Macronutrient Suppression in Nutrient Solution Alters the Growth and Citral Content of Cymbopogon flexuosus
Bibliographic record
Abstract
Cymbopogon flexuosus Stapf is a medicinal species cultivated on several continents. The essential oil extracted from its leaves has relevant commercial value and is widely used in flavoring agents, fragrances, perfumery, cosmetics, soaps, and detergents as well as in the pharmaceutical industry. This study evaluated the effect of macronutrient suppression on the growth, visual diagnosis, content, and chemical composition of C. flexuosus essential oil in a hydroponic culture. A completely randomized design with four replicates was used, with three plants per pot in each replicate. The treatments were characterized by suppressing the macronutrients, N, P, K, Ca, Mg, and S, under the missing element technique. After 90 days of cultivation, the deficiency symptoms were photographed and characterized. The dry biomass of the roots and shoot, root-to-shoot ratio, number of tillers, leaf analysis, content, yield, and chemical composition of the essential oil were evaluated. Macronutrient suppression in a hydroponic culture influenced growth and chemical composition of C. flexuosus essential oil. Total biomass production was more limited in potassium and magnesium omission. Suppressing sulfur promoted an increase in content and yield of essential oil. The highest citral content was observed in phosphorus and nitrogen omission.
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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".