Irrigation & Heat Stress Automation

Industry Partners: Nelson Irrigation Corp., Wiseconn Engineering, SWAN Systems, Dynamax Inc.

WSU Team: Srikanth Gorthi, Dattatray Bhalekar, Juan Munguia, Lav Khot, Bernardita Sallato, R. Troy Peters

Orchard irrigation automation is essential to realize block uniformity and optimal yield following sustainable production practices. At WSU Smart Apple Orchard testbed, we have multiple commercial partners collaborating with Washington State University team to evaluate their soil-plant-atmosphere continuum sensing, climatic modeling driven decision support, and automated line control at block level. In 2024 season, the evaluation is being conducted in two blocks 1 and 2 as in figure below demonstrating two scenarios.

Smart apple orchard testbed block with tall spindle training at 12 x 3 ft spacing (managed by NWFM, LLC in Mattawa, WA).
Smart apple orchard testbed block with tall spindle training at 12 x 3 ft spacing (managed by NWFM, LLC in Mattawa, WA).

Scenario 01

In block 2, the irrigation (and heat stress) has been managed by the Northwest Farm Management LLC. using a controller (TWIG-V, Nelson Irrigation Corp.) tied to soil moisture probes data (Semios Inc., CA). This has been depicted below. These probes are installed at 8, 16, 24, 36-in. and send data to Semios web interface. Typically, block manager uses their historical knowledge about site and soil moisture probe data to schedule weekly irrigation as well as continual refinements periodically. This scheduling is done via Nelson web interface and pushing it to the TWIG® controller. Note that Nelson Irrigation offers additional automation solutions. Moreover, soil and plant water stress indicators are being collected using sap flow sensors (SGA100-WS, Dynamax Inc.).

In block 2, the cooling system is automated using Nelson TWIG-V® controller with 20-minute ON and 40-minute OFF cycle. The scheduling is performed based on the weather forecasts and the cycle typically starts at noon time and continues until 18:00. 

Schematic of irrigation and heat stress automation in block 2
Schematic of irrigation and heat stress automation in block 2

Scenario 02

In block 1, irrigation system has been completely automated using a centralized controller (RF-X1, Drop Control, Wiseconn Engineering). Soil moisture probe (Drill & Drop 36’’, Sentek Inc.) data from up to 3 ft (90 cm) is being logged using a field station node (RF-X1, Drop Control, Wiseconn Engineering) at 15-min interval. SWAN Systems uses this data along with AWN weather station data, crop coefficient (varied across the season), and site-specific weather forecasts (Source: MeteoBlue, Basel, Switzerland) to run the climatic model to realize a weekly irrigation schedule. SWAN Systems has a web interface to run the scheduling scenarios and push it to the controller (e.g., Drop Control, Wiseconn Engineering).

Schematic of irrigation and heat stress automation in block 1
Schematic of irrigation and heat stress automation in block 1

In block 1, commercial partners have also integrated hardware to realize automated fogging actuation to mitigate heat stress in summer months. Overhead fogging system has been installed underneath the netting (12% shade net). An IR temperature sensor (SapIP-IRT, Dynamax Inc.) continually monitors the canopy temperature in upper top sections at 15-min interval. At set threshold of canopy temperature (e.g.: 101 °F) drop controller triggers actuation of solenoid valve to operate foggers (Jain by Rivulis, USA) with a differential temperature (6 °F) to turn off the cooling system.

Ground Truthing

In block 1, WSU PrecisionAg group has installed water flow meters (SW-3L, Dragino Inc.) to monitor and quantify water used for heat stress mitigation. This block also has micro-tensiometer probes (MT FloraPulse, Davis) inserted into the trunks for real-time plant water status monitoring along with soil moisture probes (TEROS 12, Meter Group Inc.) at 8 and 24 in. for soil moisture tracking. An all-in-one weather station (ATMOS 41, Meter Group Inc.) has been deployed inside and outside the orchard to quantify the orchard effects on weather variables. For evapotranspiration (ET) estimation and its comparison with weather data derived estimates, an eddy covariance based actual ET sensor (LI-710, LI-COR Environmental) has been deployed at 6 ft (2-m) above the canopy. All the data gets collected through LoRaWAN (Long range wide area network) based wireless sensing network (WSN) developed by our team. Similarly in block 2, micro-tensiometer and soil moisture probes have been installed to monitor plant and soil water status. In addition, Sallato lab has been doing ground truthing of canopy water stress and nutrient status.

Significant Findings (Year 1)

  • In scenario 2, where irrigation scheduling was based on a commercially available model that uses soil moisture, localized weather and forecasts data as inputs, 52.4% water saving was realized compared to grower control block.
  • Similarly, 46.4% of water saving was observed for precision and automated heat stress management using real-time canopy temperature driven cooling system actuation.
  • Grower control block (scenario 1) had larger fruit; weight and diameter equivalent to one box size different (56 to 64 mm). Starch levels were lower; however, this difference has no agronomic significance. 
  • The estimated effective yield in automated block was 21% higher, with 232% higher water use efficiency compared to Grower control block. Per the estimates, Automated and Grower control block respectively had about 116 and 50 lbs of fruit per thousand gallons of water applied.

As part of WSU research trials, we are evaluating various fogging systems to mitigate heat stress in apples. For more information, please click here.