Method for monitoring preparation of codfish immunoactive peptide on line
An immunoactive peptide, cod technology
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preparation example Construction
[0021] 1) Preparation of network training samples. The training sample refers to the use of trypsin to hydrolyze cod protein, and the hydrolysis reaction is carried out by changing the initial substrate concentration and initial protease concentration, and the hydrolysis degree, free glutamic acid and free lysine of each enzymatic hydrolysis reaction are measured respectively. The degree of hydrolysis of the enzymatic hydrolysis reaction was determined by the ninhydrin method; free glutamic acid and free lysine were measured by biosensors.
[0022] 2) The parameters of the artificial neural network are determined. It mainly includes: the number of hidden layers of the network model, the transfer function, the training function, the learning function, the input layer nodes, the output layer nodes, and the number of hidden layer nodes.
[0023] Determination of the number of hidden layers. A three-layer BP network can complete any N-dimensional to M-dimensional mapping, that ...
Embodiment 1
[0035] Example 1: GLU-BP-ANNs model online monitoring and preparation of immune peptides
[0036] Step 1: Establish and train the GLU-BP-ANNs network model.
[0037] 1) Preparation of network training samples. The training sample refers to the use of trypsin to hydrolyze the cod protein, and the hydrolysis reaction is carried out by changing the initial substrate concentration and the initial protease concentration, and the hydrolysis degree and free glutamic acid of each enzymatic hydrolysis reaction are measured respectively. The degree of hydrolysis of the enzymatic hydrolysis reaction was determined by the ninhydrin method; the free glutamic acid was determined by a biosensor.
[0038] 2) The parameters of the artificial neural network are determined. The hidden layer is 1 layer, the logsig transfer function is used between the input layer and the hidden layer, the linear purelin function is used between the hidden layer and the output layer, the network training functio...
Embodiment 2
[0047] Step 1: Establish and train the LYS-BP-ANNs network model.
[0048] 1) Preparation of network training samples. The training sample refers to the use of trypsin to hydrolyze the cod protein, and the hydrolysis reaction is carried out by changing the initial substrate concentration and the initial protease concentration, and the hydrolysis degree and free lysine of each enzymatic hydrolysis reaction are measured respectively. The hydrolysis degree of the enzymatic hydrolysis reaction was determined by the ninhydrin method; the free lysine was determined by a biosensor.
[0049] 2) The parameters of the artificial neural network are determined. One hidden layer, the logsig transfer function is used between the input layer and the hidden layer, the linear purelin function is used between the hidden layer and the output layer, the network training function uses trainlm, the adaptive learning function uses LEARNGDM, and the input layer nodes are respectively the initial enz...
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