Economic efficiency of using drones in plant growing

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Authors: Мария Юрьевна Карелина, Irina Leonidovna Bukharina, M.N. Belousova, Vitalii Andreevich Belousov
Cited by: 0

Abstract

Many agribusiness enterprises are looking for ways to increase efficiency and maintain competitive advantages. The purpose of the study is to consider the possibility of using drones in crop production and calculate the effectiveness of implementing this technology. The following methods were used: analysis, synthesis, generalization, rating, and linear programming. Quantitative tools for assessing the effectiveness of implementing digital technologies in crop production have been studied and systematized, and modern approaches to assessing individual processes effectiveness in agriculture have been considered. A comparative analysis of the agricultural drone market offered by official dealers and Russian manufacturers has been conducted. The phenomenon of implementing drones in crop production for the purpose of aerial photography and fertilization has been considered. Two possible scenarios of farmer behavior in relation to agriculture have been developed: monitoring the condition of fields and crops using their own vehicle, as well as applying fertilizers using specialized agricultural machinery and performing similar work using drones. With an increase in yields due to the efficiency of using drones, income increases by 1.11%. The calculation of the annual additional income from increasing yields through the use of agricultural drones for the main agricultural crops (corn, wheat, sunflower, barley, soybeans, rapeseed, peas, buckwheat, and millet) in Russia has been carried out. An indicator of the economic efficiency of implementing agricultural drones into agricultural production has been calculated. The need for state support for implementing agricultural drones in crop production in the form of leasing, low loan rates, and subsidies has been emphasized.

Fields of Study & Subjects

Agricultural Development and Policies Smart Agriculture and AI Agricultural Engineering and Mechanization

Publication details

Journal / source
UPRAVLENIE / MANAGEMENT (Russia)
Volume
13
Issue
4
Pages
72–80
Publication date
6 February 2026
Language
EN