The integration of mechanistic modeling and machine learning with biofeedback into hybrid, modular models can facilitate a transition to more dynamically controlled environment agriculture. This paper outlines several pathways to hybridization with modern sensing, latent state monitoring, and technological interventions to optimize cultivation and resource use efficiency.