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Record W3194656429 · doi:10.1017/wet.2021.68

Response of dry beans to tiafenacil applied preemergence

2021· article· en· W3194656429 on OpenAlexaffabout
Nader Soltani, Christy Shropshire, Peter H. Sikkema

Bibliographic record

VenueWeed Technology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsDry beanAgronomyCropBiologyGlyphosateHorticultureCultivar

Abstract

fetched live from OpenAlex

Abstract Tiafenacil is a new nonselective, protoporphyrinogen IX oxidase–inhibiting pyrimidinedione herbicide that is under consideration for registration to control grass and broadleaf weeds in corn, soybean, wheat, cotton, and other crops prior to crop emergence. The sensitivity of dry beans to tiafenacil is not known. Four field experiments were completed at Exeter and Ridgetown, ON, Canada, during the 2019 and 2020 growing seasons, to determine the sensitivity of azuki, kidney, small red, and white beans to tiafenacil applied preemergence (PRE) at 12.5, 25, 50, and 100 g ai ha −1 . Tiafenacil applied at 100 g ai ha −1 caused 5% or less injury to azuki, kidney, small red, and white beans: 0% to 3% injury to azuki bean; 1% to 5% injury to kidney bean; and 1% to 4% injury to both small red bean and white bean. Tiafenacil applied PRE at 12.5, 25, 50, and 100 g ai ha −1 caused up to 1%, 4%, 4%, and 5% visible dry bean injury, respectively, but had no negative effect on other measured growth parameters including seed yield. Crop injury was generally greatest when tiafenacil was appled at the 100 g ai ha −1 rate in dry beans. Generally, kidney, small red, and white bean were more sensitive to tiafenacil than azuki bean. Dry bean injury was persistent and increased with time with the greatest injury observed 8 wk after emergence. Tiafenacil applied PRE can be a useful addition to the current strategies to control grass and broadleaf weeds, especially glyphosate-resistant horseweed and amaranth species prior to bean emergence.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.214
Teacher spread0.204 · 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

Citations6
Published2021
Admission routes2
Has abstractyes

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