Detection of Adulteration in Camellia Oil Using Near-Infrared Spectroscopy
Near-infrared spectroscopy (NIRS) combined with chemometrics analysis was used in this study to qualitatively and quantitatively determine the adulterated Camellia oil. A binary model was constructed for determining both the authenticity and the number of adulterated contents. NIRS combined with sup...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2018-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://doi.org/10.1051/matecconf/201823204081 |
| _version_ | 1818620923220066304 |
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| author | Luo Qingsong Yu Yaru Xu Qiang Chen Yang Zheng Xiao |
| author_facet | Luo Qingsong Yu Yaru Xu Qiang Chen Yang Zheng Xiao |
| author_sort | Luo Qingsong |
| collection | DOAJ |
| description | Near-infrared spectroscopy (NIRS) combined with chemometrics analysis was used in this study to qualitatively and quantitatively determine the adulterated Camellia oil. A binary model was constructed for determining both the authenticity and the number of adulterated contents. NIRS combined with support vector machine classification was used to establish a full spectral model and a selected spectral model via competitive adaptive heavy-weighted sampling and backward interval partial least squares. Notably, both of them were proved to be suitable for determining the authenticity of Camellia oil. NIRS combined with support vector machine regression may be used to predict the amount of adulterated content in Camellia oil because of the high model correlation coefficient (R was higher than 99%, and the maximum mean square error was 0.0605). |
| first_indexed | 2024-12-16T18:01:05Z |
| format | Article |
| id | doaj.art-066e38b1a6544307a0db0474cdc963b7 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-16T18:01:05Z |
| publishDate | 2018-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-066e38b1a6544307a0db0474cdc963b72022-12-21T22:22:03ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-012320408110.1051/matecconf/201823204081matecconf_eitce2018_04081Detection of Adulteration in Camellia Oil Using Near-Infrared SpectroscopyLuo QingsongYu YaruXu QiangChen YangZheng XiaoNear-infrared spectroscopy (NIRS) combined with chemometrics analysis was used in this study to qualitatively and quantitatively determine the adulterated Camellia oil. A binary model was constructed for determining both the authenticity and the number of adulterated contents. NIRS combined with support vector machine classification was used to establish a full spectral model and a selected spectral model via competitive adaptive heavy-weighted sampling and backward interval partial least squares. Notably, both of them were proved to be suitable for determining the authenticity of Camellia oil. NIRS combined with support vector machine regression may be used to predict the amount of adulterated content in Camellia oil because of the high model correlation coefficient (R was higher than 99%, and the maximum mean square error was 0.0605).https://doi.org/10.1051/matecconf/201823204081 |
| spellingShingle | Luo Qingsong Yu Yaru Xu Qiang Chen Yang Zheng Xiao Detection of Adulteration in Camellia Oil Using Near-Infrared Spectroscopy MATEC Web of Conferences |
| title | Detection of Adulteration in Camellia Oil Using Near-Infrared Spectroscopy |
| title_full | Detection of Adulteration in Camellia Oil Using Near-Infrared Spectroscopy |
| title_fullStr | Detection of Adulteration in Camellia Oil Using Near-Infrared Spectroscopy |
| title_full_unstemmed | Detection of Adulteration in Camellia Oil Using Near-Infrared Spectroscopy |
| title_short | Detection of Adulteration in Camellia Oil Using Near-Infrared Spectroscopy |
| title_sort | detection of adulteration in camellia oil using near infrared spectroscopy |
| url | https://doi.org/10.1051/matecconf/201823204081 |
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