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<p>Recognizing the challenges in achieving effective dyeing performance following natural dyeing of textile fabrics, this paper explores the development and optimization of an environmentally friendly dyeing process for silk fabrics, using Phytolacca americana fruit extract as a natural colorant. The dyeing process established was optimized using a combination of Response Surface Methodology (RSM) and the Dragonfly Algorithm, leading to a robust analytical framework. Indeed, the Box-Behnken Design (BBD), a type of Response Surface Methodology (RSM), was utilized to conduct various statistical analyses through response surface modeling: as example, the Pareto Chart diagram was established, it made possible to emphasize the importance of pH and its great influence on the process studied. In addition, 3D and Surface contours plots were traced and they made it possible to describe the distribution of the K/S response as a function of the factors of the model studied. Moreover, the response optimizer diagram established made it possible to achieve the following optimal conditions: pH 3, dyeing time 75 min and dyeing temperature 90 °C, all combined to achieve a color yield of the dyed silk of around 13.9. Regarding the use of the Dragonfly Support Vector Machine (DA-SVMr) modeling method, the outcomes indicate that the Dragonfly algorithm remains resilient under various operational circumstances. Furthermore, the comparison between the Support Vector Machine obtained through the Dragonfly algorithm (DA-SVMr) and the traditional BBD model showcased the superior performance of DA-SVMr.</p>

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Dyeing Silk Fibers the Green Way: Modeling the Dyeing Process with a Natural Dye Extracted from Phytolacca americana Fruits Through Response Surface Methodology and SVM-Based Machine Learning Modeling

  • 期刊论文

  • 发表日期：

    2025年5月7日

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  • Noureddine Baaka,
  • Mohamed Hentabli,
  • Amel Bouzidi,
  • Manel Ben Ticha,
  • Hatem Dhaouadi

摘要

Recognizing the challenges in achieving effective dyeing performance following natural dyeing of textile fabrics, this paper explores the development and optimization of an environmentally friendly dyeing process for silk fabrics, using Phytolacca americana fruit extract as a natural colorant. The dyeing process established was optimized using a combination of Response Surface Methodology (RSM) and the Dragonfly Algorithm, leading to a robust analytical framework. Indeed, the Box-Behnken Design (BBD), a type of Response Surface Methodology (RSM), was utilized to conduct various statistical analyses through response surface modeling: as example, the Pareto Chart diagram was established, it made possible to emphasize the importance of pH and its great influence on the process studied. In addition, 3D and Surface contours plots were traced and they made it possible to describe the distribution of the K/S response as a function of the factors of the model studied. Moreover, the response optimizer diagram established made it possible to achieve the following optimal conditions: pH 3, dyeing time 75 min and dyeing temperature 90 °C, all combined to achieve a color yield of the dyed silk of around 13.9. Regarding the use of the Dragonfly Support Vector Machine (DA-SVMr) modeling method, the outcomes indicate that the Dragonfly algorithm remains resilient under various operational circumstances. Furthermore, the comparison between the Support Vector Machine obtained through the Dragonfly algorithm (DA-SVMr) and the traditional BBD model showcased the superior performance of DA-SVMr.