Evidence map›Paper›PMID 41401650›Full record

ArticleUltrasonics sonochemistry2026

Ultrasound-Assisted Deep Eutectic Solvent-Based Extraction of Polysaccharides from Okra: Optimization by Response Surface Methodology and Artificial Neural Network Modeling.

Muhammad Imran, Chih-Huang Weng, Girma Sisay Wolde, Ying-Chen Chen, Yi-Jin Wu, Shang-Ming Huang, Yao-Tung Lin

Abstract read
In one paragraph

Article in Ultrasonics sonochemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

7 authors.

Muhammad ImranDepartment of Soil and Environmental Sciences, National Chung Hsing University, Taichung 40277, Taiwan.
Chih-Huang WengDepartment of Civil Engineering, I-Shou University, Kaohsiung 84001, Taiwan.
Girma Sisay WoldeDepartment of Soil and Environmental Sciences, National Chung Hsing University, Taichung 40277, Taiwan.
Ying-Chen ChenDoctoral Program in Plant Health Care, National Chung Hsing University, Taichung 40277, Taiwan.
Yi-Jin WuMaster Program for Food and Drug Safety, College of Medicine, China Medical University, Taichung 40402, Taiwan.
Shang-Ming HuangDepartment of Nutrition, China Medical University, Taichung 40402, Taiwan. Electronic address: zxzxmj2323@mail.cmu.edu.tw.
Yao-Tung LinDepartment of Soil and Environmental Sciences, National Chung Hsing University, Taichung 40277, Taiwan. Electronic address: yaotung@nchu.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant-derived polysaccharides are critical bioactive compounds; however, conventional extraction methods are often inefficient, energy-intensive, and may compromise their bioactivity. Ultrasound-assisted deep eutectic solvent (UA-DES) extraction offers a greener alternative by integrating acoustic cavitation with tunable solvent properties; however, optimization remains complex due to the interaction of multiple processing variables. This study reports a novel application of ultrasound-assisted deep eutectic solvent (UA-DES) extraction for okra polysaccharides (OPs), with process optimization using response surface methodology (RSM) and artificial neural network (ANN) modeling to identify optimal conditions and clarify nonlinear extraction behavior. Among the tested DES systems, choline chloride-citric acid (CCA) exhibited the highest extraction performance. Single-factor experiments and RSM identified sonication time and liquid-solid ratio as key variables. The ANN model achieved higher predictive accuracy than RSM and captured nonlinear and synergistic parameter interactions that were not evident in traditional response surfaces, providing deeper insight into process behavior. Under optimized conditions (2 h, 80 °C, 190 W, 60 mL/g), UA-DES extraction produced 23.56 % OPs and 80.75 % DPPH• scavenging activity, representing 94 % higher yield and 28 % greater antioxidant activity than hot-water ultrasonic (HWU) extraction. UA-DES-derived OPs contained higher contents of uronic acids, total sugars, and glucans, and uniquely included arabinose absent in HWU extracts. Structural analyses revealed pyranose configurations, amorphous crystallinity, and porous microstructures, which collectively contribute to improved solubility and bioactivity. Overall, UA-DES extraction using CCA provides an eco-efficient strategy for producing high-value okra polysaccharides. The integrated RSM-ANN framework enables precise optimization and enhanced mechanistic understanding, supporting UA-DES as a scalable, green technology for the production of functional polysaccharides.

Indexed as

AbelmoschusChemical FractionationDeep Eutectic SolventsNeural Networks, ComputerPolysaccharidesSonicationUltrasonic WavesSolventsSurface PropertiesDeep Eutectic SolventsPolysaccharidesSolventsAntioxidantsBioactivityCavitationHydrogen bondingMicrostructure

Identifiers

PMID41401650
PMCPMC12769841

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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.