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Record W2075802402 · doi:10.2134/agronj2013.0357

Seed Safety Limits for Cereals and Canola Using Seed‐Placed ESN Urea Fertilizer

2014· article· en· W2075802402 on OpenAlexafffundabout
Shuhao Qin, F. Craig Stevenson, Ross H. McKenzie, Brian L. Beres

Bibliographic record

VenueAgronomy Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicPolymer-Based Agricultural Enhancements
Canadian institutionsAgriculture Food and Rural DevelopmentAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsCanolaUreaCoated ureaAgronomyFertilizerSeed treatmentNitrogen fertilizerNitrogenAnimal scienceHorticultureChemistryBiology

Abstract

fetched live from OpenAlex

Environmentally Smart Nitrogen (ESN) (Agrium, Calgary, AB) is a polymer‐coated form of urea N that provides controlled‐release, allowing higher seed‐placed safe rates. Field studies were conducted from 2009 to 2012 near Lethbridge, AB, Canada, to determine how upper limits of seed safety using seed‐placed ESN in cereals and canola change with increased N rates and alterations to the coating integrity of ESN. Alterations to the coating integrity of ESN were created in the laboratory (consistent within an incremental range of 20 to 80% N release after 7 d immersion in 23°C water) and then arranged in a factorial combination with five rates (30, 45, 60, 75, and 90 kg N ha−1) of the seed‐placed ESN lots and urea (100% N release). Low N release rates (20–40%) were important for all three crops and increased the safe rate of seed‐placed ESN to the optimum range of 60 to 90 kg N ha−1 for spring cereals and 60 kg N ha−1 for canola. This confirms three times the safe rate of urea (observed at 30 kg N ha−1 for cereals) can be seed‐placed and achieve N sufficiency for spring wheat in one operation. Canola stand establishment was negatively affected by greater N release and rates. However, reductions to canola yield were modest (5%) unless ESN was replaced with urea, which reflects its greater compensatory response to stand thinning. Results from this study confirm the substitution of urea with ESN allows 3× rates of seed‐placed N provided N release was ≤40%, which is readily achieved through proper handling.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.013
GPT teacher head0.219
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 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

Citations9
Published2014
Admission routes3
Has abstractyes

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