PROSPECTS OF PRE-HARVEST MONITORING OF FLAX CROPS USING UNMANNED AERIAL VEHICLES

Abstract

Modern agricultural monitoring approaches require increased efficiency and accuracy in assessing crop conditions during the pre-harvest period. This paper presents an algorithm for comprehensive assessment of the flax crop stand condition prior to harvesting, based on the integration of data obtained using unmanned aerial vehicles and results from traditional field and laboratory measurements. A mathematical model of an integrated indicator describing the flax crop stand condition is developed, incorporating key agronomic, technological, and biological parameters. Furthermore, an approach for generating digital field maps with mapped values of the integrated crop stand condition index is proposed, enabling visualization of the quality of the flax crop stand within fields. The resulting information enables well-founded decisions on optimal harvesting dates, selection of appropriate harvesting technologies, and optimization of harvesting machinery settings. The proposed methodology is applicable to both fiber flax and oilseed flax and contributes to improving harvesting efficiency and overall crop management.