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Record W2030027511 · doi:10.2134/agronj2011.0342

Spring Wheat Yield and Quality Related to Soil Texture and Nitrogen Fertilization

2012· article· en· W2030027511 on OpenAlexafffundabout
Judith Nyiraneza, Athyna N. Cambouris, Noura Ziadi, Nicolas Tremblay, Michel C. Nolin

Bibliographic record

VenueAgronomy Journal · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsNational Association of Friendship CentresAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsSowingAgronomyNitrogenTest weightHuman fertilizationYield (engineering)Animal scienceSoil textureGrowing seasonGrain yieldChemistrySoil waterBiologyMaterials science

Abstract

fetched live from OpenAlex

Efficient N fertilization is crucial for economic wheat ( Triticum aestivum L.) production and is of great agronomical and environmental significance. A study was conducted at 12 site‐years in eastern Canada to evaluate the effect of soil surface textural groups, N rate (0–200 kg N ha −1 ) and application timing on grain yield (GY), N uptake, nitrogen uptake efficiency (NUE), grain protein content (GPC), test weight, and thousand kernel weight (TKW). Chlorophyll meter readings (CMR) were taken at tillering and at flowering to assess in‐season wheat N nutrition. Fertilization and soil textural group effects were significant on all measured parameters and their interaction was significant on GPC, TKW, test weight, and CMR. Total N uptake and GPC ranged from 39 to 96 kg N ha −1 and from 13 to 18 g kg −1 , respectively, and total N uptake increased proportionally to N rates. Applying N levels >120 kg N ha −1 did not increase total yield, test weight, TKW, or CMR values. The variation in GY, N uptake, and GPC explained by the relative CMR taken at flowering was 87, 88, and 73%, respectively. This study demonstrates that in‐season wheat N nutrition can be monitored by CMR and that surface soil texture is an important parameter that influences wheat N response and wheat quality parameters. Applying half of the recommended rate (120 kg ha −1 ) at planting and the rest at tillering resulted in a high total yield, high grain N uptake, and the highest GPC price premium.

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 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 score0.083
Threshold uncertainty score0.287

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.033
GPT teacher head0.247
Teacher spread0.214 · 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 teacher head, 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

Citations46
Published2012
Admission routes3
Has abstractyes

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