Drying kinetics and modeling of the physical properties of bean grains

• Ano de defesa: 2023
• Autor(a) principal: Araujo, Marcos Eduardo Viana de
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Viçosa; Engenharia Agrícola
• Palavras-chave em Português: Feijão - Medição; Grãos - Medição; Grãos - Tamanho; Análise numérica; Análise volumétrica; Engenharia de Processamento de Produtos Agrícolas
• Link de acesso: https://locus.ufv.br//handle/123456789/31588; https://doi.org/10.47328/ufvbbt.2023.230

Common bean is one of the most produced and consumed legumes worldwide. The nutritional quality of this food has made it a fundamental constituent in the diet of thousands of people every day. However, the losses observed during the productive chain of this culture show that the equipment and operations are dimensioned/conducted inefficiently. Over the years, technological advances in the food industry have required up-to-date data on the engineering properties of agricultural products, aiming to optimize processes and reduce losses at all stages of the agricultural production chain. Although the determination of the properties of several products is available in the literature, the genetic improvement and advancement of cultivars have made the industry optimize its processes based on obsolete data, which no longer represent the characteristics of the material. Given the above, this study aimed to determine and model the geometric properties (circularity, sphericity, geometric diameter, projected area, surface area, volume, and surface-to-volume ratio), physical (real and apparent specific gravity, porosity, and 1000-grain mass), aerodynamics (terminal velocity and drag coefficient), and thermal (specific heat, thermal conductivity, and thermal diffusivity) of common bean grain as a function of water content. Furthermore, the drying kinetics and thermodynamic properties (enthalpy, entropy, and Gibbs free energy) of drying were obtained for different temperatures. This comprehensive determination of the properties and behavior of bean grains during drying will be of great use not only for industry but for all areas that require specific knowledge of the evaluated properties. To determine the aforementioned properties, except for drying kinetics and thermodynamic properties, bean grains with an initial water content of 0.41 (decimal, d.b.) were dried at 45 ± 2 °C to different levels of water content. The properties were obtained experimentally, and regression models were adjusted to represent the variation of properties as a function of water content. To obtain the geometric properties, an algorithm in the Phyton language was developed to obtain the characteristic dimensions of the grains from digital images. The results were compared to the traditional method, where measurements are obtained by a digital caliper. To determine the drying kinetics and thermodynamic properties of the drying of bean grains, the grains were subjected to drying at different temperatures (40, 50, 60, 70, and 80 ± 2 °C). The experimental data were adjusted to literature models commonly used to describe the drying process of agricultural products. In addition, a CFD (Computational Fluid Dynamics) analysis was carried out to demonstrate the feasibility of computational modeling in predicting the drying process. The results obtained in this study showed that the use of digital images to obtain the characteristic dimensions of grains was highly effective. Among the geometric properties, projected area and volume showed the greatest variations during drying. The Araujo-Copace model satisfactorily described the volumetric contraction of the grains. Among the physical, aerodynamic, and thermal properties, the 1000-grain weight, the drag coefficient, and the thermal conductivity showed the greatest variations during the drying process. The modified Henderson and Pabis model satisfactorily represented the drying kinetics of bean grains at all evaluated drying temperatures. CFD analysis proved to be a powerful tool for predicting the drying process, with low errors compared to experimental data. The effective diffusion coefficient and the thermodynamic properties of drying showed values consistent with those found for other agricultural products. Keywords: Moisture diffusivity. Numerical modeling. Phaseolus vulgaris. Size and shape. Volumetric contraction.L