Benefits of Vermicompost as a Constituent of Growing Substrates Used in the Production of Organic Greenhouse Tomatoes
Bibliographic record
Abstract
Six individual growing substrate components were selected. From the individual components, 35 growing substrates were constructed. Preliminary analyses, which included pH, electrical conductivity, and macro- and micronutrient concentrations, combined with environmental and cost implications were conducted to identify which substrates had the appropriate properties for growing tomatoes. From the 35 combinations, four growing substrates were chosen as having preferred properties required for organic greenhouse tomato production. A 22-week growth experiment was performed to determine if any of the selected substrates could improve the marketable yield of tomatoes when compared with rockwool (RW) under greenhouse conditions. The greenhouse crop used for this experiment was Lycopersicon esculentum ‘beefsteak’ tomato, cultivar Matrix F1 Hybrid. Within the experiment, Forterra Royal GRO 1 (GRO 1; coconut coir/vermicompost) and Forterra Royal GRO 2 (GRO 2; aged pine bark/coconut coir/vermicompost) attained significantly higher marketable yields per plant compared with the plants grown in RW. A similar trend was seen in the incidence of Blossom End Rot (BER) with GRO 1 and GRO 2 having reduced numbers of BER incidences per plant when compared with RW. In conclusion, the addition of vermicompost to organic growing substrates is beneficial for tomato growth and yield.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".