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Record W2789660304 · doi:10.31274/etd-180810-5846

Effect of seed treatments and soybean cultivars on root rot caused by Fusarium virguliforme

2017· dissertation· en· W2789660304 on OpenAlexaboutno aff
Daniel A. Sjarpe

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsCultivarRoot rotBiologyHorticultureAgronomyFusariumBotanyMathematics

Abstract

fetched live from OpenAlex

Fusarium virguliforme, the causal agent of sudden death syndrome (SDS), is one of the most important soybean pathogens in the United States and Canada. Cultivar selection, seed treatments and some cultural practices are currently the main management practices for this disease. Fusarium virguliforme is a soilborne pathogen that infects soybean roots early in development (root rot phase), but also leads to the characteristic foliar symptoms (foliar phase) later in the season. Recently, the product fluopyram (ILeVO®, Bayer CropScience) was registered for management of SDS. The research described in this manuscript explains how fluopyram, in combination with cultivar selection, affects the two phases of SDS under field conditions. Two different greenhouse techniques were also evaluated for their ability to quickly and accurately screen seed treatments for efficacy against SDS.\nAll field experiments evaluated two seed treatments: (1) base seed treatment (control), which was prothioconazole + penflufen + metalaxyl (0.019 mg a.i/seed) + metalaxyl (0.02 mg a.i/seed) + clothianidin + Bacillus firmus I-1582 (0.13 mg a.i/seed) and (2) base treatment + fluopyram (0.15 mg a.i/seed). For the Roland, IA and Muscatine, IA locations in 2015, a third seed treatment was included; (3) base treatment + fluopyram (0.075 mg a.i./seed). All three seed treatments were included in all of the 2016 locations. Three soybean cultivars, categorized as susceptible, moderately resistant or resistant, were planted at each location. Fluopyram significantly reduced root rot at 7 of the 10 locations and foliar symptoms at 5 of the 9 locations where foliar symptoms occurred. Yield was significantly increased by fluopyram at 5 of the 10 locations. Our findings suggest that yields could be reduced by the root rot phase and should be managed in addition to the foliar phase of SDS.\nTwo greenhouse techniques: (1) soil-incorporated technique and (2) layer technique used the aforementioned seed treatments in the greenhouse. Neither technique consistently differentiated between treatments for foliar symptoms. However, both experiments showed approximately 20% reductions in root rot severity between the base seed treatment and both rates of fluopyram. Further work is needed to identify a controlled experiment in the greenhouse for evaluating seed treatments for both phases of SDS.\nOur findings suggest that at locations with known SDS history in years with favorable weather for the F. virguliforme pathogen, both phases of SDS can cause significant yield loss. The use of fluopyram as a seed treatment, along with resistant cultivars can protect soybean yields from both phases of SDS. However, more work is needed to identify an integrated management plan for both the root rot and foliar phases of SDS

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 score0.006
Threshold uncertainty score0.012

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 integrity0.0000.001
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 head0.005
GPT teacher head0.257
Teacher spread0.252 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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