|Authors: ||J.D. Lea-Cox, B.E. Belayneh|
|Keywords: ||web-based, sensor networks, monitoring, control, micro-pulse|
Irrigation scheduling in ornamental operations is complex, given the large number (100-500) of species grown by individual growers and rationalization of many environmental variables, required to make precision irrigation decisions on a daily basis.
We have developed a smart wireless sensor node (nR5) that is capable of integrating outputs from a range of soil moisture and environmental sensors, to schedule irrigation events based on plant daily water use.
During 2012, we imple-mented a sensor-controlled vs. grower-controlled irrigation study at a pot-in-pot nursery in McMinnville, TN. Sensor networks were installed in two separate produc-tion blocks of 3-year-old Cornus florida (dogwood) and 2-year-old Acer rubrum (red maple) trees grown in 58-L and 116-L containers, respectively.
One row of trees in each block were irrigated using sensor-based micropulse irrigation; the adjacent row and the rest of the block was independently irrigated by the grower using standard 6-minute irrigation events, typically scheduled between 2 and 4 times per day.
All sensor data were logged by the nodes on a 15-min basis, and sensor-controlled irrigations were based on the running average from five individual trees per block.
Tree diameters (n=10) were measured for each treatment four times during the year, to provide comparative growth data for each species.
During 2012, average daily irrigation water applied by the grower to the dogwood block totaled 3.57 L/tree, compared to 1.33 L/tree applied using sensor-controlled irrigation.
This near 3-fold increase in irrigation-efficiency did not reduce growth or quality of this species.
We anticipate a return on investment of between three months and one year for sensor networks, depending on location, production costs and the cost of water.
With reliable sensors and easy-to-use software, we are providing real-time information to growers who are scheduling irrigation applications more precisely, greatly reducing water use, reducing production costs and increasing profitability.
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