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Record W6977293810 · doi:10.6084/m9.figshare.13536383

Effect of fungicide application technology on seed yield in field pea under variable Mycosphaerella blight pressure

2021· article· en· W6977293810 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFungicideMycosphaerellaField peaBlightYield (engineering)CanopyCultivarChemical control

Abstract

fetched live from OpenAlex

Mycosphaerella blight, caused by <i>Peyronellaea pinodes</i> (Berk. &amp; A. Bloxam) Aveskamp, Gruyter &amp; Verkley (syn. <i>Mycosphaerella pinodes</i> (Berk. et Blox.) Vesterg.), is a destructive foliar pathogen of field pea that is managed, in large part, through application of foliar fungicide at flowering. The fungicides are usually applied into dense crop canopies, so reaching the lower areas of the canopy where the pathogen is initially most active is a challenge. Field trials were conducted across the Canadian prairies from 2008 to 2011 to assess the efficacy of various nozzle numbers and orientations, droplet sizes, and water volumes for the management of Mycosphaerella blight to increase yield in field pea. Pea plants were assessed for disease severity during flowering and seed yield was measured. In 10 of the 13 trials, double-nozzle configurations provided a 15% reduction in disease severity and up to a 60% increase in yield. In contrast, droplet size and angle of application had no effect on field pea yield. Water volume trials using up to 400 L ha<sup>−1</sup> improved fungicide efficacy relative to control treatments, however, volumes above 400 L ha<sup>−1</sup> resulted in high-disease severity and lower yield, likely as a result of fungicide run-off due to saturation of the leaf surface. When deciding on effective sprayer techniques for fungicide application, disease pressure, environmental conditions and cultivar characteristics are important to consider.

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 categoriesInsufficient payload (model declined to judge)
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 score0.093
Threshold uncertainty score0.977

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)0.0240.000

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 head0.201
Teacher spread0.191 · 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.

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
Published2021
Admission routes1
Has abstractyes

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