Hyperspectral Remote Sensing for Early Detection of Wheat Leaf Rust Caused by Puccinia triticina

Early crop disease detection is one of the most important tasks in plant protection. The purpose this work was to evaluate early wheat leaf rust possibility using hyperspectral remote sensing. first task study choose tools for processing and analyze sensing data. second biochemical profile by chromatographic spectrophotometric methods. third discuss a possible relationship between data results from leaves, analysis. used an interdisciplinary approach, including methods, as well As result, (1) VIS-NIR spectrometry analysis showed high correlation with data; (2) wavebands identification were revealed (502, 466, 598, 718, 534, 766, 694, 650, 866, 602, 858 nm). An accuracy 97–100% achieved fourth dai (day/s after inoculation) SVM.