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

• Published in: Computers and electronics in agriculture Vol. 179; p. 105855
• Main Authors: Cairo, F.C., Pereira, L.G.R., Campos, M.M., Tomich, T.R., Coelho, S.G., Lage, C.F.A., Fonseca, A.P., Borges, A.M., Alves, B.R.C., Dorea, J.R.R.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.12.2020; Elsevier BV
• Subjects: Accuracy; agriculture; Algorithms; Animal behavior; Artificial insemination; Artificial neural network; Artificial neural networks; Bins; Computer vision; Drinking water; electronics; estrus; estrus detection; Evaluation; feed intake; Feeds; Generalized linear models; Heat detection; Holstein; Learning theory; Machine learning; Model accuracy; neural networks; Precision livestock; prediction; Random forest; Statistical models; Time series; time series analysis; Vision systems; Windows (intervals); Precision livestock; Random forest; Artificial neural network; Heat detection; Machine learning

•Earlier and automated detection of estrus can improve on-farm decisions.•Estrus events altered feeding and drinking behavior pattern and feed intake.•Behavioral data generated by electronic bins have not been explored for estrus detection.•Machine learning algorithms were applied to feeding behavio...