Bacterial Formulations in Induction of Resistance and Growth Promotion of Tomato Plants
Bibliographic record
Abstract
The objective of this work was to evaluate the effectiveness of seed treatment with fresh suspensions and powder formulations with Bacillus methylotrophicus to promote plant growth and induction of resistance against fusarium wilt (Fusarium oxysporum f. sp. lycopersici) in tomato plants under greenhouse conditions, verifying the occurrence of morphological and biochemical changes in the evaluated plants. Powder formulations based on Cassava (Manihot esculenta), Arrowroot (Maranta arundinacea) and sodium alginate containing Bacillus, in addition to the commercial product Quartz®, were used to microbiolize the tomato seeds of the cultivar Santa Cruz. The formulations promoted plant growth, with a seedling vigor index greater than 50% for all treatments containing B. mthylotrophicus, in addition to a significant increase in total dry matter. The treatments induced systemic resistance, controlling the fusarium wilt with a 75% reduction of the disease and activation of enzymes such as peroxidase and polyphenoloxidase, only β-1,3-glucanase presented less activity than controls (treatments without B. mthylotrophicus). Thus, the use of formulations containing Bacillus are efficient in promoting plant growth of tomato plants and in inducing resistance to the control of fusarium wilt.
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 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) | 0.000 | 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 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".