Convective drying of pumpkin: Brief literature review and new data for organically produced indigenous pumpkin (Cucurbita pepo L.) over an expanded temperature range

Selected cultivars form part of the neglected and underutilized species (NUS), which can contribute to building sustainable and resilient food systems, particularly for food-insecure households. Advances in the drying of pumpkin cultivars are briefly reviewed. Background on drying, including pretreatment techniques, is discussed. It emerged that convective air drying remains the most used dehydration technique, while most pretreatment and drying approaches, although innovative and promising, have not yet been investigated for pumpkin species. Areas for future scientific investigations are also suggested. A closer look at the literature data revealed notable inconsistencies for pumpkin diffusivity data even for the same species. For this reason, independently of the review, new data are reported in this study for the Cucurbita Pepo cultivar in a quest for more accuracy and a wider temperature validity range. A convective dryer using hot air was used to determine the drying characteristics of pumpkin (Cucurbita pepo L.) slices at four different temperatures (40, 45, 50, 55 and 65) °C at a constant velocity of 1.5 m/s. The extended temperature range and the large number of experimental temperatures were meant to increase the newly reported properties’ accuracy and validity range. The Page model stood out as the most accurate approach to describe the investigated dehydration process. Pumpkin effective diffusivity was calculated as 3.74–7.30 × 10−9 m2/s while the activation energy was 21.07 kJ/mol based on experiments undertaken in the present study. The newly obtained data did not solve the problem associated with inconsistencies between the two data sets found in the literature for drying the same pumpkin cultivar. The reported data would be helpful in the accurate determination of diffusivity data instrumental for convective drying process modelling and optimization.