This review describes the physiological role of cortisol in the horses’ body and the usefulness of cortisol concentration measurements in assessing welfare and diagnosing diseases. Cortisol is examined in terms of its production and functions, along with the concept of circadian cortisol rhythms and potential disruptions in these patterns. The significance of cortisol concentration is emphasized, as it provides insights into stress levels, and the connection between cortisol and stereotypical horse behaviors, raising the question of whether these behaviors signify stress or serve as coping mechanisms. Moreover, cortisol concentration helps in diagnosing various health conditions such as Cushing’s Disease, inflammation, and metabolic imbalances. As cortisol concentration is considered a stress indicator that may be affected by the sampling protocol, the matrices for cortisol sampling and their practical applications are summarized. In this review, three major cortisol sampling methods: plasma, salivary, and hair cortisol, are described in detail. Plasma cortisol measurements offer acute stress insights, while salivary cortisol analysis provides a non-invasive method for continuous stress monitoring. Hair cortisol, on the other hand, offers an assessment of long-term stress levels. This text underscores the importance of cortisol control in safeguarding the welfare and health of horses.

Since donkey breeding has increased due to their variety of uses, welfare evaluation has become more important. This study aimed to compare donkey, pony, and horse dorsal profiles and head shapes using geometric morphometrics (GM). Photographs of 14 donkeys, 14 ponies, and 14 horses were analyzed using GM, including the sliding semilandmarks method. The variations in the first three principal components (PCs) were PC1: 57.16%, PC2: 16.05%, and PC3: 8.31% for the dorsal profiles and PC1: 44.77%, PC2: 13.46%, and PC3: 7.66% for the head shapes. Both the dorsal profiles and head shapes differed between donkeys and horses (p < 0.0001) but not between donkeys and ponies (p > 0.05). Moreover, both the dorsal profiles and head shapes differed in size between ponies and horses (p < 0.0001) but not in shape (p > 0.05). Higher Mahalanobis and Procrustes distances were noted between donkeys and horses as well between donkeys and ponies than between ponies and horses. The use of geometric morphometrics revealed the differences in the dorsal profiles and head shapes between the studied equids. These differences should be taken into account when adapting welfare scales and methods from horses to donkeys.

Infrared thermography is a valuable tool adapted for veterinary diagnostics with an increasing number of uses. However, proper image acquisition is hard, not only due to various factors affecting the image but also because informative image processing is a struggle. Thus, this study aims to quantify the area of maximum temperature (Area of Tmax) on the lateral surface of horses and foals to compare the Areas of Tmax between horses and foals and to compare two new approaches to the Area of Tmax quantification in horses. Infrared images were acquired with a thermographic camera from 12 horses and 12 foals in the same ambient condition. The backgrounds of the images were removed, and the images were then processed in Rainbow HC and a grayscale palette. Then, 10 images were created, showing the Areas of Tmax in gradually decreasing ranges. The evaluation of the Area of Tmax with two image processing methods showed higher maximum temperatures in foals, although the high-temperature values covered less of their total body area than in adult horses. The results indicate the struggles of foals with thermal homeostasis. The proposed methods—multi-colored annotated pixels on Rainbow HC and red-annotated pixels on grayscale—provide a common quality in the thermogram evaluation of foals and adult horses. Further research is essential to determine their diagnostic application.

As obesity is a serious problem in the human population, overloading of the horse’s thoracolumbar region often affects sport and school horses. The advances in using infrared thermography (IRT) to assess the horse’s back overload will shortly integrate the IRT-based rider-horse fit into everyday equine practice. This study aimed to evaluate the applicability of entropy measures to select the most informative measures and color components, and the accuracy of rider:horse bodyweight ratio detection. Twelve horses were ridden by each of the six riders assigned to the light, moderate, and heavy groups. Thermal images were taken pre- and post-exercise. For each thermal image, two-dimensional sample (SampEn), fuzzy (FuzzEn), permutation (PermEn), dispersion (DispEn), and distribution (DistEn) entropies were measured in the withers and the thoracic spine areas. Among 40 returned measures, 30 entropy measures were exercise-dependent, whereas 8 entropy measures were bodyweight ratio-dependent. Moreover, three entropy measures demonstrated similarities to entropy-related gray level co-occurrence matrix (GLCM) texture features, confirming the higher irregularity and complexity of thermal image texture when horses worked under heavy riders. An application of DispEn to red color components enables identification of the light and heavy rider groups with higher accuracy than the previously used entropy-related GLCM texture features.

Water treadmill (WT) exercise is gaining popularity among equine athletes as it allows for increased workload through the resistance posed by water. However, the effect of an artificial river (AR), which further increases this resistance, on equine fitness indicators has not yet been investigated. This study aimed to determine whether WT exercise with varying water depths and the presence of an AR influences physiological response indicators. Fifteen school horses (n = 15) underwent five treadmill exercise sessions: on a dry treadmill (DT), in fetlock-depth water with and without AR, and in carpal-depth water with and without AR. Physiological responses were assessed pre-exercise, during the highest workload, and at 30 min and 24 h post-exercise by measuring heart rate (HR), blood lactate concentration (LAC), red blood cell count (RBC), hemoglobin concentration (HGB), and the activity of three serum enzymes: creatine phosphokinase (CK), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH). HR and LAC increased significantly (p < 0.0001) from the pre-exercise resting state to the highest workload time point during treadmill exercise, regardless of session type. During the carpal-depth WT+AR session, horses achieved a fitness level characterized by the highest HR (p < 0.0001), LAC (p < 0.0001), and LDH activity (p = 0.001). Thus, horses’ physiological responses to walking on a WT with AR differ from those observed on a DT and a WT without AR. WT exercise with AR represents a low-to-moderate intensity aerobic workload for horses, which increases with water depth from fetlock to carpal levels. However, further research is required to evaluate its inclusion in training or rehabilitation programs for athletic horses and its potential beneficial effects.

Since interest in equine manual therapy and rehabilitation is constantly growing, the need for quantification of the horse’s postural response to used alternative therapy has increased. This study implemented geometric morphometrics (GM) for a dorsal profile comparison between the horse groups. The dorsal profile was represented by the centroid size and the centroid shape. The horse groups were defined using four classifiers: horse’s age, height at the withers, time lap in the massage session, and technique of the massage (dorsal, ventral, and dorso–ventral). Out of a total of 900 photographs of 20 horses, 180 photos were analyzed using GM, including thirty landmarks. Variation of the principal components (PCs) representing consecutive dorsal profiles were reported for the first three PSs as 59.50% for PC1, 14.36% for PC2, and 9.01% for PC3. The dorsal profiles differed depending on the classifier ‘height’ in terms of centroid size (p < 0.0001) as well as classifier ‘time’ (p < 0.0001) and classifier ‘technique’ (p < 0.0001) in terms of centroid shape, but not depending on the classifier ‘age’ (p > 0.05). GM allows visualizing the differences in the horses’ posture resulting from the selected manual rehabilitation techniques. The quantification of the horse’s body posture in the studied protocol indicates horses’ body posture after being warmed-up and massaged using the dorso–ventral technique is the most desirable.