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使用MARC牛肉胴体图像分析系统对产肉等级、背最长肌面积、初步产肉等级、调整后的初步产肉等级和大理石花纹评分进行在线预测。

On-line prediction of yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score using the MARC beef carcass image analysis system.

作者信息

Shackelford S D, Wheeler T L, Koohmaraie M

机构信息

Roman L. Hruska US Meat Animal Research Center, USDA, ARS, Clay Center, NE 68933-0166, USA.

出版信息

J Anim Sci. 2003 Jan;81(1):150-5. doi: 10.2527/2003.811150x.

Abstract

The present experiment was conducted to evaluate the ability of the U.S. Meat Animal Research Center's beef carcass image analysis system to predict calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score under commercial beef processing conditions. In two commercial beef-processing facilities, image analysis was conducted on 800 carcasses on the beef-grading chain immediately after the conventional USDA beef quality and yield grades were applied. Carcasses were blocked by plant and observed calculated yield grade. The carcasses were then separated, with 400 carcasses assigned to a calibration data set that was used to develop regression equations, and the remaining 400 carcasses assigned to a prediction data set used to validate the regression equations. Prediction equations, which included image analysis variables and hot carcass weight, accounted for 90, 88, 90, 88, and 76% of the variation in calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score, respectively, in the prediction data set. In comparison, the official USDA yield grade as applied by online graders accounted for 73% of the variation in calculated yield grade. The technology described herein could be used by the beef industry to more accurately determine beef yield grades; however, this system does not provide an accurate enough prediction of marbling score to be used without USDA grader interaction for USDA quality grading.

摘要

本试验旨在评估美国肉类动物研究中心的牛肉胴体图像分析系统在商业牛肉加工条件下预测计算产量等级、背最长肌面积、初步产量等级、调整后的初步产量等级和大理石花纹评分的能力。在两家商业牛肉加工设施中,在应用传统的美国农业部牛肉质量和产量等级后,立即对牛肉分级链上的800头胴体进行图像分析。胴体按加工厂进行分组,并观察计算产量等级。然后将胴体分开,400头胴体被分配到用于建立回归方程的校准数据集,其余400头胴体被分配到用于验证回归方程的预测数据集。包含图像分析变量和热胴体重的预测方程分别解释了预测数据集中计算产量等级、背最长肌面积、初步产量等级、调整后的初步产量等级和大理石花纹评分变异的90%、88%、90%、88%和76%。相比之下,在线分级员应用的美国农业部官方产量等级解释了计算产量等级变异的73%。本文所述技术可被牛肉行业用于更准确地确定牛肉产量等级;然而,该系统对大理石花纹评分的预测不够准确,无法在没有美国农业部分级员参与的情况下用于美国农业部质量分级。

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