Mississippi State University researchers are advancing agricultural applications for a sustainable future with a new $750,000 grant to develop cutting-edge, soil health-sensing technology and ultimately improve farm efficiency.
With the ultimate objective of developing an unmanned ground vehicle capable of independently assessing soil health, a team of scientists is using spectroscopic technology that measures the interaction of different wavelengths, or colors, with chemical compounds found in soil. Leading the team is Nuwan Wijewardane, along with colleagues Vitor Martins and Xin Zhang, all assistant professors in the MSU Department of Agricultural and Biological Engineering and scientists in the Mississippi Agricultural and Forestry Experiment Station, or MAFES. The trio will delve into the intricacies of soil by examining its carbon compounds, textures and other properties.
New knowledge
“We want to generate new knowledge and build a system which can go around a field and measure soil health at a minimum cost. Funding from MAFES supported our preliminary research, which led to securing competitive external funding,” Wijewardane said.
The four-year project, funded by the USDA National Institute of Food and Agriculture, could revolutionize soil health research, leading to the development of smart machines that could significantly impact agricultural practices.
“Our LiDAR, or light detection and ranging, and camera-based, visual-guided navigation will enable the vehicle to check its surroundings when it’s in an unstructured environment,” Zhang said. “We will also integrate different sensors and RTK—or real-time kinematics—GPS, providing coordinates that will serve as waypoints for the autonomous vehicle.”
Spectroscopic sensing
Spectroscopic sensing could ease the workload and cost to farmers and offer vastly improved efficiency. Currently, manually sampled soil is sent to an offsite lab where chemical methods are used to measure soil properties, a time-consuming and expensive process. The spectroscopic sensing will measure soil health onsite and in one machine, saving time and money.
“The integrated spectroradiometer in an autonomous robot will collect data points along the way, and we will develop the software to generate the soil property maps. Ideally, we will have the spatial variability of soil properties in this map, and we can inform the farmer of what kind of actions they need to take to adjust for optimal plant growth conditions in the area,” Martins said. “Having this technology installed in robots could automate data collection, which is a big deal.”
This team’s work is coordinated with the MSU Agricultural Autonomy Institute, the nation’s first institute designed to develop and further technology and equipment focused on agricultural autonomy.
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