摘要
该文研究了热处理对减小西红柿贮藏中呼吸强度的作用及其控制。在试验中以5～40℃温度作为输入参数,输出参数为西红柿的呼吸强度,通过动态控制温度降低呼吸强度。目标函数是平均呼吸强度的倒数。通过神经网络来模拟确定温度对呼吸强度的动态影响,神经网络模型的输出结果与实验观察结果拟合很好。优化控制通过4个控温步骤,经过基因算法使目标函数最大,即呼吸强度最小,从而降低西红柿呼吸强度,减缓贮藏品质的衰败。
The effect of heat treatment on the respiration rate and optimal control for respiration of tomato fruit was studied. The storage temperature was the control input varying from 5~40℃ and the changes of tomato respiration rate was monitored as an output. The purpose was to minimize the respiration by the temperature ((e.g. heat) treatment). An objective function was given by the reciprocal number of the average value of the respiration rate. The dynamic changes in the respiration rate affected by temperature, was first identified using neural networks. A neural-network model identified here showed a good agreement with the observed responses of respiration. The temperature control process was divided into 4 steps (l=4) and the optimal 4 step points of temperature which maximize the objective function were obtained using genetic algorithms. The optimal control method was found effective in reducing respiration rate of tomato fruit during the storage.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2004年第2期199-203,共5页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家自然科学基金项目(30270765)
关键词
西红柿
采后热处理
呼吸强度
优化控制
tomato fruit
post-harvest heat treatment
respiration rate
optimal control
