Coupling machine vision and crop models for closed-loop plant production in advanced life support systems.

We present a conceptual framework for coupling nondestructive sensing to crop models for closed-loop plant production for NASA's program in advanced life support. Coupling is achieved by comparing nondestructive observations with model predictions of plant growth and development. The information thus provided may be useful in diagnosing problems with the plant growth system, or as a feedback to the model for evaluation of plant scheduling and potential yield. We illustrate this concept using canopy height and machine vision measured top projected canopy area (TPCA), and the CROPGRO crop growth model. Model simulations of soybean TPCA and canopy height were evaluated against data for hydroponic soybean grown under two separate light/dark cycle temperature regimes (23/19 degrees C and 26/22 degrees C). Our results suggest that TPCA and canopy height are potentially useful variables for closed-loop plant production in controlled environments during the first few weeks of growth, before canopy closure.