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Record W1979371846 · doi:10.4141/a02-015

Effect of diet on odorant emissions from cattle manure

2002· article· en· W1979371846 on OpenAlexaffvenue
S. M. McGinn, K. M. Koenig, Trevor Coates

Bibliographic record

VenueCanadian Journal of Animal Science · 2002
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsManureFeedlotSilageAmmoniaAgronomyStrawAnimal scienceDistillers grainsChemistrySoybean mealBiologyBiochemistry

Abstract

fetched live from OpenAlex

Ammonia loss from livestock manure is of special concern because it contributes to odour, can impact non-targeted environments through atmospheric deposition, and represents a potential loss of available nitrogen in manure used as fertilizer for crop growth. Our study investigated the effect of three barley-based diets on manure composition and the emissions of ammonia and volatile fatty acids (VFA) from beef feedlot manure. The results of our study suggest that the metabolizable protein requirements of heavyweight feedlot cattle (400 to 550 kg) were met when finished on a barley grain and barley silage diet [12.9% crude protein (CP)]. Therefore, the ability to reduce total N content of manure or manipulate the route of N excretion is limited, unless lower protein ingredients, such as corn silage or cereal straw, were incorporated into the diet to lower the basal diet CP concentration. There was no relationship between protein level and animal weight gain in our study. There was a positive relationship (P < 0.05) between level of intake protein and ammonium-N content of the surface-sampled pen manure. However, chamber data suggested that the higher ammonium-N content of manure did not translate to any significant difference in ammonia emissions, although the lowest emission rate for surface manure coincided with the lowest protein level. There was also no significant difference in VFA emission related to diet treatments. Key words: Ammonia, volatile fatty acid, odour intensity, cattle, manure, diet

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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 designBench or experimental
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

Citations18
Published2002
Admission routes2
Has abstractyes

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