(345) Mushroom Farm and Anaerobic Digestion Wastewaters as Supplemental Fertilizer Sources for Growing Container Nursery Stock
Bibliographic record
Abstract
Wastewaters from farm and composting operations are often rich in certain nutrients that can be reutilized in crop production. Liners of silverleaf dogwood ( Cornusalba L. `Argenteo-marginata'), common ninebark [ Physocarpusopulifolius (L.) Maxim.], and `Anthony Waterer' spirea ( Spiraea × bumalda Burvenich) were grown in 6-L containers filled with a medium consisting of 73% bark, 22% peat, and 5% pea gravel, by volume. Plants were fertigated daily via a computer-controlled multi-fertilizer injector with three recirculated fertilizer treatments: 1) a stock solution with macro- and micronutrients, electrical conductivity (EC) 2.2 dS·m -1 ; 2) wastewater from a mushroom farm; and 3) process wastewater from anaerobic digestion of municipal solid waste. The wastewaters used in both treatments 2 and 3 were diluted with tap water, and the computer was programmed to amend, dispense, and recirculate nutrients, based on the same target EC as in treatment 1. For comparison, there was a traditional controlled-release fertilizer treatment [Nutryon 17–5–12 (17N–2P–10K) plus micronutrients incorporated into the medium at a rate of 6.5 kg·m -1 , nutrients not recirculated]. All three species responded similarly to the three recirculated fertilizer treatments. Growth in the recirculated treatments was similar and significantly higher than that obtained with controlled-release fertilizer. A similar trend in EC was observed in the media near harvest. Throughout the study, there was no sign of nutrient toxicity or deficiency with any of the species or treatment.
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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".