MétaCan
Menu
Back to cohort
Record W3202583369 · doi:10.1002/ejlt.202100079

Optimization of Aqueous Enzymatic Microwave Assisted Extraction of Macadamia Oil And Evaluation of Its Chemical Composition, Physicochemical Properties, and Antioxidant Activities

2021· article· en· W3202583369 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Lipid Science and Technology · 2021
Typearticle
Languageen
FieldNursing
TopicNuts composition and effects
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsExtraction (chemistry)ChemistryFlavorChromatographyHexaneFlame ionization detectorYield (engineering)Gas chromatographyAqueous solutionAntioxidantEnvironmentally friendlyOrganic chemistryMaterials scienceFood science

Abstract

fetched live from OpenAlex

Abstract This study presents the green and effective aqueous enzymatic process assisted microwave extraction (AEME) to preparate macadamia nut oil (MNO). The conditions of the extraction process are optimized (extraction temperature 50 °C, extraction time 64 min, enzyme concentration 1.60% (w/w), and irradiation power 450 W). An oil yield of 58.09 ± 0.63% is achieved under these optimal conditions. The scanning electron micrograph (SEM) analysis of nuts before and after extraction illustrates that AEME promotes the emancipation of oil stored within the organelles. Gas chromatography‐flame ionization detector (GC‐FID) analysis reveals the fatty acid compositions of MNOs obtained by AEME and the Soxhlet extraction (SE) are similar and mainly dominated by monounsaturated fatty acids beneficial to human health which is higher in MNO than in any other known food. Moreover, gas chromatography‐mass spectrometry (GC‐MS) analysis reveals higher amounts of more odoriferous oxygenated terpenes is present in the MNO extracted by AEME in comparison with SE. The physicochemical properties of AEME oil are more excellent than those of SE oil. Moreover, AEME oil exhibits superior antioxidant capacities. In conclusion, green AEME gives relatively satisfactory yield and better retains the fragrance and functionality of MNO. Practical Applications : The present study provides a green extraction method and valuable data for the process design as well as industrial scale‐up applications. In addition, compared to the nonsustainable and environmentally nonfriendly traditional method, AEME preserves the initial composition of the flavor substances and enhances the extraction of healthy beneficial compounds in MNO. Therefore, AEME oil can be used to develop functional edible oils or even in medicinal, cosmetic, and pharmaceutical preparations.

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.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.025
GPT teacher head0.264
Teacher spread0.239 · 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