Cigar raw material sensory quality prediction method based on BP neural network

The invention discloses a cigar raw material sensory quality prediction method based on a BP neural network. The cigar raw material sensory quality prediction method comprises the steps of obtaining cigar tobacco leaf samples; the cigar tobacco leaf sample is treated to obtain a cigar tobacco leaf treated sample, and the cigar tobacco leaf treated sample comprises a training sample and a test sample; constructing a BP neural network model, and inputting the training sample into the BP neural network model for training to obtain a trained BP neural network model; obtaining the conventional chemical component content of the test sample; and inputting the conventional chemical component content of the test sample into the trained BP neural network model to obtain the sensory quality of the cigar raw material. The prediction model can be extended to the prediction process of sensory quality index scores of cigar raw materials in other production areas, and provides powerful technical support for applying the neur