Quantitative Determination of Allergenic 5-Alk(en)ylresorcinols in Mango (Mangifera indica L.) Peel, Pulp, and Fruit Products by High-Performance Liquid Chromatography
Bibliographic record
Abstract
Despite a number of serious case reports of mango dermatitis, no attempts at the identification and quantification of allergenic 5-alk(en)ylresorcinols in mango fruits have so far been made. Therefore, total alk(en)ylresorcinol content and relative homologue composition in 13 mango peel samples and 7 samples of mango pulp were determined by HPLC and LC-MS/MS analyses. Furthermore, mango puree and nectar prepared on pilot plant scale were also analyzed and compared with commercially available thermally preserved products. Depending on cultivar, alk(en)ylresorcinol contents ranged from 79.3 to 1850.5 mg/kg of dry matter (DM) in mango peels and from 4.9 to 187.3 mg/kg of DM in samples of mango pulp. The profile of alk(en)ylresorcinols was found to be highly characteristic, with an average homologue composition of C15:0 (6.1%), C15:1 (1.7%), C17:0 (1.1%), C17:1 (52.5%), C17:2 (33.4%), C17:3 (2.4%), C19:1 (2.1%), and C19:2 (0.8%). Mango puree samples prepared from peeled and unpeeled fruits revealed contents of 3.8 and 12.3 mg/kg of fresh weight, respectively. Content and homologue composition were not significantly affected during puree processing and thermal preservation. In nectar samples prepared from peeled and unpeeled fruits, contents of 1.4 and 4.6 mg/L, respectively, were found.
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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 | 0.001 |
| 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".