METHODS OF DETECTION OF DISEASES ON WHEAT CROPS ACCORDING TO REMOTE SENSING (overview)

Abstract

Nowadays multi- and hyperspectral data of remote sensing is widely used in many countries worldwide for agricultural lands monitoring. The issue of their application for detection and assessment of infestation of agricultural crops, damage from diseases and weeds is understudied both in Russia and abroad. Early detection and accurate diagnosis of various wheat diseases are key factors in crop production, contributing to the reduction of qualitative and quantitative crop losses, as well as improving the effectiveness of protective measures. The paper presents a review of up-to-date methods for detecting diseases and assessing the extent of crop damage by remote sensing of wheat using optical imaging systems, the most promising of which is hyperspectral imaging equipment. The identification spectra of healthy plants and the ones with signs of damage from the main fungal diseases as well as the correlation of spectra with the degree of damage are shown. To be able to effectively use the results of diagnostics and detection of diseases, the informational value of the spectral indices of vegetation in the detection of diseases is presented. A table of vegetation indices is given, calculated from the values of reflection coefficients in wide and narrow spectral ranges when determining wheat diseases. The use of optical methods in the monitoring of the main fungal diseases of wheat will accurately identify lesions of crops, reliably diagnose diseases and the extent of plant damage from diseases, and thereby provide support to agricultural producers in decision-making on timely and effective crop protection measures. The results of the review will be used to develop digital technology of early detection and lesion focalization of spring wheat and other agricultural crops.

Detection of spring wheat plants affected by powdery mildew using hyperspectral survey data

“…As follows from the analysis of various vegetational indices previously used in the diagnosis and monitoring of other wheat diseases development [13], along with the basis of spectrum characteristics analysis obtained in laboratory experiment, 11 vegetational indices were selected to identify powdery mildew (Blumeria graminis (DC) Speer). They are presented in Table 1.…”

“…For purposes of plants analysis for the powdery mildew detection, 11 vegetation indices were calculated: NBNDVI, RVSI, PSRI, NRI, PRI, SIPI, PhRI, TCARI, MTVI1, TVI, PMI, which were described earlier [13].…”