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. 2021 Oct;56(10):1315-1328.
doi: 10.1111/rda.13994. Epub 2021 Aug 16.

Thermal features, ambient temperature and hair coat lengths: Limitations of infrared imaging in pregnant primitive breed mares within a year

Małgorzata Maśko  1 , Olga Witkowska-Piłaszewicz  2 , Tomasz Jasiński  2 , Małgorzata Domino  2
Affiliations
Free PMC article

Thermal features, ambient temperature and hair coat lengths: Limitations of infrared imaging in pregnant primitive breed mares within a year

Małgorzata Maśko et al. Reprod Domest Anim. 2021 Oct.
Free PMC article

Abstract

Infrared thermography is a non-invasive technique which allows to distinguish between pregnant and non-pregnant animals. Detecting accurate body surface temperatures can be challenging due to external factors altering thermograph measurements. This study aimed to determine the associations between the ambient temperature, the hair coat features and the temperatures of mares' abdomens. It compared pregnant and non-pregnant mares throughout 11 months. The research was carried out on 40 Konik Polski mares, which were divided into pregnant and non-pregnant groups. The temperature (Tmax, maximal; Taver, average; Tmin, minimal) of the mares' abdomen was evaluated in two regions of interest: the whole area of the lateral surface of the mares' abdomen (Px1) and the flank area of the lateral surface of mares' abdomen (Px2). During the increasing period, the slopes in the linear regression equation did not differ significantly for ambient (Tamb) and surface temperatures in both groups. In the decreasing period, the slopes did not differ significantly for Tamb and Tmax in the non-pregnant group. They also did not differ for Tamb and Taver in Px1 and Tamb and Tmin in Px1 in both pregnant and non-pregnant groups respectively. Other slopes varied significantly (p < .001). There was no evidence of parallel changes in hair coat features and measured temperatures. The flank area appears more suitable for thermal imaging in pregnant mares due to the seasonal fluctuations in hair coat lengths.

Keywords: Konik Polski; gestation; seasonal fluctuations; hair coat length; thermography.

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Conflict of interest statement

None of the authors has any conflict of interest to declare.

Figures

FIGURE 1
FIGURE 1
Protocol of thermal images analysis. The raw thermal images (a), thermal image after digital enhancement of details (b), thermal image with annotated the whole area of the lateral surface of the mares' abdomen (Px1) and the flank area of the lateral surface of mares' abdomen (Px2)
FIGURE 2
FIGURE 2
The environmental condition indicators (Tamb; humidity) (a), the hair coat length (b) and the hair coat Index (c) in consecutive months of study in pregnant (n = 26) and non‐pregnant (n = 14) groups. Bars represent values (a) or mean ± SD (b, c). Different superscripts within pregnant (a, b, c) and non‐pregnant (x, y, z) groups were statistically different (p < .05)
FIGURE 3
FIGURE 3
The maximal temperature (Tmax) in Px1 and Px2 in consecutive months of study in pregnant (n = 26) and non‐pregnant (n = 14) groups. Bars represent mean ± SD. Different superscripts within pregnant (a, b, c) and non‐pregnant (x, y, z) groups were statistically different (p < .05). Differences between pregnant and non‐pregnant groups were indicated with individual p value when p < .05 (a). Linear regressions of Tmax, Tamb and HC Index in pregnant (b, c) and non‐pregnant (d, e) groups in the increasing period (b, d) and the decreasing period (C, E)
FIGURE 4
FIGURE 4
The average temperature (Taver) in Px1 in consecutive months of study in pregnant (n = 26) and non‐pregnant (n = 14) groups. Bars represent mean ± SD. Different superscripts within pregnant (a, b, c) and non‐pregnant (x, y, z) groups were statistically different (p < .05). Differences between pregnant and non‐pregnant groups were indicated with individual p value when p < .05 (a). Linear regressions of Taver Px1, Tamb and HC Index in pregnant (b, c) and non‐pregnant (d, e) groups in the increasing period (b, d) and the decreasing period (c, e)
FIGURE 5
FIGURE 5
The average temperature (Taver) in Px2 in consecutive months of study in pregnant (n = 26) and non‐pregnant (n = 14) groups. Bars represent mean ± SD. Different superscripts within pregnant (a, b, c) and non‐pregnant (x, y, z) groups were statistically different (p < .05). Differences between pregnant and non‐pregnant groups were indicated with individual p value when p < .05 (a). Linear regressions of Taver Px2, Tamb and HC Index in pregnant (b, c) and non‐pregnant (d, e) groups in the increasing period (b, d) and the decreasing period (c, e)
FIGURE 6
FIGURE 6
The minimal temperature (Tmin) in Px1 in consecutive months of study in pregnant (n = 26) and non‐pregnant (n = 14) groups. Bars represent mean ± SD. Different superscripts within pregnant (a, b, c) and non‐pregnant (x, y, z) groups were statistically different (p < .05). Differences between pregnant and non‐pregnant groups were indicated with individual p value when p < .05 (a). Linear regressions of Tmin Px1, Tamb and HC Index in pregnant (b, c) and non‐pregnant (d, e) groups in the increasing period (b, d) and the decreasing period (c, e)
FIGURE 7
FIGURE 7
The minimal temperature (Tmin) in Px2 in consecutive months of study in pregnant (n = 26) and non‐pregnant (n = 14) groups. Bars represent mean ± SD. Different superscripts within pregnant (a, b, c) and non‐pregnant (x, y, z) groups were statistically different (p < .05). Differences between pregnant and non‐pregnant groups were indicated with individual p value when p < .05 (A). Linear regressions of Tmin Px2, Tamb and HC Index in pregnant (B, C) and non‐pregnant (D, E) groups in the increasing period (B, D) and the decreasing period (C, E)
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