Improvements in sensor technology coupled with advances in knowledge about plant physiology have made it feasible to use real-time substrate volumetric water content sensors to accurately determine irrigation timing and application rates in soilless substrates in greenhouse and container production environments (Belayneh et al., 2013; Burnett and van Iersel, 2008; Lea-Cox et al., 2010). Wireless transmission of sensor data allows for real-time management of the irrigation system. Wireless sensor-based irrigation management offers significant potential benefits to greenhouse operators (Nemali et al., 2007; Scoggins and van Iersel, 2006). By matching water applications with moisture availability and plant uptake rates, sensor-based irrigation can reduce irrigation water use without risking adverse consequences from under- or overwatering. Better matching of moisture availability with plant demands can also reduce leaching of nutrients, resulting in fertilizer savings as well as water savings. In the many watersheds where runoff of nutrients causes eutrophication, reductions in nutrient leaching can benefit the environment as well as contribute to growers’ bottom lines (Majsztrik et al., 2013). Wireless soil moisture sensor systems provide more accurate measurements of substrate moisture status than qualitative methods (weight, appearance, length between irrigation cycles, etc.) and require less labor (Lea-Cox et al., 2010; Majsztrik et al., 2011; Nemali and van Iersel, 2006; van Iersel et al., 2009).
Savings in irrigation water, labor, energy, and fertilizer expenditures are obvious potential benefits of soil moisture sensor systems. Other potential benefits of sensor systems are less obvious. Greater precision in maintaining soil moisture at desired levels can lower disease pressure, often caused by precautionary overwatering (Chappell et al., 2012). Lower disease pressure means reduced crop losses in addition to less fungicide use. Better matching of water availability to plant uptake has also been shown to accelerate growth in some instances (Chappell et al., 2013). Shorter production times mean higher profits, just as lower costs do.
Achieving these potential benefits requires installation and calibration of equipment and software (Kohanbash et al., 2013). In essence, sensor-based irrigation systems substitute capital for water and associated variable inputs such as energy, labor, and fertilizer (Shani et al., 2009). The profitability of investing in wireless sensor systems thus depends on the relative magnitudes of benefits and costs. Those benefits and costs are incurred at different times: Investment in sensor systems is made up front, while reductions in spending on water, energy, labor, fertilizer, and pesticides accrue later on, as do any benefits from shortening production time or reducing disease losses. This paper presents a methodology for calculating the profitability of investing in sensor-based irrigation management that takes these differences in timing into account. It then applies that methodology to data from gardenia production in a Georgia nursery as part of a project focused on implementation of wireless irrigation sensor networks for ornamental plant production.
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