Logistic Regression Model for Determination of the Age of Brown Hare (Lepus europaeus Pall.) Based on Body Weight

Abstract

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.

Analysis of Morphological Traits, Mineralization, and Mechanical Properties of Femoral Bones in Young and Adult European Hares (Lepus europaeus)

“…Youngs are those born in the same year as the hunting season; therefore, young hares are those born between March and August of the same year. Adult hares refer to those born in the previous year or earlier, as the typical survival period for individuals of this species does not exceed 3 years [ 18 ]. The first shot individuals that met the criteria for age and sex were used for the study ( n = 24), ensuring random sampling.…”