ReviewJournal of animal science2025
Galyean Appreciation Club review: knowledge gaps in the nutrition of grazing beef cattle.
Review in Journal of animal science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Developing a Decision-Support Tool to Improve the Performance and Sustainability of Cow-Calf Grazing Systems Using Satellite Remote Sensing and Mechanistic Nutrition Models.Animals : an open access journal from MDPI · 2026Article
- Effects of cow efficiency phenotype on performance, energy partitioning, ultrasound carcass composition, and gas exchange during gestation and lactation.Translational animal science · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Feeding the increasing world population is a grand challenge for animal agriculture. Ruminants in general, and beef cattle specifically, fill a unique role in addressing this challenge as they convert large quantities of forage-based feed resources, which are inedible by humans, into high-quality, nutrient food products for human consumption. In North American beef cattle production systems, grazed forage represents a large portion of whole-herd dietary intake. In fact, within the United States, approximately 57% of the feed energy required to produce 1 kg of beef carcass weight is derived from grazing systems, and another 19% of feed energy is provided by harvested forage sources. Nutritional management of grazing beef herds is a critical component of efficient and effective production systems. Understanding nutrient supply and demand fosters more precise approaches to strategic supplementation practices. Limited source data from grazing beef cattle constrain modeling approaches of nutrient supply and demand and consequently limit our ability to nutritionally manage grazing beef cattle. Reviewing the available data exposes numerous knowledge gaps in the nutrition of grazing beef cattle. Needs include more robust source data collection and data collection technologies in the specific areas of intake, macro and micronutrient supply and demand, and nutrient demands associated with environmental extremes and physical activity. Additionally, more accurate and precise mathematical models are needed in the area of intake, energy, protein, and micronutrient supply and demand. In addition, coupling investigations of grazing livestock nutrition with behavior, climate, land use, socioeconomic, and sustainability needs will foster a more holistic understanding of the importance of accurately assessing and managing grazing cattle nutrition. Extensive opportunities exist to improve grazing livestock nutrition and consequently enhance sustainable capture of grazed forage nutrients and improved beef cattle production from grazing lands; however, limited funding streams to support these research efforts limit progress.
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What OpenQuestion holds
Registered trials
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.