期刊
INTERNATIONAL JOURNAL OF FOOD SCIENCE AND TECHNOLOGY
卷 57, 期 7, 页码 4507-4517出版社
WILEY
DOI: 10.1111/ijfs.15786
关键词
NIR spectroscopy; PLS-DA; geographical origin; green coffee bean; Classification; species
资金
- Ho Chi Minh City University of Technology (HCMUT)
- VNU-HCM
This study investigates the use of near-infrared spectroscopy (NIRS) for the authentication of agricultural resources, specifically green coffee beans. The results show that NIRS has great potential in accurately predicting coffee species and geographical indication.
To prevent the adulteration of agricultural resources and provide a solution to enhance the green coffee bean supply chain, authentication using the near-infrared spectroscopy (NIRS) technique was investigated. Partial least square with discrimination analysis (PLS-DA) models combined with various preprocessing methods were built from NIR spectra of 153 Vietnamese green coffee samples. The model combined with the standard normal variate and the first order of derivative yielded excellent performance in predicting coffee species with the error cross-validation of 0.0261. PLS-DA model of mean centre and first-order derivative spectra also yielded good performance in verifying geographical indication of green coffee with the error of 0.0656. By contrast, the predicting abilities of post-harvest methods were poor. The overall results showed a high potential of the NIRS in online authentication practices.
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