RESUMO
The effectiveness of dry ageing with regard to retaining meat quality is still subject to debate. At 4 d post mortem, samples of boneless strip loins were excised from young Charolais carcasses and then stored for a further 26 d in a cooler, either vacuum-packaged (VP) or dried-aged (DA). Loin samples were also dissected 7 d post mortem as a control treatment (CT). Chemical, instrumental and microbiological data (n = 18) were determined in longissimus dorsi and underwent ANOVA to estimate the differences in the ageing fixed factor split into two orthogonal contrasts: control vs. aged and VP vs. DA. Ageing loss (both surface dehydration and water purge) was greater in DA compared to VP samples, resulting in the lowest moisture content and highest crude protein and fat percentage in DA loins. The ageing method did not affect meat surface colour, except for redness, which had the lowest value in DA samples. Meat tenderness improved a similar amount following both VP and DA ageing treatments. Compared to the control, prolonged ageing raised both the peroxide value and the total microbial count, especially in DA samples, though both remained within the recommended limits. In summation, both ageing methods improved beef meat tenderisation, preserving its shelf life.
RESUMO
Determining cocoa bean quality is crucial for many players in the international supply chain. However, actual methods rely on a cut test protocol, which is limited by its subjective nature, or on time-consuming, expensive and destructive wet-chemistry laboratory procedures. In this context, the application of near infrared (NIR) spectroscopy, particularly with the recent developments of portable NIR spectrometers, may represent a valuable solution for providing a cocoa beans' quality profile, in a rapid, non-destructive, and reliable way. Monitored parameters in this work were dry matter (DM), ash, shell, fat, protein, total polyphenols, fermentation index (FI), titratable acidity (TA) and pH. Different chemometric analyses were performed on the spectral data and calibration models were developed using modified partial least squares regression. Prediction equations were validated using a fivefold cross-validation and a comparison between the different prediction performances for the portable and benchtop NIR spectrometers was provided. The NIRS benchtop instrument provided better performance of quantification considering the whole than the portable device, showing excellent prediction capability in protein and DM quantification. On the other hand, the NIRS portable device, although showing lower but valuable performance of prediction, can represent an appealing alternative to benchtop instruments for food business operators, being applicable in the field.
RESUMO
The possibility of using near-infrared spectroscopy (NIRS) for the authentication of wild European sea bass ( Dicentrarchus labrax ) was investigated in this study. Three different chemometric techniques to process the NIR spectra were developed, and their ability to discriminate between wild and farmed sea bass samples was evaluated. One approach used spectral information to directly build the discrimination model in a latent variable space; the second approach first used wavelets to transform the spectral information and subsequently derived the discrimination model using the transformed spectra; in the third approach a cascaded arrangement was proposed whereby very limited chemical information was first estimated from spectra using a regression model, and this estimated information was then used to build the discrimination model in a latent variable space. All techniques showed that NIRS can be used to reliably discriminate between wild and farmed sea bass, achieving the same classification performance as classification methods that use chemical properties and morphometric traits. However, compared to methods based on chemical analysis, NIRS-based classification methods do not require reagents and are simpler, faster, more economical, and environmentally safer. All proposed techniques indicated that the most predictive spectral regions were those related to the absorbance of groups CH, CH(2), CH(3), and H(2)O, which are related to fat, fatty acids, and water content.
