Microbial diversity of buckwheat rhizosphere in wireworm-infested and non-infested soils using metagenomics
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".