The use of drones to gather remote data and soil sensors to collect ground information has become a powerful method for agricultural monitoring and analysis. However, integrating data from drone remote sensing and soil sensors in agricultural contexts can be problematic due to variations in spatial and temporal resolutions. Ensuring precise synchronization and calibration is crucial for accurate comparative analysis. The objective of this study was to investigate the strengths and limitations of drone-based remote sensing and on-the-go Veris U3 sensor in agricultural contexts and explore the potential for data fusion. Through a series of field trials, data from drone-based remote sensing and ground-based soil sensing were collected in parallel. These data encompassed a range of factors, including vegetation health (vegetation indices), soil properties such as EC, pH, and optical measurements. The study delves into the challenges of data synchronization, calibration, and validation between the two methodologies. We discuss the potential for synergy in building a more holistic understanding of agriculture by fusing data from drones and in situ soil sensors. The findings of this research have implications for environmental monitoring, agriculture, and ecosystem management, suggesting that the combination of aerial and ground sensing offers a multi-dimensional perspective that can enhance decision-making processes and our grasp of intricate environmental processes.

The influence of biologically active substances on the physiological processes of soybean plants with the use of a multispectral camera and unmanned aerial vehicle has been assessed in the article. The researches were carried out on soybean variety MK 100, cultivated on the experimental field of the All-Russian Scientific Research Institute of Soybean in 2018, Sadovoe village of the Amur region. The use of UAV with a multispectral camera made it possible to evaluate the physiological processes of soybean crops in microplot trials and to determine the state of the vegetation using NDVI and NDRE indices. The study of physiological processes was carried out at the biochemical level, where the peroxidase enzyme activity represents an adaptation marker. Under the study site conditions, the treatment with Pulsar herbicide in the phase of the third ternate leaf had a negative influence on soybean plants, as there is a decrease in the specific enzyme activity. The highest indicators of quantum yield of photosynthesis were observed in the stages of flowering and at the beginning of the pod formation that indicates a high activity of the photosynthetic apparatus. The studies aim to assess the influence of biologically active substances on the physiological processes of soybean plants using "DJI Matrice 100" UAV and "Micasense Red Edge" multispectral camera and with laboratory analysis comparison in various growth stages.

Application of NDVI Data to Analyse the Effects of Sowing Methods and Seeding Rates on Soybean Crop Yield

Information systems and their management are the main tools in all aspects of human life. Computer science is an integral part of 21st-century farming. The interaction of computer technology and nature is important in the agricultural industry. One of the main tools in data collection, management, and analysis is a satellite. Satellite images are used in analyzing crop health, detecting crop losses, and managing fields from data collected over an observed period of time. This study used high-resolution satellite imagery to obtain field data and identify the type of crops by using R software computing. These studies may help farmers to monitor their losses, and administrative authorities to prevent possible falsification of crop losses. Therefore, a year-long crop growth analysis was conducted in the Amur Region, Russia, on the All-Russian Scientific Research Institute of Soybean agricultural field. Two types of crops were identified in the field using computer technology based on analyzed data. The results of the analyzes will be used in the subsequent determination of crops in the agricultural development program of the Amur Region.

These studies were conducted on the effects of new converter slag fertilizer (complex mineral fertilizer, limestone, soil ameliorant) for land reclamation, provided by the Japanese agricultural chemical manufacturer, containing 37.3% of CaO and 18.0% of MgO, on two types of soil in the Amur Region (Russia). About 85% of arable land has a high acidity (pH_KCl ≤ 5.5) in the region. Therefore, the need for the use of land reclamation in the region is high. Studies aimed to establish the effect of various doses of the slag fertilizer on the change in the acidity of brown forest and meadow chernozem-like (Amur prairie) soils, as well as increase the yield of soybean and wheat in crop rotation. The experimental scheme was tested in doses of the limestone from 1 to 4 t/ha on the background of nitrogen-phosphorus fertilizer. The application of studied mineral fertilizer ensured a decrease in soil acidity by 0.05-0.30 (pH_KCl) units by increasing of exchangeable Ca²⁺ and Mg²⁺ ions in soil exchange complex. The result was an increase in soybean yield by 0.18-0.45 t/ha and an increase in seed quality. Based on the results, fertilizer was recommended in doses of 2 to 4 t/ha, depending on the type of soil.