Abstract

The objective of the present study was to quantify the within- and between-cow, operator, and day variances of various descriptive temperature parameters from different anatomical areas captured using thermal images on Holstein-Friesian cows. Three experiments were undertaken. In Exp. 1, 30 images were captured by a single operator of each of the eye, hoof, and udder from each of 45 cows; in Exp. 2, three different operators captured eye and hoof images from 12 cows; and in Exp. 3, eye and hoof images were captured by a single operator from 8 cows over a 5-d period. Maximum, minimum, and average descriptive temperature parameters were manually extracted from all thermal images within the study. The repeatability of thermal imaging and the number of replicates required to obtain a certain level of precision was evaluated. Precision was defined as the 95% CI range within which the (average of the) measured temperature(s) was expected to lie relative to the gold standard; the gold standard temperature of an entity in this study was the average of 30 temperature measurements. The partitioning of the variance into error, cow, operator, and day variances was undertaken using mixed models. Results show that the most repeatable anatomical area was the hoof, with the total proportion of variation attributed to the cow ranging from 91.37 to 99.28%. The descriptive temperature parameter with the lowest error variance was the maximum temperature for the eye (0.11°C) and udder (0.03°C) images, whereas the average temperature was the most precise descriptive temperature parameter for hoof (0.08°C) images. Additionally, no significant between-day variance was detected for maximum hoof temperatures. Results from the present study indicate that when the most precise descriptive temperature parameter is used, measurements made using infrared thermography can achieve a high level of precision in an agricultural environment if at least 3 replicate images of the eye, udder, or hooves of cows are captured and averaged. Additionally, when multiple operators capture thermal images in an agricultural environment, a standard operating procedure should be put in place to minimize the variance between operators.

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