Joao Ricardo Reboucas Dórea

Assistant Professor

University of Wisconsin-Madison

United States

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Joao Ricardo Reboucas Dórea is an Assistant Professor at the University of Wisconsin–Madison, USA. His research focuses on animal health, nutrition, and behavior, with recent publications that include analyses of bovine mammary gland development and automated disease detection models for dairy calves. He is also engaged in developing technologies for improving livestock management, such as solar-powered ventilation systems and biometric imaging for weight prediction in cattle.

Articles (18)

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2023

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Associate Professor

Michigan State University

UNITED STATES

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Joao Ricardo Reboucas Dórea

Research Interests

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Articles (18)

Longitudinal analysis of bovine mammary gland development

Increasing the prepartum dose of rumen-protected choline: Effects on milk production and metabolism in high-producing Holstein dairy cows

Feeding behaviors collected from automated milk feeders were associated with disease in group-housed dairy calves in the Upper Midwest United States

Use of Biometric Images to Predict Body Weight and Hot Carcass Weight of Nellore Cattle

Predictive models for disease detection in group-housed preweaned dairy calves using data collected from automated milk feeders

Image analysis to automatically classify anemia based on Famacha© score in sheep using ocular conjunctiva images

Actively ventilating calf hutches using solar-powered fans: Effects on hutch microclimate and calf thermoregulation

Using pseudo-labeling to improve performance of deep neural networks for animal identification

The quest to develop automated systems for monitoring animal behavior

Towards Smart Cattle Farms: Automated Inspection of Cattle Health with Real-Life Data

Applying machine learning techniques on feeding behavior data for early estrus detection in dairy heifers

Would large dataset sample size unveil the potential of deep neural networks for improved genome-enabled prediction of complex traits? The case for body weight in broilers

Image Analysis and Computer Vision Applications in Animal Sciences: An Overview

Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems

Comparison of data analytics strategies in computer vision systems to predict pig body composition traits from 3D images

Forecasting beef production and quality using large-scale integrated data from Brazil

Automated computer vision system to predict body weight and average daily gain in beef cattle during growing and finishing phases

Beef cattle responses to pre-grazing sward height and low level of energy supplementation on tropical pastures

Collaborators (5)

Guilherme J. M. Rosa

William Brown

Jennifer Van Os

Tiago Bresolin

Daniel Morris

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