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Record W2766340637 · doi:10.1139/cjps-2017-0184

Altering the competitiveness of tame oat (<i>Avena sativa</i> L.) versus wild oat (<i>Avena fatua</i> L.) with phosphorus and seeding rate

2017· article· en· W2766340637 on OpenAlexaffvenue
William E. May

Bibliographic record

VenueCanadian Journal of Plant Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsAvena fatuaAvenaSeedingAgronomyBiologyPhosphorusGrain qualityYield (engineering)CropChemistryGermination

Abstract

fetched live from OpenAlex

Currently, no in-crop herbicide is registered to control wild oat (Avena fatua L.) in tame oat (Avena sativa L.). Wild oat must be controlled in tame oat using other agronomic practices. The objective of this research was to determine if side-banded phosphorus (P) in combination with seeding rate would increase the competitiveness of tame oat with wild oat, increasing yield and quality. An experiment was conducted from 2003–2005 at Indian Head, SK. The experimental design was a strip-plot design with four replications. The strips were low and high wild oat density. A two-way factorial, seeding rate (150, 250, 350, and 450 plants m −2 ), and P rate (0, 15, and 30 kg P 2 O 5 ha −1 ) were seeded across the strips. Phosphorus affected seed density, grain yield, oat biomass, and wild oat fecundity. Seeding rate affected most of the measured variables and interacted with wild oat and year. The application of P increased the competiveness of oat by increasing crop biomass by 7.6% and grain yield by 3.4% and decreasing wild oat seed from 1.26% to 0.76% in the harvested grain. Wild oat decreased grain yield by 23% in 2003, 4.4% in 2004, and 11% in 2005. Increasing the seeding rate increased grain yield by 5% when wild oat was present. Wild oat did not interfere with the uptake of side-banded P. Producers need to use both P fertilization and higher seeding rates to improve the competitiveness of tame oat and the management of wild oat in tame oat.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.210
Teacher spread0.190 · 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.

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

Citations4
Published2017
Admission routes2
Has abstractyes

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