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The objective of this study was to examine the online use of near infrared reflectance (NIR) spectroscopy to estimate the concentration of individual and groups of fatty acids (FA) as well as intramuscular fat (IMF) in crossbred Aberdeen Angus (AAx) and Limousin (LIMx) cattle. This was achieved by direct application of a fibre-optic probe to the muscle immediately after exposing the meat surface in the abattoir at 48 h post mortem. Samples of M. longissimus thoracis from 88 AAx and 106 LIMx were scanned over the NIR spectral range from 350 to 1800 nm and samples of the M. longissimus lumborum were analysed for IMF content and FA composition. Statistically significant differences (P < 0.001) were observed in most FA between the two breeds studied, with FA concentration being higher in AAx meat mainly. NIR calibrations, tested by cross-validation, showed moderate to high predictability in LIMx meat samples for C16:0, C16:1, C18:0, trans11 C18:1, C18:1, C18:2 n-6, C20:1, cis9, trans11 C18:2, SFA (saturated FA), MUFA (monounsaturated FA), PUFA (polyunsaturated FA) and IMF content with R-2 (SECV, mg/100 g muscle) of 0.69 (146), 0.69 (28), 0.71 (62), 0.70 (8.1), 0.76 (192), 0.65 (13), 0.71 (0.9), 0.71 (2.9), 0.68 (235), 0.75 (240), 0.64 (17) and 0.75 (477), respectively. FA such as C14:0, C18:3 n-3, C20:4 n-6, C20:5 n-3, C22:6 n-3, n-6 and n-3 were more difficult to predict by NIR in these LIMx samples (R-2 = 0.12 to 0.62; SECV = 0.5 to 26 mg/100 g muscle). In contrast, NIR showed low predictability for FA in AAx beef samples. In particular for LIMx, the correlations of NIR measurements and several FA in the range from 0.81 to 0.87 indicated that the NIR spectroscopy is a useful online technique for the early, fast and relatively inexpensive estimation of FA composition in the abattoir.

The potential of X-ray computed tomography (CT) as a predictor of cuts composition and meat quality traits using a multivariate calibration method (partial least square regression, PLSR) was investigated in beef cattle. Sirloins from 88 crossbred Aberdeen Angus (AAx) and 106 Limousin (LIMx) cattle were scanned using spiral CT. Subsequently, they were dissected and analyzed for technological and sensory parameters, as well as for intramuscular fat (IMF) content and fatty acid composition. CT-PLSR calibrations, tested by cross-validation, were able to predict with high accuracy the subcutaneous fat (R-2, RMSECV=0.94, 34.60 g and 0.92, 34.46 g). intermuscular fat (R-2, RMSECV=0.81, 161.54 g and 0.86, 42.16 g), total fat (R-2, RMSECV=0.89, 65.96 g and 0.93, 48.35 g) and muscle content (R-2, RMSECV=0.99, 58.55 g and 0.97, 57.45 g) in AAx and LIMx samples, respectively. Accurate CT predictions were found for fatty acid profile (R-2=0.61-0.75) and intramuscular fat content (R-2=0.71-0.76) in both sire breeds. However, low to very low accuracies were obtained for technological and sensory traits with R-2 ranged from 0.01 to 0.26. The image analysis evaluated provides the basis for an alternative approach to deliver very accurate predictions of cuts composition, IMF content and fatty acid profile with lower costs than the reference methods (dissection, chemical analysis), without damaging or depreciating the beef cuts. (C) 2010 The American Meat Science Association.

The potential of the composition of the forerib measured by X-ray computed tomography (CT) as a predictor of carcass composition was evaluated using data recorded on 30 Aberdeen Angus and 43 Limousin crossbred heifers and steers. The left sides of the carcasses were split into 20 cuts, which were CT scanned and fully dissected into fat, muscle and bone. Carcass and forerib tissue weights were assessed by dissection and CT. Carcass composition was assessed very accurately by CT scanning of the primal cuts (adj-R-2 = 0.97 for the three tissues). CT scanning predicted weights of fat muscle and bone of the forerib with adj-R-2 of 0.95, 0.91 and 0.75, respectively. Single regression models with the weights of fat muscle or bone in the forerib measured by CT as the only predictors to estimate fat, muscle or bone of the left carcass obtained by CT showed adjusted coefficients of determination (adj-R-2) of 0.79, 0.60 and 0.52, respectively. By additionally fitting breed and sex, accuracy increased to 0.85, 0.73 and 0.67. Using carcass and forerib weights in addition to the previous predictors improved significantly the prediction accuracy of carcass fat and muscle weights to adj-R-2 values of 0.92 and 0.96, respectively, while the highest value for carcass bone weight was 0.77 In general, equations derived using CT data had lower adj-R-2 values for bone, but better accuracies for fat and muscle compared to those obtained using dissection. CT scanning could be considered as an alternative very accurate and fast method to assess beef carcass composition that could be very useful for breeding programmes and research studies involving a large number of animals, including the calibration of other indirect methods (e.g. in vivo and carcass video image analysis).

Carcass composition and meat traits are relevant for the definition of beef quality. Direct assessments of both groups of traits require the slaughter of the animal and are costly and time-consuming, which has limited the inclusion of quality traits in breeding programmes. X-ray computed tomography (CT) is a non-invasive technique that provides accurate predictions of beef carcass composition (Navajas et al., 2009). Studies in sheep showed that average CT muscle density is correlated with intramuscular fat content, fatty acid profile and eating quality (Bishop and Karamichou, 2009). The aim of this study was to assess the potential of CT tissue density values, analysed using a multivariate approach, as predictors of beef cut composition and meat quality in Aberdeen Angus and Limousin crossbred cattle.

[EN] Dissection is the reference method to measure carcass composition, which is one of the attributes that defines carcass value. Full carcass dissection is an expensive and time-consuming procedure, and therefore only suitable for a limited number of applications such as research trials involving a relatively small number of animals. Partial dissection using a sample joint was one of the first methods to be considered to reduce costs and increase the number of carcasses to be assessed. X-ray computed tomography (CT) is a non-invasive method recently evaluated as a predictor of beef carcass composition. Carcass tissue weights were assessed with R2 values between 0.96 and 0.97 based on the CT scanning of all primal cuts (Navajas et al., 2009). The aim of this study was to compare the potential of the compositions of a forerib sample joint measured by CT and dissection as predictors of beef carcass composition.

[EN] Current grading methods for fat yield in UK abattoirs are limited to subjective fat classification score based on the EUROP based system. Video image analyses (VIA) methods have previously been employed commercially to estimate fat classification and carcass yield in other EU countries. Recently, fat trim yield has been strongly predicted (R2 = 0.8) by VIA system (Vote et al., 2009) and fat thickness measured manually has shown to correlate with intramuscular fat content (Indurain et al., 2009). Carcass and primal fat-yield information would be commercially useful in determining the quality and value of primal cuts. The aim of this study was to assess the potential of predicting half carcass and selected primal-cut subcutaneous fat yield using features extracted from high-resolution carcass digital images taken on-line at chain speed.

Meat tenderness is the single most important quality attribute in consumer acceptance studies of meat eating quality. Several mechanical-based techniques have been developed to provide an objective measure of meat tenderness that have good correlation with sensory tenderness, as assessed by trained taste panel. The classic Warner-Bratzler shear force technique (WBSF) has shown correlations with sensory tenderness in the range of -0.39 to -0.77 (Van Oeckel et al., 1999; Shackelford et al., 1999a), whilst the Volodkevitch bite test attempts to imitate the incisor biting action by a compression method. A rapid slice shear force (SSF) test, which uses only one steak and hot meat (significant benefits in a commercial environment), had a stronger correlation with taste panel tenderness scores than WBSF (Shackelford et al., 1999b). The Meat Industry Research Institute of New Zealand (MIRINZ) test results, transformed into categories, was highly correlated (-0.97) with sensory tenderness (Bickerstaffe et al., 2001). The objective of this study was to evaluate the associations between objective physical measures (SSF, MIRINZ and Volodkevitch) and taste panel tenderness scores in beef.

The amount and fatty acid (FA) composition of beef intramuscular fat (IMF) are key factors that influence technological and sensory quality, especially shelf-life (lipid and pigment oxidation) and flavour. Furthermore, consumers are interested in the fat composition of meat, as nutritional guidelines are recommending a lower saturated FA (SFA) intake due to its association with cardiovascular diseases. The amount and composition of ruminant IMF, which depends on factors such as the genetic origin of the animals, feeding regime, age or live weight, influences the final quality of the product, which also explains the increasing interest in defining the FA profile of meat. However, quantitative chemical techniques for the determination of FA involve extraction of total lipids and determination of FA methyl esters by gas chromatography, so that this procedure is costly, time-consuming and generates hazardous waste. The use of near infrared reflectance spectroscopy (NIR) is increasing in food analysis because it offers several advantages over conventional methods, giving fast, non-destructive, clean and cost effective measurements. Therefore, the aim of this study was to test the on-line estimation of the concentration of major individual FA (C16:0, C18:0 and C18:1) and main groups of FA (SFA, monounsaturated FA (MUFA) and polyunsaturated FA (PUFA)) of beef IMF using NIR, by direct application of a fibreoptic probe to the M. longissimus thoracis with no prior sample treatment.

X-ray computed tomography (CT) scanning makes use of the different rates at which the tissues attenuate Xrays depending on their densities. CT muscle density (MD) is the average pixel value for this tissue in the CT images and is related to real density of the tissue, which depends on its chemical composition. One of the components determining muscle density is intramuscular fat (IMF). Studies in sheep have shown that MD, measured in vivo, was phenotypically and genetically correlated to IMF and to fatty acid (FA) composition in Scottish Blackface lambs (Karamichou et al. 2006). Intramuscular fat and FA are important traits to measure due to their association with the nutritional value and eating quality of meat. A novel automatic image analysis for spiral CT scans (SCTS) of beef primal cuts allows very accurate estimations of primal cut and carcass composition with R2 of 0.90 to 0.99 (Navajas et al., 2008). The aim of this study was to investigate the associations of MD of beef primal cuts with IMF and FA profile in Aberdeen Angus (AA) and Limousin (LIM) cattle, based on the CT thresholds estimated as part of the development of the image analysis described by Navajas et al. (2008).

The aim of this study was to assess the on-line implementation of visible and near infrared reflectance (Vis-NIR) spectroscopy as an early predictor of beef quality traits, by direct application of a fibre-optic probe to the muscle immediately after exposing the meat surface in the abattoir. Samples from M. longissimus thoracis from 194 heifers and steers were scanned at quartering 48 h postmortem over the Vis-NIR spectral range from 350 to 1800 nm. Thereafter, samples from M. longissimus thoracis et lumborum were analysed for colour (L*, a*, b*; 48 h postmortem), cooking loss (14 days postmortem), instrumental texture (Volodkevitch, 10 days aged meat; slice shear force, 3 and 14 days aged meat) and sensory characteristics. Vis-NIR calibrations, tested by cross-validation, showed high predictability for L*, a* and b* (R-2 = 0.86, 0.86 and 0.91; SECV = 0.96, 0.95 and 0.69, respectively). The accuracy of Vis-NIR to estimate cooking loss and instrumental texture ranged from R-2 = 0.31 to 0.54, suggesting relatively low prediction ability. Sensory characteristics assessed on 14 days aged meat samples showed R 2 in the range from 0.21 (juiciness) to 0.59 (flavour). Considering the subjective assessment of sensory characteristics the correlations of Vis-NIR measurements and several meat quality traits in the range from 0.46 to 0.95 support the use of on-line Vis-NIR in the abattoir. Improvement of predictability was achieved if only extreme classes of meat characteristics have to be predicted by Vis-NIR spectroscopy.