The density of robotization of agriculture in Russia and its regions

According to the Rosstat data a share of agricultural organizations which introduce technological innovations is low (2.7%). The study aims to determine the density of agricultural robotization in Russia and its regions. The density of agricultural robotization is influenced by the average annual number of employees in the industry, which was 5802 thousand people in 2013-2019 and decreased by 22% over the studied period. The data show that 435 units of robotics were introduced in agricultural organizations in the Russian Federation in 2006-2019. The vast majority of robotics used in agriculture in Russia is milking robots mainly by European manufacturers. Robotics is used in the agricultural sector in the Central (185 units), Volga (95 units), NorthWest (66 units) and Ural (68 units) federal districts. The introduction of robotics in agriculture in the Southern, Siberian and North Caucasian federal districts is practically not carried out. The highest density of agricultural robotization is observed in the Kaluga (42.67 robots per 10 thousand employees in the industry), the Ryazan (14.8), the Sverdlovsk (6.32) and the Vologda Region (6.21). The results of the study will allow development of a mechanism that promotes priority robotization of rural areas where robotization is slow or is not carried out to prevent their technological lagging behind and the further development of a stagnation processes. The scientific significance of the research results will contribute to the development of theoretical aspects of robotics application in agriculture and the spatial aspects of robotization. © 2020, World Scientific and Engineering Academy and Society. All rights reserved.The study was funded by RFBR, a project number is 20-010-00636 А «Spatial development of agricultural robotization in Russia: trends, factors, mechanisms

The density of robotization of agriculture in Russia and its regions

According to the Rosstat data a share of agricultural organizations which introduce technological innovations is low (2.7%). The study aims to determine the density of agricultural robotization in Russia and its regions. The density of agricultural robotization is influenced by the average annual number of employees in the industry, which was 5802 thousand people in 2013-2019 and decreased by 22% over the studied period. The data show that 435 units of robotics were introduced in agricultural organizations in the Russian Federation in 2006-2019. The vast majority of robotics used in agriculture in Russia is milking robots mainly by European manufacturers. Robotics is used in the agricultural sector in the Central (185 units), Volga (95 units), NorthWest (66 units) and Ural (68 units) federal districts. The introduction of robotics in agriculture in the Southern, Siberian and North Caucasian federal districts is practically not carried out. The highest density of agricultural robotization is observed in the Kaluga (42.67 robots per 10 thousand employees in the industry), the Ryazan (14.8), the Sverdlovsk (6.32) and the Vologda Region (6.21). The results of the study will allow development of a mechanism that promotes priority robotization of rural areas where robotization is slow or is not carried out to prevent their technological lagging behind and the further development of a stagnation processes. The scientific significance of the research results will contribute to the development of theoretical aspects of robotics application in agriculture and the spatial aspects of robotization. © 2020, World Scientific and Engineering Academy and Society. All rights reserved.The study was funded by RFBR, a project number is 20-010-00636 А «Spatial development of agricultural robotization in Russia: trends, factors, mechanisms

Method of analysis of the spatial galaxy distribution at gigaparsec scales. I. Initial principles

Initial principles of a method of analysis of the luminous matter spatial distribution with sizes about thousands Mpc are presented. The method is based on an analysis of the photometric redshift distribution N(z) in the deep fields with large redshift bins \Deltaz=0.1{\div}0.3. Number density fluctuations in the bins are conditioned by the Poisson's noise, the correlated structures and the systematic errors of the photo-z determination. The method includes covering of a sufficiently large region on the sky by a net of the deep multiband surveys with the sell size about 10^{\circ}x10^{\circ} where individual deep fields have angular size about 10'x10' and may be observed at telescopes having diameters 3-10 meters. The distributions of photo-z within each deep field will give information about the radial extension of the super large structures while a comparison of the individual radial distributions of the net of the deep fields will give information on the tangential extension of the super large structures. A necessary element of the method is an analysis of possible distortion effects related to the methodic of the photo-z determination.Comment: 12 page

Main Factors of the Spatial Development in Promoting and Hindering Agriculture Robotization in Russia

This research determines the significant differences in the level of robotization of agriculture in Russia. As the processes of robotization of agriculture can be associated with certain socio-economic characteristics of the spatial development of regions, this study aims to analyze the factors of the spatial development of regions that promote and hinder the robotization of agriculture. Having identified and systematized influencing factors makes it possible to reduce the impact of obstacles and intensify the influence of factors contributing to the introduction of robotics. A 2D projection of the characteristics of the expert group (the Phi contingency coefficient) and the results of the expert survey (the Pearson's correlation coefficient) was developed. The most significant factor in the spatial development of regions, which currently hinders the robotization of agriculture, is a share of profitable agricultural organizations in the region. According to the experts, the factors of the spatial development of region, hindering the robotization of agriculture are insufficient volumes of subsidies for the technical renewal of agriculture and investment risks in the region. The most significant factor in the spatial development of regions, contributing to the robotization of agriculture is the availability of a Developed network of servicing for robotics. Considering these factors will make it possible to choose the optimal measures of influence in order to intensify the activity in robotizing the production and rural areas. (C) 2021 INT TRANS J ENG MANAG SCI TECH

Robotic milking implementation in the Sverdlovsk region

The research topic is relevant due to a high rate of the implementation of milking robots (automatic milking system, AMS) in Western Europe and in the Middle Urals. As of January 1, 2016, 21 milking robot systems of six different brands of foreign production were installed in the region. Milking robotics is used in small, medium and large enterprises (by the number of personnel), in contrast to Western Europe, where it is mainly used on the farms of family type. The article examines the socioeconomic causes of the introduction of robotics, as well as the impact of the use of robots to the economic indicators of milk production. The expert survey has revealed as the main reasons for the introduction of robotics, a desire to reduce the risks of personnel (45.5 %) and a shortage of staff (18.2 %). The analysis of the utilization efficiency of fixed assets in all organizations introduced robots has shown both a decrease of capital productivity after the introduction of milking robots for 15-60 % or more, and the reduce of the profit rate in 9 out of 11 of the analysed organizations because of the high capital intensity of robotics projects. The analysis of labour indicators and the net cost of milk is carried out in 45.5 % of organizations, where we have obtained the consistent results of the use of robotics. The authors have analysed the direct costs for the production of 1 quintal of milk. In a group of 5 companies, on a robotic farm, it is 5.1 % lower than in a conventional farm. The complexity of the production of milk on a robotic farm is lower by 48.7 %, and labour productivity per person is higher on 95.3 % than on conventional farms. The results of the study can be used as the recommendations for agricultural organizations to use robotics milking to reduce the deficit of staff and to minimize the impact of personnel risks on production results. The growth of the importance of the reasons for the introduction of milking robots and a high capital intensity of import robotics can justify the need for a national milking robotics.Рассмотрены социально-экономические причины внедрения робототехники, а также влияние использования роботов на экономические показатели производства молока в сельскохозяйственных организациях Свердловской области. Представлена динамика доильной робототехники и характеристика организаций, использующих роботов