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Optimization of Process Parameters of Continuous Microwave Drying Raspberry Puree Based on RSM and ANN-GA 被引量:1
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作者 Zheng Xian-zhe Gao Feng +2 位作者 Fu Ke-sen Lu Tian-lin Zhu Chong-hao 《Journal of Northeast Agricultural University(English Edition)》 CAS 2023年第1期69-84,共16页
To improve drying uniformity and anthocyanin content of the raspberry puree dried in a continuous microwave dryer,the effects of process parameters(microwave intensity,air velocity,and drying time)on evaluation indexe... To improve drying uniformity and anthocyanin content of the raspberry puree dried in a continuous microwave dryer,the effects of process parameters(microwave intensity,air velocity,and drying time)on evaluation indexes(average temperature,average moisture content,average retention rate of the total anthocyanin content,temperature contrast value,and moisture dispersion value)were investigated via the response surface method(RSM)and the artificial neural network(ANN)with genetic algorithm(GA).The results showed that the microwave intensity and drying time dominated the changes of evaluation indexes.Overall,the ANN model was superior to the RSM model with better estimation ability,and higher drying uniformity and anthocyanin retention rate were achieved for the ANN-GA model compared with RSM.The optimal parameters were microwave intensity of 5.53 W•g^(-1),air velocity of 1.22 m·s^(-1),and drying time of 5.85 min.This study might provide guidance for process optimization of microwave drying berry fruits. 展开更多
关键词 raspberry puree continuous microwave drying response surface method(RSM) artificial neural network(ANN) genetic algorithm(GA)CLC number:TG376 Document code:A Article id:1006-8104(2023)-01-0069-16
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