Abstract: Forty-one Dutch Warmblood immature horses were used in a study to quantify temperamental traits on the basis of heart rate (HR) and heart rate variability (HRV) measures. Half of the horses received additional training from the age of 5 months onwards; the other half did not. Horses were tested at 9, 10, 21 and 22 months of age in a novel object and a handling test. During the tests, mean HR and two heart variability indices, e.g. standard deviation of beat-to-beat intervals (SDRR) and root mean square of successive beat-to-beat differences (rMSSD), were calculated and expressed as response values to baseline measures. In both tests, horses showed at all ages a significant increase in mean HR and decrease in HRV measures, which suggests a marked shift of the balance of the autonomic nervous system towards a sympathetic dominance. In the novel object test, this shift was more pronounced in horses that had not been trained. Furthermore, statistical analysis showed that the increase in mean HR could not be entirely explained by the physical activity. The additional increase in HR, the nonmotor HR, was more pronounced in the untrained horses compared to the trained. Hence, it is suggested that this nonmotor HR might be due to the level of emotionality. HR variables showed consistency between years, as well as within the second year. These tests bring about a HR response in horses, part of which may indicate a higher level of emotionality; and horses show individual consistency of these HR variables over ages. Therefore, it is concluded that mean HR and HRV measures used with these tests quantify certain aspects of a horse's temperament.

Abstract: In various species, sex, hormonal treatments and oestrous-cycle stage have been shown to affect the animal's response in behavioural tests. Few such studies have been performed in the horse. The main aim of the present study was to investigate whether oestrous-cycle stage affects mares' response to a novel object test and isolation test and, in part, to study whether mares, assumed to suffer from oestrous-related behavioural problems, respond differently in these tests when compared with controls. Twelve mares were tested twice, in oestrus and dioestrus, in a crossover design. Seven behavioural and two heart rate variables were measured for the novel object test and two heart rate variables for the isolation test. Oestrous-cycle stage and whether a mare was classified as a 'problem' mare did not affect the mare's response. However, test order, i.e. the cycle stage a mare was tested in first, affected its reaction. This effect could partly be explained by significant differences between test occasions 1 and 2 in three behavioural variables and one heart rate variable (p < 0.05) in the novel object test. The mares explored the novel object more and had a higher mean heart rate in the first test. Exploring the novel object more could largely be attributed to those mares tested in dioestrus first, perhaps indicating that the mares in oestrus were less receptive to the novel object. The reason for the differences between test occasions could be an effect of learning or habituation.

Abstract: Many large mammals show pronounced seasonal fluctuations of metabolic rate (MR). It has been argued, based on studies in ruminants, that this variation merely results from different levels of locomotor activity (LA), and heat increment of feeding (HI). However, a recent study in red deer (Cervus elaphus) identified a previously unknown mechanism in ungulates--nocturnal hypometabolism--that contributed significantly to reduced energy expenditure, mainly during late winter. The relative contribution of these different mechanisms to seasonal adjustments of MR is still unknown, however. Therefore, in the study presented here we quantified for the first time the independent contribution of thermoregulation, LA and HI to heart rate (f(H)) as a measure of MR in a free-roaming large ungulate, the Przewalski horse or Takhi (Equus ferus przewalskii Poljakow). f(H) varied periodically throughout the year with a twofold increase from a mean of 44 beats min(-1) during December and January to a spring peak of 89 beats min(-1) at the beginning of May. LA increased from 23% per day during December and January to a mean level of 53% per day during May, and declined again thereafter. Daily mean subcutaneous body temperature (T(s)) declined continuously during winter and reached a nadir at the beginning of April (annual range was 5.8 degrees C), well after the annual low of air temperature and LA. Lower T(s) during winter contributed considerably to the reduction in f(H). In addition to thermoregulation, f(H) was affected by reproduction, LA, HI and unexplained seasonal variation, presumably reflecting to some degree changes in organ mass. The observed phase relations of seasonal changes indicate that energy expenditure was not a consequence of energy uptake but is under endogenous control, preparing the organism well in advance of seasonal energetic demands.

Abstract: Equine training methods, and consequently, performance times have improved little since the last decades. With advances in measuring signals on-line by means of several new technologies and analytical procedures, and processing these signals immediately with strong and compact processors, it may be possible to develop new training methods. In this research, the objective was to explore the possibilities of using modern model-based algorithms to control the heart rate of horses (bpm) on-line by means of the control input running speed (km/h). Forty-five experiments with five horses and four riders were carried out to generate measurements of physiological status during running. The dynamical characteristics of each horse were quantified using linear discrete transfer function models. The dynamic response of heart rate to step changes in running speed were accurately described. In 90% of the cases, a first-order model gave the best fit. For 69% of the models, the r2 was higher than 0.90 and for 34% of the models, the r2 was even higher than 0.95. In a next step, the model-based algorithm was evaluated by controlling cardiac responses of two horses (horses 2 and 4) to a pre-defined trajectory. The model parameters were kept constant. On average, the error between the defined target trajectory in heart rate and the actual controlled heart rate ranged between 0.2 and 1.4 bpm for the whole target heart rate trajectory. During the steady-state part of the trajectory the average error was maximum 1.1 bpm. In the transient from one steady-state heart rate to another level, the error could increase on average up to 5 bpm. In the future, the combination of on-line measured bioresponses with real-time analysis can be used for adjusting the work load of the horse, during training, directly to the immediate needs of horse (welfare) and trainer (performance).

Abstract: Current definitions of horse personality traits are rather vague, lacking clear, universally accepted guidelines for evaluation in performance tests. Therefore, the aim of the present study was to screen behavioural and physiological measurements taken during riding for potential links with scores the same horses received in the official stallion performance test for rideability and personality traits. Behaviour, heart rate (HR) and HR variability from thirty-six stallions participating in a performance test were recorded repeatedly during their performance test training. Using the coefficient of determination, regression analysis revealed that about 1/3 of variation (ranging between r = 0.26 (“constitution” (i.e. fitness, health)) and r = 0.46 (rideability)) in the personality trait scores could be explained by selecting the three most influential behaviour patterns per trait. These behaviour patterns included stumbling (with all traits except character), head-tossing (temperament, rideability), tail-swishing (willingness to work), involuntary change in gait (character) and the rider's use of her/his hands (constitution, rideability), voice (temperament) or whip (constitution). Subsequent mixed model analysis revealed a significant (P < 0.05) influence of the behaviour pattern “horse-induced change in gait” on character (-0.98 ± 0.31 scores per additional occurrence of change in gaits), of head-tossing (-0.25 ± 0.08 scores) and rider's use of voice (-0.51 ± 0.25; P = 0.0594) on temperament, and of stumbling on each of the following: willingness to work (-2.5 ± 1.2), constitution (-2.5 ± 1.2 scores; P = 0.0516) and rideability scores (-3.3 ± 1.4). In addition, constitution scores tended (P = 0.0889) to increase with higher low frequency/high frequency heart rate variation ratios (LF/HF), indicating a shift towards sympathetic dominance and thus a higher stress load in horses with higher scores for constitution. Rideability scores from the training phase were also significantly influenced by head-tossing (-0.5 ± 0.1), and in addition rideability scores from the final test were influenced by the training rider, ranging between average estimated rideability scores of 6.8 ± 0.4 for one training rider and 8.36 ± 0.3 scores for another training rider. Horses ridden with their nose-line predominantly behind the vertical received higher scores for rideability (8.3 ± 0.3) than horses ridden with their nose-line at the vertical (7.7 ± 0.2). These findings indicate that either judges perceive horses to have a better rideability when they readily offer a more extreme poll flexion, or that riders make use of horses’ better rideability by imposing a more extreme poll flexion. Several of the above described associations, but also of the non-existing links (e.g. no association between shying or heart rate and temperament) between behaviour patterns and scores for personality traits are rather surprising, warranting further investigation regarding the underlying causes of these relationships. Some of these behaviour patterns should be considered when redesigning the current guidelines for evaluation of personality traits during breeding horse performance tests, ultimately leading to improved genetic selection for equine personality traits. However, ethical implication of defining aversive behaviour such as head-tossing as an indicator of, for example, poor temperament, should not be neglected when devising new guidelines: such aversive behaviour may in fact be an indication of inadequate training techniques rather than poor horse personality.