Background The horses’ backs are particularly exposed to overload and injuries due to direct contact with the saddle and the influence of e.g. the rider’s body weight. The maximal load for a horse’s back during riding has been suggested not to exceed 20% of the horses’ body weight. The common prevalence of back problems in riding horses prompted the popularization of thermography of the thoracolumbar region. However, the analysis methods of thermographic images used so far do not distinguish loaded horses with body weight varying between 10 and 20%. Results The superficial body temperature (SBT) of the thoracolumbar region of the horse’s back was imaged using a non-contact thermographic camera before and after riding under riders with LBW (low body weight, 10%) and HBW (high body weight, 15%). Images were analyzed using six methods: five recent SBT analyses and the novel approach based on Gray Level Co-Occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRLM). Temperatures of the horse’s thoracolumbar region were higher (p < 0.0001) after then before the training, and did not differ depending on the rider’s body weight (p > 0.05), regardless of used SBT analysis method. Effort-dependent differences (p < 0.05) were noted for six features of GLCM and GLRLM analysis. The values of selected GLCM and GLRLM features also differed (p < 0.05) between the LBW and HBW groups. Conclusion The GLCM and GLRLM analyses allowed the differentiation of horses subjected to a load of 10 and 15% of their body weights while horseback riding in contrast to the previously used SBT analysis methods. Both types of analyzing methods allow to differentiation thermal images obtained before and after riding. The textural analysis, including selected features of GLCM or GLRLM, seems to be promising tools in considering the quantitative assessment of thermographic images of horses’ thoracolumbar region.

Appropriate matching of rider–horse sizes is becoming an increasingly important issue of riding horses’ care, as the human population becomes heavier. Recently, infrared thermography (IRT) was considered to be effective in differing the effect of 10.6% and 21.3% of the rider:horse bodyweight ratio, but not 10.1% and 15.3%. As IRT images contain many pixels reflecting the complexity of the body’s surface, the pixel relations were assessed by image texture analysis using histogram statistics (HS), gray-level run-length matrix (GLRLM), and gray level co-occurrence matrix (GLCM) approaches. The study aimed to determine differences in texture features of thermal images under the impact of 10–12%, >12 ≤15%, >15 <18% rider:horse bodyweight ratios, respectively. Twelve horses were ridden by each of six riders assigned to light (L), moderate (M), and heavy (H) groups. Thermal images were taken pre- and post-standard exercise and underwent conventional and texture analysis. Texture analysis required image decomposition into red, green, and blue components. Among 372 returned features, 95 HS features, 48 GLRLM features, and 96 GLCH features differed dependent on exercise; whereas 29 HS features, 16 GLRLM features, and 30 GLCH features differed dependent on bodyweight ratio. Contrary to conventional thermal features, the texture heterogeneity measures, InvDefMom, SumEntrp, Entropy, DifVarnc, and DifEntrp, expressed consistent measurable differences when the red component was considered.

Endometrosis is an important mares’ disease which considerably decreases their fertility. As classic endometrial classification methods might be insufficient for tissue pathological evaluation, further categorization into active/inactive and destructive/non-destructive types was developed by Hoffmann and others. This study aimed to compare NF-κB pathway genes transcription among histopathological types of endometrosis, following Hoffmann and co-authors’ classification. Endometrial samples, collected postmortem from cyclic mares (n = 100) in estrus or diestrus, were classified histologically and used for gene transcription assessment. Gene transcription of NF-κB subunits (RelA, NF-κB1, NF-κB2), pro-inflammatory molecules (MCP-1, IL-6), and hyaluronan synthases (HAS 1, HAS 2, HAS 3) was compared among endometrosis types (active, non-active, destructive, non-destructive). Most individual mRNA samples showed high expression of RelA, NF-κB1, and MCP-1 gene transcripts and the destructive type of endometrosis, simultaneously. The expression of RelA and NF-κB1 genes was higher in active destructive group than in the other groups only in the follicular phase, as well as being higher in the inactive destructive group than in the others, only in the mid-luteal phase. The increase in gene transcription of the NF-κB canonical activation pathway in destructive endometrosis may suggest the highest changes in extracellular matrix deposition. Moreover, the estrous cycle phase might influence fibrosis pathogenesis.

Determination of the pregnancy status is one of the most important factors for effective pregnancy management. Knowledge of the stage of pregnancy is important to interpret many of the reproductive hormones’ concentrations, including progesterone (P4), estrone sulfate (E1S), 17-ß estradiol (E2), and relaxin (REL). However, it is limited in wildlife or captive equids that cannot be handled. Reproductive hormones affect regional blood flow, the proliferation of tissues, and local metabolism intensity. Therefore, this preliminary study aimed to assess changes in thermal features of the abdomen lateral surface and concentrations of reproductive hormones in Polish native pregnant mares. The study was carried out on 14 non-pregnant and 26 pregnant Polish Konik mares during eleven months of pregnancy. Infrared thermography was conducted to image the lateral surface of mares' abdomen (Px1) and flank area (Px2); P4, E1S, E2, and REL concentrations in serum were also determined. The evidence of the association between the area with the highest temperatures (Area of Tmax) and serum concentrations of P4 (the slope = 1.373; p = 0.9245) and REL (the slope = 1.342; p = 0.4324) were noted dependent across months of pregnancy. Measures of superficial body temperatures were found to change monthly, similarly to ambient temperatures, with no evidence of coincidence with changes in reproductive hormone concentrations. Individual thermal characteristics of the lateral surface of the abdomen differed between pregnant and non-pregnant mares in other periods. Differences in maximal and average temperature and Area of Tmax were observed from the sixth month of pregnancy, and those in minimal temperature were observed from the eighth month.

Background: The natural head and neck position (HNP) of horses differs from the position in horse riding when bit is used. The special lunging aids (LAs) are applied in order to modify HNP. Different types of LAs have the potential to affect the work of horse muscles and the superficial thermographic patterns (STPs). The effects of thre LAs on STPs of neck, chest, back, and hindquarters were investigated. Methods: Sixteen leisure horses were lunged with freely moving head (FMH), rubber band (RB), chambon (CH), and triangle side reins (TRs). The thermographic images (n = 896) were analyzed before/after lunging for mean temperatures (Tmean) and minimum–maximum difference (Tdiff). Results: Superficial Tmean increased (p < 0.001) in cranial part of neck, back, thoracic area, and limbs after lunging regardless of LAs application or its type. In comparison to other LAs: With RB, Tmean was higher in regions of interest (ROIs) 2,7 and lower in ROIs 3–4 (p < 0.05); with CH, Tmean was higher in ROIs 2–4 and 7 (p < 0.01); and with TRs, Tmean was higher in ROIs 2–4,7,9–11 (p < 0.01). In ROIs 2–4 and 7, Tdiff was lower with LAs than with FMH (p < 0.01) and in ROIs 9–10 with TRs. Conclusions: The choice of LAs should be dictated by the expected effect; however, all LAs increase the quality of the leisure horse lunging. LA use is more desirable than lunging with FMH.

As the breeding of donkeys has increased due to different types of use, welfare evaluation importance increases. This equid’s welfare state has been described using body condition indicators and the geometric morphometrics method. However, the dorsal profile has not yet been assessed in donkeys. In this study, the body condition score (BCS), fatty neck score (FNS), dental condition score (DCS), sex, and breed were used as criteria of dorsal profile deformations. Photographs of 40 donkeys were analyzed using geometric morphometrics. Within the entire set of dorsal profiles, the variance of the first three principal components (PCs) was PC1 = 37.41%, PC2 = 23.43%, and PC3 = 13.34%. The dorsal profiles displayed deformation as an effect of FNS and BCS on size (FNS p = 0.012; BCS p = 0.024) and shape (FNS p < 0.0001; BCS p < 0.0001), rather than as an effect of DCS (p < 0.0001), sex (p = 0.0264), and breed (p < 0.0001) only on shape. The highest distances among the categories (Mahalanobis distances: MD ≥ 13.26; Procrustes distances: PD ≥ 0.044) were noted for FNS. The lowest distances were noted between jennets and males (MD = 4.58; PD = 0.012) and between BCS 1 and BCS 2 (MD = 4.70; PD = 0.018). Donkeys’ body condition affects their dorsal profile and both FNS and BCS measurements should be considered when a donkey’s dorsal profile is investigated.

Infrared thermography (IRT) was applied as a potentially useful tool in the detection of pregnancy in equids, especially native or wildlife. IRT measures heat emission from the body surface, which increases with the progression of pregnancy as blood flow and metabolic activity in the uterine and fetal tissues increase. Conventional IRT imaging is promising; however, with specific limitations considered, this study aimed to develop novel digital processing methods for thermal images of pregnant mares to detect pregnancy earlier with higher accuracy. In the current study, 40 mares were divided into non-pregnant and pregnant groups and imaged using IRT. Thermal images were transformed into four color models (RGB, YUV, YIQ, HSB) and 10 color components were separated. From each color component, features of image texture were obtained using Histogram Statistics and Grey-Level Run-Length Matrix algorithms. The most informative color/feature combinations were selected for further investigation, and the accuracy of pregnancy detection was calculated. The image texture features in the RGB and YIQ color models reflecting increased heterogeneity of image texture seem to be applicable as potential indicators of pregnancy. Their application in IRT-based pregnancy detection in mares allows for earlier recognition of pregnant mares with higher accuracy than the conventional IRT imaging technique.

Leisure riding is a popular way of using horses however, unlike sport or racing horses, those are mostly not associated with one rider with high skills. Constant overload of equine musculoskeletal system causes pathologies, which are affecting horse mobility and decreases the horse‐rider communication. The aim was to propose the new scoring system of thermograph analysis as an aspect of differences in heat distributions on horseback before and after leisure ridings. The study was conducted on sixteen Polish warmblood horses, scanned with a non‐contact thermographic camera. Heat pattern of the thoracolumbar area was evaluated on thermograms taken before and after exercise. The criteria with point values for horse‐rider‐matching were created: heat points on the dorsal midline of saddle‐back contact area and degree of muscle unit overload. The results of thermograph analysis were compared with the results of a questionnaire on horse‐rider communication during riding in order to estimate the relevance of matching. The maximum score was obtained in 38.3% and 39.8% of combinations based on the thermograph analysis and questionnaire, respectively. Results of both scoring systems were strongly positive correlated (r = .937), demonstrating high sensitivity (61.72%) and specificity (90.23%) of the matching. The horse‐rider matching may improve horse comfort during leisure type of work.