Potential of a custom-designed fluorescence imager combined with multivariate statistics for the study of chemical and mechanical characteristics of beef meat

International audienceThe potential of fluorescence imaging to discriminate different bovine muscles in relation with animal age, muscle type, chemical and mechanical properties was examined. Twenty-four muscles of three types (Gluteus medius, Longissimus dorsi, and Semitendinosus) and two animal age groups (10-13-years old and 12-24-months old) were obtained from the carcasses of Limousin breed cows. One hundred and forty-four images were collected at three illuminating conditions (exc 320 nm, exc 380 nm, and white light) using a custom-designed imager. The image cubes were processed using "regionprops" algorithm developed earlier in order to extract image shape features (number of shapes, area, major-axis-length, eccentricity, and solidity). Extracted image shape features were processed using custom-designed programs. The results of the PLSDA performed on image shape features showed 100% good discrimination for the three types of muscles. Muscle samples were also subjected to chemical analysis (dry matter, fat, pyridinoline, total, insoluble and soluble collagen) and mechanical tests (shear stress and breaking energy). PLSR models indicated relations between extracted image shape features and mechanical properties. i.e., R(2) = 0.69 and RMSEV = 0.514 were observed for breaking energy for adult-animal muscles. Regarding chemical composition, image shape features allowed to predict total collagen of L. dorsi with R(2) = 0.61 and RMSEV = 0.756. This study has demonstrated a promising potential of the custom-designed fluorescence imager combined with multivariate statistical tools in the study of beef meat. (C) 2011 Elsevier Ltd. All rights reserved

Investigation at the molecular level of soft cheese quality and ripening by infrared and fluorescence spectroscopies and chemometrics-relationships with rheology properties

International audienceTwelve traditional and 12 stabilised experimental soft cheeses were made according to a factorial design to two levels of dry matter (44% and 48%) and two fat on dry matter ratios (51% and 55%). Cheese samples were analysed using various methods to give physico-chemical data, uniaxial compression test data, emission spectra of tryptophan residues, excitation spectra of vitamin A, and the 900–1500, 2800–3000 and 1500–1700 cm−1 infrared regions. Common components and specific weights analysis showed that the common component 1 discriminating young and ripened cheeses explained 95%, 92%, 73% of the inertia of the 900–1500, 2800–3000 and 1500–1700 cm−1 infrared regions, respectively, and 51% of the rheology data. Common component 2 discriminating cheeses as a function of the technology explained 88%, 23% and 11% of the inertia of vitamin A spectra, chemical data and rheology data, respectively. The spectral patterns allowed molecular interpretations of the discrimination