Wrigglesworth David J, Mort Emily S, Upton Sarah L, Miller Andrew T
WALTHAM Centre for Pet Nutrition, Waltham-on-the-Wolds, Leicestershire, LE14 4RT, England.
Am J Vet Res. 2011 Sep;72(9):1151-5. doi: 10.2460/ajvr.72.9.1151.
To determine accuracy of the use of triaxial accelerometry for measuring daily activity as a predictor of maintenance energy requirement (MER) in healthy adult Labrador Retrievers.
10 healthy adult Labrador Retrievers.
Dogs wore an accelerometer for two 2-week periods, with data on daily activity successfully collected for 24 to 26 days. These data, along with body weight, were used as independent variables in a multiple linear regression model to predict the dependent variable of daily MER. The predictive accuracy of the model was compared with that of a model that excluded activity. Dietary energy intake at a stated amount of body weight stability was used as an equivalent measure of MER in these analyses.
The multiple linear regression model that included body weight and daily activity as independent variables could be used to predict observed MER with a mean absolute error of 63.5 kcal and an SE of estimation of 94.3 kcal. Removing activity from the model reduced the predictive accuracy to a mean absolute error of 129.8 kcal and an SE of estimation of 165.4 kcal.
Use of triaxial accelerometers to provide an independent variable of daily activity yielded a marked improvement in predictive accuracy of the regression model, compared with that for a model that used only body weight. Improved accuracy in estimations of MER could be made for each dog if an accelerometer was used to record its daily activity.
确定在健康成年拉布拉多寻回犬中,使用三轴加速度计测量日常活动作为维持能量需求(MER)预测指标的准确性。
10只健康成年拉布拉多寻回犬。
犬佩戴加速度计,为期两个2周时间段,成功收集到24至26天的日常活动数据。这些数据以及体重被用作多元线性回归模型中的自变量,以预测每日MER这一因变量。将该模型的预测准确性与排除活动因素的模型进行比较。在这些分析中,将体重稳定状态下规定摄入量的膳食能量摄入用作MER的等效指标。
包含体重和日常活动作为自变量的多元线性回归模型可用于预测观察到的MER,平均绝对误差为63.5千卡,估计标准误为94.3千卡。从模型中去除活动因素后,预测准确性降低至平均绝对误差为129.8千卡,估计标准误为165.4千卡。
与仅使用体重的模型相比,使用三轴加速度计提供日常活动的自变量可使回归模型的预测准确性显著提高。如果使用加速度计记录每只犬的日常活动,则可以提高MER估计的准确性。