Organic Fertilizers for Greenhouse Tomatoes: Productivity and Substrate Microbiology
Bibliographic record
Abstract
Organic fertilizer regimens consisting of combinations of composts (yard waste, swine manure, or spent mushroom substrate) and liquid fertilizers (fish- or plant-based) were evaluated against conventional hydroponic fertilizers in two experiments with greenhouse tomatoes grown in peat-based substrate. Crop yield and fruit quality were evaluated and several assays of substrate microbial activity and community profiles (fluorescein diacetate analysis and EcoLog, values, nematode counts) were conducted. Crops grown in 20% to 40% compost (yard waste or yard waste plus swine manure) plus a continuously applied liquid source of organic potassium (K), calcium (Ca), magnesium (Mg), and sulphate (SO 4 ) could not be sustained more than 1 month before nutrient deficiencies became visible. Supplementation with a nitrogen (N)- and phosphorus (P)-containing plant-based liquid fertilizer at the point when plant deficiencies became apparent subsequently produced yields ≈80% that of the hydroponic control. In a second experiment, the proportion of mushroom or yard waste compost was increased to 50% of the mix, and liquid delivery of K, Ca, Mg and SO 4 plus either plant-based or fish-based N- and P-containing liquid feeds was started at the date of transplanting. In this case, organic yields equal to that of the hydroponic control (8.5 kg/plant) were observed in some treatments. The most productive organic treatment was the mushroom compost supplemented with a low concentration of the plant-based liquid fertilizer. In general, organic tomatoes had a lower postharvest decay index (better shelf life) than did the hydroponic controls, possibly as an indirect consequence of overall reduced yield in those treatments. High concentrations of both organic liquid feeds resulted in lower yields as a result of treatment-induced fusarium crown and root rot. In contrast to some previous studies, those treatments showing fusarium crown and root rot also had the highest gross microbial activity. Measures of gross microbial activity and numbers of microbivorous nematodes were higher (average of 37% and 6.7 times, respectively) in compost/organic feed treatments than in the hydroponic control. Community physiological profiles of the bacterial populations, on the other hand, did not differ between organic and hydroponic treatments. Nematode populations were significantly correlated with gross microbial activity in the organic treatments.
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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) | 0.001 | 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".