Volatilization or Recovery of Fairway Foliar Nitrogen Fertilizer via Time and Spray Oil Inclusion
Bibliographic record
Abstract
Nitrogen (N) is the essential plant nutrient needed by turfgrass in the greatest quantity. Urea and urea-based liquids are arguably the safest, least expensive, and subsequently most popular soluble N fertilizers. Unfortunately, urea fertilizer application to turfgrass is often subject to NH3 volatilization: a deleterious phenomenon from both environmental and agronomic perspectives. The objective of this research was to quantify the efficacy of creeping bentgrass (Agrostis stolonifera L.) golf course fairway foliar fertilization by urea-based N fertilizers as influenced by a petroleum-derived spray oil (PDSO) containing Cu II phthalocyanine colorant (Civitas Turf DefenseTM Pre-M1xed, Intelligro LLC, Mississauga, ON, Canada). In 2019 and 2020, a maintained creeping bentgrass fairway received semimonthly 9.76 kg ha–1 soluble N treatment either alone or in combination with Civitas at a rate of 27 L ha–1. In the 48 h following foliar application, fertilizer N loss as NH3 ranged from 1.3 to 5.5% and corresponded directly to fertilizer urea content but not Civitas inclusion. In the 1 to 14 d following semimonthly treatment, Civitas had either a beneficial (methylol urea and UAN) or negligible (urea) effect on canopy mean dark green color index. Once cumulative N inputs exceeded 47 kg ha–1, creeping bentgrass fairway shoot growth and N nutrition were consistently increased by Civitas complementation of commercial liquid N fertilizer. Over the 2-yr study, absolute mean percent fertilizer N recovery from plots treated by Civitas-complemented foliar liquid N treatment exceeded their ’N only’ counterparts by 8.7%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.001 | 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".