Evidence map›Paper›PMID 41723815›Full record

ArticleJournal of animal science2026

Characterization of individual beef cattle water intake.

Nathan E Blake, K E Arunkumar, Matthew Walker, Tylor J Yost, Domingo Mata-Padrino, Ida Holásková, Jarred W Yates, Duane Bishoff, Samanthia Johnson, Godstime Ayobami Taiwo and 4 more

Abstract read
In one paragraph

Article in Journal of animal science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Nathan E BlakeSchool of Agriculture and Food Systems, Davis College of Agriculture and Natural Resources, West Virginia University, Morgantown, WV 26506, United States.
K E ArunkumarSchool of Agriculture and Food Systems, Davis College of Agriculture and Natural Resources, West Virginia University, Morgantown, WV 26506, United States.
Matthew WalkerWest Virginia Agricultural and Forestry Experiment Station, Morgantown, WV 26506, United States.
Tylor J YostSchool of Agriculture and Food Systems, Davis College of Agriculture and Natural Resources, West Virginia University, Morgantown, WV 26506, United States.
Domingo Mata-PadrinoSchool of Agriculture and Food Systems, Davis College of Agriculture and Natural Resources, West Virginia University, Morgantown, WV 26506, United States.
Ida HoláskováWest Virginia Agricultural and Forestry Experiment Station, Morgantown, WV 26506, United States.
Jarred W YatesWest Virginia Agricultural and Forestry Experiment Station, Morgantown, WV 26506, United States.
Duane BishoffWest Virginia Department of Agriculture, Charleston, WV 25305, United States.
Samanthia JohnsonSchool of Agriculture and Food Systems, Davis College of Agriculture and Natural Resources, West Virginia University, Morgantown, WV 26506, United States.
Godstime Ayobami TaiwoSchool of Agriculture and Food Systems, Davis College of Agriculture and Natural Resources, West Virginia University, Morgantown, WV 26506, United States.
Modoluwamu IdowuSchool of Agriculture and Food Systems, Davis College of Agriculture and Natural Resources, West Virginia University, Morgantown, WV 26506, United States.
Ibukun OgunadeSchool of Agriculture and Food Systems, Davis College of Agriculture and Natural Resources, West Virginia University, Morgantown, WV 26506, United States.ORCID 0000-0003-3875-6156
Joseph HattonWest Virginia Department of Agriculture, Charleston, WV 25305, United States.
Matthew E WilsonSchool of Agriculture and Food Systems, Davis College of Agriculture and Natural Resources, West Virginia University, Morgantown, WV 26506, United States.ORCID 0000-0001-7419-6358

Funding

Enriched Ag and grant support from the USDA NRCS #68-3D47-15-10National Institute of Food and Agriculture, U.S. Department of Agriculture 1024859National Institute of Food and Agriculture, U.S. Department of Agriculture 1025826National Institute of Food and Agriculture, U.S. Department of Agriculture 738National Institute of Food and Agriculture, U.S. Department of Agriculture 743Reymann Memorial Farm and the Animal ScienceScientific Article 3477
6 · The paper itself

Abstract

Water intake (WI) in beef cattle is influenced by animal class, breed, production system, and environmental conditions, yet current models rely on limited, outdated data. We analyzed 130,000+ daily records of individual WI, dry matter intake (DMI), and body weight (BW) across 10 breeds from grazing and drylot systems over 5 yr. WI varied significantly by class (P < 0.001), with bulls consuming the most water (25.62 ± 0.03 L/d), followed by heifers (23.21 ± 0.07 L/d), and steers (21.83 ± 0.06 L/d), but heifers and steers had higher WI per 100 kg BW (P < 0.001). Breed effects were also significant (P < 0.001), with Red Angus and Limousin exhibiting the highest weight-adjusted WI. Drylot cattle drank more than grazing cattle (24.66 vs. 21.60 L/d; P < 0.001). WI increased with heat load; animals in THI ≥ 90 consumed 8.47 ± 0.03 L/100 kg BW compared to 5.53 ± 0.01 in THI < 72. However, relationships between WI and BW or DMI were weak (R2 = 0.06). These results challenge assumptions embedded in current recommendations (e.g., NASEM) and highlight the need for individualized, context-sensitive models. Our findings support future efforts in water-efficient selection, climate resilience, and sustainable beef production.

Indexed as

DrinkingAnimalsBody WeightCattleFemaleMalebeef cattlebody weightdry matter intakegrazingtemperature humidity indexwater intake

Identifiers

PMID41723815
PMCPMC13023050

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.