Deficit Irrigation Effects on Water Use Characteristics of Bentgrass Species
Bibliographic record
Abstract
This study was designed to determine the effects of deficit irrigation on water use traits of colonial (Agrostis capillaris L.), creeping (A stolonifera L.), and velvet (A canina L.) bentgrasses and to compare their water use. Field experiments were conducted from July to November in 2002 and 2003. Plots were irrigated at four levels of irrigation based on the percentage of actual evapotranspiration (ETa): 100, 80, 60, and 40% ETa replacement. The influence of deficit irrigation on water use was evaluated by measuring soil water depletion (SWD) and water use efficiency (WUE). The WUE was quantified by the ratio of canopy net photosynthetic rate to transpiration rate and carbon isotope discrimination (CID). Evapotranspiration (ET) rates were compared among the three species under nonlimiting moisture conditions (100% ETa). Our results demonstrated that water use characteristics varied with species, irrigation regime, and climatic conditions. Irrigating at either 60 or 80% ETa had no significant effects on WUE compared with 100% ETa irrigation; however, plots irrigated at 60% ETa exhibited higher SWD compared with plots at 80 and 100% ETa Velvet bentgrass exhibited lower SWD, higher WUE, and lower CID compared with colonial bentgrass during the summer treatment period, and creeping bentgrass exhibited intermediate water use characteristics among the three species. These results suggest that irrigating bentgrass species at 60 to 80% ETa could be practiced to increase WUE during summer and 40% ETa during fall months under the conditions of this study.
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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) | 0.000 | 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 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".