Authentication of Geographical Origin and Crop System of Grape Juices by Phenolic Compounds and Antioxidant Activity Using Chemometrics

The main goal of this work was to propose an authentication model based on the phenolic composition and antioxidant and metal chelating capacities of purple grape juices produced in Brazil and Europe in order to assess their typicality. For this purpose, organic, conventional, and biodynamic grape juices produced in Brazil (n = 65) and in Europe (n = 31) were analyzed and different multivariate class-modeling and classification statistical techniques were employed to differentiate juices based on the geographical origin and crop system. Overall, Brazilian juices, regardless of the crop system adopted, presented higher contents of total phenolic compounds and flavonoids, total monomeric anthocyanins, proanthocyanidins, flavonols, flavanols, cyanidin-3-glucoside, delphinidin-3-glucoside, and malvidin-3,5-glucoside. No differences were observed for trans-resveratrol, malvidin-3-glucoside, and pelargonidin-3-glucoside between countries and among crop systems. A total of 91% of Brazilian and 97% of European juices were adroitly classified using partial least squares discriminant analysis when the producing region was considered (92% efficiency), in which the free-radical scavenging activity toward 2,2-diphenyl-1-picrylhydrazyl, content of total phenolic compounds, gallic acid, and malvidin-3-glucoside were the variables responsible for the classification. Intraregional models based on soft independent modeling of class analogy were able to differentiate organic from conventional Brazilian juices as well as conventional and organic/biodynamic European juices

Prediction of the identity of fats and oils by their fatty acid, triacylglycerol and volatile compositions using PLS-DA

The identity of a variety of animal fats and vegetable oils was predicted by three different analytical techniques with help of chemometrics. The sample material of animal origin consisted of milk fat, cow fat, pig fat and poultry fat. The vegetable oils comprised coconut, palm and palm kernel oils. Each product group was composed of at least eight samples of independent batches. For the identity prediction of the fats/oils several (combinations of) datasets were used: absolute and relative measurements of fatty acid compositions, of triacylglycerol compositions, and of combined fatty acid and triacylglycerol compositions. Volatile organic compound compositions were used as well. Fatty acid and triacylglycerol compositions were determined by gas chromatography. Fingerprints of volatile compositions were acquired using Proton transfer reaction-mass spectrometry. The rates of successful prediction were high and varied between 89 and 100%. The 100% rate was obtained for the absolute combined fatty acid/triacylglycerol dataset. Proton transfer reaction-mass spectrometry resulted in 89% correct classifications, has the advantage that it allows very rapid measurements compared to the other techniques, but requires further studie