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Record W4386648556 · doi:10.5539/jas.v15n10p1

Tolerance of White Bean to Tiafenacil Herbicide Mixtures and Control of Multiple Herbicide-Resistant Horseweed With Tiafenacil Herbicide Mixtures

2023· article· en· W4386648556 on OpenAlexafffundvenueabout
Nader Soltani, Christy Shropshire, Peter H. Sikkema

Bibliographic record

VenueJournal of Agricultural Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Guelph
FundersOntario Agri-Food Innovation AllianceGrain Farmers of Ontario
KeywordsGlyphosateDicambaMetribuzinBromoxynilAgronomyBiologyHerbicide resistanceWeed controlYield (engineering)Biomass (ecology)

Abstract

fetched live from OpenAlex

There is limited information on the tolerance of white bean to tiafenacil herbicide mixtures applied preplant (PP) and the efficacy of tiafenacil herbicide mixtures applied PP to control multiple herbicide-resistant (MHR) horseweed. The objective aim of this research was to ascertain the tolerance of white beans to tiafenacil herbicide mixtures and determine if MHR horseweed control with tiafenacil can be improved by adding herbicide partners in a surrogate soybean crop. During 2021 and 2022 four experiments were performed to determine the tolerance of white bean to tiafenacil herbicide mixtures and five experiments were conducted to determine MHR horseweed control with tiafenacil mixtures in ON, Canada. All tiafenacil mixtures evaluated except those that included 2,4-D ester caused minimal (≤ 4%) white bean injury and had no adverse effect on white bean stand, dry biomass, height, maturity (as measured by seed moisture (SM) content at harvest), or yield. Glyphosate + tiafenacil + 2,4-D ester and glyphosate + tiafenacil + bromoxynil + 2,4-D ester caused up to 8% white bean injury but had no adverse effect on white bean stand, dry biomass, height, maturity, or yield. Glyphosate + tiafenacil or co-applied with bromoxynil, metribuzin, or 2,4-D controlled MHR horseweed 23-75%, reduced density up to 62% and reduced biomass up to 56%; consequently, horseweed interference with these tiafenacil mixtures resulted in soybean yield comparable to the non-treated (weedy) control. Glyphosate + tiafenacil + halauxifen-methyl and the co-application of glyphosate + tiafenacil + bromoxynil with metribuzin, halauxifen-methyl, or 2,4-D ester controlled MHR horseweed 73-94%, reduced density up to 79%, and reduced biomass up to 86%. Reduced MHR horseweed interference with the aforementioned tiafenacil mixtures resulted in soybean yield comparable to the weed-free control. In conclusion, all tiafenacil mixtures evaluated except those that contained 2,4-D ester can be safely used in white bean. Glyphosate + tiafenacil + halauxifen-methyl and the co-application of glyphosate + tiafenacil + bromoxynil with metribuzin, halauxifen-methyl, or 2,4-D ester provided the most consistent control of MHR horseweed.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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 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

Citations0
Published2023
Admission routes4
Has abstractyes

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