed: 01/12/2024] Open
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.
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Affiliation(s)
- Ting Tang
- College of Engineering, South China Agricultural University, Guangzhou 510642, China; (T.T.); (Q.L.); (L.Y.); (C.G.)
| | - Qing Luo
- College of Engineering, South China Agricultural University, Guangzhou 510642, China; (T.T.); (Q.L.); (L.Y.); (C.G.)
| | - Liu Yang
- College of Engineering, South China Agricultural University, Guangzhou 510642, China; (T.T.); (Q.L.); (L.Y.); (C.G.)
| | - Changlun Gao
- College of Engineering, South China Agricultural University, Guangzhou 510642, China; (T.T.); (Q.L.); (L.Y.); (C.G.)
| | - Caijin Ling
- Tea Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China
| | - Weibin Wu
- College of Engineering, South China Agricultural University, Guangzhou 510642, China; (T.T.); (Q.L.); (L.Y.); (C.G.)
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