Considering the Value of Real-Time Sensor Information

Wireless sensor networks are allowing specialty crops growers to collect precise environmental and production data, including temperature, relative humidity, total and photosynthetically active radiation, rainfall, leaf wetness, wind speed and direction, soil moisture, irrigation water application, leaching volumes and soil / substrate electrical conductivity.  We have established a number of sensor networks in nursery and greenhouse operations with different configurations, to provide instantaneous (typically 5-15 minute interval) and long-term (seasonal; yearly) information for answering specific research and crop production questions.  The long-term goals of this research are to provide site-specific information to growers about current irrigation practices, to assess the ability of these sensors to precisely monitor and control water applications in these diverse and complex production environments, and to increase resource use efficiency and reduce costs. We are also focused on how growers use this sensor information, specifically which data gives the most benefit to the grower for making irrigation decisions in their operation and which has a rapid return on investment.  Some questions remain about the quality and quantity of information that growers require (to make the most informed decisions on which sensors are necessary), and where sensors are best deployed to achieve intended objectives.  Conversely, we need to quantify the value that this information provides in light of equipment, operational and maintenance costs.  By using databases and graphical software to integrate these data (e.g. degree-day, vapor pressure deficit and daily light integral calculations) into models for plant growth, water use and insect phenological development, we are entering a realm where this information could have major benefits not only on reducing water and nutrient use, but also on pest and disease management decisions.  These concepts will be illustrated using a preliminary cost-benefit analysis based on sensor network data from a field nursery in Maryland and a pot-in-pot container operation in Tennessee during Mar–Oct, 2010.