Vacuum drying optimum conditions and lowest energy consumption were investigated by surface response methodology and process simulation in Aspen Plus. Temperature, time and vacuum pressure effects on moisture, effective diffusivity, polyphenols and antioxidant capacity were evaluated. As a result, temperature was the most significant variable controlling the different responses. Optimum drying conditions were 68.33C, 46.33 kPa (abs) and 4.27 h. Dried apple pomace was obtained with 10% final moisture, 2.44 mg gallic acid equivalent/g as total polyphenolic content and 98.59 μmol Trolox equivalent/g as oxygen radical absorbance capacity. From simulation results, lower energy demand (1.2 kWh/kg of pomace) was obtained compared with other drying methods. Sensitivity analyses showed that apple pomace inlet temperature and apple pomace moisture content impacted energy requirements, whereas pressure and temperature adjustments inside the dryer did not. As a result, vacuum drying might be a feasible alternative to preserve antioxidants in apple pomace.
Practical Applications
Currently, there is an interest for developing economically feasible processes capable of recovering polyphenols from apple pomace in order to use such compounds in the food industry. Research has been performed regarding the optimization of polyphenols' solvent extraction. Preservation operations such as drying are critical before extraction. Vacuum drying is known as an efficient technique when processing temperature‐sensitive materials such as polyphenols. So far, there is no research available regarding vacuum drying effects in apple pomace polyphenols and antioxidant capacity. Because of this, this paper contributes to fill this gap, so the industry can implement this kind of process in the near future with the minimum negative effects in the polyphenolic and antioxidant capacity available; all this while having an efficient vacuum drying process.
Sustainable processes have recently awaked an increasing interest in the process systems engineering literature. In industry, this kind of problems inevitably required a multi-objective analysis to evaluate the environmental impact in addition to the economic performance. Bio-based processes have the potential to enhance the sustainability level of the energy sector. Nevertheless, such processes very often show variable conditions and present an uncertain behavior. The approaches presented for solving multi-objective problems under uncertainty have neglected the potential effects of different quality streams on the overall system. Here, it is presented an alternative approach, based on a State Task Network formulation, capable of optimizing under uncertain conditions, considering multiple selection criteria and accounting for the material quality effect. The resulting set of Pareto solutions are then assessed using the Elimination and Choice Expressing Reality-IV method, which identify the ones showing better overall performance considering the uncertain parameters spacePeer ReviewedPostprint (author's final draft
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