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建立一种合适的比较模式,以衡量基于视频图像分析的牛肉胴体分级系统中大理石花纹评分输出的性能。

Establishing an appropriate mode of comparison for measuring the performance of marbling score output from video image analysis beef carcass grading systems.

机构信息

Cargill Meat Solutions, Wichita, KS 67219, USA.

出版信息

J Anim Sci. 2010 Jul;88(7):2464-75. doi: 10.2527/jas.2009-2593. Epub 2010 Mar 26.

Abstract

A beef carcass instrument grading system that improves accuracy and consistency of marbling score (MS) evaluation would have the potential to advance value-based marketing efforts and reduce disparity in quality grading among USDA graders, shifts, and plants. The objectives of this study were to use output data from the Video Image Analysis-Computer Vision System (VIA-CVS, Research Management Systems Inc., Fort Collins, CO) to develop an appropriate method by which performance of video image analysis MS output could be evaluated for accuracy, precision, and repeatability for purposes of seeking official USDA approval for using an instrument in commerce to augment assessment of quality grade, and to use the developed standards to gain approval for VIA-CVS to assist USDA personnel in assigning official beef carcass MS. An initial MS output algorithm was developed (phase I) for the VIA-CVS before 2 separate preliminary instrument evaluation trials (phases II and III) were conducted. During phases II and III, a 3-member panel of USDA expert graders independently assigned MS to 1,068 and 1,242 stationary carcasses, respectively. Mean expert MS was calculated for each carcass. Additionally, a separate 3-member USDA expert panel developed a consensus MS for each carcass in phase III. In phase II, VIA-CVS stationary triple-placement and triple-trigger instrument repeatability values (n = 262 and 260, respectively), measured as the percentage of total variance explained by carcasses, were 99.9 and 99.8%, respectively. In phases II and III, 95% of carcasses were assigned expert MS for which differences between individual expert MS, and for which the consensus MS in phase III only, was < or = 96 MS units. Two differing approaches to simple regression analysis, as well as a separate method-comparability analysis that accommodates error in both dependent and independent variables, were used to assess accuracy and precision of instrument MS predictions vs. mean expert MS. Method-comparability analysis was more appropriate in assessing the bias and precision of instrument MS predictions. Ether-extractable fat percentages (n = 257; phase II) differed among MS (P < 0.05) but were not suitable to predict or validate assigned MS. The performance and reproducibility of expert MS assignment in future evaluations was considered, and an official USDA performance standard was established, to which an instrument must conform to be approved for official on-line MS assessment. The VIA-CVS subsequently was approved to assign MS to carcasses on-line after completion of a 2006 USDA instrument approval trial conducted according to methods developed during completion of this study.

摘要

一种能够提高大理石花纹评分(MS)评估准确性和一致性的牛肉胴体仪器分级系统,有可能推动基于价值的营销工作,并减少美国农业部分级员、班次和工厂之间在质量分级方面的差异。本研究的目的是使用来自视频图像分析-计算机视觉系统(VIA-CVS,Research Management Systems Inc.,科罗拉多州福斯堡)的输出数据,开发一种合适的方法,用于评估视频图像分析 MS 输出的准确性、精密度和可重复性,以寻求美国农业部官方批准使用仪器进行商业评估,以补充对质量等级的评估,并使用制定的标准为 VIA-CVS 获得批准,以帮助美国农业部人员分配官方牛肉胴体 MS。在进行了两次单独的仪器初步评估试验(第二阶段和第三阶段)之前,先开发了 VIA-CVS 的初始 MS 输出算法(第一阶段)。在第二阶段和第三阶段,由三名美国农业部专家评审员独立地对 1068 头和 1242 头静止胴体进行了 MS 评分,分别计算出每头胴体的平均专家 MS。此外,在第三阶段,一个单独的三人美国农业部专家小组为每头胴体制定了一个共识 MS。在第二阶段,VIA-CVS 静止三重放置和三重触发仪器重复性值(n=262 和 260,分别),以胴体解释的总方差的百分比来衡量,分别为 99.9%和 99.8%。在第二阶段和第三阶段,95%的胴体被分配了专家 MS,其中个体专家 MS 之间的差异,以及第三阶段的共识 MS 之间的差异,均<或=96 MS 单位。使用两种不同的简单回归分析方法,以及一种单独的方法可比较性分析方法,该方法可以同时适应因变量和自变量的误差,用于评估仪器 MS 预测值与专家平均 MS 的准确性和精密度。在评估仪器 MS 预测值的偏倚和精度方面,方法可比较性分析更为合适。乙醚提取物脂肪百分比(n=257;第二阶段)因 MS 而异(P<0.05),但不适合预测或验证分配的 MS。还考虑了未来评估中专家 MS 分配的性能和可重复性,并制定了官方美国农业部性能标准,仪器必须符合该标准才能获得官方在线 MS 评估的批准。在根据本研究完成的 2006 年美国农业部仪器批准试验完成后,VIA-CVS 随后被批准在线分配 MS 给胴体。

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