Digital Transformation Of Agriculture Research Articles

How does the digital transformation of agriculture affect carbon emissions? Evidence from China’s provincial panel data

Agriculture is becoming a substantial contributor to carbon emissions in China, and the efficient reduction of agricultural carbon emissions (ACEs) has become a universal concern. Currently, the digital transformation of agriculture (DTA) provides a new way to reduce carbon emissions. However, questions regarding whether and how DTA suppresses ACEs remain the focus of both academic and practical attention; thus, they serve as the objectives of this study. Based on theoretical analyzes, the carbon emission reduction effect of DTA is empirically analyzed using panel data from 30 Chinese provinces between 2015 and 2021 with a benchmark regression model, mediating effect model and threshold effect model. The results show the following: (1) DTA significantly reduces ACEs. (2) DTA reduces ACEs through three paths: expanding the agricultural production scale, optimizing the agricultural industrial structure, and promoting agricultural technological progress. The agricultural industrial structure has the most considerable mediating effect, while the agricultural production scale expansion has the smallest effect. (3) The inhibitory effect of DTA on ACEs shows very distinct heterogeneity. DTA primarily reduces ACEs in eastern and nongrain production areas yet has an insignificant impact on other areas. In addition, the DTA has a significant inhibitory effect on ACEs from both fertilizers and diesel oil. (4) The inhibitory effect of DTA on ACEs is nonlinear rather than linear. There is a single threshold effect for the effect of DTA on ACEs, which is insignificant below the threshold and significantly negative above the threshold. Therefore, China’s central and local governments need to increase the level of DTA, encourage farmers to moderately expand the scale of their operations, emphasize the agricultural service industry, and enhance agricultural technological innovation to ultimately reduce ACEs.

Цифровая трансформация сельского хозяйства в контексте обеспечения продовольственной безопасности: правовой опыт стран БРИКС

В статье на примере БРИКС рассмотрено стратегическое планирование в сфере обеспечения продовольственной безопасности. Отмечается, что цифровизация – инструмент, обеспечивающий устойчивое развитие сельского хозяйства. Осуществляемая цифровая трансформация сельского хозяйства стран БРИКС требует новых подходов к определению механизмов совершенствования правового регулирования и стратегического планирова-ния. Выявлены правовые проблемы цифровой трансформации сельского хозяйства и сформулированы предложения по их возможному решению. The article considers strategic planning in the field of food security using the example of BRICS countries. Digitalization is a tool that ensures sustainable development of agriculture. Current digital transformation of agriculture in the BRICS countries requires new approaches to defining mechanisms for improving legal regulation and strategic planning. Legal problems of digital transformation of agriculture are identified and the author’s proposals for their possible solution are formulated.

Национальное стратегическое планирование цифровой экономики: конкурентный анализ на материале Китая и России

At present, the wave of digital economy is sweeping the world. Countries all over the world are competing for the strategic commanding height in digital economy. In order to firmly seize this major historical opportunity and to transform and upgrade its economic structure faster, Russia keeps on strengthening the core capabilities of the digital economy such as information infrastructure, new generation information technology, ICT industry, human resources, information security, and digital environment supervision. Research purpose: a competitive analysis of the national strategic planning for the digital economies in China and Russia. Research objectives: 1) to provide definition for the digital economy; 2) to show the current improvement of the digital economy; 3) to study Russia’s digital economy; 4) to explore China’s digital economy. Research methodology: study of theoretical literature, data collection and analysis. Research results. “Strategy of the Information Society Development in the Russian Federation for 2017–2030” (2017) implies creating conditions for developing large companies in the information and communications technology industry in order to protect national interests in the digital economy. In 2021, Russia’s investment in the development of the digital economy reached the total of 4.094 trillion rubles. It represents an increase of 7.8 % compared to 2020 and amounts to 3.7 % of GDP. Over the past decade, China’s digital economy has made world-renowned development achievements. The overall scale has been the second best in the world for many years. The construction of information and communication networks is a global leader in terms of scope. The "Broadband China" strategy has been diligently implemented. The country has built the world’s largest fiber optic and mobile broadband network. The length of optical cable lines increased 2.7 times from 14.79 million km in 2012 to 54.81 million km in 2021. By June 2022, the total number of data center racks in China exceeded 5.9 million standard racks, and 153 national green data centers were built. Key core technologies have experienced breakthroughs. Investment in research and development of digital technologies is increasing every year. The level of digitalization in the service sector has increased significantly. The digital transformation of agriculture is making steady progress. In China, the deep implementation of the development strategy focused on innovation, promoting key technology research, accelerating the forging of long boards, making up for short boards, and building an independent and controlled industrial ecology.

Digital transformation of agriculture: A new integrated modeling framework for arable farm enterprises

With the increasing integration of information technology in arable farms, enterprise integration (EI) is becoming increasingly important. As farms handle many applications, all of which work in isolation from one another, integrating these disparate systems to create unity across the enterprise has clear value. One critical aspect of EI is business integration, which helps the enterprise align the use of technology assets with the business to achieve strategic goals. While existing enterprise modeling (EM) methods are often used to model industrial or general enterprises for business integration, they do not fully meet the needs of arable farm enterprises. This study aims to propose an EM framework for arable farm enterprises that provides an effective and practical method for business integration. Therefore, an integrated EM framework for arable farm enterprises (IEMFAFE) is proposed using a domain analysis approach based on EM theory. Additionally, steps and methods for modeling arable farm enterprises based on IEMFAFE are provided. A multi-case study shows that IEMFAFE is well suited for modeling arable farm enterprises. The high expressiveness of IEMFAFE enables accurate descriptions of enterprise details and extraction of the service modules and information entities necessary for system design, significantly improving the speed and quality of the system design. The contributions of this study will benefit both researchers investigating the integration of arable farm enterprises and practitioners aiming to architect integrated farm management information systems.

Unlocking sustainability? The power of corporate lock-ins and how they shape digital agriculture in Germany

The digital transformation of agriculture is widely presented as a path to sustainability and a win-win strategy that benefits the environment, farmers, and consumers alike. However, recent studies show how the digital economy is characterized by monopoly structures, market concentration and corporate power that determine patterns of control over digital technology, distribution of benefits and value creation from data. In the field of agriculture, there is a lack of empirical research on lock-ins that examines in detail the logic of these effects, the actors, and the power dynamics behind them. Yet such insights are exactly what is needed to better understand the effects and to break unsustainable lock-ins towards more sustainable agri-food systems. Drawing on the literature on the political economy of food and agriculture, and on studies of innovation and sustainability transitions, this article aims to fill this research gap. Based on an empirical case study in Germany, it identifies systemic, technological, data, legal, soft, and discursive lock-ins that reinforce existing power relations and farmers' dependence on corporate agro-industrial farming models. It concludes that sustainable transformations in agriculture require a disruption of the identified lock-ins at multiple levels.

Digital Agriculture Policies and Strategies for Innovations in the Agri-Food Systems—Cases of Five West African Countries

The digital transformation of agriculture can support economic growth and food and nutrition security in Africa. The objectives of this study were to provide an overview of the status of digital agriculture in five West African countries, analyze their efforts in developing the enabling environment and innovations, and formulate recommendations based on the identified gaps for the effective transformation of the sector. For this purpose, a literature search was performed using various sources, including web pages and databases of national agricultural and digital transformation institutions and start-ups of the five target countries (Benin, Burkina Faso, Côte d’Ivoire, Ghana, and Nigeria) and regional/international institutions. The information retrieved was used for individual country and cross-country comparative analysis of the progress and propositions of feasible actions for improvements. The results showed increasing agri-digital initiatives in the five countries, which were grouped into seven categories based on their objectives. Steady progress was also observed in mobile internet adoption, despite the differences in deploying crucial infrastructure to promote digital agriculture. The mobile connectivity index (MCI) in all five countries is below 60. Nonetheless, Ghana and Côte d’Ivoire demonstrated more efforts in internet and electricity access, especially in rural areas. Benin and Nigeria have developed separate documents depicting the roadmap for digital agriculture, while the other countries are working to create one or have it embedded in their national development plans. Similarities and specificities exist among countries for laws and processes protecting agri-digital innovators. To be competitive and self-reliant in the global e-economy, these countries must reposition themselves to accelerate changes in digital agriculture through effective governance and synergy of actions in different sectors and across nations.

Тренды цифровизации в энергообеспечении АПК

The work is devoted to the analysis of the current level of digitalization of agriculture in the Russian Federation, the main indicators of digitalization that ensure the stable development of the agro-industrial complex are identified, and the prospects for the further development of digital technologies for the energy supply of the agro-industrial complex are identified. The project "Digital Transformation" of the Ministry of Energy of the Russian Federation is analyzed. As a result of the research, a number of conclusions were made about the current level of digital development of agriculture. Keywords: AGRO-INDUSTRIAL COMPLEX, DIGITALIZATION, ENERGY SUPPLY, DIGITAL TRANSFORMATION OF AGRICULTURE, THE LEVEL OF DIGITALIZATION OF AGRICULTURE, THE POTENTIAL OF DIGITALIZATION

Can agricultural digital transformation help farmers increase income? An empirical study based on thousands of farmers in Hubei Province.

With the deep integration of the digital economy and agricultural development, agricultural digital transformation promotes agricultural production, and industrial upgrading and broadens sales channels to achieve the strategic goal of rural revitalization in China. To explore whether agricultural digitization can help farmers increase their income and what path can be achieved, this study is based on the theoretical framework of rural revitalization theory and digitization. Through a questionnaire survey of 1500 farmers in Hubei Province, the impact mechanism of agricultural digitization transformation on farmers' income is empirically studied. The empirical results show that the digital transformation of agriculture can promote the increase in farmers' income, and promote the increase in farmers' income by improving production efficiency, broadening sales channels, and promoting the upgrading of agricultural structure. At the same time, both production efficiency and sales channels form a chain double intermediary path with the upgrading of agricultural structure. Under the background of rural revitalization, this study provides theoretical references and guidance for further promoting agricultural digital transformation to increase farmers' income. The marginal contribution of this study is to construct a theoretical model of agricultural digitization to promote farmers' income increase, which has important theoretical reference and guiding significance for guiding the development direction of agricultural digitization and promoting farmers' income increase.

On-Device Intelligence for Malfunction Detection of Water Pump Equipment in Agricultural Premises: Feasibility and Experimentation.

The digital transformation of agriculture is a promising necessity for tackling the increasing nutritional needs on Earth and the degradation of natural resources. Toward this direction, the availability of innovative electronic components and of the accompanying software programs can be exploited to detect malfunctions in typical agricultural equipment, such as water pumps, thereby preventing potential failures and water and economic losses. In this context, this article highlights the steps for adding intelligence to sensors installed on pumps in order to intercept and deliver malfunction alerts, based on cheap in situ microcontrollers, sensors, and radios and easy-to-use software tools. This involves efficient data gathering, neural network model training, generation, optimization, and execution procedures, which are further facilitated by the deployment of an experimental platform for generating diverse disturbances of the water pump operation. The best-performing variant of the malfunction detection model can achieve an accuracy rate of about 93% based on the vibration data. The system being implemented follows the on-device intelligence approach that decentralizes processing and networking tasks, thereby aiming to simplify the installation process and reduce the overall costs. In addition to highlighting the necessary implementation variants and details, a characteristic set of evaluation results is also presented, as well as directions for future exploitation.

Does Digital Transformation Promote Agricultural Carbon Productivity in China?

Against the background of global climate change and the rapid rise of the digital economy, the digital transformation of agriculture is profoundly changing the agricultural production and operation mode with the help of digital technology, becoming a new driving force for low-carbon and sustainable development of agriculture. However, previous studies rarely examined the impact of agricultural digital transformation on agricultural low-carbon transformation from the perspective of carbon productivity. To fill this gap, this study attempts to build a theoretical analysis framework for the impact of agricultural digital transformation on agricultural carbon productivity (ACP). By using a set of panel data from 30 provinces (cities) in China from 2011 to 2019, this study explores the impact of agricultural digital transformation on ACP, as well as its conduction mechanism and the non-linear mechanism. Empirical results show that the transformation of agricultural digitalization is conducive to the promotion of ACP. A series of robustness analyses support this conclusion. The main transmission mechanisms for digital transformation to affect ACP include agricultural industrial structure upgrading, and the agricultural scale operation. In addition, with the improvement of urbanization level and rural human capital, the impact of agricultural digital transformation on ACP presents a “U” type non-linear feature of inhibition first and promotion later. Furtherly, heterogeneity analysis shows that the impact of digital transformation on ACP will vary greatly depending on the levels of ACP, the geographical location of the studied area and whether it is a main grain-producing area. This study provides a theoretical and empirical basis for the improvement of China’s agricultural carbon productivity from the perspective of the digital economy.

Influencing the Success of Precision Farming Technology Adoption—A Model-Based Investigation of Economic Success Factors in Small-Scale Agriculture

Even more than 30 years after the introduction of precision farming technologies and studies of their benefits in terms of productivity gains and environmental improvements, adoption rates, especially for variable-rate technologies, are very low. In particular, in smallholder areas, farm managers are reluctant to adopt these technologies. Therefore, this study identifies factors that hinder or facilitate adoption from an economic perspective. Using a model-based sensitivity analysis with three farms of different sizes (11 ha, 57 ha and 303 ha), it is shown that larger farms have higher resilience to external factors due to economies of scale. In addition, it is clarified that the certainty of obtaining additional benefits with GPS guidance systems can explain the higher adoption rates in farming practice, although the additional benefits (per hectare and year) are much lower for this technology than for variable-rate technologies. Small farms (>30 ha) are by no means excluded from the use of digital technologies, as it is shown that the influence of learning costs on profitability is very low, low subsidies can lead to a drastic reduction in the minimum farm size and the presence of low-cost technologies is an efficient solution which allows small farms to participate in the digital transformation of agriculture.

Enriching IoT Modules with Edge AI Functionality to Detect Water Misuse Events in a Decentralized Manner.

The digital transformation of agriculture is a promising necessity for tackling the increasing nutritional needs of the population on Earth and the degradation of natural resources. Focusing on the “hot” area of natural resource preservation, the recent appearance of more efficient and cheaper microcontrollers, the advances in low-power and long-range radios, and the availability of accompanying software tools are exploited in order to monitor water consumption and to detect and report misuse events, with reduced power and network bandwidth requirements. Quite often, large quantities of water are wasted for a variety of reasons; from broken irrigation pipes to people’s negligence. To tackle this problem, the necessary design and implementation details are highlighted for an experimental water usage reporting system that exhibits Edge Artificial Intelligence (Edge AI) functionality. By combining modern technologies, such as Internet of Things (IoT), Edge Computing (EC) and Machine Learning (ML), the deployment of a compact automated detection mechanism can be easier than before, while the information that has to travel from the edges of the network to the cloud and thus the corresponding energy footprint are drastically reduced. In parallel, characteristic implementation challenges are discussed, and a first set of corresponding evaluation results is presented.

Labour productivity in the agricultural sector of the national economy is a key factor in the rise of production efficiency

Labour productivity is a parameter characterizing production efficiency, the state of the economy and prospects for its development. The socio-economic well-being of the population depends on its level. The modern vector of the country’s development into the digital economy allows concluding that the main goal of the digital transformation is the ability to reach higher labour productivity through digital technologies. Such a rise should occur, first, in material production, being the basis for the existence of society. Studies confirm that labour productivity in all sectors of the regional economy is at a low level. In a steadily developing economy, its rise rate should significantly outstrip the rise rate of its payment. For a more detailed assessment of the correspondence of the level of labour productivity to material incentives and analysis of their changes in time and space, it is proposed to calculate the “indicator of the level of labour productivity”. There is a regional outflow of labour resources from agriculture and the main condition for the rise of labour productivity in the present and foreseeable future will be the process of replacing living labour with highly productive machine labour, based on the digital transformation of agriculture.

МОДУЛЬ БАЗОВОЙ СТАНЦИИ ПРИЕМА-ПЕРЕДАЧИ ДАННЫХ ФИЗИОЛОГИЧЕСКОГО СОСТОЯНИЯ КРС

The digital transformation of agriculture and animal husbandry, in particular, involves, along with the development of sensors for the physiological state of cattle, the development of modular radio-technical digital devices for receiving and transmitting data. The developed module of the base station receives and transmits signals from bolus sensors located in the animal’s rumen according to three main parameters (acidity, pH; temperature; motor activity). The base station module consists of two parts connected by cables: a Raspberry Pi 4 minicomputer, which acts as a control device, and an external data transmission module, which includes a transceiver for communication with bolus sensors mounted on animals and a GSM module for Internet access and communication with the server. The analysis of these basic parameters makes it possible to monitor the physiological state of animals using the developed software according to the corresponding correlation relationships. The authors have developed basic electrical and structural diagrams of the data transmission module as part of the base station. Also, the article presents a block diagram of the logical structure of the base station software. A test program has been developed that includes checking signal levels in various types of rooms using sensor simulators-boluses. Tests have shown that the signal level measured in the rooms under consideration at various heights does not exceed the minimum permissible signal level –70 dB. The experimental results have established a relatively uniform signal level distribution in the room and increased heterogeneity in the corners, which makes it possible to find a compromise between the system parameters and make the necessary analyses to predict the performance of the entire complex.

ВОПРОСЫ ПРИМЕНЕНИЯ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА И ИЗМЕРЕНИЙ В СОВРЕМЕННОМ АГРОСЕКТОРЕ

The processes of globalization and internationalization of the modern economy, modernization of legislation, the increasing role of business in a competitive environment and the struggle for raw materials with an acute shortage of time have led to the need to make the only right decision – the creation of specialized intelligent information systems. The development of this direction is very relevant today, as it allows you to automate and significantly accelerate any kind of human activity. Potential directions for the development of the agroindustrial complex with the help of artificial intelligence are the more active introduction of electronic document management, a more extensive video surveillance system, a smart irrigation system, unmanned tractors and combines. Artificial intelligence (AI) can lead to a global digital transformation of agriculture. AI occupies a stable position in such areas as precision agriculture and smart animal husbandry, where decisions are made in connection with information received through satellite and computer technologies.

Issues of agriculture digitalization in the Russian Federation (legal aspect)

The President of the Russian Federation has set the task of achieving “digital maturity” of the key economic sectors, including agriculture, by 2030. At the same time, the digitalization of the agro-industrial complex is clearly lagging behind the pace of digital transformation in other sectors of the national economy. There are several reasons for this: the regulatory standards of the agricultural crops cultivation and the farm animals breeding are not perfect; the legal regulation of digitalization in the field of both production and agriculture is fragmented; the use of digital tools and information technologies in agricultural activities appears to be quite complicated. The article not only analyzes modern acts affecting the digital transformation of agriculture in the Russian Federation (including acts of the Ministry of Agriculture of the Russian Federation) and the problems of their application, but also suggests measures aimed to stimulate agricultural producers and food-processing companies, introducing innovative digital technologies, as well as provides recommendations for the use of special legal regimes that entered into force in 2021.

Цифровизация АПК с точки зрения процессного подхода к управлению

The article is devoted to the problem of searching for theoretical and managerial approaches to forecasting and designing the process of digital transformation of agriculture. The main directions of digitalization of the agricultural sector are considered by the authors from the point of view of a process approach to management that ensures integrity and consistency in understanding the ongoing and planned changes.

The digital transformation of agriculture in the context of the digital inequality

The purpose of the study is to identify the features of the digital development of the agricultural industry and to identify significant factors restraining its development. To achieve this goal, a comparative analysis of the impact of the level of accessibility availability and use of information and communication technologies (ICT) tools by agricultural entrepreneurs on sectoral performance indicators was carried out in the study. The paradox of performance in the context of digital inequality is revealed. The author’s position is formulated, the essence of which is to build digital platforms - ecosystems to support the industry’s growth mechanisms. The results obtained in this study can act as a driving force in agricultural production and sale systems.

Transformation of agriculture in the digital economy

The agricultural sector of the Russian economy is developing under the influence of digital technologies that contribute to the growth of competitiveness, which determines the relevance of this study. The Russian market of agricultural products is currently under economic sanctions that restrict trade and economic turnover and external relations. Despite the geo-political pressure, agriculture in the federal subjects of the country is successfully developing due to the purposeful course of the state on the systematic technological modernization of the industry. The Ministry of Agriculture of the Russian Federation has developed a project "Digital Agriculture", due to which it is possible to develop the industry on the basis of information technologies, and active work in this direction is carried out at the regional level. The dependence of agricultural producers on foreign technologies still persists. The introduction of digital solutions and equipment of domestic production will significantly increase the pace of the production intensification and the competitiveness of products, since the agricultural complex of the country has high potential. The article presents a study of the impact of innovative digital technologies on the development of agricultural production. The author applied general logical methods, systematization and scientific approaches to the analysis of the formation of the digital economy in the framework of increasing the production efficiency and improving the indicators of the agrarian economy as a whole. As a result, it was noted that the digital transformation of agriculture contributes to the modernization of production and high rates of its intensification, optimization of key business processes, and the improvement of financial and economic indicators of the industry enterprises. Digital solutions will have a positive impact on the quality of the production cycle stages, reducing the need for various types of resources and energy, and creating safe conditions for agricultural work. At the moment, there is an accumulation of successful experience in the implementation of digital solutions in the field of agricultural production, which is based on a project approach that unites various subjects of regional markets. Large agricultural holdings are implementing innovations at a faster pace, as they positively assess the planned effects. Positive dynamics in the management of business processes of industrial enterprises is provided by innovative technologies for monitoring the internal environment and conditions in which the preparation and organization of agricultural work is carried out.

Machine Learning in Agriculture: A Comprehensive Updated Review.

The digital transformation of agriculture has evolved various aspects of management into artificial intelligent systems for the sake of making value from the ever-increasing data originated from numerous sources. A subset of artificial intelligence, namely machine learning, has a considerable potential to handle numerous challenges in the establishment of knowledge-based farming systems. The present study aims at shedding light on machine learning in agriculture by thoroughly reviewing the recent scholarly literature based on keywords’ combinations of “machine learning” along with “crop management”, “water management”, “soil management”, and “livestock management”, and in accordance with PRISMA guidelines. Only journal papers were considered eligible that were published within 2018–2020. The results indicated that this topic pertains to different disciplines that favour convergence research at the international level. Furthermore, crop management was observed to be at the centre of attention. A plethora of machine learning algorithms were used, with those belonging to Artificial Neural Networks being more efficient. In addition, maize and wheat as well as cattle and sheep were the most investigated crops and animals, respectively. Finally, a variety of sensors, attached on satellites and unmanned ground and aerial vehicles, have been utilized as a means of getting reliable input data for the data analyses. It is anticipated that this study will constitute a beneficial guide to all stakeholders towards enhancing awareness of the potential advantages of using machine learning in agriculture and contributing to a more systematic research on this topic.