Smart drones take flight for precision agriculture use in plant and soil science
By: Haleigh Erramouspe
Fields of cotton, wheat, sorghum and other crops are a common sight in the Texas High Plains, but what you might not expect is to see drones whipping through the air above these fields.
However, if you drive out to a field of cotton about 30 miles north of Texas Tech University, that is exactly what you might see.
Wenxuan Guo, an assistant professor in crop ecophysiology and precision agriculture in Texas Tech University's Department of Plant and Soil Science, is using the drones to study the effects of variable rate irrigation in cotton yields.
"We know in this area water is the number one limiting factor for agricultural production," Guo said. "One of my top priorities for research is to use less water and get the same amount of production or use less water to have an optimized production."
Guo came to Texas Tech University in 2016, and since then he has worked to discover methods of water conservation and efficient water use using precision agriculture technologies while still optimizing yields.
This soon led him to working with South Plains Precision Ag in Plainview, Texas. This company has a variable rate irrigation system, which allows farmers to apply the right amount of water in the right area at the right time in their fields.
However, current challenges in variable rate irrigation in this area are knowing the timing, location and rate of water application to optimize production. Guo said solving this issue became the goal of his research.
Throughout 2017, Guo and his research team applied three different rates of irrigation across a 480-acre cotton field to discover how the crop would respond at different landscape positions of the field.
Studying the responsiveness of the different areas, said Guo, is where the drones played a key role.
The drones were equipped with various sensors, and Guo would fly them about 60 meters above the plant canopy. Through the sensors, Guo and his research team were able to measure and identify the spatial variability for plant growth, as well as the soil moisture within the field.
Guo said they discovered variability in several agronomic factors that affected how well the crop responded to different amounts of irrigation. These factors included soil properties and topography – soil texture, organic matter, elevation and slope.
Guo said they discovered cotton yield responded well to irrigation in areas with flat land and fertile soils, but it did not respond well to irrigation at areas with high slope and sandy soils.
Because of their varied responses to irrigation, these agronomic factors were shown to affect yield potential in those different areas of the same field. By applying less irrigation to areas with high slope and sandy soils and areas without crops, farmers can use less water and get the same or a better return on their investments.
"Those factors all affect the water availability for plant growth and also the final yield," Guo said. "If we adjust our allocation of irrigation water, matching the yield potential in the field, our water use efficiency will be optimized."
Guo said this research could prove to be beneficial for farmers who produce various types of crops. He said he knows many types of agricultural fields have a substantial amount of variation in soil properties and topography, and he recognizes this research could apply to other crops in the future.
Using precision agriculture technologies to identify and measure variability could lead to farmers in the community using less water and more sustainable agriculture in this region, Guo said.
"Based on this study," Guo said, "we can design a strategy to optimize the allocation of irrigation water in the field to save water or improve water use efficiency. The result would be better profitability for the farmer."
CONTACT: Wenxuan Guo, Assistant Professor, Crop Ecophysiology & Precision Agriculture, Department of Plant and Soil Science, Texas Tech University at (806) 834-2266 or email@example.com
1204NM18 / Editor's Note: High-resolution images and audio sound bites can be found here
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Editor: Norman Martin
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