{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T16:02:37Z","timestamp":1792857757431,"version":"4.5.0"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T00:00:00Z","timestamp":1770768000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T00:00:00Z","timestamp":1770768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"This study was supported by Chungnam National Univeristy, Republic of Korea."}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Food Sci Anim Resour"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1007\/s44463-025-00039-4","type":"journal-article","created":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T09:26:11Z","timestamp":1770801971000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Development of a smartphone-based bone maturity classification algorithm with XAI for beef carcass grading"],"prefix":"10.1007","volume":"46","author":[{"given":"Juntae","family":"Kim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sung-Hwan","family":"Ahn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suk-Ki","family":"Yoon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyang-Rae","family":"Noh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hwa-Jin","family":"Jeong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chang-Wan","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Byoung-Kwan","family":"Cho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,11]]},"reference":[{"key":"39_CR1","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.inffus.2019.12.012","volume":"58","author":"AB Arrieta","year":"2020","unstructured":"Arrieta, A. B., D\u00edaz-Rodr\u00edguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garc\u00eda, S., Gil-L\u00f3pez, S., Molina, D., Benjamins, R., & Chatila, R. (2020). Explainable artificial intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82\u2013115. https:\/\/doi.org\/10.1016\/j.inffus.2019.12.012","journal-title":"Information Fusion"},{"key":"39_CR2","doi-asserted-by":"publisher","first-page":"101603","DOI":"10.1109\/ACCESS.2024.3431437","volume":"12","author":"S Atakishiyev","year":"2021","unstructured":"Atakishiyev, S., Salameh, M., Yao, H., & Goebel, R. (2021). Explainable artificial intelligence for autonomous driving: A comprehensive overview and field guide for future research directions. IEEE Access, 12, 101603\u2013101625. https:\/\/doi.org\/10.1109\/ACCESS.2024.3431437","journal-title":"IEEE Access"},{"key":"39_CR3","unstructured":"AUS-MEAT (2005). Handbook of Australian meat.\u00a07th ed. AUS-MEAT Ltd, Brisbane, Australia."},{"key":"39_CR4","doi-asserted-by":"publisher","unstructured":"Chattopadhay, A., Sarkar, A., Howlader, P., & Balasubramanian, V. N. (2018). Grad-CAM++: Generalized gradient-based visual explanations for deep convolutional networks. In: 2018 IEEE Winter Conference on Applications of Computer Vision (WACV 2018). pp. 839\u2013847. https:\/\/doi.org\/10.1109\/WACV.2018.00097","DOI":"10.1109\/WACV.2018.00097"},{"issue":"5","key":"39_CR5","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1111\/1754-9485.13261","volume":"65","author":"P Chlap","year":"2021","unstructured":"Chlap, P., Min, H., Vandenberg, N., Dowling, J., Holloway, L., & Haworth, A. (2021). A review of medical image data augmentation techniques for deep learning applications. Journal of Medical Imaging and Radiation Oncology, 65(5), 545\u2013563. https:\/\/doi.org\/10.1111\/1754-9485.13261","journal-title":"Journal of Medical Imaging and Radiation Oncology"},{"key":"39_CR6","unstructured":"Garreau, D., & Luxburg, U. (2020). Explaining the explainer: A first theoretical analysis of LIME. In: Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS 2020). pp. 1287\u20131296. Available from: http:\/\/proceedings.mlr.press\/v108\/garreau20a.html"},{"issue":"22","key":"39_CR7","doi-asserted-by":"publisher","first-page":"3535","DOI":"10.3390\/ani13223535","volume":"13","author":"W Hao","year":"2023","unstructured":"Hao, W., Ren, C., Han, M., Zhang, L., Li, F., & Liu, Z. (2023). Cattle body detection based on YOLOv5-EMA for precision livestock farming. Animals, 13(22), 3535. https:\/\/doi.org\/10.3390\/ani13223535","journal-title":"Animals"},{"issue":"2","key":"39_CR8","doi-asserted-by":"publisher","first-page":"1206","DOI":"10.1093\/tas\/txaa017","volume":"4","author":"KC Hoffman","year":"2020","unstructured":"Hoffman, K. C., Colle, M. J., Nasados, J. A., Gray, S. J., Rogers, J., Van Buren, J. B., Puga, K. J., Murdoch, G. K., Richard, R. P., & Doumit, M. E. (2020). Relationship between heifer carcass maturity and beef quality characteristics. Transl Anim Sci, 4(2), 1206\u20131215. https:\/\/doi.org\/10.1093\/tas\/txaa017","journal-title":"Transl Anim Sci"},{"key":"39_CR9","unstructured":"Jeghem, N., Koh, C. Y., Abdelatti, M., & Hendawi, A. (2024). Evaluating the evolution of YOLO (You only look Once) models: A comprehensive benchmark study of YOLO11 and its predecessors. ArXiv Preprint arXiv:241100201. https:\/\/arxiv.org\/abs\/2411.00201"},{"key":"39_CR10","doi-asserted-by":"publisher","unstructured":"Jeong, K., Kim, D. R., Ryu, J. H., Kim, H. W., Cho, J., Lee, E., & Jeong, J. H. (2024). A monitoring system for cattle behavior detection using YOLO-v8 in IoT environments. In: Proceedings of the IEEE International Conference on Consumer Electronics (ICCE 2024). pp. 1\u20134. https:\/\/doi.org\/10.1109\/ICCE59016.2024.10444145","DOI":"10.1109\/ICCE59016.2024.10444145"},{"key":"39_CR11","doi-asserted-by":"publisher","first-page":"344","DOI":"10.5851\/kosfa.2008.28.3.344","volume":"28","author":"DY Kim","year":"2008","unstructured":"Kim, D. Y., Kim, B. D., Baek, S. G., Jeong, H. J., Kim, D. G., & Han, G. D. (2008). Correlation between shear force and grade decision factors on Hanwoo cow carcass. Korean J Food Sci Anim Resour, 28, 344\u2013348. https:\/\/doi.org\/10.5851\/kosfa.2008.28.3.344","journal-title":"Korean J Food Sci Anim Resour"},{"issue":"5","key":"39_CR12","doi-asserted-by":"publisher","first-page":"1297","DOI":"10.3390\/ani11051297","volume":"11","author":"J Kim","year":"2021","unstructured":"Kim, J., Han, H. D., Lee, W. Y., Wakholi, C., Lee, J., Jeong, Y. B., & Bae, J. H. (2021). Economic analysis of the use of VCS2000 for pork carcass meat yield grading in Korea. Animals, 11(5), 1297. https:\/\/doi.org\/10.3390\/ani11051297","journal-title":"Animals"},{"issue":"4","key":"39_CR13","doi-asserted-by":"publisher","first-page":"651","DOI":"10.3390\/ani13040651","volume":"13","author":"J Kim","year":"2023","unstructured":"Kim, J., Kwon, Y. K., Kim, H. W., Seol, K. H., & Cho, B. K. (2023). Robot technology for pork and beef meat slaughtering process: A review. Animals, 13(4), 651. https:\/\/doi.org\/10.3390\/ani13040651","journal-title":"Animals"},{"key":"39_CR14","unstructured":"Korean Ministry of Government Legislation (KMGL). (2023). Enforcement Rule of the Livestock Act. National Law Information Center. Available from: https:\/\/www.law.go.kr. Accessed Jan 15, 2025."},{"key":"39_CR15","doi-asserted-by":"publisher","first-page":"116989","DOI":"10.1016\/j.lwt.2023.116989","volume":"212","author":"H Kurniawan","year":"2024","unstructured":"Kurniawan, H., Arief, M. A. A., Manggala, B., Lee, S., Kim, H., & Cho, B. K. (2024). Advanced detection of foreign objects in fresh-cut vegetables using YOLOv5. LWT-Food Sci Technol, 212, 116989. https:\/\/doi.org\/10.1016\/j.lwt.2023.116989","journal-title":"LWT-Food Sci Technol"},{"key":"39_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.104041","volume":"126","author":"PR Magesh","year":"2020","unstructured":"Magesh, P. R., Myloth, R. D., & Tom, R. J. (2020). An explainable machine learning model for early detection of Parkinson\u2019s disease using LIME on DaTSCAN imagery. Computers in Biology and Medicine, 126, Article 104041. https:\/\/doi.org\/10.1016\/j.compbiomed.2020.104041","journal-title":"Computers in Biology and Medicine"},{"key":"39_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103655","volume":"113","author":"AF Markus","year":"2021","unstructured":"Markus, A. F., Kors, J. A., & Rijnbeek, R. (2021). The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies. Journal of Biomedical Informatics, 113, Article 103655. https:\/\/doi.org\/10.1016\/j.jbi.2020.103655","journal-title":"Journal of Biomedical Informatics"},{"key":"39_CR18","doi-asserted-by":"publisher","first-page":"102161","DOI":"10.1016\/j.jestch.2025.102161","volume":"70","author":"AA Murat","year":"2025","unstructured":"Murat, A. A., & Kiran, M. S. (2025). A comprehensive review on YOLO versions for object detection. Engineering Science and Technology an International Journal, 70, 102161. https:\/\/doi.org\/10.1016\/j.jestch.2025.102161","journal-title":"Engineering Science and Technology an International Journal"},{"key":"39_CR19","doi-asserted-by":"publisher","unstructured":"Narkhede, J. (2024). Comparative evaluation of post-hoc explainability methods in AI: LIME, SHAP, and Grad-CAM. In: Proceedings of the 4th International Conference on Sustainable Expert Systems (ICSES 2024). pp. 826\u2013830. https:\/\/doi.org\/10.1109\/ICSES63445.2024.10762963","DOI":"10.1109\/ICSES63445.2024.10762963"},{"key":"39_CR20","doi-asserted-by":"publisher","unstructured":"Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You only look once: Unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 779\u2013788. https:\/\/doi.org\/10.1109\/CVPR.2016.91","DOI":"10.1109\/CVPR.2016.91"},{"key":"39_CR21","doi-asserted-by":"publisher","unstructured":"Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). Why should I trust you? Explaining the predictions of any classifier. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2016). pp. 1135\u20131144. https:\/\/doi.org\/10.1145\/2939672.2939778","DOI":"10.1145\/2939672.2939778"},{"key":"39_CR22","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1016\/j.meatsci.2010.11.020","volume":"87","author":"HC Sch\u00f6nfeldt","year":"2011","unstructured":"Sch\u00f6nfeldt, H. C., & Strydom, P. E. (2011). Effect of age and cut on tenderness of South African beef. Meat Science, 87, 206\u2013218. https:\/\/doi.org\/10.1016\/j.meatsci.2010.11.020","journal-title":"Meat Science"},{"issue":"4","key":"39_CR23","doi-asserted-by":"publisher","first-page":"662","DOI":"10.3390\/make3030035","volume":"3","author":"JH Sejr","year":"2021","unstructured":"Sejr, J. H., Schneider-Kamp, P., & Ayoub, N. (2021). Surrogate object detection explainer (SODEx) with YOLOv4 and LIME. Machine Learning and Knowledge Extraction, 3(4), 662\u2013671. https:\/\/doi.org\/10.3390\/make3030035","journal-title":"Machine Learning and Knowledge Extraction"},{"key":"39_CR24","doi-asserted-by":"publisher","unstructured":"Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Batra, D. (2017). Grad-CAM: visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV 2017). pp. 618\u2013626. https:\/\/doi.org\/10.1109\/ICCV.2017.74","DOI":"10.1109\/ICCV.2017.74"},{"issue":"8","key":"39_CR25","doi-asserted-by":"publisher","first-page":"1629","DOI":"10.3390\/genes14081629","volume":"14","author":"KA Shira","year":"2021","unstructured":"Shira, K. A., Murdoch, B. M., Davenport, K. M., Becker, G. M., Xie, S., Colacchio, A. M., Bass, P. D., Colle, M. J., & Murdoch, G. K. (2021). Advanced skeletal ossification is associated with genetic variants in chronologically young beef heifers. Genes, 14(8), 1629. https:\/\/doi.org\/10.3390\/genes14081629","journal-title":"Genes"},{"key":"39_CR26","doi-asserted-by":"publisher","first-page":"107527","DOI":"10.1016\/j.cmpb.2023.107527","volume":"235","author":"D Song","year":"2023","unstructured":"Song, D., Yao, J., Jiang, Y., Shi, S., Cui, C., Wang, L., Yu, M., Zhou, X., Li, H., Gao, Z., Li, Y., Chen, F., & Dong, F. (2023). A new xAI framework with feature explainability for tumors decision-making in ultrasound data: Comparing with Grad-CAM. Computer Methods and Programs in Biomedicine, 235, 107527. https:\/\/doi.org\/10.1016\/j.cmpb.2023.107527","journal-title":"Computer Methods and Programs in Biomedicine"},{"key":"39_CR27","unstructured":"Tatum, D. (2007). Beef grading. Colorado State University, Department of Animal Science. Available from: https:\/\/www.beefresearch.org\/resources\/product-quality\/fact-sheets\/beef-grading. Accessed Jan 26, 2025."},{"key":"39_CR28","unstructured":"USDA. (1997). United States standards for grades of slaughter cattle. Agricultural Marketing Service, USDA,\u00a0Washington, DC, USA."},{"issue":"11","key":"39_CR29","doi-asserted-by":"publisher","first-page":"1368","DOI":"10.1071\/EA07184","volume":"48","author":"R Watson","year":"2008","unstructured":"Watson, R., Polkinghorne, R., & Thompson, J. M. (2008). Development of the meat standards Australia (MSA) prediction model for beef palatability. Australian Journal of Experimental Agriculture, 48(11), 1368\u20131379. https:\/\/doi.org\/10.1071\/EA07184","journal-title":"Australian Journal of Experimental Agriculture"}],"container-title":["Food Science of Animal Resources"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44463-025-00039-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44463-025-00039-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44463-025-00039-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T09:26:19Z","timestamp":1770801979000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44463-025-00039-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,11]]},"references-count":29,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,12]]}},"alternative-id":["39"],"URL":"https:\/\/doi.org\/10.1007\/s44463-025-00039-4","relation":{},"ISSN":["2636-0772","2636-0780"],"issn-type":[{"value":"2636-0772","type":"print"},{"value":"2636-0780","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,11]]},"assertion":[{"value":"13 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 October 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 February 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"This article does not require IRB\/IACUC approval because there are no human and animal participants.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}}],"article-number":"13"}}