Objective discrimination of fur type based on electrophoresis optimized for fur-hair proteins.

Abstract

The accurate identification of animal species used for fur is important for conserving endangered animals, stopping illegal fur distribution, and addressing consumer concerns. Animal species used for fur are currently differentiated by observing species-specific morphological fur-hair features through a microscope. Although this method is simple, the results may differ among inspectors owing to its subjective nature. To develop an objective approach for differentiating animal species based on fur, we utilized the electrophoretic patterns of fur-hair proteins. First, we optimized protein extraction methods to produce clear electrophoretic patterns from fur-hair proteins. Then, we obtained 324 electrophoretic patterns from 54 fur samples belonging to 24 different animals; 216 of the 324 patterns were used for the construction of a discrimination model using two-way orthogonal partial least squares discriminant analysis. The model correctly discriminated between all the remaining 108 patterns without any false negatives or positives. Moreover, this model could discriminate between fur samples from closely related species that are difficult to distinguish using conventional microscopic identification because of the visual similarity of the fur hairs.