Abstract: Systems and methods for training a machine learning model for generating a structural representation of a plant are provided, as well as systems and methods for generating a structural representation of a plant via such a model. The training method involves encoding a plant image into a structural representation of the plant (e.g. a “skeleton”), decoding the structural representation of the plant into a reconstructed image of the plant, and classifying the reconstructed image as having been generated based on a ground-truth structural representation or output of the encoder. Such classification incentivizes the encoder to produce structural representations which do not “smuggle” texture information (e.g. appearance, such as color). Texture information may be separately represented. The encoder, once trained, may be used to generate structural representations from plant images without necessarily requiring decoding or classification.