Journal of Agricultural Science; Vol. 11, No. 8; 2019 ISSN 1916-9752 E-ISSN 1916-9760 Published by Canadian Center of Science and Education 225 Mathematical Modeling of Thin-Layer Drying Kinetics of Piper aduncum L. Leaves Wellytton Darci Quequeto 1 , Valdiney Cambuy Siqueira 2 , Geraldo Acácio Mabasso 2 , Eder Pedroza Isquierdo 3 , Rafael Araujo Leite 2 , Lucas Rodrigues Ferraz 2 , Renata Henrique Hoscher 2 , Vanderleia Schoeninger 2 , Rodrigo Aparecido Jordan 2 , André Luis Duarte Goneli 2 & Elton Aparecido Siqueira Martins 2 1 Instituto Federal de Educação, Ciência e Tecnologia Goiano, Campus Rio Verde, Goiás, Brazil 2 Faculdade de Ciências Agrárias, Universidade Federal da Grande Dourados, Dourados, Mato Grosso do Sul, Brazil 3 Universidade do Estado de Mato Grosso, Campus de Cáceres, Mato Grosso, Brazil Correspondence: Wellytton Darci Quequeto, Instituto Federal de Educação, Ciência e Tecnologia Goiano, Campus Rio Verde, Goiás, Brazil. E-mail: wellytton_quequeto@hotmail.com Received: March 16, 2019 Accepted: April 27, 2019 Online Published: June 15, 2019 doi:10.5539/jas.v11n8p225 URL: https://doi.org/10.5539/jas.v11n8p225 Abstract As well as most agricultural products, some medicinal plants need to go through a drying process to ensure quality maintenance, however each product behaves differently. Therefore, the present study aimed to evaluate the drying kinetics of spiked pepper (Piper aduncum L.) leaves and determine their thermodynamic properties at different drying temperatures in laboratory scale. Leaves with initial moisture content of 78% w.b. (wet basis) were subjected to drying at temperatures of 40, 50, 60 and 70 ºC and air speed of 0.85 m s -1 in an experimental fixed bed dryer. The drying kinetics of the leaves was described by statistical fitting of mathematical models and determination of effective diffusion coefficient and activation energy. Enthalpy, entropy and Gibbs free energy were also evaluated for all drying conditions. It was concluded that, among the models evaluated, only Midilli and Valcam can be used to represent the drying of Piper aduncum leaves; the first for the two highest temperatures (60 and 70 ºC) and the second for 40 and 50 ºC. The activation energy was approximately 55.64 kJ mol -1 , and the effective diffusion coefficient increase with the elevation of temperature. The same occurs with the values of Gibbs free energy, whereas the specific enthalpy and entropy decrease. Keywords: spiked pepper, AIC and BIC, activation energy, medicinal plant 1. Introduction The species Piper aduncum L., popularly known as spiked pepper, has organic compounds with antifungal action which act on the elimination of skin and hair diseases (Monzote, Scull, Cos, & Setzer, 2017). It has a stimulating action for digestion, liver and healing (Maia et al., 1998). Its essential oil can be used to combat fungi of the species Colletotrichum musae, Trichophyton mentagrophytes, Trichophyton tonsurans and Magnaporthe grisea (Guerrini et al., 2009), besides the action against the protozoa Leishmania amazonenses and Trypanosoma cruzi (Bastos & Albuquerque, 2004; Villamizar, Cardoso, Andrade, Teixeira, & Soares, 2017), which caused infectious diseases in humans. Drying is one of the main processes conducted to ensure the maintenance of quality of most agricultural products. There are several advantages in using drying, such as product preservation, stability of aromatic components at room temperature for long periods of time, protection against enzymatic degradation and oxidation, mass reduction, energy saving for not requiring refrigeration, and it also contributes with more adequate conditions of storage, making the product available during any period of the year. Since it is a complex process, which involves heat and mass transfers (Yilbas, Hussain, & Dincer, 2003; Delgado & Lima, 2016; Haghi & Amanifard, 2008), several studies have been conducted in the attempt to describe drying, especially at laboratory scale, by fitting mathematical models, using statistical parameters. Modeling allows describing the drying kinetics (Al-Ali & Parthasarathy, 2019) and therefore predicting the behavior of the product during the process, as well as optimizing the operation parameters in the dryer project (Nadi, 2016).