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Record W2743277088 · doi:10.2134/jeq2017.03.0106

Combining Urease and Nitrification Inhibitors with Incorporation Reduces Ammonia and Nitrous Oxide Emissions and Increases Corn Yields

2017· article· en· W2743277088 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.

Bibliographic record

VenueJournal of Environmental Quality · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsUreaseVolatilisationChemistryAmmoniaNitrificationAmmonia volatilization from ureaUreaNitrous oxideAnimal scienceFertilizerAmmoniumNitrateNitrogenAgronomyEnvironmental chemistryBiochemistryBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Less than 50% of applied nitrogen (N) fertilizer is typically recovered by corn ( Zea mays L.) due to climatic constraints, soil degradation, overapplication, and losses to air and water. Two application methods, two N sources, and two inhibitors were evaluated to reduce N losses and enhance crop uptake. The treatments included broadcast urea (BrUrea), BrUrea with a urease inhibitor (BrUrea+UI), BrUrea with a urease and a nitrification inhibitor (BrUrea+UI+NI), injection of urea ammonium nitrate (InjUAN), and injected with one or both inhibitors (InjUAN+UI, InjUAN+UI+NI), and a control. The BrUrea treatment lost 50% (64.4 kg N ha −1 ) of the applied N due to ammonia volatilization, but losses were reduced by 64% with BrUrea+UI+NI (23.0 kg N ha −1 ) and by 60% with InjUAN (26.1 kg N ha −1 ). Ammonia losses were lower and crop yields were greater in 2014 than 2013 as a result of the more favorable weather when N was applied in 2014. When ammonia volatilization was reduced by adding a urease inhibitor, N 2 O emissions were increased by 30 to 31% with BrUrea+UI and InjUAN+UI compared with BrUrea and InjUAN, respectively. Pollution swapping was avoided when both inhibitors were used (BrUrea+UI+NI, InjUAN+UI+NI) as both ammonia volatilization and N 2 O emissions were reduced, and corn grain yields increased by 5% with BrUrea+UI+NI and by 7% with InjUAN+UI+NI compared with BrUrea and InjUAN, respectively. The combination of two N management strategies (InjUAN+UI+NI) increased yields by 19% (12.9 t ha −1 ) compared with BrUrea (10.8 t ha −1 ). Core Ideas Ammonia volatilization resulted in 50% loss of applied urea over 2 yr. When urease inhibitors were added with urea, ammonia volatilization was reduced by 64%. Injection of UAN reduced ammonia volatilization by 60% compared with broadcast urea. N 2 O emissions were increased by 30 to 31% when urease inhibitors were applied. Pollution swapping was avoided when both urease and nitrification inhibitors were used.

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)0.000
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 score0.273
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.252
Teacher spread0.232 · 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