Mushroom identification method based on BP neural network

Mushrooms, as a delicacy in people's lives, are deeply loved by people, and the nutrients in mushrooms play an essential role in people's health. However, the characteristics of poisonous mushrooms and non-toxic mushrooms are extremely similar, and they are easily confused in the field of miscellaneous circumstances, and therefore often cause the eaters to ingest poisoning. The identification of poisonous mushrooms is a basic measure to avoid poisoning. At present, the methods for identifying poisonous mushrooms mainly include shape recognition method based on folk experience, chemical analysis methods, and animal testing methods. However, these methods have some disadvantages such as low accuracy in the practical application identification, complex experimental equipment required, unsatisfactory detection of unknown toxins, and long experimental period. Aim at the deficiency of the traditional poisonous mushroom identification method; this paper proposes a poison mushroom identification method based on BP neural network. Through the learning of the characteristics of the known poisonous mushroom, identify unknown poisonous mushrooms.