Fertigation of Cool Season Turfgrass Species with Anaerobic Digestate Wastewater
Bibliographic record
Abstract
Wastewater, uniquely derived from the anaerobic digestion of MSW and containing high contents of essential plant nutrients, was used as a primary N source for turfgrass cultivation. Creeping bentgrass (Agrostis palustris Huds.) and Kentucky bluegrass (Poa pratensis L.) were grown under controlled growth room conditions and fertilized with nutrient solution supplied from wastewater or from a commercial soluble turf fertilizer. Bentgrass supplied with wastewater-N grew similarly to those plants supplied with commercial-N in the second of three clipping harvests. In the third harvest, bentgrass supplied with wastewater-N slightly outperformed those fertilized with commercialN. In the first harvest of bentgrass, as well as with all three harvests of bluegrass, clipping yields were comparable up to the recommended N application rate of 25 kg N·ha -1 , while at higher rates, growth with commercial-N exceeded that with wastewater-N. Poor plant growth response at high rates of wastewater addition was related to high concentrations of soluble salts in the wastewater. Field trials were also conducted on three established turfgrass plots typical of PGA regulation turf. Green-area turf was treated with fertilizer solutions supplied at 25, 50, and 100 kg·ha -1 from each of commercial-N, wastewater-N, wastewater-N + calcium nitrate, or 50 kg·ha -1 of a granular control fertilizer. Landing- and rough-area turf received half of each of these rates of N. All turf areas receiving the recommended or lower rates of N performed as well with wastewater-N versus commercial-N. Response of shoot chlorophyll content followed a similar trend as clipping yields, while soil moisture and shoot color were not significant for any treatment on any area.
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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) | 0.002 | 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".