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Record W7010666335

Inhibition of nitrification and effects on N2O and CO2 emissions estimated using the flux gradient method from agricultural soils in Southern Manitoba

2024· dissertation· en· W7010666335 on OpenAlexfundaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2024
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaWestern Grains Research Foundation
KeywordsNitrificationSoil waterLoamFertilizerAmmoniaNitrogenUrea
DOInot available

Abstract

fetched live from OpenAlex

Nitrification inhibitors reduce the emissions of nitrous oxide (N2O) from agricultural soils treated with ammoniacal nitrogen fertilizers. Most studies to date, and all for Manitoba, have examined the benefits of nitrification inhibitors on N2O emissions using soil chambers. Here, N2O emissions were monitored using the flux gradient method, and the effect of nitrification inhibition of spring-applied nitrogen fertilizers on clay and loam farm fields near Glenlea and Clearwater, Manitoba, respectively, was examined. Established since 2005, the Trace Gas Manitoba (TGAS-MAN) research site on a clay field was used to examine the effect of the nitrification inhibitor, eNtrenchTM, coated urea in 2022 and the nitrification and urease inhibitor, SuperUTM, in 2023. The TGAS-MAN site utilized two 4-ha fields for each inhibited and uninhibited fertilizer treatment, all seeded to spring wheat (Triticum aestivum L.) in 2022 and canola (Brassica napus L.) in 2023. A new flux gradient installation was established on the loam field, Trace Gas Harvest Moon (TGAS-HM). This site utilized one 4-ha field of anhydrous ammonia treated with the nitrification inhibitor, Centuro®, and one of uninhibited anhydrous ammonia planted to grain corn (Zea mays L.). In 2022, soil moisture and high air temperature and humidity challenged fertilizer flow through operational machinery and an evaluation on the inhibition of nitrification and N2O emissions. In 2023, SuperU reduced cumulative (Jan 1st – Dec 31st) N2O emissions by 1,786.1 kg CO2-eq ha-1 compared to conventional urea. Both treatments lost approximately 6,200 kg CO2-eq ha-1 in 2022, compared to 2023 where SuperU lost 1,774 kg CO2-eq ha-1 and conventional urea lost 4,224 kg CO2-eq ha-1. Growing season (May 1st – Oct 13th) cumulative N2O emissions for anhydrous ammonia was 1.4 kg N2O-N ha-1 and, contrary to expectation, 1.8 kg N2O-N ha-1 for the Centuro® treatment. Across both research sites and study years, differences in treatment grain yield were not statistically significant. Study findings highlight greater N2O emissions for clay than loam soils in Manitoba, the challenges of coating urea with nitrification inhibitors for commercial purposes, employing the flux gradient method to observe a reduction in N2O emissions using SuperUTM, and the surprising ineffectiveness of a new nitrification inhibition product, Centuro®, to reduce N2O emissions.

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)0.000
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 score0.259
Threshold uncertainty score0.521

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.020
GPT teacher head0.226
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

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

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

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