Robot assisting with precision irrigation in an orchard.
Photo Credit: Elia Scudiero / University of California, Riverside
Scientific Frontline: Extended "At a Glance" Summary: Robotic Soil Moisture Mapping
The Core Concept: A precision agriculture system developed by UC Riverside utilizing an autonomous robot to map soil moisture on a tree-by-tree basis. The technology aggregates dynamic field data with stationary sensors to create highly accurate statistical models of water distribution across entire orchards.
Key Distinction/Mechanism: Traditional irrigation management relies on scattered, stationary soil moisture sensors that only provide localized data, forcing growers to guess field-wide conditions. This new system deploys a robot to measure soil electrical conductivity—which fluctuates based on moisture, salt, and clay content—across the entire field. By correlating these mobile conductivity measurements with direct water readings from the fixed buried sensors, the system accounts for soil texture variations (e.g., sandy versus fine soils) and generates comprehensive, actionable moisture maps.
Major Frameworks/Components:
- Autonomous Surveying Robotics: Mobile robotic units designed to navigate agricultural environments and collect field-wide data without disturbing existing infrastructure.
- Electrical Conductivity Measurement: The utilization of soil conductivity as a proxy variable for assessing water retention capabilities and soil composition.
- Statistical Predictive Modeling: The integration of dynamic mobile data with static sensor readings to construct accurate, comprehensive maps of soil moisture availability.
- Hyper-Localized Precision Irrigation: The translation of data into tree-by-tree irrigation directives to avoid blanket watering.
Branch of Science: Precision Agriculture, Soil Science, Agronomy, Agricultural Engineering, Robotics, and Data Science.
Future Application: Future phases involve adapting the technology into ruggedized commercial products for widespread agricultural deployment. The system will be utilized to sustain crop yields amid strict groundwater regulations and severe droughts by enabling variable-rate irrigation. Additionally, it will be applied to environmental conservation efforts to prevent nutrient and fertilizer runoff into groundwater systems.
Why It Matters: As drought and water scarcity increasingly threaten global agriculture, optimizing water management is critical for food security. By delivering "more crop per drop," this technology provides farmers with a sustainable alternative to retiring orchards, mitigating economic losses while significantly reducing the ecological impact of agricultural runoff and overwatering.
Advanced technology can help farmers get to the root of a growing problem ¾ overwatering in an era of increasing drought and water scarcity. A new UC Riverside system can map soil moisture tree by tree, so growers water only where and when it’s needed.
Robot assisting with precision irrigation in an orchard. (Elia Scudiero/UCR)
This system, detailed in the journal Computer and Electronics in Agriculture, was led by the research group of Elia Scudiero, associate professor of precision agriculture and the Director of UCR’s Center for Agriculture, Food, and the Environment (CAFE).
Water management is one of the biggest challenges facing agriculture in California and other dry regions. Currently, some growers rely on soil moisture sensors buried in the ground to determine when to irrigate. These sensors are expensive and typically installed in only a few locations, leaving growers to guess how conditions vary across hundreds or thousands of trees.
“The information those sensors provide is very limited,” Scudiero said. “It really only tells you what’s happening in the immediate areas where they’re placed.”
Even when sprinkler systems deliver the same amount of water throughout an orchard, the soil moisture and its availability to trees can vary greatly from spot to spot within a single field.
One reason is soil texture. Fine soils packed with tiny particles hold water tightly because they have more surface area where water can cling. Sandy soils contain larger particles and fewer small ones, which allows water to drain more quickly. These differences can leave neighboring trees experiencing very different conditions.
The new system replaces limited sensor data and guesswork with detailed maps. A robot moves through an orchard measuring a property of the soil called electrical conductivity. These readings, combined with data from the fixed moisture sensors already in the ground, allow researchers to build a statistical model that predicts water content across the entire field.
Electrical conductivity indicates how easily electricity moves through the soil and is influenced by factors including moisture as well as salt and clay content. By pairing those measurements with direct water readings from buried sensors, the system can translate conductivity into accurate estimates of soil moisture.
The result is a tree-by-tree picture of water distribution. “Using this method, growers will finally know how much water they have, and how much they need, and can water specific trees if they’re dry,” Scudiero said.
Maintaining the right moisture level is important for plant health. Trees that receive too little water become stressed, and more vulnerable to pests and disease. Too much water, however, can deprive roots of oxygen as soil pores fill with water rather than air. “There’s a sweet spot,” he said.
Enhanced precision could also keep orchards from folding. Growers already face tightening regulations on groundwater use while water costs continue to rise.
“If water becomes limited, farmers have two choices,” Scudiero said. “They can retire orchards, or they can find ways to produce the same crops using less water.”
The technology may also reduce fertilizer pollution. When fields are overwatered, nutrients applied to crops can wash below the root zone and into groundwater, polluting it.
“If you apply only the amount of water the plants actually need, you reduce the risk of washing those nutrients away from the roots of the crops and into the environment,” Scudiero said.
This project has been years in the making. Researchers began developing it in 2019 through collaborations between agricultural scientists and engineers at CAFE.
For Scudiero, it represents the realization of a long-standing goal. He has studied soil conductivity technology for about 15 years and had hoped to someday pair it with autonomous vehicles capable of surveying entire fields.
The team has already filed a patent related to how the robot interacts with sensors without disturbing their measurements. This research was conducted at the UCR Citrus Research Center & Agricultural Experiment Station. Future work will focus on testing the system with commercial growers beyond the university’s research orchards.
Moving from research plots to real farms will require rugged machines capable of operating in all weather conditions and across different crop systems. Private industry partners may eventually adapt the technology into commercial products.
The work is part of broader efforts at UCR to further the field of precision agriculture, where researchers are developing technologies that combine robotics, sensors, and data science to help farmers manage resources more efficiently.
For growing facing limited water supplies, the payoff for this research could be significant.
“More crop per drop!” Scudiero said.
Published in journal: Computer and Electronics in Agriculture
Authors: Francesco Morbidini, Aritra Samanta, Carmelo Maucieri, Konstantinos Karydis, Peggy A. Mauk, Todd H. Skaggs, and Elia Scudiero
Source/Credit: University of California, Riverside | Jules Bernstein
Reference Number: agri040226_01