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Record W4417521665 · doi:10.1093/jas/skaf436

Nutritional composition of beef: a comparison of commercial North American grass- and grain-finishing systems

2025· article· en· W4417521665 on OpenAlexaff
Joseph Vinod Varre, Travis Statham, A. E. Smith, Muhammad Ahsin, Jennifer Cloward, Marina Carbonell Herrera, Camille Mittendorf, C. W. Crompton, Robert E. Ward, Tiffany‐Jane Evans, T. Bird, S Lyons, Amanda Pinelli, Dan Kittredge, Stephan van Vliet

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsBarrie Urology GroupGeorgian College
FundersAgricultural Research ServiceNational Institute of Food and AgricultureU.S. Department of AgricultureUtah State UniversityGrantham Foundation for the Protection of the EnvironmentGreenacres Foundation
KeywordsForagePolyunsaturated fatty acidGrazingFatty acidEicosapentaenoic acidSeleniumLinoleic acid

Abstract

fetched live from OpenAlex

Beef's fatty acid and mineral profile is influenced by finishing diets, yet the nutritional variability within both grass- and grain-fed beef samples from commercial operations remains underexplored. Understanding potential differences is important for producers and consumers. This study profiled grass- and grain-fed beef from commercial North American producers and retailers, and evaluated relationships among grazing practices, forage quality, soil characteristics, and beef fatty acid and mineral composition. Beef samples (grass-fed, n = 253; grain-fed, n = 84), along with forage and soil samples where possible, were collected from 108 commercial producers and retailers. Fatty acids were analyzed using gas chromatography-flame ionization detection (GC-FID), and minerals were quantified using inductively coupled plasma atomic emission spectroscopy (ICP-AES). Statistical models evaluated differences and correlations between and within finishing practices using Welch's t-test and Pearson's correlation analysis. Grass-fed beef had a lower omega-6:3 ratio (2.14 vs. 8.28, P < 0.001) and higher concentrations of the fatty acids alpha-linolenic acid (ALA; 0.99 vs. 0.27%), eicosapentaenoic acid (EPA; 0.28 vs. 0.07%), docosapentaenoic acid (DPA; 0.41 vs. 0.17%), conjugated linoleic acid (CLA; 0.49 vs. 0.31%), and the minerals calcium (9.26 vs. 3.08 mg/100 g), copper (0.253 vs. 0.129 mg/100 g), iron (2.29 vs. 1.92 mg/100 g), and selenium (0.012 vs. 0.002 mg/100 g) compared with grain-fed beef (all P < 0.05). However, considerable nutritional variation exists, particularly within grass-finished beef, with omega-6:3 ratios ranging from 0.62 to 11.45. Animals finished on biodiverse pastures exhibited fatty acid profiles characterized by higher omega-3 to total polyunsaturated FA content, resulting in a higher omega balance (r = 0.30, P = 0.02). However, some grass-fed samples, particularly several retail-purchased samples, displayed fatty acid compositions with relatively low omega-3 content, resulting in an omega balance similar to grain-fed beef. These findings highlight the need for clearer guidance on "grass-fed" management definitions and more transparent labeling that reflects measurable nutritional attributes, such as omega-3 content, omega-6:3 ratio, and/or omega balance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.297
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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