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Artificial neural network and mathematical modeling on the drying kinetics of Costus pictus rhizomes and its impact on the polyphenol, flavonoid content and antioxidant activity

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Abstract

Costus pictus, recognized as the “insulin plant,” is a renowned medicinal plant with a diverse phytochemical composition, which confers a comprehensive spectrum of biological attributes. This is the first study on modeling the drying kinetics of Costus pictus rhizomes and analyzing the predictive capability of mathematical modeling and artificial neural network (ANN). C. pictus rhizomes were dried in a laboratory tray dryer at different temperatures (40 °C, 50 °C, and 60 °C) to produce a functional dried powder. Henderson and Pabis’s model well-described the drying kinetics. ANN with a feed-forward backpropagation algorithm was applied to understand the drying characteristics. Moisture ratio and moisture content were optimally trained with the Levenberg-Marquardt algorithm and hyperbolic tangent sigmoid transfer function for hidden layer. Comparative analysis validated that ANN had an unrivaled prediction potential. Color studies substantiated the overall acceptability of a dried product. Rhizomes dried at 60 °C had the best antioxidant, polyphenol, and flavonoid properties. Investigation into the influence of different solvents (water, ethanol, methanol, and ethyl acetate) on these attributes revealed that methanol, followed by water, showed most significant effects. Thus, 60 °C–dried rhizomes revealed shorter drying time with accelerated drying rates, and moisture diffusivity and activation energy were observed as 2.3520 × 10−7 m2/s and 41.088 kJ/mol, respectively. It also exhibited conserved qualitative characteristics and had high phytochemical constituents with remarkable antioxidant potential. The results provided a thorough grasp of the diverse traits of C. pictus rhizome powders, suggesting their utilization in herbal formulations and nutraceutical products.

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Authors and Affiliations

  1. Department of Biotechnology, Bannari Amman Institute of Technology, -638401, Sathyamangalam, Tamil Nadu, India

    Saranya Selvakumarasamy & Balakrishnaraja Rengaraju

  2. Department of Food Technology, Rajalakshmi Engineering College, Chennai, India

    Ramalakshmi Kulathooran

  3. Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, Uttar Pradesh, India

    Ayon Tarafdar

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  1. Saranya Selvakumarasamy
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SS—Experimental analysis, validation, manuscript (original draft and review). BR—Supervision and review of the manuscript. RK—Conceptualization. AT—Subject expert for statistical tools.

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Correspondence to Saranya Selvakumarasamy.

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Selvakumarasamy, S., Rengaraju, B., Kulathooran, R. et al. Artificial neural network and mathematical modeling on the drying kinetics of Costus pictus rhizomes and its impact on the polyphenol, flavonoid content and antioxidant activity. Biomass Conv. Bioref. (2023). https://doi.org/10.1007/s13399-023-04958-4

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