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Record W4381309656 · doi:10.1094/pdis-05-23-0960-sc

Effect of Mulching on Soil Temperatures and Its Impact on <i>Plasmodiophora brassicae</i> and Clubroot

2023· article· en· W4381309656 on OpenAlexaff
Yingzhe Hong, Jie Feng, Yue Liang

Bibliographic record

VenuePlant Disease · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsAlberta Health
FundersNational Key Research and Development Program of ChinaLiaoning Revitalization Talents ProgramShenyang Agricultural University
KeywordsClubrootBiologyAgronomyMulchBotanyHorticultureBrassica

Abstract

fetched live from OpenAlex

Clubroot caused by Plasmodiophora brassicae is a serious soilborne disease on cruciferous crops worldwide. Agricultural practice is a preferable clubroot management strategy because of its low investment requirement and environmental safety. Among the agricultural practices, solarization has been widely applied in the integrated management of other soilborne diseases. However, only few reports exist on the effect of solarization on clubroot management. In this study, we measured the effect of plastic mulching on soil temperature at different depths and on clubroot incidence and severity under greenhouse and field conditions. The pathogen density in the soil after solarization was measured by quantitative PCR analysis. Results indicated that the mulching treatment increased soil temperature especially in the soil layer ranges of 0 to 20 cm. Solarization with mulching also effectively reduced the incidence and severity of clubroot in the greenhouse assay and the field trial by decreasing the P. brassicae population in the soil. This study suggested that solarization with mulching can impair clubroot development and thus contribute to the sustainable management of clubroot.

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 score0.002
Threshold uncertainty score0.005

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 head0.007
GPT teacher head0.241
Teacher spread0.234 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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