Monitoring of the state of agricultural crops and forecasting the crops development begin with aerial photography using a unmanned aerial vehicles and a multispectral camera. Vegetation indexes are selected empirically and calculated as a result of operations with values of diff erent spectral wavelengths. When assessing the state of crops, especially in breeding, it is necessary to determine the limiting factors for the use of vegetation indexes.(Research purpose) To analyze, evaluate and select vegetation indexes for conducting operational, high-quality and comprehensive monitoring of the state of crops and the formation of optimal management decisions.(Materials and Methods) The authors studied the results of scientifi c research in the fi eld of remote sensing technology using unmanned aerial vehicles and multispectral cameras, as well as the experience of using vegetation indexes to assess the condition of crops in the precision farming system. The limiting factors for the vegetation indexes research were determined: a limited number of monochrome cameras in popular multispectral cameras; key indicators for monitoring crops required by agronomists. After processing aerial photographs from an unmanned aerial vehicle, a high-precision orthophotomap, a digital fi eld model, and maps of vegetation indexes were created.(Results and discussion) More than 150 vegetation indexes were found. Not all of them were created through observation and experimentation. The authors considered broadband vegetation indexes to assess the status of crops in the fi elds. They analyzed the vegetation indexes of soybean and winter wheat crops in the main phases of vegetation.(Conclusions) The authors found that each vegetative index had its own specifi c scope, limiting factors and was used both separately and in combination with other indexes. When calculating the vegetation indexes for practical use, it was recommended to be guided by the technical characteristics of multispectral cameras and took into account the index use eff ectiveness at various vegetation stages.

The calculation of aircraft cost is stated necessary to assess the economic feasibility of their operation, as well as in agriculture, the possibility of acquiring new ones, and to justify air transportation tariffs. (Research purpose) The research purpose is to substantiate the methodology and calculate the prime cost of using BAS-137 VIM unmanned aerial system for the application of pesticides, fertilizers and other agrochemicals. (Materials and methods) When developing the methodology for calculating the prime cost of using an unmanned aerial system for applying pesticides and fertilizers, the Guidelines for determining the cost of domestic and international flights for Russian airlines were used. (Results and discussion) We have obtained the main dependences of the prime cost of using BAS-137 VIM for the introduction of working fluids: on the application rate, the field rut length, the distance of approach to the refueling place, and the operating flight speed. (Conclusions) The authors developed a methodology for calculating the prime cost of using an unmanned aerial system for applying pesticides and fertilizers, including direct and indirect operating costs. It was found out that at the working fluid application rates of 5-100 liters per hectare, the changes in the cost of using BAS-137 VIM are within the range from 280.9 to 1315.5 rubles per hectare. At an application rate of 10 liters per hectare within the rut length of 0.3-2.0 kilometers, the application prime cost is 307.1-529.5 rubles per hectare. It was obtained that at the application rates of 5-20 liters per hectare and the rut length of 0.6-1.0 kilometers, the prime cost will be the lowest, within the range of 264-369 rubles per hectare at an operating flight speed of 60 kilometers per hour and within the range of 482-587 rubles per hectare at a flying speed of 30 kilometers per hour. It was shown that with a twofold increase in BAS-137 VIM operating speed, the prime cost decreases by 1.2-1.5 times.

Федеральный научный агроинженерный центр ВИМ, Москва, Российская Федерация Реферат. Цифровое сельское хозяйство предопределяет развитие роботизированных агротехнологий применения пестицидов и удобрений с использованием беспилотных авиационных систем, основу которых составляют беспилотные летательные аппараты с определенной полезной нагрузкой для мониторинга сельскохозяйственных угодий и внесения агрохимикатов. (Цель исследований) Разработать технологию дифференцированного внесения пестицидов и удобрений с помощью беспилотных летательных аппаратов в цифровом сельском хозяйстве. (Материалы и методы) В ходе работы использовали Методические рекомендации по применению средств химизации в системе точного земледелия (ВИМ), нормативно-техническую документацию на беспилотные авиационные системы. (Результаты и обсуждение) Показали, что разрабатываемая технология включает последовательное выполнение информационных и технологических операций в режимах off-line и оn-line. Установили, что норма внесения рабочей жидкости пестицидов 10-20 литров на гектар сокращает потери вследствие сноса из зоны обработки и обеспечивает наибольшую производительность внесения пестицидов с применением беспилотных летательных аппаратов. Определили, что производительность обработки поля возрастает с повышением длины гона и уменьшается с увеличением нормы расхода рабочей жидкости. Выявили рациональные значения длины гона-0,8-3,2 километра. Установили требования к качеству авиационного опрыскивания. Доказали, что для увеличения производительности беспилотных летательных аппаратов при подкормке растений необходимо использовать их с большой полезной нагрузкой-300-400 килограммов. (Выводы) Разработали технологию дифференцированного внесения пестицидов и удобрений с помощью беспилотных летательных аппаратов, алгоритмы подготовки аппаратов к полету, мониторинга сельскохозяйственных угодий, создания ортофотоплана полей, электронных карт вегетационных индексов, фитосанитарного состояния посевов, дифференцированного внесения пестицидов и удобрений. Ключевые слова: цифровое сельское хозяйство, точное земледелие, беспилотные летательные аппараты, пестициды, удобрения, дифференцированное внесение.

As of today existing techniques and tools for measuring leaf area involve the detachment of leaves for further scanning and calculations to determine leaf area. The disadvantages of existing solutions for determining the area of the sheet surface are labor intensity, the duration of these studies, the relatively low accuracy of measurements. Due to these facts this study is an important work aimed to simplifying the process of analyzing biological parameters and other important characteristics of plants, as well as increasing the efficiency of this agrotechnical task. This work aims developing a set of software tools with trained neural networks to determine whether a photographed leaf belongs to the leaves of a soybean crop, assess the health of soybean plants and determine the surface area of a soybean leaf with geotagging.

One of the ways to increase the efficiency of crop production is to maximize the genetic potential of agricultural crops. To do this, it is necessary to create the most favorable, ideal conditions for the growth of plants. At all stages of growth and development of plants there are their own indicators, which should be ideal (optimal). (Research purpose) The research purpose is in developing an algorithm for calculating the parameters of an ideal field on the example of differential fertilization. (Materials and methods) Authors have used mathematical modeling using three basic concepts: responsiveness functions, the digital double of the agroecosystem (field), and the ideal field. The article presents the comparison of the parameters of the real field with the ideal one using a digital double of the real field. (Results and discussion) the parameters of the ideal field has been adjusted taking into account the parameters of the actual field based on the planned yield, requirements for agricultural technology, the used optimization criterion (the target function), and restrictions. In order to make optimal management decisions, along with the agrotechnical requirements for the cultivation of a particular crop, it is necessary to specify the parameters of the ideal field, which must be achieved in the actual field. The article presents the procedure for calculating the ideal field parameters using the example of solid mineral fertilizers. (Conclusions) The article presents an algorithm for calculating the optimal doses of differentiated fertilizer application based on the digital double of a specific field. The dose values are used to refine the parameters of the ideal field and adjust it during the growing season. The algorithm can be used to make optimal management decisions on differentiated seeding, tillage, and the use of plant protection products. As data on the state of soil, plants and knowledge base are accumulated in the form of plant responsiveness functions to certain agro-technical techniques, it is possible to increase the adequacy of the digital double of the actual field and obtain more reliable data for correcting the parameters of the ideal field.