CAN ACCURACY ISSUES OF LOW-COST SENSOR MEASUREMENTS BE OVERCOME WITH DATA ASSIMILATION?

The use of mechanistic plant growth models relies on the availability high-quality inputs to reduce uncertainty in estimates. Measurements photosynthetically active radiation inside a protected environment are either more expensive obtain or dependent assumptions regarding external measurements. This study aimed influence measurements low-cost lux meters by using data assimilation strategy. We first determined, simulation, impact different sensors then used Ensemble Kalman Filter assimilate artificial observations tomato Reduced-State Tomgro model, simulations for which solar were obtained from meter. compared assimilated estimates that with scientific-grade quantum sensor. For periods larger intensity, differences both instruments larger, low errors lead closer ones scientific grade sensors. These results suggest could be environments, provided there also imperfect state.