Fruit tree variety identification method based on visible near infrared spectrum

The invention discloses a fruit tree variety identification method based on a visible near infrared spectrum. The invention relates to the fruit tree variety identification method based on the fruit tree leaf visible near infrared spectrum, which is mainly composed of a convolution noise reduction auto-encoder (CDAE) and a random forest (RF), wherein the convolution noise reduction auto-encoder is mainly used for carrying out feature extraction on fruit tree leaf visible near infrared spectrum data; and the random forest classifier is responsible for classifying the features extracted by the convolution noise reduction auto-encoder so as to identify different varieties of fruit trees. According to the fruit tree variety identification method, feature values are extracted by using the convolution noise reduction auto-encoder, the method has the advantages of high classification accuracy, strong noise immunity, good feature extraction capability, omission of a data preprocessing step and no need of spectrum pre