| Title: | Chemometric Analysis of the Volatile Compounds Generated by Aspergillus carbonarius Strains Isolated from Grapes and Dried Vine Fruits |
| Author(s): | Cheng Z; Li M; Marriott PJ; Zhang X; Wang S; Li J; Ma L; |
| Address: | "College of Food Science and Nutritional Engineering, China Agriculture University, Beijing 10083, China. cz421420@cau.edu.cn. College of Food Science and Nutritional Engineering, China Agriculture University, Beijing 10083, China. limenghua127@126.com. Australian Centre for Research on Separation Science, School of Chemistry, Monash University, Clayton, VIC 3800, Australia. philip.marriott@monash.edu. College of Food Science and Nutritional Engineering, China Agriculture University, Beijing 10083, China. zxxjoypeace@foxmail.com. College of Food Science and Nutritional Engineering, China Agriculture University, Beijing 10083, China. wang744447@126.com. Institute of Forestry, Xinjiang Agricultural University, Urumqi 830052, China. lijiangui1971@163.com. College of Food Science and Nutritional Engineering, China Agriculture University, Beijing 10083, China. lyma1203@cau.edu.cn. Supervision, Inspection & Testing Center for Agricultural Products Quality, Ministry of Agriculture, Beijing 100083, China. lyma1203@cau.edu.cn. Key Laboratory of Safety Assessment of Genetically Modified Organism (Food Safety), Ministry of Agriculture, Beijing 10083, China. lyma1203@cau.edu.cn" |
| ISSN/ISBN: | 2072-6651 (Electronic) 2072-6651 (Linking) |
| Abstract: | "Ochratoxin A (OTA) contamination in grape production is an important problem worldwide. Microbial volatile organic compounds (MVOCs) have been demonstrated as useful tools to identify different toxigenic strains. In this study, Aspergillus carbonarius strains were classified into two groups, moderate toxigenic strains (MT) and high toxigenic strains (HT), according to OTA-forming ability. The MVOCs were analyzed by GC-MS and the data processing was based on untargeted profiling using XCMS Online software. Orthogonal projection to latent structures discriminant analysis (OPLS-DA) was performed using extract ion chromatogram GC-MS datasets. For contrast, quantitative analysis was also performed. Results demonstrated that the performance of the OPLS-DA model of untargeted profiling was better than the quantitative method. Potential markers were successfully discovered by variable importance on projection (VIP) and t-test. (E)-2-octen-1-ol, octanal, 1-octen-3-one, styrene, limonene, methyl-2-phenylacetate and 3 unknown compounds were selected as potential markers for the MT group. Cuparene, (Z)-thujopsene, methyl octanoate and 1 unknown compound were identified as potential markers for the HT groups. Finally, the selected markers were used to construct a supported vector machine classification (SVM-C) model to check classification ability. The models showed good performance with the accuracy of cross-validation and test prediction of 87.93% and 92.00%, respectively" |
| Keywords: | Aspergillus/isolation & purification/*metabolism Fruit/*microbiology Ochratoxins/analysis/metabolism Secondary Metabolism Support Vector Machine Vitis/*microbiology Volatile Organic Compounds/*analysis/metabolism Aspergillus carbonarius biosynthetic pathw; |
| Notes: | "MedlineCheng, Zhan Li, Menghua Marriott, Philip J Zhang, Xiaoxu Wang, Shiping Li, Jiangui Ma, Liyan eng Research Support, Non-U.S. Gov't Switzerland 2018/02/09 Toxins (Basel). 2018 Feb 6; 10(2):71. doi: 10.3390/toxins10020071" |
