Research in Beef Tenderness and Palatability in the Era of Big Data
For decades, research has focused on predicting beef palatability using muscle biochemical traits, and various biomarkers. In these approaches, a precise definition of the variable to predict (tenderness assessed by panelists, untrained consumers, or shear force), and repeatability of the measuremen...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Iowa State University Digital Press
2020-07-01
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| Series: | Meat and Muscle Biology |
| Subjects: | |
| Online Access: | https://www.iastatedigitalpress.com/mmb/article/id/9488/ |
| _version_ | 1797222191180283904 |
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| author | David Pethick Graham Gardner Isabelle Legrand Jean-François Hocquette Jerzy Wierzbicki Marie-Pierre Ellies-Oury1 Rod J. Polkinghorne |
| author_facet | David Pethick Graham Gardner Isabelle Legrand Jean-François Hocquette Jerzy Wierzbicki Marie-Pierre Ellies-Oury1 Rod J. Polkinghorne |
| author_sort | David Pethick |
| collection | DOAJ |
| description | For decades, research has focused on predicting beef palatability using muscle biochemical traits, and various biomarkers. In these approaches, a precise definition of the variable to predict (tenderness assessed by panelists, untrained consumers, or shear force), and repeatability of the measurements are crucial for creating significant data resources for the derivation of robust predictive models, and rigorous validation testing. This “big data” approach also requires careful definition of traits and transparent principles for data sharing and management. As in other fields, meat science researchers should improve the Findability, Accessibility, Interoperability, and Reuse of data (known as the FAIR principles). Furthermore, with the rapid evolution of new measurement technologies, the traits that they measure must be consistently described, enhancing our ability to integrate these new measurements into existing description systems. For beef, strategic choices have been made in order to consider real consumers’ expectations, not well estimated correctly by lab approaches. This strategy has been successfully developed in Australia, which set up the “Meat Standards Australia” grading scheme, now partly adopted by the beef industry. The ambitions of the International Meat Research 3G Foundation is to develop beef ontology, to set up an international database with a huge number of consumers’ scores related to beef palatability and collected according to standard protocols. The foundation also aims to support the beef industry by offering an international predictive model of beef palatability, flexible enough to take into account any local livestock characteristics or regional consumer specificity. This approach is supported by the United Nations Economic Commission for Europe (UNECE), which is promoting development of regulations and norms, technical cooperation and exchange of best expertise and practices. This will substantially improve the transparency of data flow and price signaling between all participants of the value chain, from beef producers through to consumers at retail. |
| first_indexed | 2024-04-24T13:17:24Z |
| format | Article |
| id | doaj.art-99a2047a0b1840ac81557f1fe1e2dcda |
| institution | Directory Open Access Journal |
| issn | 2575-985X |
| language | English |
| last_indexed | 2024-04-24T13:17:24Z |
| publishDate | 2020-07-01 |
| publisher | Iowa State University Digital Press |
| record_format | Article |
| series | Meat and Muscle Biology |
| spelling | doaj.art-99a2047a0b1840ac81557f1fe1e2dcda2024-04-04T17:22:22ZengIowa State University Digital PressMeat and Muscle Biology2575-985X2020-07-014210.22175/mmb.9488Research in Beef Tenderness and Palatability in the Era of Big DataDavid Pethick0Graham Gardner1Isabelle Legrand2Jean-François Hocquette3https://orcid.org/0000-0003-2409-3881Jerzy Wierzbicki4Marie-Pierre Ellies-Oury15https://orcid.org/0000-0002-5776-7566Rod J. Polkinghorne6N/aSchool of Veterinary and Life Sciences, Murdoch UniversityService Qualité des Carcasses et des Viandes, Institut de l’ElevageINRAE, Université Clermont Auvergne, VetAgroSupPolish Beef AssociationDépartement Feed and Food, Bordeaux Sciences AgroBirkenwood International Pty LtdFor decades, research has focused on predicting beef palatability using muscle biochemical traits, and various biomarkers. In these approaches, a precise definition of the variable to predict (tenderness assessed by panelists, untrained consumers, or shear force), and repeatability of the measurements are crucial for creating significant data resources for the derivation of robust predictive models, and rigorous validation testing. This “big data” approach also requires careful definition of traits and transparent principles for data sharing and management. As in other fields, meat science researchers should improve the Findability, Accessibility, Interoperability, and Reuse of data (known as the FAIR principles). Furthermore, with the rapid evolution of new measurement technologies, the traits that they measure must be consistently described, enhancing our ability to integrate these new measurements into existing description systems. For beef, strategic choices have been made in order to consider real consumers’ expectations, not well estimated correctly by lab approaches. This strategy has been successfully developed in Australia, which set up the “Meat Standards Australia” grading scheme, now partly adopted by the beef industry. The ambitions of the International Meat Research 3G Foundation is to develop beef ontology, to set up an international database with a huge number of consumers’ scores related to beef palatability and collected according to standard protocols. The foundation also aims to support the beef industry by offering an international predictive model of beef palatability, flexible enough to take into account any local livestock characteristics or regional consumer specificity. This approach is supported by the United Nations Economic Commission for Europe (UNECE), which is promoting development of regulations and norms, technical cooperation and exchange of best expertise and practices. This will substantially improve the transparency of data flow and price signaling between all participants of the value chain, from beef producers through to consumers at retail.https://www.iastatedigitalpress.com/mmb/article/id/9488/open scienceontologypalatabilitytenderness |
| spellingShingle | David Pethick Graham Gardner Isabelle Legrand Jean-François Hocquette Jerzy Wierzbicki Marie-Pierre Ellies-Oury1 Rod J. Polkinghorne Research in Beef Tenderness and Palatability in the Era of Big Data Meat and Muscle Biology open science ontology palatability tenderness |
| title | Research in Beef Tenderness and Palatability in the Era of Big Data |
| title_full | Research in Beef Tenderness and Palatability in the Era of Big Data |
| title_fullStr | Research in Beef Tenderness and Palatability in the Era of Big Data |
| title_full_unstemmed | Research in Beef Tenderness and Palatability in the Era of Big Data |
| title_short | Research in Beef Tenderness and Palatability in the Era of Big Data |
| title_sort | research in beef tenderness and palatability in the era of big data |
| topic | open science ontology palatability tenderness |
| url | https://www.iastatedigitalpress.com/mmb/article/id/9488/ |
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