Vivek Sharma, PhD


Sandra Guzmán, PhD Haimanote Bayabil, PhD Kati Migliaccio, PhD, PE


Contrary to irrigated scheduling apps for field crops, additional inputs are required for specialized and tree crops such as tomatoes, avocados, strawberries, citrus, etc., including row spacing, bed spacing, irrigation system flow rate and other related variables. For vegetable crops, many apps do not account for rainfall and soil data as these cropping systems are operating under drip irrigation systems and raised-bed plastic mulch. The final irrigation schedule from these apps provides information on the irrigation system run time per day rather than soil water content and soil water deficit. Most of the apps such as the avocado app and the cotton app have been evaluated under different field and environmental conditions. The apps have resulted in significant improvements in crop water use efficiencies and water conservation compared to conventional irrigation scheduling methods.


WHAT’S NEXT? Overall, smartphone irrigation scheduling apps provide an easy way to determine your irrigation schedule for different crops and come with the flexibility of making user-specific customization, including water savings, irrigation event schedules and notifications. For example, many apps allow


users to modify the estimated soil water content using the measured soil moisture data from soil moisture sensors. Apart from the many benefits, currently there are no available options to fully integrate these apps with irrigation systems to achieve a fully automated closed-loop feedback system for irrigation scheduling options. As a result, users are expected to input app recommendations regarding irrigation application depth or run time into their irrigation control systems.


In addition, another major limitation that affects the effectiveness of these apps in accurately calculating irrigation schedules for maximum irrigation water use efficiency is spatial variability of rainfall and other climate variables and the availability of accurate site-specific soil information. With the continuous advancement of technology and artificial intelligence solutions, the future of irrigation scheduling apps will more likely include different types of data that are seamlessly integrated such as remote sensing data including drone and satellite imagery, historical information and climate projections, and high-resolution gridded weather data. Using these in conjunction with crop models would benefit irrigation water management.


George Vellidis, PhD


Vivek Sharma, PhD, is  precision water management specialist, agricultural and biological engineering  


Sandra Guzmán, PhD, is an assistant   and hydrology in the agricultural and biological engineering department at the Indian River Research  


Haimanote Bayabil, PhD, is an assistant  resources in the agricultural and biological engineering department at the Tropical Research  


Kati Migliaccio, PhD, PE, is the chair and a  and biological engi-  


Figure 2. These screenshots represent the stepwise instructions for the soybean irrigation app. irrigationtoday.org


George Vellidis, PhD,  and soil sciences in  and soil sciences at the 


Summer 2022 | Irrigation TODAY 33


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