Suchergebnisse

1 page, 1 table.-- The Proceedings of the British Society of Animal Science constitute summaries of papers presented at the Society's Annual Conference (Southport, UK, 30 March-1 April, 2009). ; Due to an increasingly discerning consumer demand, the eating quality of beef has become a major focus of research effort for the beef supply chain and some pricing schemes currently reward Aberdeen Angus sired animals over animals sired by other breeds. However, the animal performance characteristics of beef cattle at a farm level must also be examined in studies on beef eating quality since they will remain an integral part of primary producer returns for the foreseeable future. As part of a wider beef eating quality project, the objective of the current study was to assess the onfarm and carcass animal performance characteristics in suckler-bred steers and heifers during the finishing phase. ; SAC receives support from the Scottish Government. Support is also acknowledged from Signet Breeding Services, BCF Technology Ltd and Scotbeef Ltd. ; Peer reviewed

11 páginas, 4 tablas, 2 figuras. ; 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. ; Ministry of Science and Innovation (MICINN), Spain. Scottish Government. ; Peer reviewed

1 page, 1 table.-- Contributed to: Proceedings of the British Society of Animal Science or the Agricultural Research Forum (Belfast, UK, 12-14 April, 2010). ; 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. ; We are grateful to the Scottish Government for funding the research and Scotbeef, QMS, BCF and Signet for their substantial support. ; Peer reviewed

1 page, 1 table.-- Contributed to: Proceedings of the British Society of Animal Science or the Agricultural Research Forum (Belfast, UK, 12-14 April 2010). ; [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. ; We are grateful to Scottish Government for funding this work. The support of Scotbeef is gratefully acknowledged. ; Peer reviewed

10 páginas, 3 tablas, 1 figura. ; 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. ; Scottish Government. Ministry of Science and Innovation (MICINN), Spain. ; Peer reviewed

5 pages.-- Contributed to: 55th International Congress of Meat Science and Technology ( Copenhagen, aug 16-21, 2009). ; The objective of this study was to test the on-line estimation of the concentration of individual fatty acids (FA) and groups of FA in crossbred Limousin (LIM) and Aberdeen Angus (AA) beef samples using NIR spectroscopy (NIRS), immediately after exposing the meat surface in the abattoir at 48 h post mortem. Samples from 106 LIM and 88 AA M. longissimus thoracis were scanned over the NIR spectral range from 1100-1800 nm and samples of the M. longissimus lumborum were analyzed for fatty acid composition. NIR calibrations, tested by cross-validation, showed high predictability in LIM meat samples for the C16:0, C16:1, C18:0, C18:1, cis9, trans11 C18:2, C20:1, saturated (SFA) and monounsaturated (MUFA) fatty acids, with R2 of 0.689, 0.692, 0.714, 0.755, 0.714, 0.713, 0.676 and 0.753 and SECV (mg.100 g-1 muscle) of 146.2, 28.4, 62.4, 192.5, 2.87, 0.92, 235.5 and 239.8, respectively. Fatty acids such as C18:2 n-6 and polyunsaturated (PUFA) were more difficult to predict by NIRS in those samples (R2 = 0.653 and 0.643, SECV = 13.1 and 17.3 mg.100 g-1 muscle, respectively). The accuracy of prediction for individual and groups of FA concentration in AA beef samples was lower than that found in LIM ones, probably due to a less homogeneous distribution of meat sample population. The correlation of NIR measurements and several FA in the range from 0.82 to 0.87 indicated that NIRS is a useful on-line technique for the early, fast and relatively inexpensive estimation of FA composition in LIM beef samples in the abattoir. ; We are grateful to the Scottish Government for funding the research and Scotbeef, QMS, BCF and Signet for their substantial support. N. Prieto is grateful to the Ministry of Science and Innovation (MICINN), Spain, for financial assistance via a post-doctoral grant. ; Peer reviewed

8 páginas, 7 tablas, 1 figura. ; 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). ; Scottish Government. ; Peer reviewed

1 page, 1 table.--Contributed to: Proceedings of the British Society of Animal Science or the Agricultural Research Forum (Belfast, UK, 12-14 April, 2010). ; [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. ; Financial support for this research was received from the Scottish Government. ; Peer reviewed

1 page, 1 table.-- The Proceedings of the British Society of Animal Science constitute summaries of papers presented at the Society's Annual Conference (Southport, UK, 30 March-1 April, 2009). ; 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). ; We are grateful to Scottish Government for funding this work. The support of Scotbeef, MLC Signet Breeding Services and QMS are gratefully acknowledged. ; Peer reviewed

1 page, 1 figure.--The Proceedings of the British Society of Animal Science constitute summaries of papers presented at the Society's Annual Conference (Southport, UK, 30 March-1 April 2009). ; 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. ; We are grateful to the Scottish Government for funding the research and Scotbeef, QMS, BCF and Signet for their substantial support. ; Peer reviewed

1 page, 1 table.-- The Proceedings of the British Society of Animal Science constitute summaries of papers presented at the Society's Annual Conference (Southport, UK, 30 March-1 April 2009). ; Visible and near infrared reflectance spectroscopy (Vis-NIR) has been widely used by the industry researchbase for large-scale meat quality evaluation to predict the chemical composition of meat quickly and accurately. Meat tenderness is measured by means of slow and destructive methods (e.g. Warner-Bratzler shear force). Similarly, sensory analysis, using trained panellists, requires large meat samples and is a complex, expensive and time-consuming technique. Nevertheless, these characteristics are important criteria that affect consumers' evaluation of beef quality. Vis-NIR technique provides information about the molecular bonds (chemical constituents) and tissue ultra-structure in a scanned sample and thus can indirectly predict physical or sensory parameters of meat samples. Applications of Vis-NIR spectroscopy in an abattoir for prediction of physical and sensory characteristics have been less developed than in other fields. Therefore, the aim of this study was to test the on-line Vis-NIR spectroscopy for the prediction of beef quality characteristics such as colour, instrumental texture, water holding capacity (WHC) and sensory traits, by direct application of a fibre-optic probe to the M. longissimus thoracis with no prior sample treatment. ; We are grateful to the Scottish Government for funding the research and Scotbeef, QMS, BCF and Signet for their substantial support. ; Peer reviewed

1 page, 1 table.-- Contributed to: Proceedings of the British Society of Animal Science (Belfast, UK, 12-14 April, 2010). ; [EN] Weight, proportion and distribution of fat and muscle in beef carcasses are of importance in order to maximise economic value and reduce waste. In-vivo ultrasound-measured predictors of cattle carcass composition could be of use when taken at the beginning of the finishing period (to allocate feeding groups and levels or for early selection of potential breeding stock), or pre-slaughter (to market-select finished animals, sort carcasses on quality, or feed back information from slaughter animals to breeding programmes). The aims of this study were to investigate the ability of ultrasound-measured fat and muscle depths to predict carcass composition and tissue distribution and to quantify the relative accuracy of predictions using ultrasound measurement taken at the start or end of the finishing period. ; SAC receives funding from the Scottish Government. ; Peer reviewed

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in >omic> data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent >omics> approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges. ; SH, DM, MP, RM-T, SW, IT, HS, JE, SK, GA, and CC acknowledge the support of ERA-net gas co-fund for funding (Project name: RumenPredict). SH, HM and CC acknowledge support from BBSRC (BBL/L026716/1 and BBL/L026716/2) and a British Council Newton Institutional Links funding (Grant 172629373). IM acknowledges funding from the European Research Council under the European Union's Horizon 2020 research and innovation program (Grant 640384). JE acknowledges funding from an EU H2020 Marie Curie Fellowship (706899). CC, AK-S, and EH were supported by the Biotechnology and Biological Sciences Research Council (Grants BBS/OS/GC/000011B and BBS/E/W/0012843D). CN and OM acknowledge the support of the British Council Newton Institutional Links funding (Grant 216425215). SRUC receives financial support from the Scottish Government's Rural and Environment Science and Analytical Services Division (RESAS). RD and RR acknowledge financial support from the Biotechnology and Biological Sciences Research Council (BBSRC BB/N01720X/1). DY-R and AB acknowledge funding from MINECO, Spain (Grant AGL2017-86938-R). GS acknowledges funding from the U.S. Department of Agriculture National Institute of Food and Agriculture foundational (Grant 2015-67015-23246). EP acknowledges funding from CNPq (Grant 401590/2014-3). All authors are also members of the Global Research Alliance Rumen Microbial Genomics network. ; Peer Reviewed