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https://www.selleckchem.com/products/kynurenic-acid.html Correlation and validation of the results of simulated gastrointestinal digestion of food compounds towards in vivo data is essential. The objective of this work was to monitor the digestion of milk micellar casein in the porcine upper intestinal tract and to match the outcome with the gastric in vitro digestion following the Infogest harmonized protocol. In pig duodenum, small amounts of intact caseins were present in all samples, while caseins were observed up to 60 min of gastric in vitro digestion. The peptide profile generated after in vitro and in vivo digestion showed clear similarities with specific overrepresented regions rich in proline and other hydrophobic residues. The statistical comparison of the in vivo and in vitro peptidome resulted in satisfactory correlation coefficients, up to 0.8. Therefore, the in vitro protocol used was a robust and simple model that provides a similar peptide profile than that found in porcine duodenum.With increasing demand for fast and reliable techniques for intact meat discrimination, we explore the potential of Raman spectroscopy in combination with three chemometric techniques to discriminate beef, lamb and venison meat samples. Ninety (90) intact red meat samples were measured using Raman spectroscopy, with the acquired spectral data preprocessed using a combination of rubber-band baseline correction, Savitzky-Golay smoothing and standard normal variate transformation. PLSDA and SVM classification were utilized in building classification models for the meat discrimination, whereas PCA was used for exploratory studies. Results obtained using linear and non-linear kernel SVM models yielded sensitivities of over 87 and 90 % respectively, with the corresponding specificities above 88 % on validation against a test set. The PLSDA model yielded over 80 % accuracy in classifying each of the meat specie. PLSDA and SVM classification models in combination with Raman spec

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