{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T22:39:45Z","timestamp":1773441585045,"version":"3.50.1"},"reference-count":35,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2020,5,24]],"date-time":"2020-05-24T00:00:00Z","timestamp":1590278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Increased global temperatures and climatic anomalies, such as heatwaves, as a product of climate change, are impacting the heat stress levels of farm animals. These impacts could have detrimental effects on the milk quality and productivity of dairy cows. This research used four years of data from a robotic dairy farm from 36 cows with similar heat tolerance (Model 1), and all 312 cows from the farm (Model 2). These data consisted of programmed concentrate feed and weight combined with weather parameters to develop supervised machine learning fitting models to predict milk yield, fat and protein content, and actual cow concentrate feed intake. Results showed highly accurate models, which were developed for cows with a similar genetic heat tolerance (Model 1: n = 116, 456; R = 0.87; slope = 0.76) and for all cows (Model 2: n = 665, 836; R = 0.86; slope = 0.74). Furthermore, an artificial intelligence (AI) system was proposed to increase or maintain a targeted level of milk quality by reducing heat stress that could be applied to a conventional dairy farm with minimal technology addition.<\/jats:p>","DOI":"10.3390\/s20102975","type":"journal-article","created":{"date-parts":[[2020,5,25]],"date-time":"2020-05-25T11:42:02Z","timestamp":1590406922000},"page":"2975","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":69,"title":["Artificial Intelligence Applied to a Robotic Dairy Farm to Model Milk Productivity and Quality based on Cow Data and Daily Environmental Parameters"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0377-5085","authenticated-orcid":false,"given":"Sigfredo","family":"Fuentes","sequence":"first","affiliation":[{"name":"Digital Agriculture, Food, and Wine Group, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9207-9307","authenticated-orcid":false,"given":"Claudia","family":"Gonzalez Viejo","sequence":"additional","affiliation":[{"name":"Digital Agriculture, Food, and Wine Group, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2327-0946","authenticated-orcid":false,"given":"Brendan","family":"Cullen","sequence":"additional","affiliation":[{"name":"Agricultural Production System Modelling Group, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia"}]},{"given":"Eden","family":"Tongson","sequence":"additional","affiliation":[{"name":"Digital Agriculture, Food, and Wine Group, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1150-379X","authenticated-orcid":false,"given":"Surinder S.","family":"Chauhan","sequence":"additional","affiliation":[{"name":"Agricultural Production System Modelling Group, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3998-1240","authenticated-orcid":false,"given":"Frank R.","family":"Dunshea","sequence":"additional","affiliation":[{"name":"Agricultural Production System Modelling Group, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3722","DOI":"10.3168\/jds.2017-14025","article-title":"Invited review: Learning from the future\u2014A vision for dairy farms and cows in 2067","volume":"101","author":"Britt","year":"2018","journal-title":"J. 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