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Record W1991207563 · doi:10.1614/ws-08-090.1

Validation of a Management Program Based on A Weed Cover Threshold Model: Effects on Herbicide Use and Weed Populations

2009· article· en· W1991207563 on OpenAlexaff
Marie‐Josée Simard, B. Panneton, Louis Longchamps, Claudel Lemieux, Anne Légère, Gilles Leroux

Bibliographic record

VenueWeed Science · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsBC Research (Canada)Université LavalAgriculture and Agri-Food Canada
Fundersnot available
KeywordsWeedWeed controlAgronomyCover cropWeed scienceGlyphosateCropBiology

Abstract

fetched live from OpenAlex

Weed management decisions based on weed threshold models offer the opportunity to reduce herbicide use by allowing the possibility of forgoing treatment or lowering rates. Weed thresholds based on a relative leaf-cover model were tested during a 4-yr period at two locations. Two 1.62-ha fields, planted to conventional and glyphosate-resistant corn (2004, 2005, 2007) or soybean (2006), were divided in 900 m2sections. Herbicides were applied postemergence to each of these sections with either variable rates based on weed thresholds, or constant full rates. Variable herbicide rates included: no application, half rate, or full rate. Relative weed cover values of 0.2 and 0.4 (corn) or 0.1 and 0.3 (soybean) served as thresholds for incremental rates. Digital images were used to evaluate the relative weed cover. Weed density was assessed before and after herbicide application. Weed seed production was estimated for two species in 2004 and 2005. No difference in crop yield, relative weed cover, weed density, or weed seed production was observed between conventional and glyphosate-resistant cropping systems. During the first year, herbicide use reduction was obtained (−85.4%) with marginal crop yield loss (5 to 15%). In the subsequent 3 yr, preherbicide weed densities increased and concomitant increases in relative weed cover values did not allow more than a 10% overall reduction in herbicide use. This threshold model designed to maintain crop yields within a given year did not allow significant reduction in herbicide use during the following 3 yr. Residual weed populations most likely replenished the seed bank to levels that allowed weed densities to increase afterward. Increased weed density over time in plots treated with full rates of herbicide every year also indicated that a single postemergence herbicide treatment was not sufficient to contain weed populations at low levels every year in this corn–soybean rotation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.267
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations16
Published2009
Admission routes1
Has abstractyes

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