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Record W2061946739 · doi:10.2134/agronj2005-0022

Slope Position, Nitrogen Fertilizer, and Fungicide Effects on Diseases and Productivity of Wheat on a Hummocky Landscape

2005· article· en· W2061946739 on OpenAlexaff
H. R. Kutcher, S. S. Malhi, K. S. Gill

Bibliographic record

VenueAgronomy Journal · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsFertilizerAgronomyFungicideBiomass (ecology)Yield (engineering)Field experimentProductivityGrain yieldNitrogenRandomized block designHorticultureBiologyMathematicsChemistry

Abstract

fetched live from OpenAlex

Precision agriculture technology allows growers to selectively apply inputs to different management units within a single field. A 4‐yr study consisting of a split‐split block experiment was conducted in the northern prairies to determine the effects of foliar fungicide (FU) and N fertilizer application to slope (SL) position based management units across a hummocky landscape on leaf spot and root diseases, biomass and seed yield, and seed quality of wheat ( Triticum aestivum L.). Fertilizer rates (0, 40, 80, and 120 kg N ha −1 ) were applied in strips across two SL positions (upper and lower) as main plots with FU application (treated and untreated) as subplots. Leaf spot diseases were consistently more severe on the upper than lower SL and reduced by FU treatment but varied inconsistently with changes in N rate. Biomass and seed yield in the two dry years were greater on the lower than upper SL. They were increased by FU treatment in 3 of 4 yr and N rate in 1 yr. Thousand‐kernel weight (TKW) and grain test weight (TW) were usually greater on the upper than lower SL, and TKW was increased by FU application in 2 yr. Protein content usually increased with increasing N rate, but the effect of SL and FU varied among years. The paucity of interactions among treatment factors indicated that selective application of FU and N fertilizer to SL position based management units for improvement of yield and seed quality was not warranted.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.156

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 head0.008
GPT teacher head0.201
Teacher spread0.193 · 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

Citations6
Published2005
Admission routes1
Has abstractyes

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