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Record W2068206052 · doi:10.1021/jf803934p

Quantitative Determination of Allergenic 5-Alk(en)ylresorcinols in Mango (Mangifera indica L.) Peel, Pulp, and Fruit Products by High-Performance Liquid Chromatography

2009· article· en· W2068206052 on OpenAlexaff
Matthias Knödler, Katharina Reisenhauer, Andreas Schieber, Reinhold Carle

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2009
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMangiferaPulp (tooth)ChemistryFood scienceCultivarComposition (language)AnacardiaceaeDry matterHorticultureBotanyBiologyMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.214
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2009
Admission routes1
Has abstractyes

Explore more

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