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The possibility of using front-face fluorescence spectroscopy to characterize red wines was investigated, and a tentative identification of their main fluorescent components was attempted. Fifty-seven red wine samples from different origins were included in the present study. Their fluorescence excitation-emission matrices (EEMs) were registered directly on 3-mL aliquots of untreated samples. The assayed excitation and emission ranges were 245-340 and 300-500 nm, respectively. The set of 57 EEMs was analyzed by means of parallel factor analysis (PARAFAC). Thus, the spectral excitation and emission profiles of possible "pure" fluorescence components (PARAFAC loadings) and the relative contribution of each component to the individual EEMs (PARAFAC scores) were obtained. The red wine system contained four main fluorescence components, and the excitation and emission loadings had maxima at the wavelength pairs 260/380, 275/323, 330/410, and 280/364 nm, respectively. A tentative identification of fluorophores was done by matching PARAFAC score values with HPLC measurements on the same 57 samples, as well as fluorescence measurements on pure compounds typically present in red wine. It was found that the third component was highly correlated with concentrations of catechin and epicatechin. When the PARAFAC score values were plotted against each other, they did to some extent discriminate the wines according to origin (country) and grape variety.

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The objective of this work was to better understand the photosensitizing effect of riboflavin versus naturally occurring tetrapyrroles in cow's milk. This was done by exposure of milk samples to blue light (400-500 nm), which is absorbed by riboflavin and tetrapyrroles, orange light (575-750 nm), which is absorbed by tetrapyrroles but not riboflavin, and white light, which contains the entire visible region. The milk was exposed to about 1.6 W/m(2) in 20 h, and two different light sources were tested: HMI lamp and fluorescent light tubes used for commercial display. Sensory analysis showed that wavelengths longer than 575 nm induced significantly more off-flavors than wavelengths shorter than 500 nm. By fluorescence spectroscopy it was observed that tetrapyrroles, in particular, chlorophyllic compounds, were degraded more by orange light than by blue and that the degree of degradation correlated closely with the formation of sensory off-flavors. The fluorescent agent Singlet Oxygen Sensor Green (SOSG) was used to monitor the formation of singlet oxygen under the different light exposure conditions, and the method verified that singlet oxygen was formed in large proportions in milk exposed to wavelengths longer than 575 nm, presumably with minor or no involvement of riboflavin. The results suggest that cholorophyllic compounds are responsible for a major part of photooxidation in milk. It is also suggested that β-carotene protects against photooxidation under blue light because it absorbs a major portion of the light below 500 nm and thereby reduces reactions with photosensitizers.

An FTIR-based multivariate approach is developed for monitoring molecular weight distribution during enzymatic protein hydrolysis of byproducts.

Currently, there are a number of educational applications that allow students to reinforce theoretical or numerical concepts through an interactive way. More precisely, in the field of the analytical chemistry, MATLAB has been widely used to write easy-to-implement code, facilitating complex performances and/or tedious calculations. The main objective of this research is to present an ad hoc open MATLAB code toolbox, named AChemTitri, aimed to construct acid−base titration curves in an interactive format. The software has been designed by the means of pop-up windows where students only need to be acquainted with a basic or elementary knowledge of MATLAB. With this application, students will be able to practice with comprehensive titration options such as the titration of strong, weak, or polyfunctional acids and bases and, for each titration, different concentration of each compound as well as the titration volume can be selected. As a result, the software plots the titration curve (pH vs volume) and the first and second derivative of this former curve as well, together with the numerical results. Thus, students will have the opportunity to calculate the final point and pH of the titration graphically and numerically. In addition, concentration diagrams are also displayed (log of the species participating in the titration vs pH); thus, it will be easy to follow how the acid−base titration is progressing. In conclusion, this application is a feasible way to improve the basic concepts of acid−base titration throughout the practice of numerical exercise assisted by computer calculation. The possibility of changing all the chemical parameters and the graphic visualization of results could ease the learning process of students facing the titration concepts for the first time.