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Research Progress on Aroma Compounds in Almonds and Factors Influencing Its Flavor Quality

2023· article· en· W6902865268 on OpenAlexaff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldNursing
TopicNuts composition and effects
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsAromaFlavorMaillard reactionRaw materialFlavour

Abstract

fetched live from OpenAlex

Raw almonds are rich in aldehydes, alcohols and other odorants contributing to fresh fruity and hay-like aromas. The flavor of almonds can change significantly due to various chemical reactions during thermal processing and storage, which can greatly affect its flavor quality. In this context, this review summarizes the major aroma compounds in raw almonds and the major aroma compounds formed by the Maillard reaction, the oxidation of fatty acids, and the degradation of amino acids and soluble sugars in roasted almonds, and it compares the effects of different thermal processing methods and conditions on the aroma compounds and aroma properties of almonds. In addition, this review summarizes the changes of the major aroma compounds and off-odor compounds in almonds during storage and the rational storage methods and conditions. Finally, possible future directions for research on almonds and other nuts are outlined. This review could provide a theoretical basis and reference for flavor quality control of almonds and other nuts during thermal processing and storage.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.466
GPT teacher head0.636
Teacher spread0.170 · 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.

Study designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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