Bacterial community diversity associated with the severity of bacterial wilt disease in tomato fields in southeast China
Bibliographic record
Abstract
Tomato bacterial wilt caused by Ralstonia solanacearum is a devastating plant disease. The aims of this study were to investigate the relationship among soil nutrients, rhizobacterial community, and abundance of R. solanacearum, and to gather useful information for controlling the disease. Fifteen tomato rhizosphere soils were collected from three regions, encompassing five disease grades. Then, soil physicochemical properties and rhizobacterial communities were investigated. The content of soil organic carbon (SOC), total phosphorus (TP), total potassium (TK), and exchangeable calcium was significantly higher in the healthy plant rhizosphere soils than in diseased plant rhizosphere soils (P < 0.05). The healthy soils had a relatively higher abundance of Proteobacteria and a lower abundance of Acidobacteria than the diseased soils from the same region. Redundancy analysis demonstrated that R. solanacearum abundance was positively correlated with total nitrogen content and negatively correlated with soil pH, SOC, TP, TK, and exchangeable calcium. Ralstonia solanacearum abundance correlated positively with Chloroflexi, Acidobacteria, and Planctomycetes abundance but negatively with Nitrospirae, Bacteroidetes, and Proteobacteria abundance. These results suggested that improving soil pH, applying the amount of P and K fertilizers, and controlling the dosage of N fertilizer might be an effective approach in controlling bacterial wilt disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".