{"title":"用一系列金属氧化物传感器和化学计量学快速检测葡萄糖浆掺假","authors":"Mahdi Ghasemi-Varnamkhasti , Puneet Mishra , Morteza Ahmadpour-Samani , Mojtaba Naderi-Boldaji , Davoud Ghanbarian , Mojtaba Tohidi , Zahra Izadi","doi":"10.1016/j.eaef.2019.04.002","DOIUrl":null,"url":null,"abstract":"<div><p><span>Among the different cases of emerging food<span> fraud during the post-harvest processing, the adulteration in grape<span> syrup is one. Typically, the grape syrup is adulterated with some illegitimate foreign materials such as grape paste (sauce), date syrup and even adding sugar-water solution to the pure grape syrup. The present study deals with assessing an electronic nose (e-nose) consisting of eight different metal oxide semiconductor (MOS) sensors for prompt detection of adulteration in the grape syrup. Three different adulterants i.e. grape paste, date syrup and sugar-water solution, each at three levels of 50, 60 and 75%, were tested. The collected data from MOS were normalised and visualised with the help of standard normal variate (SNV) and principal component analysis (PCA), respectively. Moreover, the scores obtained from PCA were used to perform hierarchal cluster analysis (HCA) to identify the similarities between different adulterated mixtures and pure grape syrup. Three different classification cases were considered to (i) address the presence of adulteration, (ii) detect the different adulterants and (iii) classify the amount of each adulteration. Linear discriminant analysis (LDA) and multi-class </span></span></span>support vector machine (SVM) were used for classification analyses. Results showed that PCA identified provided separate clusters for the MOS data corresponding to different adulterants and their levels. The HCA showed a hierarchal of similarities between pure grape syrup and different levels of adulterations. LDA and SVM resulted in a successful classification modelling. However, the performance of SVM was considerably better than LDA with classification accuracies of 98.6 ± 0.10%, 98.9 ± 1.16% and 95.1 ± 1.39% for detecting adulteration, different adulterants and different concentrations of adulterants, respectively. MOS sensors coupled with chemometrics could provide a useful instrument and fast procedure for detection of adulteration in grape syrup.</p></div>","PeriodicalId":38965,"journal":{"name":"Engineering in Agriculture, Environment and Food","volume":"12 3","pages":"Pages 351-359"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.eaef.2019.04.002","citationCount":"9","resultStr":"{\"title\":\"Rapid detection of grape syrup adulteration with an array of metal oxide sensors and chemometrics\",\"authors\":\"Mahdi Ghasemi-Varnamkhasti , Puneet Mishra , Morteza Ahmadpour-Samani , Mojtaba Naderi-Boldaji , Davoud Ghanbarian , Mojtaba Tohidi , Zahra Izadi\",\"doi\":\"10.1016/j.eaef.2019.04.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>Among the different cases of emerging food<span> fraud during the post-harvest processing, the adulteration in grape<span> syrup is one. Typically, the grape syrup is adulterated with some illegitimate foreign materials such as grape paste (sauce), date syrup and even adding sugar-water solution to the pure grape syrup. The present study deals with assessing an electronic nose (e-nose) consisting of eight different metal oxide semiconductor (MOS) sensors for prompt detection of adulteration in the grape syrup. Three different adulterants i.e. grape paste, date syrup and sugar-water solution, each at three levels of 50, 60 and 75%, were tested. The collected data from MOS were normalised and visualised with the help of standard normal variate (SNV) and principal component analysis (PCA), respectively. Moreover, the scores obtained from PCA were used to perform hierarchal cluster analysis (HCA) to identify the similarities between different adulterated mixtures and pure grape syrup. Three different classification cases were considered to (i) address the presence of adulteration, (ii) detect the different adulterants and (iii) classify the amount of each adulteration. Linear discriminant analysis (LDA) and multi-class </span></span></span>support vector machine (SVM) were used for classification analyses. Results showed that PCA identified provided separate clusters for the MOS data corresponding to different adulterants and their levels. The HCA showed a hierarchal of similarities between pure grape syrup and different levels of adulterations. LDA and SVM resulted in a successful classification modelling. However, the performance of SVM was considerably better than LDA with classification accuracies of 98.6 ± 0.10%, 98.9 ± 1.16% and 95.1 ± 1.39% for detecting adulteration, different adulterants and different concentrations of adulterants, respectively. MOS sensors coupled with chemometrics could provide a useful instrument and fast procedure for detection of adulteration in grape syrup.</p></div>\",\"PeriodicalId\":38965,\"journal\":{\"name\":\"Engineering in Agriculture, Environment and Food\",\"volume\":\"12 3\",\"pages\":\"Pages 351-359\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.eaef.2019.04.002\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering in Agriculture, Environment and Food\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1881836618300703\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering in Agriculture, Environment and Food","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1881836618300703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
Rapid detection of grape syrup adulteration with an array of metal oxide sensors and chemometrics
Among the different cases of emerging food fraud during the post-harvest processing, the adulteration in grape syrup is one. Typically, the grape syrup is adulterated with some illegitimate foreign materials such as grape paste (sauce), date syrup and even adding sugar-water solution to the pure grape syrup. The present study deals with assessing an electronic nose (e-nose) consisting of eight different metal oxide semiconductor (MOS) sensors for prompt detection of adulteration in the grape syrup. Three different adulterants i.e. grape paste, date syrup and sugar-water solution, each at three levels of 50, 60 and 75%, were tested. The collected data from MOS were normalised and visualised with the help of standard normal variate (SNV) and principal component analysis (PCA), respectively. Moreover, the scores obtained from PCA were used to perform hierarchal cluster analysis (HCA) to identify the similarities between different adulterated mixtures and pure grape syrup. Three different classification cases were considered to (i) address the presence of adulteration, (ii) detect the different adulterants and (iii) classify the amount of each adulteration. Linear discriminant analysis (LDA) and multi-class support vector machine (SVM) were used for classification analyses. Results showed that PCA identified provided separate clusters for the MOS data corresponding to different adulterants and their levels. The HCA showed a hierarchal of similarities between pure grape syrup and different levels of adulterations. LDA and SVM resulted in a successful classification modelling. However, the performance of SVM was considerably better than LDA with classification accuracies of 98.6 ± 0.10%, 98.9 ± 1.16% and 95.1 ± 1.39% for detecting adulteration, different adulterants and different concentrations of adulterants, respectively. MOS sensors coupled with chemometrics could provide a useful instrument and fast procedure for detection of adulteration in grape syrup.
期刊介绍:
Engineering in Agriculture, Environment and Food (EAEF) is devoted to the advancement and dissemination of scientific and technical knowledge concerning agricultural machinery, tillage, terramechanics, precision farming, agricultural instrumentation, sensors, bio-robotics, systems automation, processing of agricultural products and foods, quality evaluation and food safety, waste treatment and management, environmental control, energy utilization agricultural systems engineering, bio-informatics, computer simulation, computational mechanics, farm work systems and mechanized cropping. It is an international English E-journal published and distributed by the Asian Agricultural and Biological Engineering Association (AABEA). Authors should submit the manuscript file written by MS Word through a web site. The manuscript must be approved by the author''s organization prior to submission if required. Contact the societies which you belong to, if you have any question on manuscript submission or on the Journal EAEF.