Greenhouse production of container plants typically involves the intensive use of water and water-soluble fertilizers. To prevent drought stress, water is commonly applied in excess, resulting in leaching and runoff. This can contaminate surface and groundwater with nutrients or pesticide residues (Dumroese et al., 2006). Governmental regulations concerning nutrient solution disposal are becoming increasingly strict around the world. Conservative irrigation practices can be implemented to help growers comply with environmental regulations while reducing production costs (Lumis et al., 2000; Majsztrik et al., 2011). Recirculating irrigation systems, including subirrigation, prevent leaching and runoff because excess nutrient solution is collected and stored for later use (Schmal et al., 2011). Subirrigation can also reduce overall water and nutrient use (Majsztrik et al., 2011). For example, Dumroese et al. (2006) found that subirrigation requires 56% less water than overhead irrigation. However, subirrigation is typically controlled using timers to irrigate based on a pre-determined schedule. Further refinement of subirrigation scheduling practices that apply water based on plant demand would enable growers to more efficiently produce high-quality plants, conserving both water and fertilizer.
Capacitance substrate moisture sensors have been successfully used to monitor and control drip irrigation based on target θ thresholds for containerized plants grown in greenhouses (Burnett and van Iersel, 2008; Garland et al., 2012; Nemali and van Iersel, 2006; van Iersel et al., 2010; Zhen et al., 2014) as well as outdoor nurseries (Bayer et al., 2013). Sensor-controlled drip irrigation can precisely maintain substrate θ close to set values and thereby minimize water use and reduce nutrient leaching (Bayer et al., 2013; Nemali and van Iersel, 2006). Sensor-based automation could also allow growers to have better control over subirrigation. Soil moisture sensors allow real-time θ monitoring, and θ thresholds for triggering irrigation can easily be adjusted to meet particular crop watering requirements or in response to changing environmental conditions.
Soil moisture sensors can be connected to data loggers to automatically measure θ and control irrigation. A limitation is that a basic knowledge of data logger programming and wiring is required (Miralles-Crespo and van Iersel, 2011). However, newly developed hardware and software, specifically designed for greenhouse and nursery irrigation, is expected to make sensor-based irrigation available for growers of ornamental crops in the near future (Kohanbash et al., 2013). Prototype systems have been trialed in commercial facilities and can benefit both growers and domestic users (Chappell et al., 2013; Lea-Cox et al., 2013). Recent research has demonstrated that sensor control can be implemented using low-cost, open-source microcontrollers for small systems (Ferrarezi et al., 2015), whereas extensive wireless networks have been used at large production sites (Chappell et al., 2013; van Iersel et al., 2013). Thus, scale-appropriate solutions for automating subirrigation systems exist for many growers. Subirrigation systems have been successfully automated based on substrate water content using tensiometers (Montesano et al., 2010; Rouphael et al., 2006) as well as capacitance moisture sensors (Ferrarezi et al., 2014).
We assessed the effects of different θ thresholds for controlling irrigation on θ dynamics and plant growth in a sensor-controlled subirrigation system. Our objectives were: 1) to automate a subirrigation system using capacitance-type soil moisture sensors to monitor and control substrate θ; 2) to evaluate short-term substrate θ dynamics in subirrigated pots; and 3) to quantify the effect of different θ thresholds on hibiscus ‘Panama Red’ growth. Hibiscus was chosen as the model crop because of previous work showing its responsiveness to substrate θ (Bayer et al., 2013).
Alem, P.O. 2014 Irrigation, fertilization, and non-chemical plant growth regulation in greenhouse production. PhD diss., Univ. Georgia, Athens, GA
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