Weed vegetation is one of the most significant factors limiting productivity potential of grain crops in the North-West Region of the Russian Federation. Modern trends in monitoring weed infestation of agrocenoses include the use of unmanned aerial vehicles and hyperspectral imaging with coordinate reference to the terrain. The study of the reflectivity of winter triticale and spring wheat crops depending on the degree of weed infestation and the level of nitrogen nutrition was carried out in 2022–2023 at the experimental base of Menkovsky Branch of Agrophysical Research Institute using hyperspectral imaging from an unmanned aerial vehicle. The experimental design included three levels of nitrogen nutrition (low, medium, high) and four degrees of crop weed infestation (zero, weak, medium, strong). According to the research results, it was determined that with an increase in crop weed infestation its reflectivity grew, especially strongly against the background of application of nitrogen fertilizers, which promoted growth of the aboveground mass of weeds. During the winter triticale booting phase, changes in the reflectivity of the crop under the influence of weeds were more pronounced than during the tillering phase of spring wheat under conditions of acute moisture deficit. Reliable differences in the reflectivity of plots with different degrees of weed infestation were recorded only in the near-infrared (NIR) range of the spectrum. Average values of the spectral reflectance coefficient (SRC) within this spectrum region increased from 0.49 to 0.76 and from 0.42 to 0.52, respectively, in winter triticale and spring wheat crops. The revealed patterns were confirmed in the form of statistically significant positive correlation coefficients between the SRC in the NIR range, the number of weeds (0.46 and 0.59) and their projective cover (0.68 and 0.63). The ranges of SRC values in the NIR spectrum for each degree of weed infestation and level of nitrogen nutrition of winter triticale and spring wheat were obtained, including for medium and high weed infestations, for which herbicide treatment is advisable. © 2025, Space Research Institute of the Russian Academy of Sciences. All rights reserved.
Translated title of the contributionApplication of hyperspectral imaging from an unmanned aerial vehicle to assess weed infestation of grain crops
Original languageRussian
Pages (from-to)136-148
Number of pages13
JournalСОВРЕМЕННЫЕ ПРОБЛЕМЫ ДИСТАНЦИОННОГО ЗОНДИРОВАНИЯ ЗЕМЛИ ИЗ КОСМОСА
Volume22
Issue number3
DOIs
StatePublished - 2025

ID: 149336505