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Record W1983678368 · doi:10.1080/07060660109506938

Effects of biological and chemical treatments on<i>Botrytis</i>stem canker and fruit yield of tomato under greenhouse conditions<sup>1</sup>

2001· article· en· W1983678368 on OpenAlexaffvenue
R.S. Utkhede, Carl Bogdanoff, J. McNevin

Bibliographic record

VenueCanadian Journal of Plant Pathology · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBotrytis cinereaCankerBiologyHorticultureInoculationBotrytisBiological pest controlFungicideVerticillium wiltBacillus subtilisCitrus cankerGreenhouseBotanyBacteria

Abstract

fetched live from OpenAlex

Experiments were conducted to identify, by in vitro dual culture tests, potential biological control agents producing antibiotics and to evaluate selected biological and chemical agents for control of stem canker caused by Botrytis cinerea on tomato plants (Lycopersicon esculentum) grown in yellow cedar sawdust in a research greenhouse. Four strains of Bacillus subtilis and one each of Enterobacter agglomerans and Rhodosporidium diobovatum were antagonistic towards B. cinerea in dual culture. Lesions in treatments with RootShield® and a strain of R. diobovatum were significantly shorter compared with the inoculated control. Plants treated with RootShield® or R. diobovatum had significantly higher total fruit yield than the inoculated control. The treatments with RootShield®, SoilGard®, and R. diobovatum produced significantly more total fruits than the inoculated control. The number of dead plants were significantly lower in treatments with RootShield® and R. diobovatum compared with the other treatments and inoculated control. These results suggest that RootShield® and R. diobovatum have the potential to control Botrytis stem canker and increase the fruit yield of tomato under greenhouse conditions.Key words: biological control, Botrytis cinerea, Bacillus subtilis, Enterobacter agglomerans, Rhodosporidium diobovatum, gray mold.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.314

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 head0.209
Teacher spread0.186 · 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

Citations28
Published2001
Admission routes2
Has abstractyes

Explore more

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