Spectroradiometer and thermal imaging as tools from remote sensing used for early detection of spiny bollworm, Earias insulana (Boisd.) infestation

The spiny bollworm (SBW), Earias insulana (Boisd.), is from the most destructive cotton pests in Egypt. Larvae can reduce the yield about 40%. Monitoring and forecasting have become an integral aspect of the crop production system in developed countries to control pests. Recently, remote sensing has gained popularity in agriculture for pest monitoring, yield forecasting and early warning to crop growers for proper time in pest management with the least quantity of ground sampling possible.This work aims to measure the validity of using a new methodology for pest detection in cotton bolls without exposing the plant to any danger., This action could be conducted by making a spectroscopy check using spectroradiometer for every boll in field and compare this reading automatically with the spectral library that was built in earlier by measuring numbers of well-known bolls (healthy and infected measuring of some Vegetation Indices (MCARI, TCARI, NPCI, NDVI, NDWI, WBI) also done from reflectance values that carried out, in order to detect the best indices affected by pest infection. Thermal imaging also was done to differentiate between diseased and non-infected tissue. The results described the reflectance spectra of cotton bolls with known SBW infestations and healthy ones and could identify the certain narrow band that is sensitive to SBW damage, BLUE band has found to be the best for spectrally identifying infested bolls. Normalized Pigment Chlorophyll Index (NPCI) is the best index among vegetation indices used in this research. Complementally, to use remote sensing applications, thermal imaging was used to detect thermal patterns associated with insect infestation. The result of study indicate the validity of using spectral measurement and thermal imaging as a tools of remote sensing in detection of the presence of spiny boll worm without wasting and ruined the bolls in field, this method could be also effective in detection of other pests on other crops.