Evidence map›Paper›PMID 36673401›Full record

ArticleFoods (Basel, Switzerland)2023

Extraction of Ursolic Acid from Apple Peel with Hydrophobic Deep Eutectic Solvents: Comparison between Response Surface Methodology and Artificial Neural Networks.

Haiyan Li, Yugang Liu, Shiyin Guo, Meng Shi, Si Qin, Chaoxi Zeng

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
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  3. Review
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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

6 authors.

Haiyan LiDepartment of Biology and Medicine, College of Food Science and Technology, Hunan Agricultural University, No. 1 Nongda Road, Furong District, Changsha 410128, China.
Yugang LiuDepartment of Biology and Medicine, College of Food Science and Technology, Hunan Agricultural University, No. 1 Nongda Road, Furong District, Changsha 410128, China.
Shiyin GuoDepartment of Biology and Medicine, College of Food Science and Technology, Hunan Agricultural University, No. 1 Nongda Road, Furong District, Changsha 410128, China.
Meng ShiDepartment of Biology and Medicine, College of Food Science and Technology, Hunan Agricultural University, No. 1 Nongda Road, Furong District, Changsha 410128, China.
Si QinDepartment of Biology and Medicine, College of Food Science and Technology, Hunan Agricultural University, No. 1 Nongda Road, Furong District, Changsha 410128, China.ORCID 0000-0002-0788-2099
Chaoxi ZengDepartment of Biology and Medicine, College of Food Science and Technology, Hunan Agricultural University, No. 1 Nongda Road, Furong District, Changsha 410128, China.

Funding

National Key Research and Development Program of China 2019YFC1604903Natural Science Foundation of Hunan Province 2021JJ30321
6 · The paper itself

Abstract

Extracting ursolic acid (UA) from plant resources using organic solvents is incompatible with food applications. To address this, in this study, 15 edible hydrophobic deep eutectic solvents (HDESs) were prepared to extract UA from apple peel, the extraction conditions were optimized, and the optimization strategies were compared. It was found that the solubility of UA in the HDESs can be 9 times higher than the traditional solvent such as ethanol. The response surface optimization concluded that temperature had the greatest effect on the extraction and the optimized test conditions obtained as follows: temperature of 49 °C, time of 32 min, solid-liquid ratio of 1:16.5 g/mL, respectively. Comparing the response surface methodology (RSM) and artificial neural networks (ANN), it was concluded that ANN has more accurate prediction ability than RSM. Overall, the HDESs are more effective and environmentally friendly than conventional organic solvents to extract UA. The results of this study will facilitate the further exploration of HDES in various food and pharmaceutical applications.

Indexed as

apple peelartificial neural networkresponse surface methodologyultrasonic-assisted extraction

Identifiers

PMID36673401
PMCPMC9858320

What OpenQuestion holds

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Registered trials

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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.