{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T18:59:42Z","timestamp":1790017182228,"version":"4.0.1"},"reference-count":69,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":243,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>High-quality drinking water is critical for efficient feedlot production. We performed a systematic review and meta-analysis of drinking water intake (DWI) of cattle in feedlots and developed and evaluated models that predict DWI against industry standard predictions. Three search engines were used to identify experiments that included DWI in feedlot cattle. Results of experiments were evaluated to ensure that these were: from peer-reviewed journals or theses published in English; in vivo and evaluated use of DWI in feedlot cattle; had appropriate study designs; had appropriate analysis of data; and contained data to determine the effect size for outcomes. Environmental and production measures were extracted, and temperature humidity index (THI) and heat load index (HLI) were calculated. A mixed model meta-regression with the random effects of experiment within study was used to evaluate the univariate effects of temperature, THI, HLI, body weight, dry matter intake, average daily gain, dry matter percentage of the diet, sex, and shade on DWI. Multivariable, multilevel models to predict DMI were constructed by backwards stepping separately for temperature and THI when average daily temperature is &amp;gt;12\u00b0C. Existing equations for DWI for feedlot cattle were evaluated and compared to the models developed in this study by Lin\u2019s concordance correlation coefficient \u03c1c, Pearson\u2019s correlation, and Bland and Altman\u2019s limits of agreement. Thirty-five studies with up to 131 experimental comparisons were included in the meta-analysis. The mean DWI was 31.2\u2009L\/d (SD = 4.31), mean temperature was 23.1\u00b0C (SD = 24.10), and temperature humidity index (THI) was 69.1 (SD = 9.62). Two models to predict DWI for feedlot cattle were developed, the first with temperature and body weight both independently predicting DWI (Root mean square error [RMSE]\u2009=\u20092.40\u2009L\/d) based on 20 studies and 75 experiments. The second model had THI and dry matter intake independently predicting DWI (RMSE = 2.83\u2009L\/d) based on 14 studies and 57 experiments. These models are consistent with estimates from other individual studies, but lower than those of the NRC. Drinking water intake decreased by 0.2\u2009liter for every 100\u2009mg\/L increase in water sulfate (SO4). Shade reduced DWI by 3.4\u2009L\/d. We provide updated robust estimates of changes in DWI for feedlot cattle with increases in environmental temperature, THI, body weight, and feed intake to guide industry in water resource allocation.<\/jats:p>","DOI":"10.1093\/jas\/skag263","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T14:44:45Z","timestamp":1788273885000},"source":"Crossref","is-referenced-by-count":0,"title":["Drinking water intake in feedlot cattle: a meta-analysis"],"prefix":"10.1093","volume":"104","author":[{"given":"Ian J","family":"Lean","sequence":"first","affiliation":[{"name":"Scibus , Camden, NSW 2570,","place":["Australia"]},{"name":"School of Life and Environmental Sciences, Faculty of Science, The University of Sydney , Camden, NSW 2570,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Helen M","family":"Golder","sequence":"additional","affiliation":[{"name":"Scibus , Camden, NSW 2570,","place":["Australia"]},{"name":"School of Life and Environmental Sciences, Faculty of Science, The University of Sydney , Camden, NSW 2570,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,9,1]]},"reference":[{"key":"2026092114005953000_skag263-B1","doi-asserted-by":"publisher","first-page":"4368","DOI":"10.1093\/jas\/sky267","article-title":"Environmental effects on water intake and water intake prediction in growing beef cattle","volume":"96","author":"Ahlberg","year":"2018","journal-title":"J Anim Sci"},{"key":"2026092114005953000_skag263-B2","doi-asserted-by":"publisher","first-page":"4770","DOI":"10.1093\/jas\/skz354","article-title":"Characterization of water intake and water efficiency in beef cattle","volume":"97","author":"Ahlberg","year":"2019","journal-title":"J Anim Sci"},{"key":"2026092114005953000_skag263-B3","doi-asserted-by":"publisher","first-page":"4213","DOI":"10.2527\/jas2017.1593","article-title":"Technical note: validation of an automated system for monitoring and restricting water intake in group-housed beef steers","volume":"95","author":"Allwardt","year":"2017","journal-title":"J Anim Sci"},{"key":"2026092114005953000_skag263-B4","author":"Animal Health Australia","year":"2014"},{"key":"2026092114005953000_skag263-B5","doi-asserted-by":"publisher","first-page":"245","DOI":"10.2527\/jas.2010-3014","article-title":"Environmental factors affecting daily water intake on cattle finished in feedlots","volume":"89","author":"Arias","year":"2011","journal-title":"J Anim Sci"},{"key":"2026092114005953000_skag263-B6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/ani13071150","article-title":"Pen surface temperature as a predictor of daily water intake and tympanic temperature in steers finished in feedlots","volume":"13","author":"Arias","year":"2023","journal-title":"Animals (Basel)"},{"key":"2026092114005953000_skag263-B7","first-page":"831","article-title":"Influence of breed and environment on DM digestibility, water-consumption, ruminal and blood parameters for Brangus and Angus steers","volume":"40","author":"Beaver","year":"1989","journal-title":"Nut. 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