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Record W2132610526 · doi:10.1079/ajaa200348

Agronomic performance and quality of spring wheat and soybean cultivars under organic culture

2003· article· en· W2132610526 on OpenAlexaffabout
H. G. Nass, J. A. Ivany, John Macleod

Bibliographic record

VenueAmerican Journal of Alternative Agriculture · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Prince Edward IslandAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCultivarAgronomyWeed controlManureWeedMineralization (soil science)CompostEnvironmental scienceGreen manureMoistureNutrientBiologySoil waterChemistry

Abstract

fetched live from OpenAlex

Abstract Spring milling wheat (Triticum aestivum L em. Thell) and soybean (Glycine max L.) cultivars were managed to International Organic Certification Standards on two organically certified farms to evaluate two physical weed control methods, cultivar performance and quality. Nutrients were supplied as manure and compost. There was no difference (P<0.05) between flaming plus fingerweeding versus fingerweeding twice, 10 days apart, on weed control, yield, and protein in both crops. The spring wheat cultivar, AC Barrie, may be particularly well suited to production under an organic system, as indicated by its superior performance to AC Walton at the Springfield site in 2000, when growth conditions were favorable. A severe drought in 2001 limited the mineralization of soil and manure nitrogen, with the result that all spring wheat cultivars at the Springfield site did not make 13.5% grain protein, required to meet milling quality criteria. Also, in 2001 at both sites, soybean yields were reduced by 50% compared to 2000 because of reduced moisture availability and weed competition. Delays in field operations, lack of sufficient soil moisture and reduced mineralization of manure during the 2001 growing season were major factors in influencing crop production, especially at Springfield.

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 score0.948
Threshold uncertainty score0.219

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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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

Citations22
Published2003
Admission routes2
Has abstractyes

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