Modeling excitation–emission fluorescence matrices with pattern recognition algorithms for classification of Argentine white wines according grape variety

Prediction of Firmness and pH for “Golden Delicious” Apple Based on Elasticity Index from Modal Analysis

“…After removing the outliers, in order to build the regression models, the total sample set was partitioned into 2 groups of samples based on the parameters such as OF, OG, SSC, pH, and all elasticity indices by the Kennard–Stone algorithm (Azcarate et al., ) through Matlab R2009a (MathWorks, Inc., U.S.A.), resulting in 75% samples in the calibration set for data modeling and 25% samples in the prediction set for evaluating the prediction abilities of the models (Table ).…”

Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications

“…Regarding the use of second-order data for classification studies, the scientific community has mainly focused their concern on the development of analytical methodologies for food authenticity and traceability [4,13]. Some of them have been applied on various foodstuff such as wines [12,[16][17][18][19][20][21][22][23], oils [5,[24][25][26][27][28][29][30], vinegar [31,32], mayonnaise [33], orange juice [34] , fish [35], meet [36], tomatoes [8][9], paprika [37], and honey [38,39] in order to determine characteristic patterns of compounds or parameters related to a geographical origin, the adulteration of samples or some specific conditions (e.g. processes, storage, harvest or variety).…”

Distinguishing between juniper-flavoured spirit drinks from different producers

“…The last technique is particularly attractive because of its high sensitivity and excellent specificity. By combining fluorescence spectroscopy and chemometric method discrimination of red wines according to grape variety (Airado-Rodríguez et al 2011;Saad et al 2016;Silvestri et al 2014;Yin et al 2009), typicality (Dufour et al 2006;Yin et al 2009), manufactures (Yin et al 2009) and geographical origin (Dufour et al 2006) or reliable classification of white wines according to grape variety (Azcarate et al 2015) can be successfully achieved. Furthermore, adulterations of brandy can be identified and determined by using chemometric methods even if slight fluorescent spectral variations are observed for the samples (Markechová et al 2014).…”