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Soil, climate, and management practices associated with the prevalence of clubroot in Colombia

2022· article· en· W4306749304 on OpenAlexaff
Andrea Botero-Ramirez, Fabián Leonardo Padilla-­Huertas, Celsa García

Bibliographic record

VenueAgronomía Colombiana · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsUniversity of Alberta
FundersDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)
KeywordsClubrootAgronomyCrop rotationBiologyCropBrassica

Abstract

fetched live from OpenAlex

Clubroot disease caused by Plasmodiophora brassicae is a major constraint for cruciferous crops in Colombia; however, information regarding its spread and the relationship between environmental and crop management practices with its occurrence in the country is scarce. This research established clubroot prevalence in the main cruciferous productive areas in Colombia and the relation of its occurrence with crop management practices, soil, and climatic characteristics. In total, 127 fields were visited along eight departments. Clubroot infestation was determined either by direct inspection of roots of host plants for clubroot symptoms or by report of previous observation of the disease symptoms by the farmers. Soil samples were collected for physical and chemical analysis, climatic information was obtained, and farmers were surveyed on the management practices of the production systems. The survey confirmed the presence of the disease in 53.6% of the visited fields. The only department where the disease symptoms were not observed nor reported was Nariño. A negative correlation was found between the disease occurrence and the content of aluminum in the soil, the number of days with rain per year, and the cultivation of clubroot-resistant hybrids. Moreover, a positive correlation was observed with the inclusion of cruciferous crops in the rotation scheme, the effective cation exchange capacity of the soil, soil pH, and the content of phosphorus, calcium, boron, and copper in the soil.

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 score0.029
Threshold uncertainty score0.492

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 head0.013
GPT teacher head0.209
Teacher spread0.196 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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