Use of Hyperspectral Imagery and Soil Electrical Conductivity for Site-Specific Reniform Nematode Evaluations and Economical Management
The reniform nematode is rapidly spreading across the Cotton Belt’s southeast region and has become the most economically serious cotton pest in Alabama, Louisiana and Mississippi -- where this ongoing project is being conducted. The target is to increase the effectiveness of nematicide applications using a combination of methods to improve the prediction of economic damage resulting from the nematode and to maximize an economic yield response.
To implement a successful reniform management program, producers must first identify that the nematode is present in a field and determine populations present in each location. In Mississippi, remotely sensed hyperspectral imagery has been correlated with reniform nematode population levels to obtain an accurate estimation of the infield nematode distribution without taking a soil sample. Alabama is working with the Greenseeker technology.
Merging technologies can provide information for maximizing reniform management options and preserving cotton yields. Resulting data will be applicable to other regions where the reniform is becoming a problem.
Analysis on the data collected from the selected infested fields and was begun in 2007 and continued in 2008. Yield data from all plots will be collected in 2008 and analyzed prior to reporting the information at state and national meetings and publishing in various scientific, Extension and popular journals.
The specific objectives are: 1) determining the accuracy of estimating reniform nematode numbers based on remote sensing reflectance data to provide an economical means of predicting nematode numbers without soil sampling, 2) evaluating the effectiveness of nematicides for reniform nematode management as influenced by soil electrical conductivity (EC) zones and 3) correlating the utility of these techniques in combination with real-time NDVI for predicting nematode numbers in specific EC zones to optimize nematicide use and maximize yields.