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Record W2886936150 · doi:10.1139/cjss-2018-0049

Optimizing combining green manures and pelletized manure for organic spring wheat production

2018· article· en· W2886936150 on OpenAlexafffundvenue
Md. Zahangir Alam, Derek H. Lynch, Gilles Tremblay, Rosalie Gillis-Madden, Anne Vanasse

Bibliographic record

VenueCanadian Journal of Soil Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsNova Scotia Department of AgricultureUniversité LavalMinistère de l'Agriculture, des Pêcheries et de l'AlimentationDalhousie University
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsGreen manureAgronomyRed CloverLegumeManureChemistryYield (engineering)MathematicsBiology

Abstract

fetched live from OpenAlex

Well-planned crop rotations and targeted use of organic amendments are critical to success in organic wheat production. The impact of green manure (GMr) type, GMr termination timing, and “Acti-Sol” [pelletized dehydrated poultry manure (DPM); 5-2-3] on organic wheat productivity and quality was evaluated from 2014 to 2016 in Truro, NS, and Saint-Mathieu-de-Beloeil, QC. Crops prior to wheat were soybean or GMr of hairy vetch/oat (HVO), common vetch/oat (CVO), and red clover (RC) (NS site), and HVO, red clover/oat (RCO), and oat (QC site). Trials were split-split-plot designs with treatments of precrops, GMr termination (fall vs. spring), and DPM at 0, 40, 80, and 120 kg total N ha −1 . Wheat yields ranged from 1500 to 1800 kg ha −1 if unfertilized with DPM and following soybean or oat precrops. All legume GMrs (HVO, CVO, and RC/RCO) and DPM applications increased grain yield (2000–4200 kg ha −1 ) and protein content (13%–16%), wheat total N uptake [49–60 kg N ha −1 (QC); 87–125 kg N ha −1 (NS)] and soil mineral N content mid-season and postharvest, and responses were consistently greatest following HVO. Timing of GMr incorporation largely had no impact. Applying DPM at 80 kg N ha −1 was an effective substitute for a GMr precrop.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.991

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.224
Teacher spread0.200 · 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 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

Citations11
Published2018
Admission routes3
Has abstractyes

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