Water is a precious resource that is becoming increasingly scarce as the population grows and water resources are depleted in some locations or under increased control elsewhere, due to local availability or groundwater contamination issues. It obviously affects strawberry (Fragaria x ananassa Duch.) production in populated areas and water cuts are being imposed to many strawberry growers to save water, with limited information on the impact on crop yield. Precision irrigation technologies are becoming increasingly important on the market and offers the unique opportunity to generate some water savings. Field studies were conducted on two different years, on a very fine Hueneme sandy loam in Oxnard, California, testing different irrigation setpoints imposed using real-time wireless tensiometry for soil matric potential determination. An optimal setpoint for initiating irrigation found earlier to be around -10 kPa was imposed and resulted in maximum yield relative to a conventional irrigation management. Deficit irrigation initiating watering at about -35 kPa resulted in water savings up to 26% but caused a significant yield drop between 5% to 9%. A variable setpoint based on attempting to match the soil capacity to water supply and  plant demand was also tested as a third scenario and compared to the -10 kPa constant irrigation setpoint treatment. A 18% water saving was generated relative to the -10 kPa irrigation treatment and limited the yield decrease to 2%. While low, this decrease has a very important economic impact for growers. Indeed, decreases in expenses due to water savings did not compensate for decreased revenues due to strawberry yield drop. Additional studies should therefore be conducted to estimate this yield drop more accurately given the important financial losses associated with it.

In agriculture, use of sensors and controllers to apply only the quantity of water required, where and when it is needed (i.e., precision irrigation), is growing in importance. The goal of this study was to generate relatively homogeneous management zones and determine optimal placement of just a few sensors within each management zone so that reliable estimation of plant water status could be obtained to implement precision irrigation in a 2.0 ha almond orchard located in California, USA. First Fuzzy C-means algorithm was used to create management zones using stable soil properties.  Following the creation of management zones, a slightly modified Fuzzy C-Means algorithm was used to choose the best places to locate the leaf monitors, a specially developed sensor to detect plant water status, in the field. The methodology and algorithm allowed not only the generation of efficient management zones based on soil and plant characteristics, but also the placement of a limited number of sensors within each management zone to capture spatial variability in plant water status. The algorithm can also be helpful in placement of proximal sensors in field crops.

Vineyards worldwide are subjected to spatial variability, which can be exhibited in both low and high yield areas meaning that the vineyard is not achieving his full yield potential. In addition, the grapes quality is not uniformed leading to different wine qualities from the same plot. The assumption is that a variability in available water for the plant due to soil variability leads to the observed yield variability. A variable rate drip irrigation (VRDI) concept was developed to reduce such variability. The VRDI system divides the vineyard into 30 x 30-meter irrigation zones, enabling individual irrigation of each zone according to a model based on normalized difference vegetation index (NDVI) maps. Before the VRDI installation, the natural variability of the plot was recorded by measuring LAI, SWP, and yield in a 1.2-hectare vineyard Syrah red grape in Israel during 2014. The first VDRI system was installed on the plot and operated in the 2016 and 2017 seasons. The VRDI system enabled to apply more water to areas were the vines vigor was low, and less water to vines with high vigor during 2014.  Following the operation of VRDI system, the yield, leaf area index (LAI), canopy size, water potential, and primary juice chemical analysis results were very uniformed across the plot in comparison to previous years with applying uniform irrigation across the vineyard.

Variable rate irrigation (VRI) systems use intelligent electronic devices to control individual sprinklers or groups of sprinklers to deliver the desired amount irrigation water at each specific location within a field according to VRI prescriptions. Currently VRI systems, including software tools for generate prescription maps, are commercially available for VRI practices. However, algorithms and models are required to determine the desired amount of water that needs to be applied based on the temporal and spatial variability of soil and plant characteristics. While irrigation scheduling can be based on soil water balance calculations, direct monitor of plant growing status is another method that has potential application for irrigation scheduling. Plant canopy temperature is related with plant water stress. Plant height is useful as an indicator of plant health conditions and can be used to estimate yield potential. Therefore, measurements of plant canopy temperature and plant height coupled with spatial information in field can be used for determining VRI water depths. A wireless data acquisition (WDAQ) system was developed to collect plant canopy temperature and plant height data in the field. The system included two WDAQ units installed on a 4-span center pivot VRI system. One unit was mounted at the middle of the third span, and the other at the fourth span from the pivot. Each unit consisted of a GPS receiver, programmable data logger, infrared temperature sensor, ultrasonic distance sensor, solar power supply, and wireless data transmitter/receiver. Inferred temperature sensors were used to detect the canopy temperature while the ultrasonic distance sensor to measure plant height. The WDAQ system was capable of continuously and simultaneously making measurements of plant canopy temperature and plant height, and recording spatial coordinates at each measurement location as the center pivot moved around the field. Data collected were wirelessly transferred to a wireless receiver for data process. This WDAQ system has been tested in field. The results indicated the system had great potential to be used for automatic creation of VRI prescription maps and plant-based irrigation scheduling.

Center pivot irrigation systems are commonly used for corn and cotton production in the southeast USA. Technology for variable rate water application with center pivots is available; however, it is not widely used due to increased management requirements. Methods to develop dynamic in-season prescriptions in response to changing crop conditions are needed to move this technology forward. The objective of this research was to evaluate the potential of using normalized difference vegetative index (NDVI) to estimate crop coefficients for development of spatial irrigation prescriptions. Field studies were conducted near Florence, SC, USA under center pivot irrigation systems equipped with variable rate technology. Studies in maize were conducted over several years comparing NDVI-based irrigation management to management with soil water sensors. The soil water sensors treatments were based on maintaining soil water potentials above -30 kPa (approximately 50% depletion of plant available water).  The NDVI based treatment used spatially measured NDVI values to calculate spatial crop coefficients used in the FAO 56 dual crop coefficient method for estimating crop evapotranspiration and irrigation requirements.  In each treatment, irrigations were initiated when the soil water potentials in a plot dropped below -30 kPa.  Over the three-year study, the two irrigation treatments did not significantly differ for corn grain yield or water volume applied. In 2016, a cotton irrigation study was initiated that compared the checkbook method (applying irrigation amount based on age of the crop and weekly precipitation totals) to NDVI-based irrigation prescriptions. Soil water sensors were used to initiate irrigation events. Irrigation amounts during the season for the NDVI-based method often differed from rates prescribed by the checkbook method up until about 70 days after planting when differences in NDVI among plant density treatments and field areas no longer existed. The results suggest that continued research into the use of NDVI-based irrigation prescription technology is warranted.

This paper presents a case study of the first application of the dynamic Variable Rate Irrigation (VRI) System developed by the University of Georgia to cotton. The system consists of the EZZone management zone software, the University of Georgia Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2017 in a cotton field to evaluate the performance of the system in cotton. The field was divided into four parallel strips. All four strips were 240 m wide. Two strips received variable rates of irrigation based on the UGA SSA decision support tool (DST) while the other two received uniform irrigation based on the grower’s practice. Sentinel-2 satellite images from the last two years were analyzed to find the NDVI (Normalized Difference Vegetation Index) and NDWI (Normalized Difference Water Index) variability of the field. Additionally soil electrical conductivity data, soil type data as well as elevation data were combined in the EZZone software to delineate irrigation management zones (IMZs). IMZs were delineated for the entire field but used only in the strips where irrigation was applied with variable rates. Eighteen UGA SSA sensor probes were installed in the 4 strips after planting to measure soil moisture. The UGA SSA system reported soil moisture data hourly and they were visualized on the UGA SSA web portal. The DST converted soil moisture data to actionable irrigation recommendations based on the latest soil moisture readings. This paper presents the results of the yield and irrigation water use efficiency (IWUE) comparison between the two irrigation treatments. The analysis of the data showed that the IWUE was considerably higher in the VRI strips than the strips irrigated uniformly.