Journal
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
Volume 98, Issue 6, Pages 2215-2222Publisher
WILEY
DOI: 10.1002/jsfa.8707
Keywords
data fusion; traceability; Boletaceae mushrooms; ultraviolet-visible (UV-visible) spectroscopy; Fourier transform infrared (FTIR) spectroscopy
Funding
- University Key Laboratory of Development and Utilization of Edible Mushroom Resources in Yunnan Province
- National Natural Science Foundation of China [21667031, 31660591]
- Science Foundation of the Yunnan Province Department of Education [2016ZZX106]
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BACKGROUNDBoletaceae mushrooms are wild-grown edible mushrooms that have high nutrition, delicious flavor and large economic value distributing in Yunnan Province, China. Traceability is important for the authentication and quality assessment of Boletaceae mushrooms. In this study, UV-visible and Fourier transform infrared (FTIR) spectroscopies were applied for traceability of 247 Boletaceae mushroom samples in combination with chemometrics. RESULTSCompared with a single spectroscopy technique, data fusion strategy can obviously improve the classification performance in partial least square discriminant analysis (PLS-DA) and grid-search support vector machine (GS-SVM) models, for both species and geographical origin traceability. In addition, PLS-DA and GS-SVM models can provide 100.00% accuracy for species traceability and have reliable evaluation parameters. For geographical origin traceability, the accuracy of prediction in the PLS-DA model by data fusion was just 64.63%, but the GS-SVM model based on data fusion was 100.00%. CONCLUSIONThe results demonstrated that the data fusion strategy of UV-visible and FTIR combined with GS-SVM could provide a higher synergic effect for traceability of Boletaceae mushrooms and have a good generalization ability for the comprehensive quality control and evaluation of similar foods. (c) 2017 Society of Chemical Industry
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