The invention relates to a prediction method of hydrocyanic
acid release amount in main
stream smoke of
flue-cured tobacco leaves. The method comprises the steps of subjecting tobacco leaves to be cured firstly to sample pre-
processing such as manual piece tearing, stalk removing and tobacco
cutting; detecting 6 chemical components (water,
chlorine,
malonic acid, volatile acid,
potassium and
total nitrogen) of a sample to be detected; calculating network values of 11 nodes of a
hidden layer according to the detection results of the 6 chemical components and coefficients of input
layers of a model; converting the network values of the 11 nodes of the
hidden layer to output values of the 11 nodes of the
hidden layer; and calculating to obtain a predicted value of the hydrocyanic
acid release amount in the
smoke according to the output values of the 11 nodes of the hidden layer and coefficients of output
layers of the model. According to the method, constant detection of the 6 tobacco chemical components of the sample to be detected is performed, the hydrocyanic
acid release amount in the
smoke can be predicted through the model, and the possible hydrocyanic acid accumulated content in cigarette finished products produced in future can be predicted effectively according to raw materials of the
flue-cured tobacco leaves, so that
raw material choosing in a producing process is guided.