Effect of Kale Cultivation Conditions on Biosynthesis of Xanthophylls
Bibliographic record
Abstract
Conditions of plant cultivation directly influence the chlorophyll and carotenoid pigments concentrations. The aim of investigations was the determination of lutein in kale (Brassica oleracea L. var. acephala) upon various cultivation conditions including: low and high temperature (overnight and daytime in the greenhouse the temperature was 12 ± 2C and in the laboratory the temperature was 22 ± 2C), lack of water (some plants were watered only one time weekly), saline stress (5% of sodium chloride added to irrigation water; watering two times weekly was applied), as well as UV radiation of plants by means of UV lamp (lambda = 254 nm; suitable to UVC solar radiation; duration 4 h per day). Three months old cuttings were taken and next mentioned cultivation conditions were applied during one month. Moreover, the outdoor cultivation of kale cuttings was performed. Qualitative and quantitative analyses of plant extracts were made by use of HPLC-UV-VIS-MS technique. Mean values for lutein accumulation as a function of dry mass (mg/g) in leaves of kale have been presented. Obtained results show maximum xantophylls (lutein) concentration occur in fully developed plant leaves of kale for red kale 2.04 ± 0.15 and green kale 1.10 ± 0.09 mg/g respectively.
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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 | 0.001 | 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".