کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
2441053 | 1108131 | 2006 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Comparison of Models to Identify Lame Cows Based on Gait and Lesion Scores, and Limb Movement Variables
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم دامی و جانورشناسی
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چکیده انگلیسی
Bovine lameness results in pain and suffering in cattle and economic loss for producers. A system for automatically detecting lame cows was developed recently that measures vertical force components attributable to individual limbs. These measurements can be used to calculate a number of limb movement variables. The objective of this investigation was to explore whether gait scores, lesion scores, or combined gait and lesion scores were more effectively captured by a set of 5 limb movement variables. A set of 700 hind limb examinations was used to create gait-based, lesion-based, and combined (gait- and lesion-based) models. Logistic regression models were constructed using 1, 2, or 3 d of measurements. Resulting models were tested on cows not used in modeling. The accuracy of lesion-score models was superior to that of gait-score models; lesion-based models generated greater values of areas under the receiving operating characteristic curves (range 0.75 to 0.84) and lower mean-squared errors (0.13 to 0.16) compared with corresponding values for the gait-based models (0.63 to 0.73 and 0.26 to 0.31 for receiving operating characteristic and mean-squared errors, respectively). These results indicate that further model development and investigation could generate automated and objective methods of lameness detection in dairy cattle.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Dairy Science - Volume 89, Issue 11, November 2006, Pages 4267-4275
Journal: Journal of Dairy Science - Volume 89, Issue 11, November 2006, Pages 4267-4275
نویسندگان
P.G. Rajkondawar, M. Liu, R.M. Dyer, N.K. Neerchal, U. Tasch, A.M. Lefcourt, B. Erez, M.A. Varner,