Researchers at Mississippi State University have developed technology that uses reflected light to analyze the presence of certain nematodes in cotton fields so producers can increase profits.
Since 2001, MSU associate professor of nematology Gary Lawrence and Giles Distinguished Professor of Electrical and Computer Engineering Roger King have been developing a way to use remote sensing technology to battle reniform and root-knot nematodes, which are the No. 1 cotton pest in Mississippi, Alabama and Louisiana. In recent years, Mississippi cotton producers lost more profits from these nematode infestations than any other state, including a loss of 225,000 bales worth $87.8 million in 2006.
“These worm-like parasites live on plant roots and feed off the plant's juices, weakening the plant and resulting in lower productivity,” Lawrence said. “I felt that if we could find a more cost-effective and timely way of diagnosing the nematode population in a field, producers could apply the proper amount of nematicide to the infected area.”
Earlier research indicated that the reflectance values of cotton plants infected or stressed with the reniform nematode were different than un-infected plants. Lawrence and King decided to try hyperspectral imaging. This technique uses a sensor to collect thousands of samples of reflected energy from cotton plants across the visible and near-infrared electromagnetic spectrum to determine the presence and numbers of nematodes.
Lawrence first conducted controlled tests in small plots on MSU's North Farm. Then he worked with cotton producers to determine if he got the same results in fields naturally infected. Four reflectance measurements were taken: the plant canopy, the soil, the plant canopy and soil, and a single leaf. He used an Analytical Spectral Device to gather data but needed a way to make sure the data accurately gauged the presence of nematodes.
King, who at the time was director of MSU's Computational Geospatial Technologies Center and is now director of the Center for Advanced Vehicular Systems, led the engineering portion of the research.
“These kinds of projects require interdisciplinary efforts,” King said. “We brought together the agricultural and engineering disciplines to explore what technology could do. The engineering students wrote algorithms and software programs to see which mathematical algorithm would analyze the data best to correlate with the nematode sampling.”
The software created by electrical engineering graduate students matched reflectance data with the actual nematode counts collected when the reflectance data was gathered. Nematode sampling is a multi-step process that involves extracting the nematodes from the soil and suspending them in water so they can be viewed under a microscope and counted.
“Not only is this method time- and labor-intensive, but getting an appropriate number of samples from a field can cost a farmer thousands of dollars,” Lawrence said. “It's simply not a cost-effective approach.”
20240830145952.gif)
.jpg?tr=w-120,h-60,c-at_max,cm-pad_resize,bg-ffffff "UBM China (Shanghai)")
-Ltd..jpg?tr=w-120,h-60,c-at_max,cm-pad_resize,bg-ffffff "Thermore (Far East) Ltd.")
