The relationship of parameters of body measures and body weight by using digital image analysis in pre-slaughter cattle
The relationship of parameters of body measures and body weight by using digital image analysis in pre-slaughter cattle
复制标题
DOI：
10.5194/aab-51-120-2008
复制
发表时间：
2008-10
影响因子：
1.8
通讯作者：
S. Ozkaya;Y. Bozkurt
中科院分区：
文献类型：
--
作者：
S. Ozkaya;Y. Bozkurt
摘要本研究旨在利用数位影像分析技术，预测屠宰前肉牛的体重。本研究中使用的数据收集自伊斯帕尔塔和附近省份的屠宰场的140头动物。采用数字图像分析技术，对不同品种肉牛的体尺指标（体重、体高、体长、胸深、臀宽、臀高、体面积）进行了综合比较。将身体面积作为预测BW的不同参数而不是胸围。而只考虑体面积的回归方程，荷斯坦牛的R2值最低（18.0%），而瑞士褐牛和杂交牛的R2值分别为43.2和51.7%。回归方程包括所有的身体性状的R2值分别为35.3，85.1和79.6%的荷斯坦，布朗瑞士和杂交。包括体面积和体长的回归方程表明，数字图像分析的预测能力高的预测BW的布朗瑞士和杂交动物相比，荷斯坦（R 2 82.6，76.5，29.5%，分别）。结果表明，数字图像分析对体重的预测能力较低。虽然使用体面积作为预测BW的参数的可能性很低，但可以通过进一步和更好地设计实验来开发。
objective of this study was to predict body weight (BW) of pre-slaughtering beef cattle using digital image analysis. Data used in this study were collected from slaughterhouses in Isparta and nearby provinces from 140 animals. Selected body measurements such as body weight (BW), wither height (WH), body length (BL), chest depth (CD), hip width (HW), hip height (HH) and body area (BA) of different breeds of beef cattle were combined and compared by digital image analysis. The body area was included as a different parameter for prediction of BW instead of chest girth. However, regression equation that included only body area gave the lowest R 2 value for Holstein (18.0%), but the R 2 value was 43.2 and 51.7% for Brown Swiss and crossbred animals, respectively. The regression equation which included all body traits resulted in R 2 values 35.3, 85.1, and 79.6% for Holstein, Brown Swiss and crossbred, respectively. The regression equation which included body area and body length showed that prediction ability of digital image analysis was high for prediction of BW in Brown Swiss and crossbred animals compared to Holsteins (R 2 82.6, 76.5, and 29.5%, respectively). Results indicated that the prediction ability of digital image analysis was low for prediction of BW. Although possibility of using body area as a parameter in predicting BW is low it can be developed by further and better designed experiments.