This paper describes a submission to the PlantCLEF 2020 challenge, whose topic was the classification of plant images in the field, based on a dataset composed mainly of herbaria.. This work proposes the usage of domain adaptation techniques to tackle the problem. In particular, it makes use of the Few-Shot Adversarial Domain Adaptation method proposed by Motiian et al. (9). Additionally, a modification of this architecture is proposed to take advantage of upper taxa relations between species in the dataset. Experiments performed show that domain adaptation can provide very significant increases in accuracy when compared with traditional CNN-based approaches.