Growth and Yield of Tomato Cultivated on Composted Duck Excreta Enriched Wood Shavings and Source-Separated Municipal Solid Waste
Bibliographic record
Abstract
A greenhouse experiment was conducted to evaluate the use of growth substrates, made with duck excreta enriched wood shaving compost (DMC) and the organic fraction of source-separated municipal solid waste (MSW) compost, on the growth and yield of tomato (Lycopersicum esculentum Mill. cv. Campbell 1327). Substrate A consisted of 3:2 (W/W) proportion of DMC and MSW composts. Substrates B and C were the same as A but contained 15% (W/W ratio) of brick dust and shredded plastic, respectively. Three control substrates consisted of the commercially available peat-based substrate (Pr), an in-house sphagnum peat-based substrate (Gs), and black earth mixed with sandy loam soil (BE/S) in a 1:4 (W/W) ratio. Substrates (A, B, C) and controls received nitrogen (N), phosphate (P) and potassium (K) at equivalent rates of 780 mg/pot, 625 mg/pot, and 625 mg/pot, respectively, or were used without mineral fertilizers. Compared to the controls (Pr, Gs and BE/S), tomato plants grown on A, B, and C produced a greater total number and dry mass of fruits, with no significant differences between them. On average, total plant dry-matter biomass in substrate A, B, and C was 19% lower than that produced on Pr, but 28% greater than biomass obtained for plant grown, on Gs and BE/S. Plant height, stem diameter and chlorophyll concentrations indicate that substrates A, B, and C were particularly suitable for plant growth. Although the presence of excess N in composted substrates favoured vegetative rather than reproductive growth, the continuous supply of nutrients throughout the growing cycle, as well as the high water retention capacity that resulted in a reduced watering by 50%, suggest that substrates A, B, and C were suitable growing mixes, offering environmental and agronomic advantages.
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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".