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Record W1818659155 · doi:10.1071/cp15069

Timing and rates of nitrogen fertiliser application on seed yield, quality and nitrogen-use efficiency of canola

2016· article· en· W1818659155 on OpenAlexafffundabout
B. L., Aruna Herath

Bibliographic record

VenueCrop and Pasture Science · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNitrogen and Sulfur Effects on Brassica
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaCanola Council of Canada
KeywordsCanolaMonogastricYield (engineering)AgronomyBrassicaNitrogenCropField experimentRuminantNitrogen balanceAnimal scienceBiologyMathematicsChemistry

Abstract

fetched live from OpenAlex

Effective management strategies for nitrogen (N) fertiliser are important to ensure optimum seed yields and seed quality of canola (Brassica napus L.) crop production. A field experiment was conducted for 3 years in Ontario, Canada to determine the (i) impact of different rates and timing of application of N fertiliser on canola yield and quality; and (ii) fertiliser-N economy, including agronomic N-use efficiency (aNUE), N-uptake efficiency (NupE), N-utilisation efficiency, partial N balance and N harvest index. Treatments included factorial combinations of six (2011) or eight (2012 and 2013) rates of N as urea (46% N) and timing of application (pre-plant only or preplant plus side-dressed applications at the 6-leaf stage). Side-dressed N application resulted in significant improvements in seed yield and protein concentrations (up to 16%) over equivalent preplant-only applications. The highest seed yield (2700 kg ha–1 in 2011 and 3500 kg ha–1 in 2013) was produced by the treatments including side-dressing: 50 + 50 kg N ha–1 or 50 + 100 kg N ha–1 (preplant + side-dressing). Seed protein concentrations varied from 21% to 23% in 2011 and 2013 and up to 28% in 2012. On average, the sum of protein and oil concentrations was 65–68%. Oil yield increased with increasing N rates in 2011 and 2013, but significant increases were recorded only when N was side-dressed at the 6-leaf stage. Drought conditions in 2012 negated responses to N fertiliser regardless of when it was applied. In general, aNUE and N-utilisation efficiency were decreased with increasing N fertiliser rates, but NupE varied among environments with increasing preplant and side-dressed N application. Side-dressed N applications after preplant application resulted in higher partial N balance, aNUE and/or higher NupE than comparative preplant-only N applications. Overall, side-dressed N application led to improved crop N uptake and better N economy of canola production in eastern Canada.

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 score0.172
Threshold uncertainty score0.341

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 head0.020
GPT teacher head0.289
Teacher spread0.268 · 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

Citations84
Published2016
Admission routes3
Has abstractyes

Explore more

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