کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
2842686 1571091 2016 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Prediction of rectal temperature using non-invasive physiologic variable measurements in hair pregnant ewes subjected to natural conditions of heat stress
ترجمه فارسی عنوان
پیش بینی درجه حرارت مقعدی با استفاده از اندازه گیری متغیرهای فیزیولوژیک غیرتهاجمی در میش باردار در معرض شرایط طبیعی استرس گرمائی
کلمات کلیدی
دمای بدن؛ گوسفند؛ ابر؛ هیپرترمی؛ معادله پیش بینی
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
چکیده انگلیسی


• An equation to predict rectal temperature in pregnant ewes was developed.
• Physiologic variables measured from non-invasive methods were used as predictors.
• Most variation in rectal temperature was explained by respiratory rate, and head and belly temperatures.
• The equation can predict rectal temperature with moderate accuracy.

Rectal temperature (RT) is the foremost physiological variable indicating if an animal is suffering hyperthermia. However, this variable is traditionally measured by invasive methods, which may compromise animal welfare. Models to predict RT have been developed for growing pigs and lactating dairy cows, but not for pregnant heat-stressed ewes. Our aim was to develop a prediction equation for RT using non-invasive physiological variables in pregnant ewes under heat stress. A total of 192 records of respiratory frequency (RF) and hair coat temperature in various body regions (i.e., head, rump, flank, shoulder, and belly) obtained from 24 Katahdin×Pelibuey pregnant multiparous ewes were collected during the last third of gestation (i.e., d 100 to lambing) with a 15 d sampling interval. Hair coat temperatures were taken using infrared thermal imaging technology. Initially, a Pearson correlation analysis examined the relationship among variables, and then multiple linear regression analysis was used to develop the prediction equations. All predictor variables were positively correlated (P<0.01; r=0.59–0.67) with RT. The adjusted equation which best predicted RT (P  <0.01; Radj2=56.15%; CV=0.65%) included as predictors RF and head and belly temperatures. Comparison of predicted and observed values for RT indicates a suitable agreement (P  <0.01) between them with moderate accuracy (Radj2=56.15%) when RT was calculated with the adjusted equation. In general, the final equation does not violate any assumption of multiple regression analysis. The RT in heat-stressed pregnant ewes can be predicted with an adequate accuracy using non-invasive physiologic variables, and the final equation was: RT=35.57+0.004 (RF)+0.067 (heat temperature)+0.028 (belly temperature).

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Thermal Biology - Volume 55, January 2016, Pages 1–6
نویسندگان
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