MétaCan
Menu
Back to cohort
Record W7039643056

Microbial diversity of buckwheat rhizosphere in wireworm-infested and non-infested soils using metagenomics

2019· article· en· W7039643056 on OpenAlexaboutno aff

Bibliographic record

VenueIslandScholar (University of Prince Edward Island) · 2019
Typearticle
Languageen
FieldComputer Science
TopicTopic Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsRhizosphereMetagenomicsCrop rotationContext (archaeology)CropActinobacteriaMicrobial population biologyPopulationSoil water
DOInot available

Abstract

fetched live from OpenAlex

Wireworm has become a major problem causing extensive crop loss in many potato production areas in Canada. Wireworm control methods includes the use of chemical pesticides. However, pesticides can affect human health and the environment, and their use has consequently been questioned and prohibited in many countries. Therefore, the use of environmentally friendly plant protection techniques, including crop rotation as an alternative to chemical control measures have been promoted to minimize crop damage. In that context, buckwheat is used as a rotation crop to mitigate wireworm damage in potatoes. But so far, less is known about how buckwheat contributes to mitigate disease. This study was designed in a context of integrated pest management, with primary objectives to: (1) determine the microbial diversity in the buckwheat rhizosphere in comparison with other rotation crops; and (2) determine the correlation between the buckwheat rhizosphere microbiome structure and wireworm density. To achieve these objectives, 16S rRNA metagenomic sequencing was performed to determine the microbial diversity in bulk and rhizosphere soils of buckwheat and barley grown at two locations during two growing seasons. A pilot wireworm trapping study was also performed to assess the wireworm population following buckwheat and barley as rotation crops. The study identified 27 phyla in the two crops of which Proteobacteria, Bacteroidetes, Actinobacteria were the most abundant and species identification was confidently achieved in 7 phyla including Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidetes, Firmicutes, Deinococcus-Thermus and Crenarchaeota. \nInterestingly, Methylophilus flavus, Saccharopolyspora tripterygii and Deinococcus yunwei-\nensis were three operational taxonomic units (OTUs) found at the species level to be unique to\n\nthe buckwheat rhizosphere soil at both locations and purported as non-pathogenic entophytic\nbacteria and beneficial for sustainable agriculture. Moreover, after two years, a reduction in\nwireworm density was observed in both crops although, the direct link associating the reduced\nwireworm density and the observed microbial diversity and the operating mechanisms in each\n\ncrop remain to be elucidated. Taken together, changes were observed in the soil microbial com-\nmunities associated with specific rotation crops and a reduction in wireworm density was correl-\natively observed. Thus, our study showed that the root system of buckwheat influences the struc-\nture of the microbiome in the rhizosphere as hypothesized.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.011
GPT teacher head0.200
Teacher spread0.189 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueIslandScholar (University of Prince Edward Island)Same topicTopic ModelingFrench-language works237,207