Journal
FOOD CHEMISTRY
Volume 297, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2019.124963
Keywords
Organic system; K-nearest neighbors; Support vector machines; Discriminant analysis; Food authenticity; Supervised statistical methods
Funding
- Brazilian Council for Scientific and Technological Development (CNPq) [303188/2016-2]
- National Natural Science Foundation of China [31700610]
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Authentication of ground coffee has become an important issue because of fraudulent activities in the sector. In the current work, sixty-seven Brazilian coffees produced in different geographical origins using organic (ORG, n=25) and conventional (CONV, n=42) systems were analyzed for their stable isotope ratios (delta C-13, delta O-18, delta H-2, and delta N-15). Data were analyzed by inferential analysis to compare the factors whereas linear discriminant analysis (LDA), k-nearest neighbors (k-NN), and support vector machines (SVM) were used to classify the coffees based on their origin. ORG and CONV cultivated coffees could not be differentiated according to C stable isotope ratio (delta C-13; p=0.204), but ORG coffees presented higher values of the N stable isotope ratio (delta N-15; p=0.0006). k-NN presented the best classification results for both ORG and CONV coffees (87% and 67%, respectively). SVM correctly classified coffees produced in Sao Paulo (75% accuracy), while LDA correctly classified 71% of coffees produced in Minas Gerais.
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