Control of Crop Growth and Nutrient Supply by the Combined Use of Crop Models and Plant Sensors

Abstract Some important challenges in greenhouse horticulture are to nullify losses of water and nutrients to the environment and to predict and to plan product quantity and quality, such that it meets the demands of the customers. In this paper an integrated system for monitoring and controlling process water and crop growth in closed greenhouse systems is briefly described. As part of the integrated system, the combined use of crop models and plant sensors for controlling crop growth and nutrient supply are discussed in more detail. A mechanistic model for tomato has been developed that simulates the dry weight and fresh weight growth of the different plant organs, transpiration, water use, and demand and uptake of the different macro nutrients. Some of the most important parameters of the model are light interception and leaf photosynthesis. It is shown how light interception of a lettuce crop can be estimated noninvasively from measurements of infra red reflection. Actual photosynthetic rate of tomato leaves can be estimated non-invasively from measurements of the rate of electron transport using chlorophyll-fluorescence. Photosynthetic capacity of tomato leaves can be estimated noninvasively from measurements of light-induced absorbance changes around 820 nm. It is discussed that both sensors and models have some shortcomings. By combining sensor information and a simulation model these shortcomings can be overcome and hence a powerful tool to control crop growth and nutrient supply can be generated.