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Record W6884637636 · doi:10.1139/cjss2013-118

Nitrogen application rate, timing and history effects on nitrous oxide emissions from corn (Zea mays L.)

2014· article· en· W6884637636 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNitrous oxideNitrogenGreenhouse gasFertilizerGrowing seasonSowingCropNutrient

Abstract

fetched live from OpenAlex

Roy, A. K., Wagner-Riddle, C., Deen, B., Lauzon, J. and Bruulsema, T. 2014. Nitrogen application rate, timing and history effects on nitrous oxide emissions from corn (Zea mays L.). Can. J. Soil Sci. 94: 563-573. Nitrous oxide (N2O) emissions resulting from application of nitrogen (N) fertilizer contribute to the greenhouse gas footprint of corn production. In eastern Canada, corn is a major crop with most N fertilizer applied pre- or at planting. This timing of application results in a lack of synchrony of soil N supply and crop N demand. Matching the amount and timing of application to crop uptake has been suggested as a mitigation measure to reduce N losses, and is an integral part of the 4R Nutrient Stewardship program. This study examined the effect of timing, rate and history of urea-ammonium nitrate application on N2O emissions in corn in 2011 and 2012 at Elora, ON, Canada. Treatments were three N rates (30, 145 and 218 kg N ha-1); two timings (N injected in mid-row at planting and at the 8th leaf stage, V8); two histories (short-term: applying N rate treatments on plots that had received 145 kg N ha-1 in the previous year, and long-term: applying the same N rate to a given plot over the duration of the trial). N2O emissions were measured using static chambers. History of N application did not have an effect on N2O emissions or grain yield. In both years, cumulative N2O emissions during the growing season and corn yields increased significantly with increasing N application rates. In 2011, cumulative N2O emissions were significantly lower when N was applied as side-dress at V8 (0.88 kg N ha-1) compared with planting (2.12 kg N ha-1), with no significant impact on corn grain yield (average 9.1 Mg ha-1). In contrast, in 2012, limited rainfall reduced both N2O emissions and corn grain yield, and neither N2O emission (average 0.17 kg N ha-1) nor grain yield (average 6.7 Mg ha-1) was affected by timing of N application. Applying N as side-dress at V8 instead of at planting and using the recommended N rate were shown to be effective N2O emission mitigation practices without affecting corn yield during a typical wet spring in Ontario.

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)0.001
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 score0.213
Threshold uncertainty score0.423

Distilled classifier scores by category (both heads)

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 communication0.0010.000
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 head0.140
GPT teacher head0.212
Teacher spread0.073 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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