Early detection of plant disease using close range sensing system for input into digital earth environment

Abstract

A case study on pre-symptom stage of plant disease infection using ground based hyperspectral remote sensing was conducted. The objectives of the study are: (1) to validate the existence of pre-symptom stage of Ralstonia Solanacearum infection in Solanum Melongena L. (eggplant), and (2) to determine the induced electromagnetic spectral response for infected eggplant. From the experiment, the pre-symptom duration of Ralstonia Solanacearum infection in the case of eggplant was estimated (with the artificial photosynthetic stress conditions were adopted in the experiment to induce measurable changes in daily hyperspectral measurement of disease infected eggplant samples during the pre-symptom stage) as four days which is the critical period for practicing effective treatments. Vegetation indices namely, (1) Chlorophyll Absorption Integral (CAI), (2) Photochemical Radiation Index (PRI), and (3) Normalized Difference Vegetation Index (NDVI) have successfully shown noticeable progress of index value from the infected sample plant (with 100% light stress condition) throughout the study. Yet, other infected sample plants with moderate light stress conditions (50% or 75%) did not result any similar progress of index value from the daily leaf scale hyperspectral measurements. Apparently, extreme light stress can induce significant changes at visible portion in hyperspectral measurements for a disease infected eggplant during the pre-symptom stage