Detection of Adulteration in Canola Oil by Using GC-IMS and Chemometric Analysis
The aim of the present study was to detect adulteration of canola oil with other vegetable oils such as sunflower, soybean, and peanut oils and to build models for predicting the content of adulterant oil in canola oil. In this work, 147 adulterated samples were detected by gas chromatography-ion mo...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | International Journal of Analytical Chemistry |
| Online Access: | http://dx.doi.org/10.1155/2018/3160265 |
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| _version_ | 1832565604064690176 |
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| author | Tong Chen Xinyu Chen Daoli Lu Bin Chen |
| author_facet | Tong Chen Xinyu Chen Daoli Lu Bin Chen |
| author_sort | Tong Chen |
| collection | DOAJ |
| description | The aim of the present study was to detect adulteration of canola oil with other vegetable oils such as sunflower, soybean, and peanut oils and to build models for predicting the content of adulterant oil in canola oil. In this work, 147 adulterated samples were detected by gas chromatography-ion mobility spectrometry (GC-IMS) and chemometric analysis, and two methods of feature extraction, histogram of oriented gradient (HOG) and multiway principal component analysis (MPCA), were combined to pretreat the data set. The results evaluated by canonical discriminant analysis (CDA) algorithm indicated that the HOG-MPCA-CDA model was feasible to discriminate the canola oil adulterated with other oils and to precisely classify different levels of each adulterant oil. Partial least square analysis (PLS) was used to build prediction models for adulterant oil level in canola oil. The model built by PLS was proven to be effective and precise for predicting adulteration with good regression (R2>0.95) and low errors (RMSE ≤ 3.23). |
| format | Article |
| id | doaj-art-baf70a3b45f1444d937bcd76f1768147 |
| institution | Kabale University |
| issn | 1687-8760 1687-8779 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Analytical Chemistry |
| spelling | doaj-art-baf70a3b45f1444d937bcd76f17681472025-02-03T01:07:12ZengWileyInternational Journal of Analytical Chemistry1687-87601687-87792018-01-01201810.1155/2018/31602653160265Detection of Adulteration in Canola Oil by Using GC-IMS and Chemometric AnalysisTong Chen0Xinyu Chen1Daoli Lu2Bin Chen3School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, ChinaThe aim of the present study was to detect adulteration of canola oil with other vegetable oils such as sunflower, soybean, and peanut oils and to build models for predicting the content of adulterant oil in canola oil. In this work, 147 adulterated samples were detected by gas chromatography-ion mobility spectrometry (GC-IMS) and chemometric analysis, and two methods of feature extraction, histogram of oriented gradient (HOG) and multiway principal component analysis (MPCA), were combined to pretreat the data set. The results evaluated by canonical discriminant analysis (CDA) algorithm indicated that the HOG-MPCA-CDA model was feasible to discriminate the canola oil adulterated with other oils and to precisely classify different levels of each adulterant oil. Partial least square analysis (PLS) was used to build prediction models for adulterant oil level in canola oil. The model built by PLS was proven to be effective and precise for predicting adulteration with good regression (R2>0.95) and low errors (RMSE ≤ 3.23).http://dx.doi.org/10.1155/2018/3160265 |
| spellingShingle | Tong Chen Xinyu Chen Daoli Lu Bin Chen Detection of Adulteration in Canola Oil by Using GC-IMS and Chemometric Analysis International Journal of Analytical Chemistry |
| title | Detection of Adulteration in Canola Oil by Using GC-IMS and Chemometric Analysis |
| title_full | Detection of Adulteration in Canola Oil by Using GC-IMS and Chemometric Analysis |
| title_fullStr | Detection of Adulteration in Canola Oil by Using GC-IMS and Chemometric Analysis |
| title_full_unstemmed | Detection of Adulteration in Canola Oil by Using GC-IMS and Chemometric Analysis |
| title_short | Detection of Adulteration in Canola Oil by Using GC-IMS and Chemometric Analysis |
| title_sort | detection of adulteration in canola oil by using gc ims and chemometric analysis |
| url | http://dx.doi.org/10.1155/2018/3160265 |
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