Development and assessment of organic growing substrates for tomato transplant production and disease suppression
Bibliographic record
Abstract
Organic systems are rigidly regulated in Canada and specify that no synthetic materials be permitted in growing substrates. Research on organic growing substrates is generally not sufficient enough that practical and dependable use recommendations for organic growers can be made. This thesis is an investigation of organic growing substrates for the production of healthy organic tomato transplants and an investigation of the use of manure compost, alone or in combination with 'Clonostachys rosea', for the suppression of root disease caused by 'Pythium ultimum' in organic tomato transplants. Several substrate formulations consisting of peat moss, coconut coir, fine perlite, fine vermiculite, manure compost, vermicompost, worm castings, yard waste compost, pine bark compost, and/ or aged pine bark were successful for growing healthy tomato transplants in 10-cm pots with organic fertilizer applications. Transplant roots from sterilized substrates that were inoculated with 'P. ultimum' were more fragile compared to other roots from other treatments, which suggested that some effect on roots was occurring. It was concluded that the establishment of 'P. ultimum ' in the root zone of transplants is more likely to occur when the transplants are grown in sterilized substrates that are not amended with the beneficial fungal endophyte 'C. rosea'.
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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) | 0.000 | 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".