A deep learning framework is proposed to recognize large-scale plant species by integrating attention-based deep feature extraction network and plant taxonomy-guided path-based tree classifier. First, a plant taxonomy is constructed for organizing large-scale fine-grained plant species hierarchically in a coarse-to-fine fashion. Second, a deep learning framework is proposed, where attention mechanism is used to remove useless feature components and a plant taxonomy-guided path-based two-layer tree classifier is used to replace the flat softmax classifier in traditional deep convolutional neural network structure. Furthermore, a specific path-based loss function and back-propagation method are proposed to optimize the weight parameters in both deep network and tree classifier. Experimental results on the Orchid2608 plant dataset can also prove that proposed deep attention network with path-based tree classifier can achieve improvements on large-scale plant species identification task.