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Qualitative model optimization of almond (Terminalia catappa) oil using soxhlet extraction in type-2 fuzzy environment

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Abstract

An investigation into solid–liquid-based soxhlet extraction and drying pretreatment was conducted for the oil extraction from almond seed powder. The best possible combination of extraction parameters was obtained with interval type-2 fuzzy logic. Four major parameters: extraction time, temperature, moisture content and solvent-to-sample ratio were taken as input variables, and oil recovery and stability index were taken as output variables to optimize the extraction process based on their selected linguistic nature. Using these four input and two output parameters, eight Mamdani fuzzy inference systems were formed depending on the different membership functions of the variables. Finally, a statistical analysis has been performed using type-2 fuzzy data set to improve the control of process parameters that can be easily determined in type-2 fuzzy environment to get high yield as well as prominent quality.

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Authors and Affiliations

  1. Department of Chemical Engineering, Haldia Institute of Technology, Haldia, Purba Medinipur, West Bengal, 721657, India

    Anupam Mukherjee & Kunal Roy

  2. Department of Engineering Science, Haldia Institute of Technology, Haldia, Purba Medinipur, West Bengal, 721657, India

    Dipak K. Jana

  3. Department of Mathematics, Brahmananda Keshab Chandra College, Kolkata, West Bengal, 700108, India

    Sheikh A. Hossain

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  1. Anupam Mukherjee
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  2. Kunal Roy
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  3. Dipak K. Jana
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  4. Sheikh A. Hossain
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Correspondence to Dipak K. Jana.

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Communicated by O. Castillo, D. K. Jana.

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Mukherjee, A., Roy, K., Jana, D.K. et al. Qualitative model optimization of almond (Terminalia catappa) oil using soxhlet extraction in type-2 fuzzy environment. Soft Comput 24, 41–51 (2020). https://doi.org/10.1007/s00500-019-04158-1

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