{"title":"利用荧光光谱学和化学计量学评估检测芥末油和菜籽油掺假的不同回归模型。","authors":"Kunal Shiv, Anupam Singh, Sachin Kumar, Lal Bahadur Prasad, Seema Gupta, Manoj Kumar Bharty","doi":"10.1080/19440049.2023.2297869","DOIUrl":null,"url":null,"abstract":"<p><p>Mustard and canola oils are commonly used cooking oils in Asian countries such as India, Nepal, and Bangladesh, making them prone to adulteration. Argemone is a well-known adulterant of mustard oil, and its alkaloid sanguinarine has been linked with health conditions such as glaucoma and dropsy. Utilising a non-destructive spectroscopic method coupled with a chemometric approach can serve better for the detection of adulterants. This work aimed to evaluate the performance of various regression algorithms for the detection of argemone in mustard and canola oils. The spectral dataset was acquired from fluorescence spectrometer analysis of pure as well as adulterated mustard and canola oils with some local and commercial samples also. The prediction performance of the eight regression algorithms for the detection of adulterants was evaluated. Extreme gradient boosting regressor (XGBR), Category gradient boosting regressor (CBR), and Random Forest (RF) demonstrate potential for predicting adulteration levels in both oils with high <i>R</i><sup>2</sup> values.</p>","PeriodicalId":12295,"journal":{"name":"Food Additives and Contaminants Part A-chemistry Analysis Control Exposure & Risk Assessment","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of different regression models for detection of adulteration of mustard and canola oil with argemone oil using fluorescence spectroscopy coupled with chemometrics.\",\"authors\":\"Kunal Shiv, Anupam Singh, Sachin Kumar, Lal Bahadur Prasad, Seema Gupta, Manoj Kumar Bharty\",\"doi\":\"10.1080/19440049.2023.2297869\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Mustard and canola oils are commonly used cooking oils in Asian countries such as India, Nepal, and Bangladesh, making them prone to adulteration. Argemone is a well-known adulterant of mustard oil, and its alkaloid sanguinarine has been linked with health conditions such as glaucoma and dropsy. Utilising a non-destructive spectroscopic method coupled with a chemometric approach can serve better for the detection of adulterants. This work aimed to evaluate the performance of various regression algorithms for the detection of argemone in mustard and canola oils. The spectral dataset was acquired from fluorescence spectrometer analysis of pure as well as adulterated mustard and canola oils with some local and commercial samples also. The prediction performance of the eight regression algorithms for the detection of adulterants was evaluated. Extreme gradient boosting regressor (XGBR), Category gradient boosting regressor (CBR), and Random Forest (RF) demonstrate potential for predicting adulteration levels in both oils with high <i>R</i><sup>2</sup> values.</p>\",\"PeriodicalId\":12295,\"journal\":{\"name\":\"Food Additives and Contaminants Part A-chemistry Analysis Control Exposure & Risk Assessment\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Food Additives and Contaminants Part A-chemistry Analysis Control Exposure & Risk Assessment\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1080/19440049.2023.2297869\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food Additives and Contaminants Part A-chemistry Analysis Control Exposure & Risk Assessment","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1080/19440049.2023.2297869","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
Evaluation of different regression models for detection of adulteration of mustard and canola oil with argemone oil using fluorescence spectroscopy coupled with chemometrics.
Mustard and canola oils are commonly used cooking oils in Asian countries such as India, Nepal, and Bangladesh, making them prone to adulteration. Argemone is a well-known adulterant of mustard oil, and its alkaloid sanguinarine has been linked with health conditions such as glaucoma and dropsy. Utilising a non-destructive spectroscopic method coupled with a chemometric approach can serve better for the detection of adulterants. This work aimed to evaluate the performance of various regression algorithms for the detection of argemone in mustard and canola oils. The spectral dataset was acquired from fluorescence spectrometer analysis of pure as well as adulterated mustard and canola oils with some local and commercial samples also. The prediction performance of the eight regression algorithms for the detection of adulterants was evaluated. Extreme gradient boosting regressor (XGBR), Category gradient boosting regressor (CBR), and Random Forest (RF) demonstrate potential for predicting adulteration levels in both oils with high R2 values.
期刊介绍:
Food Additives & Contaminants: Part A publishes original research papers and critical reviews covering analytical methodology, occurrence, persistence, safety evaluation, detoxification and regulatory control of natural and man-made additives and contaminants in the food and animal feed chain. Papers are published in the areas of food additives including flavourings, pesticide and veterinary drug residues, environmental contaminants, plant toxins, mycotoxins, marine biotoxins, trace elements, migration from food packaging, food process contaminants, adulteration, authenticity and allergenicity of foods. Papers are published on animal feed where residues and contaminants can give rise to food safety concerns. Contributions cover chemistry, biochemistry and bioavailability of these substances, factors affecting levels during production, processing, packaging and storage; the development of novel foods and processes; exposure and risk assessment.