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利用视频图像分析对牛肉胴体实时增强美国农业部产量等级应用

Real-time augmentation of USDA yield grade application to beef carcasses using video image analysis.

作者信息

Steiner R, Wyle A M, Vote D J, Belk K E, Scanga J A, Wise J W, Tatum J D, Smith G C

机构信息

Department of Animal Sciences, Colorado State University, Fort Collins 80523-1171, USA.

出版信息

J Anim Sci. 2003 Sep;81(9):2239-46. doi: 10.2527/2003.8192239x.

Abstract

In two phases, this study assessed the ability of two video image analysis (VIA) instruments, VIASCAN and Computer Vision System (CVS), to augment assignment of yield grades (YG) to beef carcasses to 0.1 of a YG at commercial packing plant speeds and to test cutout prediction accuracy of a YG augmentation system that used a prototype augmentation touchpanel grading display (designed to operate commercially in real-time). In Phase I, beef carcasses (n = 505) were circulated twice at commercial chain speeds (340 carcasses per hour) by 12 on-line USDA graders. During the first pass, on-line graders assigned a whole-number YG and a quality grade (QG) to carcasses as they would normally. During the second pass, on-line graders assigned only adjusted preliminary yield grades (APYG) and QG to carcasses, whereas the two VIA instruments measured the longissimus muscle area (LMA) of each carcass. Kidney, pelvic, and heart fat (KPH) was removed and weighed to allow computation of actual KPH percentage. Those traits were compared to the expert YG and expert YG factors. On-line USDA graders' APYG were closely related (r = 0.83) to expert APYG. Instrument-measured LMA were closely related (r = 0.88 and 0.94; mean absolute error = 0.3 and 0.2 YG units, for VIASCAN and CVS, respectively) to expert LMA. When YG were augmented using instrument-measured LMA and computed either including or neglecting actual KPH percentage, YG were closely related (r = 0.93 and 0.92, mean absolute error = 0.32 and 0.40 YG units, respectively, using VIASCAN-measured LMA; r = 0.95 and 0.94, mean absolute error = 0.24 and 0.34 YG units, respectively, using CVS-measured LMA) to expert YG. In Phase II, augmented YG were assigned (0.1 of a YG) to beef carcasses (n = 290) at commercial chain speeds using VIASCAN and CVS to determine LMA, whereas APYG and QG were determined by online graders via a touch-panel display. On-line grader YG (whole-number), expert grader YG (to the nearest 0.1 of a YG), and VIASCAN- and CVS-augmented YG (to the nearest 0.1 of a YG) accounted for 55, 71, 60, and 63% of the variation in fabricated yields of closely trimmed subprimals, respectively, suggesting that VIA systems can operate at current plant speeds and effectively augment official USDA application of YG to beef carcasses.

摘要

本研究分两个阶段,评估了两种视频图像分析(VIA)仪器,即VIASCAN和计算机视觉系统(CVS),在商业包装厂速度下将牛肉胴体的产量等级(YG)精确到0.1级的能力,并测试了使用原型增强型触摸面板分级显示器(设计用于商业实时操作)的YG增强系统的切块预测准确性。在第一阶段,12名美国农业部在线分级员以商业链条速度(每小时340头胴体)将505头牛肉胴体循环处理两次。在第一次循环中,在线分级员按常规给胴体分配一个整数YG和一个质量等级(QG)。在第二次循环中,在线分级员仅给胴体分配调整后的初步产量等级(APYG)和QG,而两种VIA仪器测量每头胴体的背最长肌面积(LMA)。去除肾脏、骨盆和心脏脂肪(KPH)并称重,以计算实际KPH百分比。将这些性状与专家YG和专家YG因子进行比较。美国农业部在线分级员的APYG与专家APYG密切相关(r = 0.83)。仪器测量的LMA与专家LMA密切相关(VIASCAN和CVS的r分别为0.88和0.94;平均绝对误差分别为0.3和0.2 YG单位)。当使用仪器测量的LMA并在计算中包括或忽略实际KPH百分比来增强YG时,YG与专家YG密切相关(使用VIASCAN测量的LMA时,r分别为0.93和0.92,平均绝对误差分别为0.32和0.40 YG单位;使用CVS测量的LMA时,r分别为0.95和

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