Roasting is one of the widespread methods for processing of nuts that significantly enhances the flavor,color,texture and appearance of products.In this research,the response surface methodology was used to optimize t...Roasting is one of the widespread methods for processing of nuts that significantly enhances the flavor,color,texture and appearance of products.In this research,the response surface methodology was used to optimize the roasting process over a range of infrared power(250–450 W)and roasting times(10–30 min).The moisture content,color parameters(L*,a*,b*and total color difference(DE)),textural characteristics(hardness and compressive energy),energy consumption and sensory evaluation(total acceptation)were determined after roasting and modeled by response surface methodology(RSM).Increasing in roasting IR power and time caused increasing in the energy consumption,a*,b*and DE values.The L*value,moisture content,hardness and compressive energy also decreased with increasing roasting IR power and time.The full quadratic model developed by RSM adequately described the changes in the b*value,moisture content and hardness.The result of RSM analysis showed that all color and textural parameters could be used to monitor the roasting of peanut kernels in an infrared roaster,while application of RSM for developing a predictive model that described the total acceptance changes during roasting of peanut kernels was not successful.To obtain the desired color,moisture,texture and acceptation,the optimum roasting range for production of snack was determined as 370W for 20 min.展开更多
基金The authors would like to thank the Agricultural Research Institute of Minodasht(Minodasht,Iran)for providing raw material and Gorgan University of Agricultural Sciences and Natural Resources for providing the facilities and financial support that make this work possible。
文摘Roasting is one of the widespread methods for processing of nuts that significantly enhances the flavor,color,texture and appearance of products.In this research,the response surface methodology was used to optimize the roasting process over a range of infrared power(250–450 W)and roasting times(10–30 min).The moisture content,color parameters(L*,a*,b*and total color difference(DE)),textural characteristics(hardness and compressive energy),energy consumption and sensory evaluation(total acceptation)were determined after roasting and modeled by response surface methodology(RSM).Increasing in roasting IR power and time caused increasing in the energy consumption,a*,b*and DE values.The L*value,moisture content,hardness and compressive energy also decreased with increasing roasting IR power and time.The full quadratic model developed by RSM adequately described the changes in the b*value,moisture content and hardness.The result of RSM analysis showed that all color and textural parameters could be used to monitor the roasting of peanut kernels in an infrared roaster,while application of RSM for developing a predictive model that described the total acceptance changes during roasting of peanut kernels was not successful.To obtain the desired color,moisture,texture and acceptation,the optimum roasting range for production of snack was determined as 370W for 20 min.
