Evaluation of Wound-HealingPotential of Plant Extractsvia Picture Fuzzy Multi-Attribute Decision-Making

Abstract The rising number of chronic wounds across the world makes the creation of efficient, environmentally friendly and cost-effective wound healing biopolymers an urgent need in the sphere of biopharmaceuticals. However, the selection of the most appropriate candidate from many natural plant extracts with complex and heterogeneous phytochemical composition is a difficult task of multiattribute decision-making (MADM) because of uncertainties, hesitations in expert judgments, and incomplete experimental data. A new hybrid approach of MADM with the use of picture fuzzy sets (PFS) is suggested in this paper as a realistic model of human logical judgment with membership degrees that cover positive, negative, neutral, and refusal aspects. Within the context of this study, the PiF-DEMATEL method is used to estimate causal relationships between eight attributes related to tissue repairing performance and attribute weights, while the PiF-PIV method that has been elaborated for the first time in the literature in this study is proposed as a tool for ranking ten different plant extracts. According to the attribute analysis, the “anti-inflammatory effect” (0.150) and “cell regeneration” (0.147) attributes, belonging to the group of physiological response attributes, were shown to have the highest importance, whereas the “Phytochemical content” (0.145) criterion was revealed to be the most dominating causative factor controlling the underlying biochemical engine. Centella asiatica (C. asiatica) turned out to be the most stable and efficient wound-healing candidate, being immediately followed by Hypericum perforatum (H. perforatum) and Calendula officinalis (C. officinalis). Sensitivity analysis including alternative weighting and ranking approaches showed the minimum value of rank correlation coefficient at 96.4%, which proves high reliability, mathematical validity, and robustness of the PiF-DEMATEL-PIV hybrid model. Thus, this study proposes a potent and economic guide for engineering that helps to avoid losses caused by trial-and-error during preliminary laboratory stages of creation of advance H. perforatum d wound care technologies, e.g., electrospun nanofibers and polysaccharide hydrogels.

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Publication Details

Journal
ACS Omega
Published
2026-08-17
DOI
https://doi.org/10.1021/acsomega.6c08040
Primary Topic
Medicinal Plants and Neuroprotection
Type
article
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article

Evaluation of Wound-HealingPotential of Plant Extractsvia Picture Fuzzy Multi-Attribute Decision-Making

Sait Gül, Firdevs Mert Sivri
ACS Omega
Medicinal Plants and Neuroprotection
article

Evaluation of Wound-HealingPotential of Plant Extractsvia Picture Fuzzy Multi-Attribute Decision-Making

Sait Gül, Firdevs Mert Sivri
article en

Abstract

Abstract The rising number of chronic wounds across the world makes the creation of efficient, environmentally friendly and cost-effective wound healing biopolymers an urgent need in the sphere of biopharmaceuticals. However, the selection of the most appropriate candidate from many natural plant extracts with complex and heterogeneous phytochemical composition is a difficult task of multiattribute decision-making (MADM) because of uncertainties, hesitations in expert judgments, and incomplete experimental data. A new hybrid approach of MADM with the use of picture fuzzy sets (PFS) is suggested in this paper as a realistic model of human logical judgment with membership degrees that cover positive, negative, neutral, and refusal aspects. Within the context of this study, the PiF-DEMATEL method is used to estimate causal relationships between eight attributes related to tissue repairing performance and attribute weights, while the PiF-PIV method that has been elaborated for the first time in the literature in this study is proposed as a tool for ranking ten different plant extracts. According to the attribute analysis, the “anti-inflammatory effect” (0.150) and “cell regeneration” (0.147) attributes, belonging to the group of physiological response attributes, were shown to have the highest importance, whereas the “Phytochemical content” (0.145) criterion was revealed to be the most dominating causative factor controlling the underlying biochemical engine. Centella asiatica (C. asiatica) turned out to be the most stable and efficient wound-healing candidate, being immediately followed by Hypericum perforatum (H. perforatum) and Calendula officinalis (C. officinalis). Sensitivity analysis including alternative weighting and ranking approaches showed the minimum value of rank correlation coefficient at 96.4%, which proves high reliability, mathematical validity, and robustness of the PiF-DEMATEL-PIV hybrid model. Thus, this study proposes a potent and economic guide for engineering that helps to avoid losses caused by trial-and-error during preliminary laboratory stages of creation of advance H. perforatum d wound care technologies, e.g., electrospun nanofibers and polysaccharide hydrogels.

ACS Omega
Bahçeşehir University (TR), Suleyman Demirel University (KZ)
Openalex Percentile: Top 5%
Medicinal Plants and Neuroprotection
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