TY - JOUR
T1 - Characterization of Brazilian coffee based on isotope ratio mass spectrometry (δ13C, δ18O, δ2H, and δ15N) and supervised chemometrics
AU - Peng, Chuan yi
AU - Zhang, Yan ling
AU - Song, Wei
AU - Cai, Hui mei
AU - Wang, Yijun
AU - Granato, Daniel
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/11/1
Y1 - 2019/11/1
N2 - 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 (δ13C, δ18O, δ2H, and δ15N). 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 (δ13C; p = 0.204), but ORG coffees presented higher values of the N stable isotope ratio (δ15N; 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 São Paulo (75% accuracy), while LDA correctly classified 71% of coffees produced in Minas Gerais.
AB - 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 (δ13C, δ18O, δ2H, and δ15N). 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 (δ13C; p = 0.204), but ORG coffees presented higher values of the N stable isotope ratio (δ15N; 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 São Paulo (75% accuracy), while LDA correctly classified 71% of coffees produced in Minas Gerais.
KW - Discriminant analysis
KW - Food authenticity
KW - K-nearest neighbors
KW - Organic system
KW - Supervised statistical methods
KW - Support vector machines
UR - http://www.scopus.com/inward/record.url?scp=85067197557&partnerID=8YFLogxK
U2 - 10.1016/j.foodchem.2019.124963
DO - 10.1016/j.foodchem.2019.124963
M3 - Article
C2 - 31253305
AN - SCOPUS:85067197557
SN - 0308-8146
VL - 297
SP - 124963
JO - Food Chemistry
JF - Food Chemistry
M1 - 124963
ER -