If you can measure it, then you can manage it. In agriculture, the ‘it’ you are dynamically managing is a combination of your product (the crop) and your most valuable asset (your land). But what do you measure? What can you measure and how do you measure it?
Advances in engineering, agronomy, and data science provide great promise for optimizing agricultural production, but without a thorough site characterization these tools cannot be deployed to their fullest capacity. Terms like precision management, variable rate technology, artificial intelligence, machine learning, and dynamic modeling are not fully enabled in agriculture without the creation of a digital twin. The field-scale digital twin is necessary in order to get to the next level of optimization in agriculture because it gives the manager many more measurements and enables continuous improvement.