The Experts below are selected from a list of 27522 Experts worldwide ranked by ideXlab platform
Brigitte Picard - One of the best experts on this subject based on the ideXlab platform.
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Identification of biomarkers associated with the rearing practices, carcass characteristics, and Beef Quality: An integrative approach
Journal of Agricultural and Food Chemistry, 2017Co-Authors: Mohammed Gagaoua, Valérie Monteils, Sébastien Couvreur, Brigitte PicardAbstract:Identification of biomarkers associated with the rearing practices, carcass characteristics, and Beef Quality: An integrative approach
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Expression Marker-Based Strategy to Improve Beef Quality
TheScientificWorldJournal, 2016Co-Authors: Isabelle Cassar-malek, Brigitte PicardAbstract:For Beef cattle research, a main objective is to control concomitantly the development of muscles and the qualities of Beef cuts. Beef Quality is a complex phenotype that is only detectable after slaughter and is highly variable. The Beef industry is in need of tools to estimate Beef Quality of live cattle or online in abattoirs, with specific attention towards sensory attributes (tenderness, juiciness, flavour, and colour). Identification of relevant genetic and genomic markers is ongoing, especially for tenderness--a top priority Quality attribute. In this paper, we describe the steps of an expression marker-based strategy to improve Beef sensory Quality, from the discovery of biomarkers that identify consistent Beef and the biological functions governing Beef tenderness to the integration of the knowledge into detection tests for desirable animals. These tools should soon be available for the management of sensory Quality in the Beef production chain for meeting market's demands and assuring good Quality standards.
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Beef Quality
2015Co-Authors: Jean-françois Hocquette, Dominique Bauchart, Didier Micol, R. J. Polkinghorne, Brigitte PicardAbstract:Beef Quality
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Structural and biochemical characteristics of bovine intramuscular connective tissue and Beef Quality.
Meat science, 2013Co-Authors: Annabelle Dubost, Dominique Bauchart, Didier Micol, Brigitte Picard, Claire Lethias, Donato Andueza, Anne ListratAbstract:article i nfo Article history: The aimofthe studywastoevaluate the impactofstructuralandbiochemical characteristicsof muscleintramus- cular connective tissue on Beef Quality. The experimental design was based on three muscles of three breeds sampled as fresh material and cooked at 55 °C (Longissimus thoracis and Semimembranosus )o r at 70 °C (Semimembranosus and Biceps femoris) for Quality assessment. The results showed that muscle characteristics influence Beef Quality differently from one muscle to another. In grilled LT, proteoglycan content contributed negatively to juiciness, and intramuscular lipids were linked positively to tenderness, flavour, residues and over- all liking scores. In grilled SM, cross-link and lipid contents were involved in Beef Quality. In BF cooked to 70 °C, perimysial branch points were negatively linked to tenderness. In SM cooked to 70 °C, perimysial area was in- volved in Beef Quality. These results should allow a better understanding of the factors involved in background toughness, in juiciness and flavour of meat.
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Structural and biochemical characteristics of bovine intramuscular connective tissue and Beef Quality
Meat Science, 2013Co-Authors: Annabelle Dubost, Dominique Bauchart, Didier Micol, Brigitte Picard, Claire Lethias, Donato Andueza, Anne ListratAbstract:The aim of the study was to evaluate the impact of structural and biochemical characteristics of muscle intramuscular connective tissue on Beef Quality. The experimental design was based on three muscles of three breeds sampled as fresh material and cooked at 55 degrees C (Longissimus thoracis and Semimembranosus) or at 70 degrees C (Semimembranosus and Biceps femoris) for Quality assessment. The results showed that muscle characteristics influence Beef Quality differently from one muscle to another. In grilled LT, proteoglycan content contributed negatively to juiciness, and intramuscular lipids were linked positively to tenderness, flavour, residues and overall liking scores. In grilled SM, cross-link and lipid contents were involved in Beef Quality. In BF cooked to 70 degrees C, perimysial branch points were negatively linked to tenderness. In SM cooked to 70 degrees C, perimysial area was involved in Beef Quality. These results should allow a better understanding of the factors involved in background toughness, in juiciness and flavour of meat. (C) 2013 Elsevier Ltd. All rights reserved.
Jean-françois Hocquette - One of the best experts on this subject based on the ideXlab platform.
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Beef Quality
2015Co-Authors: Jean-françois Hocquette, Dominique Bauchart, Didier Micol, R. J. Polkinghorne, Brigitte PicardAbstract:Beef Quality
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Opportunities for predicting and manipulating Beef Quality.
Meat science, 2012Co-Authors: Jean-françois Hocquette, Brigitte Picard, R. Botreau, Alain Jacquet, David W. Pethick, Nigel D. ScollanAbstract:Meat Quality is a complex concept and can be defined as the characteristics of meat which satisfy consumers and citizens. The Quality concept can be divided into intrinsic Quality traits (which are the characteristics of the product itself) and extrinsic Quality traits (which are more or less associated to the product for instance the price, a major determinant of purchase, or any brand or Quality label). Quality can also be generic for the mass market or specific for niche markets. The relative importance of the different Quality traits varies with human culture and time with a general trend of an increasing contribution of healthiness, safety and extrinsic Quality traits. This review underlines the need for the development of methods to interpret and aggregate measures under specific rules to be defined in order to produce an overall assessment of Beef Quality. Such methods can be inferred for example from genomic results or data related to muscle biochemistry to better predict tenderness or flavor. A more global assurance Quality scheme (the Meat Standards Australia System) based on the aggregation of sensory Quality traits has been developed in Australia to ensure palatability to consumers. We speculated that the combination of indices related to sensory and nutritional Quality, social and environmental considerations (carbon footprint, animal welfare, biodiversity of pasture, rural development, etc.) and economic efficiency (incomes of farmers and of others players along the supply chain, etc.) will provide objective assessment of the overall Quality of Beef (i.e. incorporating an all encompassing approach) not only for the mass market but also to support official Quality labels of niche markets which are so far mainly associated with the geographical origins of the products.
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The GENOTEND chip: a new tool to analyse gene expression in muscles of Beef cattle for Beef Quality prediction
BMC Veterinary Research, 2012Co-Authors: Jean-françois Hocquette, Carine Bernard-capel, Véronique Vidal, Beline Jesson, Hubert Levéziel, Gilles Renand, Isabelle Cassar-malekAbstract:Background: Previous research programmes have described muscle biochemical traits and gene expression levels associated with Beef tenderness. One of our results concerning the DNAJA1 gene (an Hsp40) was patented. This study aims to confirm the relationships previously identified between two gene families (heat shock proteins and energy metabolism) and Beef Quality.[br/] Results: We developed an Agilent chip with specific probes for bovine muscular genes. More than 3000 genes involved in muscle biology or meat Quality were selected from genetic, proteomic or transcriptomic studies, or from scientific publications. As far as possible, several probes were used for each gene (e.g. 17 probes for DNAJA1). RNA from Longissimus thoracis muscle samples was hybridised on the chips. Muscles samples were from four groups of Charolais cattle: two groups of young bulls and two groups of steers slaughtered in two different years. Principal component analysis, simple correlation of gene expression levels with tenderness scores, and then multiple regression analysis provided the means to detect the genes within two families (heat shock proteins and energy metabolism) which were the most associated with Beef tenderness. For the 25 Charolais young bulls slaughtered in year 1, expression levels of DNAJA1 and other genes of the HSP family were related to the initial or overall Beef tenderness. Similarly, expression levels of genes involved in fat or energy metabolism were related with the initial or overall Beef tenderness but in the year 1 and year 2 groups of young bulls only. Generally, the genes individually correlated with tenderness are not consistent across genders and years indicating the strong influence of rearing conditions on muscle characteristics related to Beef Quality. However, a group of HSP genes, which explained about 40% of the variability in tenderness in the group of 25 young bulls slaughtered in year 1 (considered as the reference group), was validated in the groups of 30 Charolais young bulls slaughtered in year 2, and in the 21 Charolais steers slaughtered in year 1, but not in the group of 19 steers slaughtered in year 2 which differ from the reference group by two factors (gender and year). When the first three groups of animals were analysed together, this subset of genes explained a 4-fold higher proportion of the variability in tenderness than muscle biochemical traits.[br/] Conclusion: This study underlined the relevance of the GENOTEND chip to identify markers of Beef Quality, mainly by confirming previous results and by detecting other genes of the heat shock family as potential markers of Beef Quality. However, it was not always possible to extrapolate the relevance of these markers to all animal groups which differ by several factors (such as gender or environmental conditions of production) from the initial population of reference in which these markers were identified.
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Recent advances in cattle functional genomics and their application to Beef Quality
Animal : an international journal of animal bioscience, 2007Co-Authors: Jean-françois Hocquette, William Barendse, Sigrid A. Lehnert, Isabelle Cassar-malek, Brigitte PicardAbstract:The advent of high-throughput DNA sequencing techniques, array technology and protein analysis has increased the efficiency of research in bovine muscle physiology, with the ultimate objective of improving Beef Quality either by breeding or rearing factors. For genetic purposes, polymorphisms in some key genes have been reported for their association with Beef Quality traits. The sequencing of the bovine genome has dramatically increased the number of available gene polymorphisms. The association of these new polymorphisms with the variability in Beef Quality (e.g. tenderness, marbling) for different breeds in different rearing systems will be a very important issue. For rearing purposes, global gene expression profiling at the mRNA or protein level has already shown that previously unsuspected genes may be associated either with muscle development or growth, and may lead to the development of new molecular indicators of tenderness or marbling. Some of these genes are specifically regulated by genetic and nutritional factors or differ between different Beef cuts. In recognition of the potential economic benefits of genomics, public institutions in association with the Beef industry are developing livestock genomics projects around the world. From the scientific, technical and economical points of view, genomics is thus reshaping research on Beef Quality.
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Indicators of milk and Beef Quality - Indicators of milk and Beef Quality.
EAAP Scientific Series, 2005Co-Authors: Jean-françois Hocquette, S. GigliAbstract:All the review papers and the short communications presented in this session are in this EAAP publication entitled “Indicators of milk and Beef Quality”. Additional papers from invited authors were written in 2004 and then added to complete the publication although not all topics related to Quality indicators are covered in the present publication. Review papers aim to describe the state of the art in different disciplines including genetics, physiology, nutrition, biochemistry as well as social and economic aspects. Short communications are recent and new results given as examples of the research done in these different areas. All the papers were peer-reviewed by international experts.
Virginia C. Resconi - One of the best experts on this subject based on the ideXlab platform.
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Perception of Beef Quality for Spanish and Brazilian consumers.
Meat science, 2020Co-Authors: Bruna Boito, Virginia C. Resconi, Eduardo Lisbinski, María Del Mar Campo, Ana Guerrero, Tamara Esteves De Oliveira, Júlio Otávio Jardim BarcellosAbstract:Abstract Understanding the priorities of Beef consumers is important for planning strategies to attract and maintain each customer. Using self-administered interviews with Spanish and Brazilian adults who regularly consume Beef, we analyzed their purchasing behaviors in relation to their perceptions and priorities regarding Beef Quality that guide their choices. The current study identifies the influences of information (labeling and marketing) requirements, concerns about humane production systems, and the intrinsic characteristics of Beef. To evaluate the data extracted from the interviews, the questions were grouped into four main factors. While extrinsic factors are the highest valued in both Spain and Brazil, those such as Beef freshness and tenderness present inverse concerns between the two countries based on cultural dissimilarities. The data also reveals a clear symmetry among consumers who increasingly seek specific pre-purchase information and products with guaranteed superior Quality. Despite other characteristics that differentiate developed and developing countries, the perceptions of Quality among consumers in Spain and Brazil are decidedly similar.
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Beef Quality attributes: A systematic review of consumer perspectives
Meat science, 2017Co-Authors: Maeve Henchion, Mary Mccarthy, Virginia C. ResconiAbstract:Informed by Quality theory, this systematic literature review seeks to determine the relative importance of Beef Quality attributes from a consumer perspective, considering search, experience and credence Quality attributes. While little change is anticipated in consumer ranking of search and experience attributes in the future, movement is expected in terms of ranking within the credence category and also in terms of the ranking of credence attributes overall. This highlights an opportunity for Quality assurance schemes (QAS) to become more consumer focused through including a wider range of credence attributes. To capitalise on this opportunity, the meat industry should actively anticipate new relevant credence attributes and researchers need to develop new or better methods to measure them. This review attempts to identify the most relevant Quality attributes in Beef that may be considered in future iterations of QAS, to increase consumer satisfaction and, potentially, to increase returns to industry.
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Indicators of Beef Quality for Consumers: a Systematic Review
2016Co-Authors: Maeve Henchion, Mary Mccarthy, Virginia C. ResconiAbstract:Quality is a subjective term and means different things to different people. However there is general agreement that Beef Quality needs to be consistent, and needs to be improved. Furthermore, there is agreement that it will become an increasingly important factor in consumer decision making (Henchion et al., 2014). Informed by Quality theory, this paper seeks to determine the relative importance of Quality attributes from a consumer perspective through undertaking a systematic review of the literature on consumer attitudes to different Beef Quality attributes.
Dedy Rahman Wijaya - One of the best experts on this subject based on the ideXlab platform.
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dwtlstm for electronic nose signal processing in Beef Quality monitoring
Sensors and Actuators B-chemical, 2021Co-Authors: Dedy Rahman Wijaya, Riyanarto Sarno, Enny ZulaikaAbstract:Abstract The smart packaging system is needed to continuously monitor the Quality of Beef and microbial population for both the meat industries as well as end consumers. Moreover, several feasibility studies of electronic nose (e-nose) for rapid Beef Quality assessment are also conducted in recent years. The characteristics of e-nose are fast, cheap, and easy to use make it suitable and scalable for Beef Quality monitoring applications. It is also potential to be integrated with consumer electronics such as refrigerator and meat chiller. However, the inevitable challenge is how to handle time-series data that is contaminated with noise. In this paper, discrete wavelet transform and long short-term memory (DWTLSTM) is proposed to overcome the e-nose signal contaminated with noise in monitoring Beef Quality. In Beef Quality classification task, our proposed has a favorable performance with 94.83% of average accuracy and 85.05% of average F-measure. Moreover, it presents a satisfactory performance in the prediction of microbial population (RMSE = 0.0515 and R2 = 0.9712). These results indicate that the DWTLSTM outperforms conventional methods such as k-nearest neighbor (k-NN), linear discriminant analysis (LDA), support vector machine/support vector regression (SVM/SVR), multilayer perceptron (MLP), and even standard long-short term memory (LSTM).
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Recent development in electronic nose data processing for Beef Quality assessment
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2019Co-Authors: Riyanarto Sarno, Dedy Rahman WijayaAbstract:Beef is kind of perishable food that easily to decay. Hence, a rapid system for Beef Quality assessment is needed to guarantee the Quality of Beef. In the last few years, electronic nose (e-nose) is developed for Beef spoilage detection. In this paper, we discuss the challenges of e-nose application to Beef Quality assessment, especially in e-nose data processing. We also provide a summary of our previous studies that explains several methods to deal with gas sensor noise, sensor array optimization problem, Beef Quality classification, and prediction of the microbial population in Beef sample. This paper might be useful for researchers and practitioners to understand the challenges and methods of e-nose data processing for Beef Quality assessment.
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Noise filtering framework for electronic nose signals: An application for Beef Quality monitoring
Computers and Electronics in Agriculture, 2019Co-Authors: Dedy Rahman Wijaya, Riyanarto Sarno, Enny ZulaikaAbstract:Abstract Beef is one of the most popular and widely consumed foodstuffs in the world. Nevertheless, it can easily decay if not properly treated during distribution and storage. The consumption of low Quality Beef causes a serious health hazard. The electronic nose (e-nose) is a rapid and low-cost instrument for Beef Quality classification. Hence, the development of a mobile e-nose for online meat Quality monitoring is appealing. In the last few years, e-noses have been used to classify different grades of Beef and to predict the number of the microbial population in Beef samples. Several methods are used to deal with these classification and regression problems. Especially in multiclass Beef classification and regression, signals contaminated with noise can significantly degrade the performance of the pattern recognition module. Therefore, the presence of internal and external noise in e-nose signals is a major challenge in Beef Quality monitoring. In this study, a noise filtering framework based on a fine-tuned discrete wavelet transform (DWT) was developed to handle noisy signals generated by an e-nose sensor array. To the best of our knowledge this is the first time the problem of e-nose signal noise in Beef Quality classification is tackled. The proposed framework was integrated and tested on several machine learning algorithms that were used in previous studies, i.e. k-nearest neighbor (k-NN), support vector machine (SVM), quadratic discriminant analysis (QDA), artificial neural network (ANN), and adaptive neuro fuzzy inference system (ANFIS). Furthermore, the effect of noise filtering was investigated in the classification with two, three, and four classes of Beef. The effect of noise filtering was also observed in regression tasks to predict the size of microbial population in Beef samples. The experimental results showed that the proposed framework provides a significant improvement in multiclass classification and regression tasks.
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Electronic nose dataset for Beef Quality monitoring in uncontrolled ambient conditions
Data in Brief, 2018Co-Authors: Dedy Rahman Wijaya, Riyanarto Sarno, Enny ZulaikaAbstract:Abstract In recent years, the development of a rapid, simple, and low-cost meat assessment system using an electronic nose (e-nose) has been the concern of researchers. In this data article, we provide a time series dataset that was obtained from a Beef Quality monitoring experiment using an e-nose in uncontrolled ambient conditions. The availability of this dataset will enable discussion on how to deal with noisy e-nose signals and non-optimum sensor array in Beef Quality monitoring. Hence, the development of proper signal processing and robust machine learning algorithm are several challenges that must be faced. Furthermore, this dataset can also be useful as a comparison dataset for similar e-nose applications, such as air Quality monitoring, smart packaging system, and food Quality monitoring.
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Development of mobile electronic nose for Beef Quality monitoring
Procedia Computer Science, 2017Co-Authors: Dedy Rahman Wijaya, Enny Zulaika, Riyanarto Sarno, Shoffi Izza SabilaAbstract:Abstract Meat is one of foodstuff that widely consumed in the world. Unfortunately, the Quality of meat can easily degrade if not handled properly and become the serious health hazards if consumed. Hence, the food safety system is very important to guarantee the Quality of food to be consumed. In this study, we introduced the development of mobile electronic nose for Beef Quality detection and monitoring. This system is developed using low-cost hardware and possible to integrate with cooling box or refrigerator for real time monitoring and analysis during distribution and storage processes. K-Nearest Neighbor with signal preprocessing is used to classify two, three, and four classes of Beef. The experimental results show that the system can perfectly distinguish fresh and spoiled Beef. Moreover, it has promising classification accuracy for binary, three classes, and four classes classification with 93.64%, 86.00%, and 85.50%, respectively. Hence, this system has a potential solution to provide low-cost, easy to use, and real-time meat Quality monitoring system.
Lisa Meier-dinkel - One of the best experts on this subject based on the ideXlab platform.
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Beef Quality labels: A combination of sensory acceptance test, stated willingness to pay, and choice-based conjoint analysis.
Appetite, 2018Co-Authors: Stephan G.h. Meyerding, Maria Gentz, Brianne A. Altmann, Lisa Meier-dinkelAbstract:Abstract Consumer perspectives of Beef Quality are complex, leading to a market that is increasingly differentiating. Thus, ongoing monitoring and assessment of changes in consumer perspectives is essential to identify changing market conditions. Often only credence and search characteristics are evaluated in consumer studies; therefore the object of the present study is to examine consumer preferences and perceptions towards Beef steaks, also including experience characteristics, using a mixed methods approach. For this reason, 55 consumers participated in an experiment in Germany, including a sensory acceptance test, stated willingness to pay, and choice-based conjoint analysis (CBCA). Different Quality characteristics were included, but a focus on the Quality labels of ‘dry aged Beef’, ‘Block House Beef’, and ‘Angus Beef’ was predominant throughout the experiment with the results showing that Quality labels significantly increased overall liking as well as the stated willingness to pay. Quality labels were also the one of the most important characteristics in the conjoint analysis, after origin and price. The results of all applied methods are comparable for the characteristic Quality label. The combination of sensory acceptance test and CBCA were additionally able to evaluate all three kinds of Beef Quality characteristics, which could not be evaluated together only using a single method. This suggests that a mixture of methods should be used to gain better knowledge on the true behavior of Beef consumers. Experience and credence characteristics, including Beef Quality labels, present opportunities for future research as well as the potential for determining product and market differentiation.