Search

The aim of the study was to demonstrate correlation between selected body condition indices of roe deer Capreolus capreolus (KFI, carcass weight) and the health status of the carcass (i.e. pathological changes found through external and internal examination of the carcass) of deer killed by hunting or road traffic. The study material consisted of 34 carcasses of roe deer found dead due to road collisions or obtained through hunting in accordance with the Principles of Individual and Population Selection of Game Animals in Poland. The results showed a significant correlation between the occurrence of disease signs (especially the presence of parasites) and the mean values of indices describing the individual condition of animals (carcass weight, KFI). This confirms that the preliminary examination of game harvested and animals killed by road collisions plays an important role in inhibiting the spread of epizootic diseases and in assessing the individual condition of animals.

We developed an algorithm to classify brown hares into two age classes, juveniles (up to 1 year old) and adults (over 1 year old), based on body weight, which can be determined by both the examination of live animals and postmortem analysis. Considering the strong correlation between lens weight and carcass weight, we assumed that hares could be classified into one of the two age groups based only on carcass weight, using a logistic regression model. Using logistic regression, a model was constructed to assess the age of hares based on their body weight. For comparison with the current age-assessment method based on the dry lens weight, a logistic regression classifying the hares based on the dry lens weight was performed as well. The results of the study facilitated the development of a method to classify hares into age groups based on body weight. The proposed approach is innovative, as it allows for the determination of the age of not only culled (postmortem) but also live hares. The method is easy and does not require laboratory tests; hence, the results can be used immediately following evaluation. This method allows hares to be categorized into two age groups (juveniles and adults). With an accuracy of 97.52% and 95.45% in the case of juvenile and adult hares, respectively, the proposed approach can be widely used both in population management and scientific research.