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Record W2791976465 · doi:10.5539/jfr.v7n3p16

Color and Antioxidant Capacity Preservation of Opuntia spp. Juices by Spray-drying Microencapsulation.

2018· article· en· W2791976465 on OpenAlexvenueno aff
Alberto Castañeda-Yañez, Sandra T. Martín del Campo, Alejandra San-Martin, Anaberta Cardador‐Martínez

Bibliographic record

VenueJournal of Food Research · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Applications
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsFood sciencePEARSpray dryingDPPHChemistryAntioxidantMatrix (chemical analysis)Antioxidant capacityChromatographyBotanyBiologyBiochemistry

Abstract

fetched live from OpenAlex

In this work, it was evaluated the effect of microencapsulation using spray drying over natural colorants present in two varieties (red and purple) of prickly pear juice (Opuntia spp.), using three kinds of carrier agents (matrixes). The dried samples after microencapsulation retained a high total amount of the betalains and their antioxidant characteristics. However, some individual betalains were lost after microencapsulation. According to ANOVA results, matrix 3204 showed a more protective effect than matrix 4801 in both microencapsulated juices over color, individual betalains, and antioxidant capacity. Globally, the protective effect was better for purple juices than red juices no matter the matrix used. Principal Component Analysis (PCA) confirmed these results. Matrix 3204 resulted in the best carrier agent since it gave a less disperse PCA group for both color juices. The parameters that separated both PCA matrixes groups were L*, a*, b* and DPPH.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.120
GPT teacher head0.342
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2018
Admission routes1
Has abstractyes

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