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

Carlos Iglesias Pastrana, Francisco Javier Navas González (), Elena Ciani, María Esperanza Camacho Vallejo and Juan Vicente Delgado Bermejo
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Carlos Iglesias Pastrana: Department of Genetics, Faculty of Veterinary Sciences, University of Córdoba, 14014 Córdoba, Spain
Francisco Javier Navas González: Department of Genetics, Faculty of Veterinary Sciences, University of Córdoba, 14014 Córdoba, Spain
Elena Ciani: Department of Biosciences, Biotechnologies and Biopharmaceutics, Faculty of Veterinary Sciences, University of Bari ‘Aldo Moro’, 70125 Bari, Italy
María Esperanza Camacho Vallejo: Andalusian Institute of Agricultural and Fisheries Research and Training (IFAPA), Centro Alameda del Obispo, Alameda del Obispo, 14004 Córdoba, Spain
Juan Vicente Delgado Bermejo: Department of Genetics, Faculty of Veterinary Sciences, University of Córdoba, 14014 Córdoba, Spain

Mathematics, 2022, vol. 10, issue 19, 1-24

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

Keywords: endangered breed; perimeters and circumferences; on-field measurements; mathematical modelling; software-assisted image analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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