144 research outputs found

    What is artificial meat and what does it mean for the future of the meat industry?

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    The meat industry cannot respond to increases in demand by ever increasing resource use. The industry must find solutions to issues regarding animal welfare, health and sustainability and will have to do so in the face of competition from emerging non-traditional meat and protein products in an increasingly complex regulatory environment. These novel meat and protein products, otherwise known as 'artificial meat' are utilising ground breaking technologies designed to meet the issues facing the conventional meat industry. These artificial meats, in vitro or cultured meat and meat from genetically modified organisms have no real capacity to compete with conventional meat production in the present environment. However, meat replacements manufactured from plant proteins and mycoproteins are currently the biggest competitors and are gaining a small percentage of the market. Manufactured meats may push conventional meat into the premium end of the market, and supply the bulk, cheap end of the market if conventional meat products become more expensive and the palatability and versatility of manufactured meats improve. In time the technology for other artificial meats such as meat from genetic modified organisms or cultured meat may become sufficiently developed for these products to enter the market with no complexity of the competition between meat products. Conventional meat producers can assimilate agroecology ecology concepts in order to develop sustainable animal production systems. The conventional meat industry can also benefit from assimilating biotechnologies such as cloning and genetic modification technologies, using the technology to adapt to the changing environment and respond to the increasing competition from artificial meats. Although it will depend at least partly on the evolution of conventional meat production, the future of artificial meat produced from stem cells appears uncertain at this time

    Review: Improving the nutritional, sensory and market value of meat products from sheep and cattle

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    This paper focuses on improving the sensory, health attributes and meat yield of beef and lamb meats. Value for meat is defined as the weight of meat × price/kg received with price linked to eating quality. To maximise value across the supply chain, accurate carcass grading systems for eating quality and yield are paramount. Grading data can then be used to target consumers’ needs at given price points and then to tailor appropriate production and genetic directions. Both the grading methodologies and key phenotypes are complex and still under intensive research with international collaboration to maximise opportunities. In addition, there is value in promoting the health aspects of red meats served as whole trimmed meats. Typically, the total fat content is relatively low (less than 5%) and for forage systems, they deliver a very significant content of long-chain n-3 fatty acids. Further research is needed to clarify the healthiness or otherwise of ground beef served as burgers given the fat content is typically 20% or more. It is important to continue to improve the feedback to producers regarding the quantity and quality of the products they produce to target new value opportunities in a transparent and quantitative manner

    The variation in the eating quality of beef from different sexes and breed classes cannot be completely explained by carcass measurements

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    Delivering beef of consistent quality to the consumer is vital for consumer satisfaction and will help to ensure demand and therefore profitability within the beef industry. In Australia, this is being tackled with Meat Standards Australia (MSA), which uses carcass traits and processing factors to deliver an individual eating quality guarantee to the consumer for 135 different ‘cut by cooking methods’ from each carcass. The carcass traits used in the MSA model, such as ossification score, carcass weight and marbling explain the majority of the differences between breeds and sexes. Therefore, it was expected that the model would predict with eating quality of bulls and dairy breeds with good accuracy. In total, 8128 muscle samples from 482 carcasses from France, Poland, Ireland and Northern Ireland were MSA graded at slaughter then evaluated for tenderness, juiciness, flavour liking and overall liking by untrained consumers, according to MSA protocols. The scores were weighted (0.3, 0.1, 0.3, 0.3) and combined to form a global eating quality (meat quality (MQ4)) score. The carcasses were grouped into one of the three breed categories: beef breeds, dairy breeds and crosses. The difference between the actual and the MSA-predicted MQ4 scores were analysed using a linear mixed effects model including fixed effects for carcass hang method, cook type, muscle type, sex, country, breed category and postmortem ageing period, and random terms for animal identification, consumer country and kill group. Bulls had lower MQ4 scores than steers and females and were predicted less accurately by the MSA model. Beef breeds had lower eating quality scores than dairy breeds and crosses for five out of the 16 muscles tested. Beef breeds were also over predicted in comparison with the cross and dairy breeds for six out of the 16 muscles tested. Therefore, even after accounting for differences in carcass traits, bulls still differ in eating quality when compared with females and steers. Breed also influenced eating quality beyond differences in carcass traits. However, in this case, it was only for certain muscles. This should be taken into account when estimating the eating quality of meat. In addition, the coefficients used by the Australian MSA model for some muscles, marbling score and ultimate pH do not exactly reflect the influence of these factors on eating quality in this data set, and if this system was to be applied to Europe then the coefficients for these muscles and covariates would need further investigation

    Carcass characteristics and beef quality of young grass-fed Angus x Salers bovines

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    To characterize carcass and meat attributes, such as beef eating quality in specific farming conditions, 31 young grass-fed crossbred Angus x Salers cattle in two farming systems (a mono-cattle system versus a mixed system with beef cattle and sheep) were used in this study. Three muscle cuts (striploin—m. longissimus dorsi et thoracis; bolar blade—m. triceps brachii caput longum; internal flank plate—m. obliquus internus abdominis) were used for consumer eating quality testing and striploin was used for panelist eating quality assessment, and objective measurements [Warner–Bratzler shear force (WBSF) and fatty acid (FA) and antioxidant contents]. Results indicated that the farming system had no impact on carcass characteristics or meat quality, but it tended to affect FA content, which is likely explained by between-system differences in animal maturity (assessed by ossification score). Animal gender had significant effects on three eating quality traits evaluated by untrained consumers, with higher flavor liking, overall liking, and overall meat eating quality (MQ4) scores in females than in males. Additionally, FA contents were correlated with sensory quality traits to varying extents: consumer-scored tenderness, flavor, and overall liking were mainly positively correlated with ω-3 and ω-6 polyunsaturated fatty acid (PUFA) contents, and panelist-evaluated tenderness and abnormal flavor were more positively correlated with total lipids, saturated fatty acid (SFA), and monounsaturated fatty acid (MUFA) contents. Overall, this study showed that specific grass-fed crossbred Angus x Salers cattle can produce lean meat rich in ω-3 PUFAs with a low ω-6/ω-3 ratio and with “better than average” beef eating quality

    Untrained consumer assessment of the eating quality of European beef: 2. Demographic factors have only minor effects on consumer scores and willingness to pay

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    The beef industry must become more responsive to the changing market place and consumer demands. An essential part of this is quantifying a consumer’s perception of the eating quality of beef and their willingness to pay for that quality, across a broad range of demographics. Over 19 000 consumers from Northern Ireland, Poland, Ireland and France each tasted seven beef samples and scored them for tenderness, juiciness, flavour liking and overall liking. These scores were weighted and combined to create a fifth score, termed the Meat Quality 4 score (MQ4) (0.3×tenderness, 0.1×juiciness, 0.3×flavour liking and 0.3×overall liking). They also allocated the beef samples into one of four quality grades that best described the sample; unsatisfactory, good-every-day, better-than-every-day or premium. After the completion of the tasting panel, consumers were then asked to detail, in their own currency, their willingness to pay for these four categories which was subsequently converted to a proportion relative to the good-every-day category (P-WTP). Consumers also answered a short demographic questionnaire. The four sensory scores, the MQ4 score and the P-WTP were analysed separately, as dependant variables in linear mixed effects models. The answers from the demographic questionnaire were included in the model as fixed effects. Overall, there were only small differences in consumer scores and P-WTP between demographic groups. Consumers who preferred their beef cooked medium or well-done scored beef higher, except in Poland, where the opposite trend was found. This may be because Polish consumers were more likely to prefer their beef cooked well-done, but samples were cooked medium for this group. There was a small positive relationship with the importance of beef in the diet, increasing sensory scores by about 4% in Poland and Northern Ireland. Men also scored beef about 2% higher than women for most sensory scores in most countries. In most countries, consumers were willing to pay between 150 and 200% more for premium beef, and there was a 50% penalty in value for unsatisfactory beef. After quality grade, by far the greatest influence on P-WTP was country of origin. Consumer age also had a small negative relationship with P-WTP. The results indicate that a single quality score could reliably describe the eating quality experienced by all consumers. In addition, if reliable quality information is delivered to consumers they will pay more for better quality beef, which would add value to the beef industry and encourage improvements in quality

    Repercussions of growth path on carcass characteristics, meat colour and shear force in Alentejana bulls

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    The aim of this study was to evaluate the carcass and meat characteristics of eight muscles from bulls with distinct growth paths. A total of 40 Alentejana male calves were allocated to two distinct feeding regimes. In the continuous growth (CG) system, the animals were fed concentrates plus hay and were slaughtered at 18 months of age. On the other hand, in the discontinuous growth (DG) system, the animals were fed hay until 15 months of age; the cattle were then fed the same diet provided to the CG group from 15 to 24 months of age. The DG reduced hot carcass weight, fatness and dressing %, but the proportions of fat, bone and muscle tissues in the leg were not affected. In contrast, there was a positive impact of compensatory growth on supraspinatus, triceps brachii, semitendinosus, biceps femoris muscle tenderness, overcoming the negative effects of age at slaughter. The reasons for such improvement in meat tenderness were not related to intra-muscular fat content or myofibrillar protein degradation values. An association between tenderness and muscle collagen properties was not established. The results indicate that the compensatory growth has a muscle-dependent effect

    European cattle breed cluster accordingly to their meat quality parameters

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    The concept of breed is rather questionable and it's used more as a tool for "labelling" production systems than as a biological category. Here, production system is intended as a whole set of animal units, techniques, breeding schemes, marketing, etc. However, man has demonstrated to be very quick in capturing and disseminating good characteristics whence they appear in a breed by mutation or by selection. Therefore, it might be expected that breeds, nevertheless of recent origin, could bear distinguished productive characteristics. Due to the quan- titative nature of them, more characteristics should be measured in order to obtain a clear and statistically significant distinction. We have measured several meat characteristics in 15 European breeds (30 individuals for each breed), mostly with beef attitude, reared in similar conditions. This was accomplished to better reveal the genetic background of breeds. A canonical discriminant analysis showed a clear distinction among breeds. In particular lipid composition of meat was able to assign individuals to breeds with 57% and 63% of individuals correctly classified respectively for neutral and phospholipids. The classification is generally good for all breeds except for the Spanish ones,indicating probably some crossing in the past for these breeds. Neutral lipids can classify double muscled breeds with high precision (84% and 95% in Asturiana de los Valles and Piedmontese respectively). Tenderness related measures (collagen, ”-calpain, m-calpain, calpastatin, MFI) poorly assign indi- viduals to breeds (average 22%). The good classification of individuals to breeds for lipid composition suggests distinctive genetic features and encourages to look further to genetic determination of fat composition in the meat, as well as to exploit particular breeds to obtain products suitable for categories of consumers needing/searching for special components in their diet

    Modelling of beef sensory quality for a better prediction of palatability

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    Despite efforts by the industry to control the eating quality of beef, there remains a high level of variability in palatability, which is one reason for consumer dissatisfaction. In Europe, there is still no reliable on-line tool to predict beef quality and deliver consistent quality beef to consumers. Beef quality traits depend in part on the physical and chemical properties of the muscles. The determination of these properties (known as muscle profiling) will allow for more informed decisions to be made in the selection of individual muscles for the production of value-added products. Therefore, scientists and professional partners of the ProSafeBeef project have brought together all the data they have accumulated over 20 years. The resulting BIF-Beef (Integrated and Functional Biology of Beef) data warehouse contains available data of animal growth, carcass composition, muscle tissue characteristics and beef quality traits. This database is useful to determine the most important muscle characteristics associated with a high tenderness, a high flavour or generally a high quality. Another more consumer driven modelling tool was developed in Australia: the Meat Standards Australia (MSA) grading scheme that predicts beef quality for each individual muscle × specific cooking method combination using various information on the corresponding animals and post-slaughter processing factors. This system has also the potential to detect variability in quality within muscles. The MSA system proved to be effective in predicting beef palatability not only in Australia but also in many other countries. The results of the work conducted in Europe within the ProSafeBeef project indicate that it would be possible to manage a grading system in Europe similar to the MSA system. The combination of the different modelling approaches (namely muscle biochemistry and a MSA-like meat grading system adapted to the European market) is a promising area of research to improve the prediction of beef quality. In both approaches, the volume of data available not only provides statistically sound correlations between various factors and beef quality traits but also a better understanding of the variability of beef quality according to various criteria (breed, age, sex, pH, marbling etc.)

    Near-infrared reflectance spectroscopy for predicting the phospholipid fraction and the total fatty acid composition of freeze-dried beef

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    Research on fatty acids (FA) is important because their intake is related to human health. NIRS can be a useful tool to estimate the FA of beef but due to the high moisture and the high absorbance of water makes it difficult to calibrate the analyses. This work evaluated near-infrared reflectance spectroscopy as a tool to assess the total fatty acid composition and the phospholipid fraction of fatty acids of beef using freeze-dried meat. An average of 22 unrelated pure breed young bulls from 15 European breeds were reared on a common concentrate-based diet. A total of 332 longissimus thoracis steaks were analysed for fatty acid composition and a freeze-dried sample was subjected to near-infrared spectral analysis. 220 samples (67%) were used as a calibration set with the remaining 110 (33%) being used for validation of the models obtained. There was a large variation in the total FA concentration across the animals giving a good data set for the analysis and whilst the coefficient of variation was nearly 68% for the monounsaturated FA it was only 27% for the polyunsaturated fatty acids (PUFA). PLS method was used to develop the prediction models. The models for the phospholipid fraction had a low R2 p and high standard error, while models for neutral lipid had the best performance, in general. It was not possible to obtain a good prediction of many individual PUFA concentrations being present at low concentrations and less variable than other FA. The best models were developed for Total FA, saturated FA, 9c18:1 and 16:1 with R2 p greater than 0.76. This study indicates that NIRS is a feasible and useful tool for screening purposes and it has the potential to predict most of the FA of freeze-dried beef. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

    Review: The variability of the eating quality of beef can be reduced by predicting consumer satisfaction

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    Publication history: Accepted - 22 February 2018; Published online - 2 April 2018The Meat Standards Australia (MSA) grading scheme has the ability to predict beef eating quality for each ‘cut×cooking method combination’ from animal and carcass traits such as sex, age, breed, marbling, hot carcass weight and fatness, ageing time, etc. Following MSA testing protocols, a total of 22 different muscles, cooked by four different cooking methods and to three different degrees of doneness, were tasted by over 19 000 consumers from Northern Ireland, Poland, Ireland, France and Australia. Consumers scored the sensory characteristics (tenderness, flavor liking, juiciness and overall liking) and then allocated samples to one of four quality grades: unsatisfactory, good-every-day, better-than-every-day and premium. We observed that 26% of the beef was unsatisfactory. As previously reported, 68% of samples were allocated to the correct quality grades using the MSA grading scheme. Furthermore, only 7% of the beef unsatisfactory to consumers was misclassified as acceptable. Overall, we concluded that an MSA-like grading scheme could be used to predict beef eating quality and hence underpin commercial brands or labels in a number of European countries, and possibly the whole of Europe. In addition, such an eating quality guarantee system may allow the implementation of an MSA genetic index to improve eating quality through genetics as well as through management. Finally, such an eating quality guarantee system is likely to generate economic benefits to be shared along the beef supply chain from farmers to retailors, as consumers are willing to pay more for a better quality product.This research was supported by Meat and Livestock Australia and Murdoch University. Data were obtained through the financial contributions of the European research project ProSafeBeef (contract no. FOOD-CT-2006-36241), the Polish ProOptiBeef Farm to Fork project funded by the EU Innovative (POIG.01.03.01-00-204/09), the French ‘Direction GĂ©nĂ©rale de l’Alimentation’ and FranceAgriMer. For the Irish data, the authors acknowledge the financial support of the Department of Agriculture and the Marine (DAFM) under the Food Institutional Research Measure (FIRM). Furthermore, this project would not have been possible without the practical support of the Association Institut du Charolais, the Syndicat de DĂ©fense et du promotion de la Viande de Boeuf de Charolles and the gourmet restaurants ‘Jean Denaud’ and representatives of the beef industry across Europe. The international travel required for this project has been funded by ‘Egide/Fast’ funds from the French and Australian governments, respectively (project no. FR090054) and by ‘Egide/Polonium’ funds from the French and Polish governments, respectively. The assistance and participation of the Beef CRC and Janine Lau (MLA, Australia), Alan Gee (Cosign, Australia), Ray Watson (Melbourne University, Australia) and John Thompson (UNE) are also gratefully acknowledged
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