In the process of flower conservation, due to the lack of professional maintenance technology, the difficulty of flower conservation and high cost, this study proposes a method based on deep learning image classification technology to realize the full automatic flower maintenance. Because the growth of flowers is often affected by many factors, it is easy to make a wrong judgment on the growth of flowers by relying on the classification of flower growth status images. Therefore, this method designs two kinds of flower image features and growth environment parameters. The convolutional neural network of the input channel automatically recognizes the state of flower growth. Experiments show that this method can improve the recognition accuracy of flower growth status, and thus improve the level of automatic maintenance technology of flowers.