Jorge M. Marchetti

Increasing global waste generation is not only a threat but also an opportunity to address energy insecurity and pollution using green valorization techniques. However, this requires pretreatment of waste and byproducts and optimization of drying to obtain high‐quality biofuels. Hence, this study aims to analyze the performance of currently used drying models, the influence of different drying temperatures, drying time, and seed pretreatment on the drying kinetics of two varieties of mango seed. Accordingly, whole seeds and crushed seeds were exposed to five drying temperatures (313–353 K) in a heating furnace. Weight loss was recorded systematically, converted into moisture ratio, and then fitted to four semitheoretical mathematical models, namely: (i) Lewis, (ii) Henderson and Pabis, (iii) Page, and (iv) Avhad and Marchetti models. The fitness of these models was compared using statistical parameters, such as R 2 , X 2 , root mean square error (RMSE), mean bias error (MBE), and mean absolute error (MAE). The results showed that seed pretreatment and increasing the drying temperature led to an increase in the rate of moisture evaporation and reduced the time required for drying. Among all models, the Avhad and Marchetti model provided higher R 2 values of 0.9994 and 0.9991 for local and hybrid mango at 313 K, and 0.9977, and 0.9970 for local and hybrid crushed mango seeds at 353 K and 313 K, respectively; hence, it showed the best performance. The activation energy (Ea) showed a slight differences for both varieties of mango seed and among pretreatments in all mathematical models. The mean Ea values for local and hybrid mango seeds were 41.18 kJ mol −1 and 46.21 kJ mol −1 , respectively. For whole and crushed local and hybrid mango varieties, the mean Ea values were 31.37 kJ mol −1 , 40.80 kJ mol −1 , 50.99 kJ mol −1 , and 51.61 kJ mol −1 . The likely reason for this variation might be differences in variety, chemical composition, growing conditions, and cellular structure of the seed varieties.