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Record W3109301385 · doi:10.3389/ffgc.2020.598527

Examining the Impact of Winter and Spring Soil Temperatures on the Growth of Hypholoma fasciculare, a Potential Biocontrol Agent Against Armillaria ostoyae, in Pine Plantations

2020· article· en· W3109301385 on OpenAlexafffund
Ryan Stevens, Gerardo P. Reyes, Kanavillil Nandakumar

Bibliographic record

VenueFrontiers in Forests and Global Change · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsLakehead University
FundersLallemandLakehead UniversityOntario Centres of Excellence
KeywordsArmillariaGrowing seasonBiologyBiological pest controlAgronomySpring (device)HorticultureMyceliumBotanyEnvironmental science

Abstract

fetched live from OpenAlex

Hypholoma fasciculare is regarded as a potentially effective biocontrol agent against Armillaria root disease. However, trials examining its effectiveness are currently limited to controlled lab conditions and field studies conducted mostly during the summer season. We examined the ability of H. fasciculare to survive and grow underground during the winter and spring seasons to offer insight on its ability to provide year-round protection. Pine blocks inoculated with H. fasciculare were buried in three thinned pine plantations at 30 and 100 cm depths from February 1, 2018 to May 13, 2018 (101 days) to examine how winter and spring soil temperatures at two different soil depths impacted growth. A significant interactive effect of soil depth and month on soil temperature ( F 3,40 = 15.94, p < 0.001) was observed. Mean growth rates did not vary significantly between the two soil depths ( F 1,23 = 0.91, p = 0.393) as growth rates were 0.25 ± 0.11 and 0.31 ± 0.10 mm/day at 30 and 100 cm depths, respectively. Our study supports developing H. fasciculare as a biocontrol agent against Armillaria root disease given its ability to grow underground during the winter and early spring seasons, a period during which Armillaria has a reduced growing capacity.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.318

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)0.0000.000

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 head0.022
GPT teacher head0.220
Teacher spread0.198 · 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 designObservational
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

Citations4
Published2020
Admission routes2
Has abstractyes

Explore more

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