Author/Authors :
Yones, Mona Sayed National Authority of Remote Sensing and Space Science (NARSS) - Cairo, Egypt , Aboelghar, Mohamed Amin National Authority of Remote Sensing and Space Science (NARSS) - Cairo, Egypt , Khdery, Ghada Ali National Authority of Remote Sensing and Space Science (NARSS) - Cairo, Egypt , Ali, Abdelraouf Massoud National Authority of Remote Sensing and Space Science (NARSS) - Cairo, Egypt , Salem, Nasser Hussien National Authority of Remote Sensing and Space Science (NARSS) - Cairo, Egypt , Farag, Eslam National Authority of Remote Sensing and Space Science (NARSS) - Cairo, Egypt , Ma’mon, Shireen Ahmed Mahmoud Entomology Department - Faculty of Science - Ain Shams University - Cairo, Egypt
Abstract :
Identification of the best spectral zone and wavelength to be used for the discrimination of healthy and infected sugar beet plants and also to discriminate between the different infections of sugar beet plants is the goal achieved in this research. Field hyperspectral radiometer was used to measure spectral reflectance characteristics. By comparing spectral reflectance for the three infections of sugar beet plants (Cotton leaf worm, Aphid and Whiteflies), showed high pattern similarity. HSD Tukey’s analysis showed that the NIR and Blue spectral zone are the best for the discrimination between healthysugar beet plantand the different infections; on the other hand SWIR-1 and SWIR-2 was the worst but Red and Green spectral zones showed reasonable discrimination. Also, Spectral discrimination was clearer in case of old leaves than young ones. Hence aresult of this study is significant, as remote sensing technologies can be used for early detection for plants infections, and thus can be used for integrated pest management system.
Keywords :
Cotton leaf worm , White fly , Sugar beet , Aphid , Hyperspectral data
