Determination of the geographical origin of green coffee beans using NIR spectroscopy and multivariate data analysis. (May 2019) - Giraudo, A.; Grassi, S.; Savorani, F.; Gavoci, G.; Casiraghi, E.; Geobaldo, F.
Abstract: In this work, near infrared (NIR) spectroscopy and multivariate data analysis were investigated as a fast and non-disruptive 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. Highlights: NIR Spectroscopy investigated to identify the geographical origin of green coffee. Partial Least Square-Discriminant Analysis applied to build classification models. Coffee origin for both continent and country was tested as discrimination parameter. Variable selection applied to NIR spectra allowed improving the model performance. Inter-laboratory comparison of the classification results was made by McNemar test.