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Record W4388540032 · doi:10.1093/jas/skad281.155

207 Effect of Sodium Sulfate in Water and Dietary Bismuth Subsalicylate on Feed and Water Intake, Ruminal Hydrogen Sulfide Concentration, and Trace Mineral Status of Growing Beef Heifers

2023· article· en· W4388540032 on OpenAlexaff
Mikaela G Evans, John Campbell, Gabriel O Ribeiro, Darren D Henry, Cheryl Waldner, Greg B Penner

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAnimal scienceChemistrySulfateDry matterBeef cattleForageAgronomyBiology

Abstract

fetched live from OpenAlex

Abstract Cattle consuming increased concentrations of sulfur (S) are at an increased risk for depletion of copper (Cu) and or S-induced polioencephalomalacia and there are limited mitigation strategies to alleviate risk for cattle consuming high sulfate water. This study evaluated the effects of feeding growing beef heifers bismuth subsalicylate (BSS; 0.0 vs. 0.4% DM basis) when provided water with a low (LS; 346 ± 13) or high (HS; 4,778 ± 263 mg/L) sulfate concentration on dry matter intake (DMI), water intake, ruminal hydrogen sulfide (H2S) concentration, and trace mineral status. Twenty-four beef heifers (221 ± 41 kg) were stratified based on initial liver copper concentrations collected 13 d before the start of the study, into a completely randomized block design using a high forage diet fed for 98 d. Feed and water intake (weekly), ruminal H2S concentration (d 42 and 91), and liver (pre-study and d 91) and serum trace mineral concentrations (d 1, 28, 56, and 91) were evaluated. Initial liver trace-mineral concentration was used as a covariate in the statistical model. Water intake tended to be reduced with the inclusion of BSS (P = 0.10) but was not affected by water sulfate (P = 0.40). Water sulfate and BSS did not affect DMI (P ≥ 0.89), but total S intake increased (P < 0.01) from LS to HS (17.6 to 51.0 g/d) resulting in diets that contained 0.28 and 0.78% S (DM basis). Heifers consuming HS had 1.58 µg/mL more (P < 0.01) ruminal H2S than LS. The inclusion of BSS reduced (P = 0.04) ruminal H2S concentration by 46%. Regardless of water sulfate concentration, heifers fed BSS had lesser liver Cu (average of 4.08 mg/kg) than heifers not provided BSS, and when not provided BSS, HS had lesser Cu than LS (42.2 vs. 58.3; sulfate × BSS, P = 0.02). Serum concentration of Cu did not differ over time for heifers not provided BSS; whereas heifers provided BSS had less serum Cu on d 91 than d 28 and 55 (BSS × time, P < 0.01). The liver concentration of selenium (Se) was reduced (P < 0.01) with BSS inclusion. The Se concentration in serum was not affected by sulfate, BSS, or time (P ≥ 0.16). Bismuth subsalicylate reduces ruminal H2S concentration, but depletes liver Cu and Se. Moreover, sulfate concentration in water does not appear to affect DMI or water intake but reduces liver Cu concentration.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.249
Teacher spread0.230 · 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
Published2023
Admission routes1
Has abstractyes

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