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Use of visual scores and biometric image in Nellore cattle

Grant number: 17/02057-0
Support type:Scholarships in Brazil - Master
Effective date (Start): August 01, 2017
Effective date (End): August 31, 2018
Field of knowledge:Agronomical Sciences - Animal Husbandry - Animal Production
Principal researcher:Otávio Rodrigues Machado Neto
Grantee:Alexandre Cominotte
Home Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
Associated scholarship(s):17/20812-0 - Prediction of body weight and hot carcass weight of Nellore cattle using digital images, BE.EP.MS

Abstract

The objective of this study is to evaluate the efficiency of using the visual scores of ANCP (National Association of Farmers and Researchers), the infrared light camera biometric images and the body measurements of sixty Nelore cattle and their correlation with performance, feed efficiency, carcass characteristics and meat quality. Evaluations of scores, body measurements and image collection will be performed at weaning, as well as during growing (at the beginning and at the end of rainy season) and at the end of feedlot. The experiment will be conducted at the Regional Technological Development Center of the Agribusiness of Alta Mogiana (PRDTA - Alta Mogiana), in Colina - SP. The hypothesis is that animals with different classifications for Visual Structure, Precocity and Muscle scores may present variations on performance, feed efficiency, carcass characteristics and meat quality, and that some biometric measurements may indicate the animals' body composition. Biometric images will be used to analyze the dorsal height, rump width, rib width, posterior width and dorsal area. Measurements obtained through the infrared light camera and body measurements will also be correlated with performance, feed efficiency, carcass characteristics and meat quality. In addition, a correlation will be made between these measures and body composition (especially percentage of EE and CP in the HH section). To measure the height of the withers, rump height, member's height, thoracic perimeter, body length, back length, rump length, rib depth, anterior width, rib width and posterior width, will be performed using a metric tape and hypometer, for correlation with visual scores and biometric images. The data will be analyzed using the statistical software SAS 9.1. For a better understanding of the relationship between the measurements and the performance, Pearson's correlation will be performed using the CORR procedure of SAS. The regressions will be evaluated using the Model Evaluation System (MES) software, version 3.1.15 (Texas A & M University, College Station, TX). (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
COMINOTTE, A.; FERNANDES, A. F. A.; DOREA, J. R. R.; ROSA, G. J. M.; LADEIRA, M. M.; VAN CLEEF, E. H. C. B.; PEREIRA, G. L.; BALDASSINI, W. A.; MACHADO NETO, O. R. Automated computer vision system to predict body weight and average daily gain in beef cattle during growing and finishing phases. LIVESTOCK SCIENCE, v. 232, FEB 2020. Web of Science Citations: 0.
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
COMINOTTE, Alexandre. Use of Biometric Images to Predict Body Weight and Hot Carcass of Nellore Cattle. 2018. Master's Dissertation - Universidade Estadual Paulista (Unesp). Faculdade de Ciências Agrárias e Veterinárias. Jaboticabal Jaboticabal.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.