Nitrogen Uptake and Leaching under Annual Bluegrass Ecotypes and Bentgrass Species: A Lysimeter Experiment
Why this work is in the frame
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Bibliographic record
Abstract
Nitrate (NO 3 − ) can leach from golf greens, potentially causing the degradation of surface and ground water quality. A greenhouse experiment was conducted with 11 annual bluegrass ( Poa annua var. reptans Hausskn.) ecotypes from eastern Canada (Quebec and Ontario) and the USA, and three bentgrass ( Agrostis spp.) species to compare N uptake and potential for N leaching. Two‐month‐old grasses were established for a 6‐wk period in lysimeter columns simulating a golf‐green profile. An unplanted root zone control was included. Water‐soluble fertilizer was applied at 25 kg N ha −1 (NH 4 NO 3 ) every 14 d for 57 d. Leachate samples were collected every second day and analyzed for NO 3 –N and ammonium N (NH 4 –N) content. Dry weight and N concentration were determined on clippings, shoots, and roots. Ammonium N leaching was negligible for all grasses. Less NO 3 –N leaching losses occurred under bentgrasses (6–11% of applied N) than under annual bluegrasses (28–71% of applied N). Differences in NO 3 –N leaching were also found within annual bluegrasses; Quebec P. annua > Ontario P. annua > USA P. annua Grasses with a greater aboveground biomass developed a larger and deeper root system and were associated with a greater N uptake ( r = 0.94) and, therefore, a lower NO 3 –N leaching ( r = −0.94). Breeding programs and management practices to improve turfgrass root development appear to be critical to reduce fertilizer N leaching under sand‐based putting greens.
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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 | 0.001 |
| 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 it