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Artificial neural networks modeling of kinetic curves of celeriac (Apium graveolens L.) in vacuum drying

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Drying agricultural products is one of the oldest methods to store them and prevent them from decay. Safe storage, less volume, longer shelf life, easy packing and transport, improving economical… Click to show full abstract

Drying agricultural products is one of the oldest methods to store them and prevent them from decay. Safe storage, less volume, longer shelf life, easy packing and transport, improving economical value and producing usage diversity are the advantages of drying (Babalis & Belessiotis, 2004; Torki-Harchegani et al., 2015). Dpen sun and shade methods is a traditional drying method that has been employed for the dehydration because of low costs and simplicity. However, these methods have some problems such as microbial contamination of the dried materials, dust as well as long drying time (Soysal, 2004). To overcome these problems, it is essential to employ artificial dryers for the removal of water from agricultural and food products (Demiray & Tulek, 2012). The type of dryer must be suitable for specific product attributes required. Omproper drying causes quality deterioration of product, unreasonable charges, high energy consumption, high process duration, etc. Therefore, food drying is heat sensitive and demands special attention (Mujumdar, 2014).

Keywords: modeling kinetic; neural networks; networks modeling; kinetic curves; artificial neural; curves celeriac

Journal Title: Food Science and Technology
Year Published: 2019

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