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Record W4412827732 · doi:10.1016/j.spc.2025.07.009

Global analysis of nutritional strategies to mitigate the environmental impacts of dairy production: the case of supplementing diets with microencapsulated B vitamins

2025· article· en· W4412827732 on OpenAlexafffundabout
Prince Agyemang, Ebenezer Miezah Kwofie, Ludovic Lahaye, Melissa Otis, Victoria Asselstine, A. I. Payne, Greg Thoma

Bibliographic record

VenueSustainable Production and Consumption · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsCegep de Saint HyacintheMcGill University
FundersMitacsJefo Nutrition
KeywordsProduction (economics)Food scienceMilk productionBiotechnologyBusinessChemistryEconomicsBiologyAnimal scienceMicroeconomics

Abstract

fetched live from OpenAlex

Over the last decade, policymakers and dairy producers worldwide have faced the challenge of reducing the environmental impact of dairy production while continuing to meet societal needs for high-quality and nutritious protein sources. Given this, the objective of the present study was to assess the net environmental impact of adopting different nutrition strategies with and without supplementing rumen-protected B vitamins (RPBV, B vitamins that are microencapsulated to bypass rumen degradation in cows and be absorbed in the small intestines) in dairy milk production. Seven representative regional dairy production systems across the United States, Canada, Mexico, Chile, Colombia, Australia, and France were investigated, utilizing a total mixed ration (TMR) feeding program supplemented with 3 g of RPBV. The estimated climate change impact scores for all control production scenarios ranged from 1.08 to 1.65 kg CO 2 -eq/kg fat protein-corrected milk (FPCM). However, the impact of climate change per kg of FPCM decreased by 5.6–18.0 % when RPBV was supplemented on top of the TMR feeding program. The highest and lowest climate change impact reductions were observed for the RPBV production scenarios in Mexico and Colombia, where the impacts decreased from 1.65 to 1.36 kg CO 2 -eq/FPCM and from 1.49 to 1.41 kg CO 2 -eq, respectively. Additionally, the impacts of agricultural land use, water consumption, and acidification, as well as eutrophication potential, were reduced by 3.0–16.3 % (with an average reduction of 7.4 % across all scenarios) when the TMR feeding programs were supplemented with 3 g of RPBV. The observed impact reduction could be attributed to improvements in milk production, which varied across different regions, with milk yields ranging from 3.3 % to 19.4 % above those of the control production scenario. Additionally, there were reductions in enteric methane (up to 2.4 %) and nitrogen emissions (up to 10 %). In dairy cows, RPBV acts as an enzyme co-factor at the cellular level by improving the efficiency of key pathways involved in energy, fat, and protein metabolism, which consequently increases milk yield and feed efficiency. The manufacturing and transportation of RPBV to the seven regional destinations examined in the current study had a minimal impact on the total environmental footprint of dairy production systems. The null hypothesis was rejected, indicating significant differences in results, as the p-value for all impacts and pairs (control and RPBV scenarios per 500 Monte Carlo runs) was less than 0.05, which is considered statistically significant. Overall, supplementation with RPBV constitutes a valuable nutritional strategy to support ongoing efforts and innovations in driving sustainable dairy production.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.045
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.235
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 teacher head, 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

Citations1
Published2025
Admission routes3
Has abstractyes

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