Greenhouse, nursery and floriculture operations collectively generate sales over $16.6 billion and employ 4.9% of hired farm workers in the United States [U.S. Department of Agriculture (USDA), 2010]. In greenhouses, the greatest operating cost is labor (USDA, 2010), and technological innovations, which reduce labor dependency, can help growers stay competitive. Automation can be achieved using technologies such as robots, sensors, and computer-controlled systems, which may also improve plant growth and aesthetic attributes and help growers meet environmental regulations (Majsztrik et al., 2011).
Greenhouse operations traditionally use large quantities of irrigation water and fertilizer to maximize plant growth, product quality, and profits (Conover and Poole, 1992). Irrigation frequency is typically based on a predetermined schedule or visual evaluation of plant water status (Ferrarezi et al., 2014), and this may lead to overwatering, which causes leaching and runoff. The release of water and nutrients from greenhouses results in surface and groundwater contamination and may contribute to eutrophication and environmental degradation (Majsztrik et al., 2011). Sensor-based irrigation can be used to minimize or eliminate leaching from containers by precisely regulating the amount of water used for irrigation (Crespo and van Iersel, 2011; Nemali and van Iersel, 2006).
Sensor-controlled irrigation can be based on a variety of measurements, including evaporation (Allen et al., 1998), substrate VWC (Nemali and van Iersel, 2006), and water tension (Shock and Wang, 2011). In these systems, plant water requirements are estimated based on the measured parameters and irrigation is provided accordingly (Blonquist et al., 2005). Because capacitance soil moisture sensors require less maintenance and provide data that are easier to interpret than tensiometers, VWC may be the most useful measurement for automating irrigation systems (Nemali et al., 2007). Capacitance sensors allow for easy automation (Jones, 2004) and such automated irrigation is reliable (Nemali and van Iersel, 2006) and can be used with a variety of container sizes (Shock and Wang, 2011) and irrigation systems.
A basic system can be made with capacitance sensors, a microcontroller, and solenoid valves, which open when VWC measurements drop below a predetermined threshold value. Such systems have been successfully used for small-scale experiments with several greenhouse crops, including gaura [Gaura lindheimeri (Burnett and van Iersel, 2008)], petunia [Petunia ×hybrida (van Iersel et al., 2010)], and ‘Panama Red’ hibiscus (Bayer et al., 2013). More advanced systems have recently been tested in production nurseries (Chappell et al., 2013; Lea-Cox et al., 2013). Cayanan et al. (2008) describe the design of a wireless, automated irrigation system that integrates with the greenhouse environmental control system. Although precision irrigation systems can drastically improve water and nutrient management in greenhouses and container nurseries, they often rely on high-precision dataloggers and computers, making those systems expensive. In addition, they typically require expertise to install and maintain (Crespo and van Iersel, 2011). Our goal was to develop a low-cost, stand-alone irrigation controller.
Low-cost open-source microcontrollers can be used to automate sensor-based irrigation. Simple and reliable microcontrollers with broad functionality have been available since 2005, when Arduino (Ivrea, Italy) made the first of its models available. Silva et al. (2013) describe the use of a microcontroller (Fio, Arduino) to build an irrigation controller, using a cheap soil moisture sensor (less than $5). However, the soil moisture sensor they used (SEN0114; DFRobot, Shanghai, China) is low tech, has exposed electronics, and does not appear to be waterproof. This sensor measures electrical conductivity as a proxy for VWC, which makes the sensors extremely sensitive to salts in the substrate or soil. Silva et al. (2013) also did not test how well their controller could maintain various VWC levels. Recently, Bitella et al. (2014) described the use of a low-cost open-source hardware platform, using another microcontroller (Mega 2560 R3, Arduino), for monitoring soil water content and multiple soil, air, and canopy parameters. However, they did not control irrigation based on the collected data; it was used for monitoring purposes only.
Our objective was to use open-source microcontrollers with capacitance soil moisture sensors to monitor and log VWC and control irrigation based on real-time measurements. This low-cost technology can easily be installed and used in a variety of settings including greenhouse and nursery production or research, home gardens, lawns, and small farms.
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