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Record W4281777443 · doi:10.1093/tas/txac074

Environmental performance of commercial beef production systems utilizing conventional productivity-enhancing technologies

2022· article· en· W4281777443 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTranslational Animal Science · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsAlberta Health ServicesAgriculture and Agri-Food CanadaUniversity of ManitobaCanadian Science Centre for Human and Animal Health
FundersAgriculture and Agri-Food CanadaBeef Cattle Research Council
KeywordsProductivityProduction (economics)BusinessEnvironmental scienceAgricultural engineeringEngineeringEconomics

Abstract

fetched live from OpenAlex

Abstract The objective of this study was to evaluate the effects of using conventional productivity-enhancing technologies (PETs) with or without other natural PETs on the growth performance, carcass traits, and environmental impacts of feedlot cattle. A total of 768 cross-bred yearling steers (499 ± 28.6 kg; n = 384) and heifers (390 ± 34.9 kg; n = 384) were offered a barley grain-based basal diet and divided into implanted or non-implanted groups. Steers were then allocated to diets that contained either: (i) no additive (control); natural feed additives including (ii) fibrolytic enzymes (Enz), (iii) essential oil (Oleo), (iv) direct-fed microbial (DFM), (v) DFM + Enz + Oleo combination; conventional feed additives including (vi) Conv (monensin, tylosin, and beta-adrenergic agonists [βAA]); or Conv with natural feed additives including (vii) Conv + DFM + Enz; (viii) Conv + DFM + Enz + Oleo. Heifers received one of the first three dietary treatments or the following: (iv) probiotic (Citr); (v) Oleo + Citr; (vi) Melengesterol acetate (MGA) + Oleo + βAA; (vii) Conv (monensin, tylosin, βAA, and MGA); or (viii) Conv + Oleo (ConvOleo). Data were used to estimate greenhouse gas (GHG) and ammonia (NH3) emissions, as well as land and water use. Implant and Conv-treated cattle exhibited improvements in growth and carcass traits as compared to the other treatments (P < 0.05). Improvements in the performance of Conv-cattle illustrated that replacing conventional feed additives with natural feed additives would increase both the land and water required to satisfy the feed demand of steers and heifers by 7.9% and 10.5%, respectively. Further, GHG emission intensity for steers and heifers increased by 5.8% and 6.7%, and NH3 emission intensity by 4.3% and 6.7%, respectively. Eliminating the use of implants in cattle increased both land and water use by 14.6% and 19.5%, GHG emission intensity by 10.5% and 15.8%, and NH3 emission intensity by 3.4% and 11.0% for heifers and steers, respectively. These results demonstrate that the use of conventional PETs increases animal performance while reducing the environmental impacts of beef production. Restricting use would increase the environmental footprint of beef produced for both domestic and international markets.

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.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.218
Teacher spread0.206 · 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