神经网络优化TG酶在罗非鱼鱼糜中的加工工艺
Optimization of the technology for applying transglutaminase to produce surimi gel from tilapia by neural network
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摘要: 通过对谷氨酰胺转氨酶(TGase)作用条件(添加量、凝胶温度和凝胶时间)对罗非鱼碎肉鱼糜凝胶强度的影响进行研究,在获得一定实验数据基础上利用得到的人工神经网络(ANN)模型对其工艺进行优化。结果表明:所建立的神经网络模型具有较好的预测能力,可准确地预测TG酶的作用条件与鱼糜凝胶强度的关系,预测值与实验值的相对误差较小(R2=0.9936);罗非鱼碎肉鱼糜的凝胶强度受TG酶的作用条件影响较大,其在实际生产中的最佳条件为:TGase添加量37U/100g鱼糜,作用温度37.5℃,作用时间43min。此条件下,罗非鱼碎肉鱼糜凝胶强度能够达到(9103±725)g·mm,具有较好的作用效果。Abstract: The effect of main processing condition(TGase addition,reaction temperature,reaction time) on the gel strength of frittered meat of tilapia surimi gel were investigated. The processing parameters were optimized by neural network and the neural network model was established. The results showed that the established neural network model was more reliable which could accurately predict the relationship of the gel strength and processing condition. The relative error of predicted values and experimental values was relatively small(R2=0.9936). When the condition of TGase addition of 37U/100 g surimi,reaction temperature of 37.5℃,reaction time of 43 min,the gel strength reached(9103±725)g·mm. Under these processing conditions,the gel strength was appropriate.
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