Non-targeted metabolomics of moldy wheat by ultra-performance liquid chromatography – quadrupole time-of-flight mass spectrometry
IntroductionAs one of the staple foods for the world’s major populations, the safety of wheat is critical in ensuring people’s wellbeing. However, mildew is one of the prevalent safety issues that threatens the quality of wheat during growth, production, and storage. Due to the complex nature of the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-04-01
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| Series: | Frontiers in Microbiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmicb.2023.1136516/full |
| _version_ | 1797851349340127232 |
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| author | Boyan Gao Weiying Lu Mengchu Jin Yumei Chen |
| author_facet | Boyan Gao Weiying Lu Mengchu Jin Yumei Chen |
| author_sort | Boyan Gao |
| collection | DOAJ |
| description | IntroductionAs one of the staple foods for the world’s major populations, the safety of wheat is critical in ensuring people’s wellbeing. However, mildew is one of the prevalent safety issues that threatens the quality of wheat during growth, production, and storage. Due to the complex nature of the microbial metabolites, the rapid identification of moldy wheat is challenging.MethodsIn this research, identification of moldy wheat samples was studied using ultra-performance liquid chromatography - quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) coupled with chemometrics. The non-targeted PCA model for identifying moldy wheat from normal wheat was established by using previously established compounds database of authentic wheat samples. The partial least squares-discriminant analysis (PLS-DA) was performed.Results and discussionBy optimizing the model parameters, correct discrimination of the moldy wheat as low as 5% (w/w) adulteration level could be achieved. Differential biomarkers unique to moldy wheat were also extracted to identify between the moldy and authentic wheat samples. The results demonstrated that the chemical information of wheat combined with the existing PCA model could efficiently discriminate between the constructed moldy wheat samples. The study offered an effective method toward screening wheat safety. |
| first_indexed | 2024-04-09T19:16:27Z |
| format | Article |
| id | doaj.art-13144615fca14803840e6dc80ec8fea2 |
| institution | Directory Open Access Journal |
| issn | 1664-302X |
| language | English |
| last_indexed | 2024-04-09T19:16:27Z |
| publishDate | 2023-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Microbiology |
| spelling | doaj.art-13144615fca14803840e6dc80ec8fea22023-04-06T05:17:29ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2023-04-011410.3389/fmicb.2023.11365161136516Non-targeted metabolomics of moldy wheat by ultra-performance liquid chromatography – quadrupole time-of-flight mass spectrometryBoyan GaoWeiying LuMengchu JinYumei ChenIntroductionAs one of the staple foods for the world’s major populations, the safety of wheat is critical in ensuring people’s wellbeing. However, mildew is one of the prevalent safety issues that threatens the quality of wheat during growth, production, and storage. Due to the complex nature of the microbial metabolites, the rapid identification of moldy wheat is challenging.MethodsIn this research, identification of moldy wheat samples was studied using ultra-performance liquid chromatography - quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) coupled with chemometrics. The non-targeted PCA model for identifying moldy wheat from normal wheat was established by using previously established compounds database of authentic wheat samples. The partial least squares-discriminant analysis (PLS-DA) was performed.Results and discussionBy optimizing the model parameters, correct discrimination of the moldy wheat as low as 5% (w/w) adulteration level could be achieved. Differential biomarkers unique to moldy wheat were also extracted to identify between the moldy and authentic wheat samples. The results demonstrated that the chemical information of wheat combined with the existing PCA model could efficiently discriminate between the constructed moldy wheat samples. The study offered an effective method toward screening wheat safety.https://www.frontiersin.org/articles/10.3389/fmicb.2023.1136516/fullwheatmildewnon-targeted detectionUPLC-QTOF-MSmetabolomics |
| spellingShingle | Boyan Gao Weiying Lu Mengchu Jin Yumei Chen Non-targeted metabolomics of moldy wheat by ultra-performance liquid chromatography – quadrupole time-of-flight mass spectrometry Frontiers in Microbiology wheat mildew non-targeted detection UPLC-QTOF-MS metabolomics |
| title | Non-targeted metabolomics of moldy wheat by ultra-performance liquid chromatography – quadrupole time-of-flight mass spectrometry |
| title_full | Non-targeted metabolomics of moldy wheat by ultra-performance liquid chromatography – quadrupole time-of-flight mass spectrometry |
| title_fullStr | Non-targeted metabolomics of moldy wheat by ultra-performance liquid chromatography – quadrupole time-of-flight mass spectrometry |
| title_full_unstemmed | Non-targeted metabolomics of moldy wheat by ultra-performance liquid chromatography – quadrupole time-of-flight mass spectrometry |
| title_short | Non-targeted metabolomics of moldy wheat by ultra-performance liquid chromatography – quadrupole time-of-flight mass spectrometry |
| title_sort | non targeted metabolomics of moldy wheat by ultra performance liquid chromatography quadrupole time of flight mass spectrometry |
| topic | wheat mildew non-targeted detection UPLC-QTOF-MS metabolomics |
| url | https://www.frontiersin.org/articles/10.3389/fmicb.2023.1136516/full |
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