In this work, near infrared (NIR) spectroscopy and multivariate data analysis were investigated as a fast and nondisruptive method to classify green coffee beans on continents and countries bases. FT-NIR spectra of 191 coffee samples, origin from 2 continents and 9 countries, were acquired by two different laboratories. Laboratory-independent Partial Least Square-Discriminant Analysis and interval PLS-DA models were developed by following a hierarchical approach, i.e. considering at first the continent and then the country of origin as discrimination rule. The best continent-based classification model was able to identify correctly more than 98% in prediction, whereas 100% of them were correctly predicted by the best country-based classification model. The inter-laboratory reliability of the proposed method was confirmed by McNemar test, since no significant differences (P > 0.05) were found. Furthermore, a validation was performed predicting the spectral test set of a laboratory using the model developed by the other one.
Determination of the geographical origin of green coffee beans using NIR spectroscopy and multivariate data analysis / Giraudo, A.; Grassi, S.; Savorani, F.; Gavoci, G.; Casiraghi, E.; Geobaldo, F.. - In: FOOD CONTROL. - ISSN 0956-7135. - 99(2019), pp. 137-145.
|Titolo:||Determination of the geographical origin of green coffee beans using NIR spectroscopy and multivariate data analysis|
|Data di pubblicazione:||2019|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1016/j.foodcont.2018.12.033|
|Appare nelle tipologie:||1.1 Articolo in rivista|
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