Advanced Livestock Measurement Technologies (ALMTech), Murdoch University, School of Science, Health and Engineering, Western Australia 6150, Australia.
Frontmatec A/S, Smørum 2765, Denmark.
Meat Sci. 2021 Nov;181:108358. doi: 10.1016/j.meatsci.2020.108358. Epub 2020 Oct 22.
The objective of this study was to test the performance of a prototype vision system in phenotypically diverse beef and lamb carcasses against visual grading of eye muscle area (EMA), marbling and chemical intramuscular fat (IMF%). Validation in beef demonstrated that the camera prototype in combination with analytical techniques enabled prediction of EMA (r = 0.83, RMSEP = 6.4 cm), MSA marbling (r = 0.76, RMSEP = 66.1), AUS-MEAT marbling (r = 0.70, RMSEP = 0.74) and chemical IMF% (r = 0.78, RMSEP = 1.85%). Accuracy was also maintained on validation with all four traits displaying minimal bias of -3.6, 6.3, 0.07 and - 0.01, for EMA, MSA marbling, AUS-MEAT marbling and IMF% respectively. Preliminary analysis in lamb indicates potential of the system for the prediction of EMA (r = 0.41, RMSEP = 1.87) and IMF% (r = 0.28, RMSEP = 1.10), however further work to standardise image acquisition and environmental conditions is required.
本研究的目的是测试一个原型视觉系统在表型多样化的牛肉和羊肉胴体中的性能,以对抗眼肌面积(EMA)、大理石花纹和肌肉内化学脂肪(IMF%)的视觉分级。在牛肉中的验证表明,相机原型与分析技术相结合,可以预测 EMA(r=0.83,RMSEP=6.4cm)、MSA 大理石花纹(r=0.76,RMSEP=66.1)、AUS-MEAT 大理石花纹(r=0.70,RMSEP=0.74)和化学 IMF%(r=0.78,RMSEP=1.85%)。在对所有四个特征的验证中,精度也得以保持,分别为 EMA、MSA 大理石花纹、AUS-MEAT 大理石花纹和 IMF%,显示出最小的偏倚为-3.6、6.3、0.07 和-0.01。在羔羊的初步分析中,该系统具有预测 EMA(r=0.41,RMSEP=1.87)和 IMF%(r=0.28,RMSEP=1.10)的潜力,然而,需要进一步的工作来标准化图像采集和环境条件。