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Jin X, Wang Z, Ma J, Liu C, Bai X, Lan Y. Electronic eye and electronic tongue data fusion combined with a GETNet model for the traceability and detection of Astragalus. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2024; 104:5930-5943. [PMID: 38459895 DOI: 10.1002/jsfa.13450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 01/23/2024] [Accepted: 03/09/2024] [Indexed: 03/11/2024]
Abstract
BACKGROUND Astragalus is a widely used traditional Chinese medicine material that is easily confused due to its quality, price and other factors derived from different origins. This article describes a novel method for the rapid tracing and detection of Astragalus via the joint application of an electronic tongue (ET) and an electronic eye (EE) combined with a lightweight convoluted neural network (CNN)-transformer model. First, ET and EE systems were employed to measure the taste fingerprints and appearance images, respectively, of different Astragalus samples. Three spectral transform methods - the Markov transition field, short-time Fourier transform and recurrence plot - were utilized to convert the ET signals into 2D spectrograms. Then, the obtained ET spectrograms were fused with the EE image to obtain multimodal information. A lightweight hybrid model, termed GETNet, was designed to achieve pattern recognition for the Astragalus fusion information. The proposed model employed an improved transformer module and an improved Ghost bottleneck as its backbone network, complementarily utilizing the benefits of CNN and transformer architectures for local and global feature representation. Furthermore, the Ghost bottleneck was further optimized using a channel attention technique, which boosted the model's feature extraction effectiveness. RESULTS The experiments indicate that the proposed data fusion strategy based on ET and EE devices has better recognition accuracy than that attained with independent sensing devices. CONCLUSION The proposed method achieved high precision (99.1%) and recall (99.1%) values, providing a novel approach for rapidly identifying the origin of Astragalus, and it holds great promise for applications involving other types of Chinese herbal medicines. © 2024 Society of Chemical Industry.
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Affiliation(s)
- Xinning Jin
- School of Computer Science and Technology, Shandong University of Technology, Zibo, China
| | - Zhiqiang Wang
- School of Computer Science and Technology, Shandong University of Technology, Zibo, China
| | - Jingyu Ma
- School of Computer Science and Technology, Shandong University of Technology, Zibo, China
| | - Chuanzheng Liu
- School of Computer Science and Technology, Shandong University of Technology, Zibo, China
| | - Xuerui Bai
- School of Computer Science and Technology, Shandong University of Technology, Zibo, China
| | - Yubin Lan
- School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo, China
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Geng J, Nie K, Wang W, Jiang S, Niu Z. Study on VOCs of Fishmeal during Storage Based on HS-SPME-GC-MS. ACS OMEGA 2024; 9:32817-32827. [PMID: 39100347 PMCID: PMC11292805 DOI: 10.1021/acsomega.4c03323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 06/02/2024] [Accepted: 06/07/2024] [Indexed: 08/06/2024]
Abstract
Fishmeal is widely used in the feed industry as the main protein material. The freshness grade directly affects the quality of the fishmeal. During the storage of fishmeal, the odor would change accordingly as the freshness grades decreased. To study the characteristic volatile organic compounds (VOCs) of fishmeal, stored at 25 °C and 80%RH with different freshness grades, headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME-GC-MS) was used to analyze. The single-factor test was chosen for 50/30 μm divinylbenzene/carboxe/polydimethylsiloxane (DVB/CAR/PDMS) fiber. The equilibration time of 24 min, the extraction time of 60 min, the extraction temperature of 87 °C, and the addition of a saturated saline volume of 4 mL were determined by Box-Behnken design. There were 15 common VOCs detected during storage, the relative contents of acids increased significantly, ketones, aldehydes, esters, and nitrogen-containing compounds increased, and aromatic compounds and alcohols decreased. Combined with freshness indexes, volatile base nitrogen (VBN) and acid value (AV), hexadecanoic acid, tetradecanoic acid, methyl (Z)-N-hydroxybenzenecarboximidate, (Z)-hexadec-9-enoic acid, 6-ethoxy-2,2,4-trimethyl-3,4-dihydro-1H-quinoline, octadecanal, and [(Z)-octadec-9-enyl] acetate were determined as the characteristic VOCs based on the PLS-DA model. This study may provide data support for the development of fishmeal freshness-detecting instruments.
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Affiliation(s)
- Jie Geng
- College
of Engineering, Huazhong Agricultural University, Wuhan 430070, China
- Key
Laboratory of Smart Farming for Agricultural Animals, Ministry of
Agriculture, Wuhan 430070, China
| | - Ke Nie
- College
of Engineering, Huazhong Agricultural University, Wuhan 430070, China
- Key
Laboratory of Smart Farming for Agricultural Animals, Ministry of
Agriculture, Wuhan 430070, China
| | - Weixia Wang
- College
of Engineering, Huazhong Agricultural University, Wuhan 430070, China
- Key
Laboratory of Smart Farming for Agricultural Animals, Ministry of
Agriculture, Wuhan 430070, China
| | - Shanchen Jiang
- College
of Engineering, Huazhong Agricultural University, Wuhan 430070, China
- Key
Laboratory of Smart Farming for Agricultural Animals, Ministry of
Agriculture, Wuhan 430070, China
| | - Zhiyou Niu
- College
of Engineering, Huazhong Agricultural University, Wuhan 430070, China
- Key
Laboratory of Smart Farming for Agricultural Animals, Ministry of
Agriculture, Wuhan 430070, China
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Kaldeli A, Zakidou P, Paraskevopoulou A. Volatilomics as a tool to ascertain food adulteration, authenticity, and origin. Compr Rev Food Sci Food Saf 2024; 23:e13387. [PMID: 38865237 DOI: 10.1111/1541-4337.13387] [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: 01/03/2024] [Revised: 05/02/2024] [Accepted: 05/18/2024] [Indexed: 06/14/2024]
Abstract
Over recent years, there has been an increase in the number of reported cases of food fraud incidents, whereas at the same time, consumers demand authentic products of high quality. The emerging volatilomics technology could be the key to the analysis and characterization of the quality of different foodstuffs. This field of omics has aroused the interest of scientists due to its noninvasive, rapid, and cost-profitable nature. This review aims to monitor the available scientific information on the use of volatilomics technology, correlate it to the relevant food categories, and demonstrate its importance in the food adulteration, authenticity, and origin areas. A comprehensive literature search was performed using various scientific search engines and "volatilomics," "volatiles," "food authenticity," "adulteration," "origin," "fingerprint," "chemometrics," and variations thereof as keywords, without chronological restriction. One hundred thirty-seven relevant publications were retrieved, covering 11 different food categories (meat and meat products, fruits and fruit products, honey, coffee, tea, herbal products, olive oil, dairy products, spices, cereals, and others), the majority of which focused on the food geographical origin. The findings show that volatilomics typically involves various methods responsible for the extraction and consequential identification of volatile compounds, whereas, with the aid of data analysis, it can handle large amounts of data, enabling the origin classification of samples or even the detection of adulteration practices. Nonetheless, a greater number of specific research studies are needed to unlock the full potential of volatilomics.
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Affiliation(s)
- Aikaterini Kaldeli
- Laboratory of Food Chemistry and Technology, School of Chemistry, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Panagiota Zakidou
- Laboratory of Food Chemistry and Technology, School of Chemistry, Aristotle University of Thessaloniki, Thessaloniki, Greece
- European Food Safety Authority (EFSA), Parma, Italy
| | - Adamantini Paraskevopoulou
- Laboratory of Food Chemistry and Technology, School of Chemistry, Aristotle University of Thessaloniki, Thessaloniki, Greece
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Fan X, Zhang K, Wang S, Qi Y, Dai G, Lu T, Mao C. Discrimination between raw and ginger juice processed Fructus Gardeniae based on UHPLC-Q-TOF-MS and Heracles NEO ultra-fast gas phase electronic nose. PHYTOCHEMICAL ANALYSIS : PCA 2024. [PMID: 38806285 DOI: 10.1002/pca.3399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 05/13/2024] [Accepted: 05/13/2024] [Indexed: 05/30/2024]
Abstract
INTRODUCTION Fructus Gardeniae (ZZ), a traditional Chinese herb, has been used in treating patients with jaundice, inflammation, etc. When mixed with ginger juice and stir-baked, ginger juice-processed Fructus Gardeniae (JZZ) is produced, and the chemical compositions in ZZ would be changed by adding the ginger juice. OBJECTIVE To illuminate the differential components between ZZ and JZZ. METHODS HPLC, UHPLC-Q-TOF-MS, and Heracles NEO ultra-fast gas phase electronic nose were applied to identify the differential components between ZZ and JZZ. RESULTS HPLC fingerprints of ZZ and JZZ were established, and 24 common peaks were found. The content determination results showed that the contents of shanzhiside, geniposidic acid, genipin-1-β-D-gentiobioside and geniposide increased, while the contents of crocin I and crocin II decreased in JZZ. By UHPLC-Q-TOF-MS, twenty-six possible common components were inferred, among which 11 components were different. In further investigation, eight components were identified as the possible distinctive non-volatile compounds between ZZ and JZZ. By Heracles NEO ultra-fast gas phase electronic nose, four substances were inferred as the possible distinctive volatile compounds in JZZ. CONCLUSION Shanzhiside, caffeic acid, genipin-1-β-D-gentiobioside, geniposide, rutin, crocin I, crocin II, and 4-Sinapoyl-5-caffeoylquinic acid were identified as the possible differential non-volatile components between ZZ and JZZ. Aniline, 3-methyl-3-sulfanylbutanol-1-ol, E-3-octen-2-one, and decyl propaonate were inferred as the possible distinctive volatile compounds in JZZ. This experiment explored a simple approach with objective and stable results, which would provide new ideas for studying decoction pieces with similar morphological appearance, especially those with different odors.
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Affiliation(s)
- Xingchen Fan
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China
| | - Kewei Zhang
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China
| | - Sichen Wang
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China
| | - Yufang Qi
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China
| | - Guiyu Dai
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China
| | - Tulin Lu
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China
| | - Chunqin Mao
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China
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Zhang JB, Wang B, Zhang YF, Wu Y, Li MX, Gao T, Lu TL, Bian ZH, Su LL. E-eye and FT-NIR combined with multivariate algorithms to rapidly evaluate the dynamic changes in the quality of Gastrodia elata during steaming process. Food Chem 2024; 439:138148. [PMID: 38064826 DOI: 10.1016/j.foodchem.2023.138148] [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: 09/21/2023] [Revised: 12/01/2023] [Accepted: 12/03/2023] [Indexed: 01/10/2024]
Abstract
Gastrodia elata (GE) is traditionally subjected to steaming, and steaming duration plays a crucially important role in determining GE quality. This study examined the variations in bioactive components during the steaming process and proposed the utilization of electronic eye and Fourier Transform near-infrared (FT-NIR) spectroscopy for quality assessment. The findings revealed that the levels of parishin E parishin B, parishin A, and gastrodin initially rose and subsequently declined, while 4-Hydroxybenzyl alcohol exhibited a rapid decrease followed by stabilization. With prolonged steaming, the brightness of GE decreased, while the red and yellow tones became more pronounced and the color saturation increased. FT-NIR divided the steaming process into three stages: 0 min (raw GE), 0-9 min (partially steamed GE), and 9-30 min (fully steamed GE), and the partial least squares regression models effectively predicted the levels of five components. Overall, this study provided valuable insights into quality control in food processing.
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Affiliation(s)
- Jiu-Ba Zhang
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Bin Wang
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Yun-Fei Zhang
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Yi Wu
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Ming-Xuan Li
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Ting Gao
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Tu-Lin Lu
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China.
| | - Zhen-Hua Bian
- Department of Pharmacy, Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi 214071, China; Jiangsu CM Clinical Innovation Center of Degenerative Bone & Joint Disease, Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi 214071, China.
| | - Lian-Lin Su
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China; Jiangsu Provincial Technology Engineering Research Center of TCM Health Preservation, Nanjing 210023, China.
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Dai L, Yang L, Li Y, Li S, Yang D, Li Y, He D. Origin differentiation based on volatile constituents of genuine medicinal materials Quisqualis indica L. via HS-GC-MS, response surface methodology, and chemometrics. PHYTOCHEMICAL ANALYSIS : PCA 2024; 35:567-578. [PMID: 38191129 DOI: 10.1002/pca.3313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 01/10/2024]
Abstract
INTRODUCTION Quisqualis indica L. (QIL) has a long history as a traditional Chinese herb in China, but the study of volatile components in QIL from different geographical sources has been relatively rare. OBJECTIVES To establish an optimal headspace gas chromatography-mass spectrometry (HS-GC-MS) method to comprehensively analyse the volatile component profile and screen quality markers of QIL from different origins. METHODS Response surface methodology (RSM) was used to optimise the conditions for headspace analysis. The volatile components of QIL from four main origins of southwest China were analysed and identified by HS-GC-MS. The similarity of all samples of QIL was evaluated by fingerprint. The differences of the volatile components in QIL from different origins were distinguished by chemometrics. RESULTS According to the optimal conditions of RSM, a total of 31 volatile components were identified, including fatty acids, aldehydes, alcohols, alkyl pyrazines, and other volatile components. Similarity evaluation presented that there were 26 common volatile components with different contents in all samples. Principal component analysis (PCA) showed that QIL from four different origins could be roughly divided into four categories. Hierarchical cluster analysis (HCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) indicated that QIL from different origins had obvious regional characteristics. CONCLUSION The optimised HS-GC-MS method provided a strategy to rapidly, effectively, and accurately elucidate the volatile component profile of QIL from different origins, and seven important differential components were screened for quality evaluation and origin traceability.
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Affiliation(s)
- Lei Dai
- College of Pharmacy, Chongqing Medical University, Chongqing, China
| | - Lin Yang
- Chongqing Pharmaceutical Preparation Engineering Technology Research Center, Chongqing Medical and Pharmaceutical College, Chongqing, China
| | - Yan Li
- Chongqing Pharmaceutical Preparation Engineering Technology Research Center, Chongqing Medical and Pharmaceutical College, Chongqing, China
| | - Shuya Li
- College of Pharmacy, Chongqing Medical University, Chongqing, China
| | - Dan Yang
- College of Pharmacy, Chongqing Medical University, Chongqing, China
| | - Yaxuan Li
- College of Pharmacy, Chongqing Medical University, Chongqing, China
| | - Dan He
- College of Pharmacy, Chongqing Medical University, Chongqing, China
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Qin Y, Zhao Q, Zhou D, Shi Y, Shou H, Li M, Zhang W, Jiang C. Application of flash GC e-nose and FT-NIR combined with deep learning algorithm in preventing age fraud and quality evaluation of pericarpium citri reticulatae. Food Chem X 2024; 21:101220. [PMID: 38384686 PMCID: PMC10879671 DOI: 10.1016/j.fochx.2024.101220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 02/04/2024] [Accepted: 02/08/2024] [Indexed: 02/23/2024] Open
Abstract
Pericarpium citri reticulatae (PCR) is the dried mature fruit peel of Citrus reticulata Blanco and its cultivated varieties in the Brassicaceae family. It can be used as both food and medicine, and has the effect of relieving cough and phlegm, and promoting digestion. The smell and medicinal properties of PCR are aged over the years; only varieties with aging value can be called "Chenpi". That is to say, the storage year of PCR has a great influence on its quality. As the color and smell of PCR of different storage years are similar, some unscrupulous merchants often use PCRs of low years to pretend to be PCRs of high years, and make huge profits. Therefore, we did this study with the aim of establishing a rapid and nondestructive method to identify the counterfeiting of PCR storage year, so as to protect the legitimate rights and interests of consumers. In this study, a classification model of PCR was established by e-eye, flash GC e-nose, and Fourier transform near-infrared (FT-NIR) combined with machine learning algorithms, which can quickly and accurately distinguish PCRs of different storage years. DFA and PLS-DA models were established by flash GC e-nose to distinguish PCRs of different ages, and 8 odor components were identified, among which (+)-limonene and γ-terpinene were the key components to distinguish PCRs of different ages. In addition, the classification and calibration model of PCRs were established by the combination of FT-NIR and machine learning algorithms. The classification models included SVM, KNN, LSTM, and CNN-LSTM, while the calibration models included PLSR, LSTM, and CNN-LSTM. Among them, the CNN-LSTM model built by internal capsule had significantly better classification and calibration performance than the other models. The accuracy of the classification model was 98.21 %. The R2P of age, (+)-limonene and γ-terpinene was 0.9912, 0.9875 and 0.9891, respectively. These results showed that the combination of flash GC e-nose and FT-NIR combined with deep learning algorithm could quickly and accurately distinguish PCRs of different ages. It also provided an effective and reliable method to monitor the quality of PCR in the market.
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Affiliation(s)
- Yuwen Qin
- College of Pharmacy, Wenzhou Medical University, Wenzhou 325035, China
- Jiuhuashan Polygonati Rhizoma Research Institute, Chizhou 247100, China
| | - Qi Zhao
- College of Pharmacy, Wenzhou Medical University, Wenzhou 325035, China
- Jiuhuashan Polygonati Rhizoma Research Institute, Chizhou 247100, China
| | - Dan Zhou
- College of Pharmacy, Wenzhou Medical University, Wenzhou 325035, China
- Jiuhuashan Polygonati Rhizoma Research Institute, Chizhou 247100, China
| | - Yabo Shi
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Haiyan Shou
- College of Pharmacy, Wenzhou Medical University, Wenzhou 325035, China
- Jiuhuashan Polygonati Rhizoma Research Institute, Chizhou 247100, China
| | - Mingxuan Li
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Wei Zhang
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China
- College of Pharmacy, Anhui University of Chinese Medicine, Anhui 230012, China
- Anhui Province Key Laboratory of Traditional Chinese Medicine Decoction Pieces of New Manufacturing Technology, China
| | - Chengxi Jiang
- College of Pharmacy, Wenzhou Medical University, Wenzhou 325035, China
- Jiuhuashan Polygonati Rhizoma Research Institute, Chizhou 247100, China
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Xie L, Guo S, Rao H, Lan B, Zheng B, Zhang N. Characterization of Volatile Flavor Compounds and Aroma Active Components in Button Mushroom ( Agaricus bisporus) across Various Cooking Methods. Foods 2024; 13:685. [PMID: 38472797 DOI: 10.3390/foods13050685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 02/19/2024] [Accepted: 02/20/2024] [Indexed: 03/14/2024] Open
Abstract
To investigate the impact of various cooking methods on the volatile aroma compounds of button mushroom, gas chromatography-mass spectrometry (GC-MS) and electronic nose (E-nose) were utilized for aroma analysis. The results indicated that the E-nose was able to effectively distinguish between the samples prepared using different cooking methods. In the raw, steamed, boiled and baked samples, 37, 23, 33 and 35 volatiles were detected, respectively. The roasting process significantly contributed to the production of flavor compounds, giving button mushroom its distinctive flavor. Sixteen differential aromas were identified based on the p-value and VIP value. Additionally, the cluster analysis of differential aroma substances revealed a stronger odor similarity between the steamed and raw groups, consistent with the results of the OPLS-DA analysis of overall aroma components. Seven key aromas were identified through OAV analysis and omission experiments. In addition, 1-octen-3-one was identified as the main aroma component of cooked button mushroom. The findings of the study can be valuable for enhancing the flavor of cooked button mushroom.
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Affiliation(s)
- Limei Xie
- College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Shaoli Guo
- College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Hongting Rao
- College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Bingying Lan
- College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Baodong Zheng
- College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China
- Fujian Provincial Key Laboratory of Quality Science and Processing Technology in Special Starch, Fuzhou 350002, China
| | - Ningning Zhang
- College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China
- Fujian Provincial Key Laboratory of Quality Science and Processing Technology in Special Starch, Fuzhou 350002, China
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Li MX, Shi YB, Zhang JB, Wan X, Fang J, Wu Y, Fu R, Li Y, Li L, Su LL, Ji D, Lu TL, Bian ZH. Rapid evaluation of Ziziphi Spinosae Semen and its adulterants based on the combination of FT-NIR and multivariate algorithms. Food Chem X 2023; 20:101022. [PMID: 38144802 PMCID: PMC10740088 DOI: 10.1016/j.fochx.2023.101022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 11/09/2023] [Accepted: 11/19/2023] [Indexed: 12/26/2023] Open
Abstract
Ziziphi Spinosae Semen (ZSS) is a valued seed renowned for its sedative and sleep-enhancing properties. However, the price increase has been accompanied by adulteration. In this study, chromaticity analysis and Fourier transform near-infrared (FT-NIR) combined with multivariate algorithms were employed to identify the adulteration and quantitatively predict the adulteration ratio. The findings suggested that the utilization of chromaticity extractor was insufficient for identification of adulteration ratio. The raw spectrum of ZMS and HAS adulterants extracted by FT-NIR was processed by SNV + CARS and 1d + SG + ICO respectively, the average accuracy of machine learning classification model was improved from 77.06 % to 97.58 %. Furthermore, the R2 values of the calibration and prediction set of the two quantitative prediction regression models of adulteration ratio are greater than 0.99, demonstrating excellent linearity and predictive accuracy. Overall, this study demonstrated that FT-NIR combined with multivariate algorithms provided a significant approach to addressing the growing issue of ZSS adulteration.
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Affiliation(s)
- Ming-xuan Li
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Ya-bo Shi
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Jiu-ba Zhang
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Xin Wan
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Jun Fang
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Yi Wu
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Rao Fu
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Yu Li
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Lin Li
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Lian-lin Su
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - De Ji
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Tu-lin Lu
- College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Zhen-hua Bian
- Department of Pharmacy, Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, 214071, China
- Jiangsu CM Clinical Innovation Center of Degenerative Bone & Joint Disease, Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, 214071, China
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