Lemongrass Productivity, Oil Content, and Composition as a Function of Nitrogen, Sulfur, and Harvest Time
Bibliographic record
Abstract
Lemongrass [Cymbopogon flexuosus (Steud.) Wats, (syn. Andropogon nardus var. flexuosus Hack; A. flexuosus Nees)] is one of the most widely grown essential oil plants in the world. Field experiments were conducted at Verona and Poplarville, MS, to evaluate the effects of N (0, 40, 80, and 160 kg N/ha) and S (0, 30, 60, and 90 kg S/ha) on lemongrass biomass productivity, essential oil content, yield, and oil composition. Overall, the essential oil content varied within 0.35 to 0.6% of the dried biomass. The major constituents were geranial (25–53%), neral (20–45%), caryophyllene oxide (1.3–7.2%), and t‐caryophyllene (0.3–2.2%). Biomass yields at Verona ranged from 9486 to 19,375 kg/ha, while oil yields ranged from 30 to 139 kg/ha. Overall, dry weight yields increased with the application of 80 kg N/ha relative to the 0 kg N/ha and with 160 kg of N/ha relative to the 0 and 40 kg N/ha treatments. At Poplarville, biomass yields varied from 8036 to 12,593 kg/ha, while oil yields ranged from 23.5 to 89.5 kg/ha. The application of N at 160 kg/ha at Poplarville increased dry weight yields relative to the N at 0 or 40 kg/ha rates, irrespective of the rate used for S. At Verona, within each S application rate, biomass yields were highest in Harvest 2, lower in Harvest 1, and the lowest in Harvest 3 (regrowth). The combined biomass yields of Harvest 1 and Harvest 3 would be lower, but oil yields would be higher compared to Harvest 2 (single‐harvest system). Lemongrass can be grown as an annual essential oil crop in the southeastern United States, with a potential for dual utilization: essential oil and lignocellulosic material for ethanol production.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".