New Mexico State University researchers are working on a method of monitoring peanuts in the field in order to help growers produce a healthier crop.

RESEARCHERS with New Mexico State University and Texas Tech University used remote sensing on peanut crops to determine crop ground cover, leaf area index, biomass and yield. (Photo courtesy of Naveen Puppala)

NMSU’s Agricultural Science Center at Clovis is collaborating with Texas Tech University to use remote sensing on peanut crops to estimate the biophysical characteristics, such as ground cover, leaf area index, biomass and yield.

“This is the first year we are using the method of remote sensing on peanuts and, since the peanut ground coverage is so dense, we are excited to see the results,” said Naveen Puppala, a peanut breeder at the Clovis center.

Puppala, along with Nithya Rajan and Stephan Maas, researchers with Texas Tech, have been observing a peanut crop near Brownfield, Texas, since the beginning of the growing season in May. They use the Texas Tech Airborne Multispectral Remote Sensing System flown aboard an aircraft provided by South Plains Precision Ag in Plainview, Texas.

The remote sensing system contains high-resolution digital cameras fitted with narrow band-pass filters that allow the cameras to acquire imagery in specific wavelengths of light.

Digital data extracted from the remote sensing imagery is used to calculate the values of vegetation indices, including the Normalized Difference Vegetation Index (NDVI) and the Perpendicular Vegetation Index (PVI) for the peanut canopies growing in plant-configuration test plots. Both NDVI and PVI are indicators used to measure a plant’s growth and leaf-canopy density. These indices are then compared with ground measurements of the biophysical characteristics of the plots when remote sensing observations are conducted.

This is the first year the Clovis science center has used remote sensing on peanuts, but the method can be used on a variety of crops. Rajan and Maas have previously used this method with success on cotton, sorghum and corn in West Texas.

Puppala and his collaborators chose to use a test site in West Texas because the area has seen growth in the peanut production. He has plans to apply the remote sensing method in New Mexico.

Development of relationships between biophysical characteristics and remote sensing data could allow routine monitoring of peanut crop growth and yield potential in producers’ fields.

“With more research on remote sensing, it will help the growers to identify the correct time to irrigate their crops,” Puppala said. “Growers can identify low-lying and deficient areas within their pivots. Peanut growers spend a lot of money on fungicides to control the foliar disease, but with remote sensing we can avoid areas where the crop is good and pinpoint or apply fungicides only to areas that are nutrient deficient or have problems with disease.”

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