Evidence map›Paper›PMID 39144187›Full record

ArticleFood science and biotechnology2024

Optimization of accelerated solvent extraction of zeaxanthin from orange paprika using response surface methodology and an artificial neural network coupled with a genetic algorithm.

Jaecheol Kim, Ga Eun Lee, Suna Kim

Abstract read
In one paragraph

Article in Food science and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jaecheol KimSchool of Bio-Health Convergence, Health & Wellness College, Sungshin Women's University, Seoul, 01133 Republic of Korea.
Ga Eun LeeDepartment of Food and Nutrition, and Research Institute of Human Ecology, Seoul National University, Seoul, 08826 Republic of Korea.
Suna KimDivision of Human Ecology, College of Natural Science, Korea National Open University, Seoul, 03078 Republic of Korea.ORCID 0000-0002-3769-761X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to optimize the accelerated solvent extraction (ASE) condition of zeaxanthin from orange paprika using a response surface methodology (RSM) or an artificial neural network (ANN) with a genetic algorithm (GA). Input variables were ethanol concentration, extraction time, and extraction temperature, while output variable was zeaxanthin. The mean squared error and regression correlation coefficient of the developed ANN model were 0.3038 and 0.9983, respectively. Predicted optimal extraction conditions from ANN-GA for maximum zeaxanthin were 100% ethanol, 3.4 min, and 99.2 °C. The relative errors under the optimal extraction conditions were RSM for 10.46% and ANN-GA for 2.18%. We showed that the recovery of hydrophobic zeaxanthin could be performed using ethanol, an eco-friendly solvent, via ASE, and the extraction efficiency could be improved by ANN-GA modeling than RSM. Therefore, combining ASE and ANN-GA might be desirable for the efficient and eco-friendly extraction of hydrophobic functional materials from food resources. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-023-01514-8.

Indexed as

Accelerated solvent extractionArtificial neural networkGenetic algorithmOptimizationOrange paprikazeaxanthin

Identifiers

PMID39144187
PMCPMC11319554

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.