Bayesian Linear Regression and Natural Logarithmic Correction for Digital Image-Based Extraction of Linear and Tridimensional Zoometrics in Dromedary Camels

This study evaluates a method to accurately, repeatably, and reliably extract camel zoo-metric data (linear tridimensional) from 2D digital images. Thirty zoometric measures, including linear tridimensional (perimeters girths) variables, were collected on-field with non-elastic measuring tape. A scaled reference was used measurement For girths perimeters, semimajor semiminor axes mathematically estimated the function of perimeter an ellipse. On-field measurements’ direct translation determined when Cronbach’s alpha (Cα) > 0.600 met (first round). If not, Bayesian regression corrections applied using live body weight particular as regressors (except for foot perimeter) (second Last, if certain trait still did not meet such criterion, its natural logarithm added (third Acceptable consistency reached all measurements after three correction rounds (Cα = 0.654 0.997, p < 0.0001). Afterwards, corrected equations issued. research helps evaluate individual conformation in reliable contactless manner through extraction measures images dromedary camels. is first develop correct routinely ignored evaluation zoometrics animals.