Australian Cooperative Research Centre for Sheep Industry Innovation, Australia; Murdoch University, School of Veterinary & Life Sciences, Western Australia 6150, Australia.
Australian Cooperative Research Centre for Sheep Industry Innovation, Australia; Murdoch University, School of Veterinary & Life Sciences, Western Australia 6150, Australia.
Meat Sci. 2018 Oct;144:43-52. doi: 10.1016/j.meatsci.2018.06.035. Epub 2018 Jun 27.
Major efforts in the sheep industry to control eating quality have resulted in reduced product variability. Yet inconsistent eating quality for consumers remains, due to a degree of inaccurate representation of cut quality. Eating quality defined through a complex interplay of different factors can be predicted for individual cuts, and Meat Standards Australia (MSA) grading schemes have been developed to achieve these defined quality outcomes. This review outlines the justifications to refine the current sheepmeat MSA pathways system to transition into a cuts-based prediction model and details some of the factors affecting sheepmeat eating quality as key factors under consideration into the new model. The development of the new sheepmeat MSA prediction model will allow for more efficient carcass sorting to underpin a value based payment system throughout the supply chain. However it requires the inclusion of individual carcass yield and eating quality measurements (i.e. IMF). Furthermore, the adoption challenges internationally of an MSA like model are discussed.
养羊业为了控制肉质已做出重大努力,使产品的可变性降低。然而,由于对切割质量的某种程度上的不准确表示,消费者的肉质仍然不一致。通过不同因素的复杂相互作用来定义的肉质可通过个体切割进行预测,澳大利亚肉类标准局(MSA)分级计划就是为了实现这些定义的质量结果而制定的。本综述概述了完善现行羊肉 MSA 途径系统的理由,以过渡到基于切割的预测模型,并详细介绍了影响羊肉食用品质的一些因素,这些因素是新模型中考虑的关键因素。新的羊肉 MSA 预测模型的开发将允许更有效地进行胴体分类,以支撑整个供应链中的基于价值的支付系统。然而,这需要包括个体胴体产肉率和食用品质测量(即 IMF)。此外,还讨论了国际上采用类似 MSA 的模型所面临的挑战。