Identification and Quantification of Natural Lecithin Phospholipids and Their Residuals in Freeze-Dried and Drum-Dried Fruits and Vegetables by LC-MS and HPLC-ELSD
Bibliographic record
Abstract
Sunflower lecithin is commonly used as a food processing agent. In this study, residues of sunflower lecithin phospholipids in drum-dried fruits and vegetables were investigated. The contents of phosphatidylcholine and phosphatidylethanolamine were of interest due to their natural levels in fresh fruits and vegetables as well as their residues after the drum drying process. Identification of these compounds in freeze-dried and drum-dried fruits and vegetables was conducted by normal-phase and reverse-phase ultra-high-performance liquid chromatography (UPLC) coupled with Q Exactive Orbitrap electrospray mass spectrometry. Quantification of phosphatidylcholine in various fruits and vegetables was performed using normal-phase high-performance liquid chromatography with evaporative light scattering detector (ELSD). The quantification results from these various products demonstrate that use of de-oiled sunflower lecithin as a processing agent in the drum drying production process does not affect the quality of final drum-dried products.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".