Agricultural Management Systems Research Articles

Precision Agriculture – A Vital Approach Towards Modernizing the Smart Farming in India

Abstract: Precision agriculture, also known as precision farming, is generally understood to be a farm management system based on information and technology that identifies, analyzes, and manages spatial and temporal variability within fields for maximum productivity and profitability, sustainability, and protection of the land resource by minimizing the production costs. The general public's growing environmental awareness makes it necessary for us to change agricultural management practices in order to sustainably conserve natural resources like water, air, and soil quality while being commercially successful. In the presented paper, we explore the idea of precision agriculture. This paper discusses the necessity for precision agriculture, related technology, the strategy for achieving it, the challenges encountered along the way, and potential solutions that can help the discipline advance. This work summarizes a thorough knowledge of the concept and the future path necessitating additional research, taking into account various research publications produced in the previous decade. Anyone interested in learning more about or conducting research on precision agriculture can use it as a starting point.

Agriculture management system

The Agriculture Management System is a web-based platform that provides farmers with a full range of agricultural information. Its goal is to increase farmers' productivity and profitability by using a centralized system for managing their agricultural operations. The system gives farmers access to critical data such as weather forecasts, soil and crop statistics, allowing them to make informed decisions and improve their farming operations. In terms of weather management, the technology provides precise forecasts, which help farmers plan their operations more efficiently. Farmers can use this data to identify the best time to plant, harvest, and perform other agricultural duties. Regarding market prices, the AMS gives farmers with real-time crop and livestock prices, allowing them to make informed pricing and marketing decisions. Furthermore, the technology provides farmers with critical soil and crop data, giving them insights into soil quality and crop health. This data helps farmers improve their agricultural practices by allowing adjustments to planting schedules, fertilizing, and irrigation systems to increase crop yields and quality. Recognizing the value of cooperation and information sharing, the AMS includes an AI-powered chatbot. This feature allows farmers to share information, seek assistance, and ask questions about the agricultural management system, including crops, soil, market trends, and weather management. The incorporation of this interactive technology encourages a communitydriven approach to agricultural management, creating a conducive atmosphere for farmers to flourish.

Effects of sustainable agronomic intensification in a forage production system of perennial grass and silage corn on nutritive value and predicted milk production of dairy cattle.

The objectives were to determine the effects of incrementally applied improved nutrient management, alternative cropping practices, and advanced production technologies in a dual forage system of perennial grass and silage corn on nutrient composition and in vitro ruminal fiber digestibility of the forages and, using these data as inputs into the Cornell Net Carbohydrate and Protein System, to predict milk production, indicators of nitrogen (N) utilization, and N excretion of dairy cattle. Farm management systems (farmlets) included a conventional system with whole manure slurry broadcast to a late maturing corn hybrid and grass harvested with 5 cuts per year (F1); improved nutrient management with a separated manure system where the sludge was applied to corn and the liquid was applied to grass (F2); improved nutrient management and alternative cropping practices with separated manure, an early maturing corn hybrid interseeded with a relay winter cover crop, and grass harvested with 3 cuts per year (F3); and improved nutrient management and alternative cropping practices combined with advanced production technologies that included irrigation and a nitrification inhibitor (F4). The field trial was a randomized complete block design over 2 yr with 4 blocks each divided into grass and corn, 4 subplots within each block for each crop, and 2 replicates within each subplot. Diets were formulation with 60% forage and 40% concentrate where the grass and corn as silage was proportional to yield for land allocations of grass and corn of 80:20, 60:40, 40:60, and 20:80. Data were analyzed using the MIXED procedure of SAS (SAS Institute Inc.). The intensified management systems (F2, F3, and F4) increased the crude protein (CP) concentration of corn with no effects on starch concentration [32.1% dry matter (DM)] compared with the conventional system (F1). Decreasing cuts of grass from 5 to 3 reduced the CP concentration in the spring harvest (15.8% vs. 12.5% DM), and increased fiber concentration and reduced digestibility in the spring, summer, and fall harvests. A common concentrate was formulated for the conventional farmlet and then combined with the forages for each farmlet within each land allocation. Forages grown under intensified management to improve N capture increased the CP concentration of the diets. However, reducing the number of cuts of grass from 5 to 3, combined with the corn and relay crop to increase yield, reduced milk production across all land allocations. To complement the nutritive value of the forages grown under each management system and land allocation, the concentrates were reformulated, which reduced dietary CP, improved the indicators of N utilization (e.g., milk urea N and milk N efficiency), reduced N excretion, and improved milk yield with no differences among the farmlets. Increasing land allocated to corn supported higher milk yield at lower dietary CP concentrations (16.5% vs. 15.4% DM) with improved milk N efficiency and lower N excretion. Intensified agronomic management increased the CP of the combined forages decreasing the need for supplemental CP in the concentrate and could reduce the importation of feed N to the farm.

Issues of digitalization of machine and tractor fleets in agriculture

The article describes an intelligent machine and tractor fleet in agriculture. The article also describes smart technologies that facilitate participants' work in agricultural management and maintenance systems in machine and tractor fleets.

RETRACTED: The research on application of agricultural big data agricultural economic management

AbstractThis paper applies agricultural big data into agricultural economics management in order to improve agricultural economics management effects and comprehensively analyzes criterion and trending, maturity and advancement, practice and advancement, usability and extension of the platform according to the structure of agricultural economics management system by using big data. Meanwhile the paper describes the actual application condition of agricultural economics management, designs tests to analyze the agricultural economics data and digs the effects according to the agricultural economics management data through the crawler technology, and explains the application effects in the agricultural economics management. Tests and studies prove the reliability of the method put in the paper.

CONCEPTUAL BASIS OF POST-WAR TRANSFORMATIONS OF AGRICULTURE OF UKRAINE

Stable and efficient functioning of agriculture has gained priority importance in ensuring food independence of the country. However, the Russian military invasion and temporary occupation of part of the territory of Ukraine caused significant destructive consequences in the agricultural sphere. The purpose of the article is to analyze the state of agriculture during the war and outline the structural transformation during the post-war reconstruction period. The task is outlined by determining the amount of losses in the agricultural sector from Russian aggression and choosing the vector of transformational shifts in its post-war reconstruction and further development. The empirical base includes information from the Institute of Agrarian Economics, the Ministry of Agrarian Policy and Food of Ukraine, scientific and review publications. Theoretical and applied processing of information is based on tabular methods ‒ to build series of production dynamics and outline agricultural production management systems; methods of system analysis ‒ for comparative characteristics of the functioning of the individual and corporate sectors of agriculture, identifying the causes and consequences of the problematic situation in the industry; abstraction ‒ to highlight the most essential signs, properties and connections that characterize the development of the agricultural sector; substantiation and generalization ‒ to establish the regularities of the further development of agriculture. As a result of the study, it was established that the agricultural sector of Ukraine's economy suffered significant losses from hostilities. The advantages and disadvantages of the individual and corporate sectors of agriculture are substantiated. The advantages and disadvantages of the corporate sector or wholesale agrarian business in Ukraine are presented on the example of the functioning of agricultural holdings. The advantages of the individual sector in ensuring the domestic consumer market have been proven. The ways of post-war reconstruction of agriculture based on the principles of farming in accordance with the recommendations of the UN and the common agrarian policy of the European Union are substantiated.

Development of QAgriSupport, a GIS-based Agricultural Production Process Management System, and Foregis, a Mobile Application

In Japan, subsistence feed production has gained momentum in recent years. There has been an increase in the establishment of feed production contractors and efforts by cultivating farmers to grow feed crops, which are then harvested and purchased by contractors and others. These efforts serve a large production scale where the target fields are dispersed over a wide area. Thus, it is challenging to manage the work progress, which is a significant issue in the production field. Multipurpose process management methods and software are available for general manufacturing industries. However, applications for agricultural production, especially those that allow process management while displaying field information on a map, are expensive and lack sufficient functionality. To address these issues, this study developed a free, map-based agricultural production process management system, QAgriSupport, and a mobile application, Foregis, which can be coupled with QAgriSupport for agricultural enterprises that are large-scale and have widely dispersed fields. These applications have been introduced at a farm-type TMR (total mixed ration) center engaged in large-scale double-cropping of corn and a large-scale rice production corporation engaged in rice WCS (whole crop silage) and forage rice production. In addition, these applications have made a significant contribution to agricultural production process management by improving the efficiency of field-to-field movement and reducing the time required for work orders.

УДОСКОНАЛЕННЯ ЕКОНОМІЧНИХ ІНСТРУМЕНТІВ ЕКОЛОГІЧНОГО УПРАВЛІННЯ В УКРАЇНІ

The article is devoted to the actual problems of improving the economic tools of environmental management. The analysis of the normative and legal framework made it possible to identify the problems of environmental management. Forms are considered and justified types, procedure, terms and peculiarities of environmental management are proposed. Attention is paid to the issues that arise between participants in industrial relations of environmental management. Proposals for improving the economic tools of ecological management, which are the provision of progressive development of the agrarian sector of the national economy, and the growth of its competitiveness, are substantiated. Numerous problems related to the procedure for conducting a financial and environmental audit are identified. ISO standards of the 1400 series are considered, the purpose of which is involved in guaranteeing the preservation of the environment. It’s established that this standard does not contain strict requirements for ecology, but is oriented towards compliance by business entities with certain procedures that will contribute to the improvement of the environmental situation in the world. These documents stipulate that the system of standards will ensure the reduction of adverse effects on the environment through the relevant areas of improvement of the economic tools of environmental management. The problems of the efficiency of the rational use of land resources and the results of the short-term requirements of landowners or tenants regarding obtaining the maximum profit and, as a result, the depletion of the country's land fund are considered. The results of the study of the financial and environmental audit as part of the environmental protection activities of agricultural enterprises are recommended for implementation not only in farms, but also in all other formations of small and medium-sized agrarian entrepreneurship. A comprehensive approach to the assessment of environmental protection activities of agrarian enterprises is used, which provides sufficient justification for a number of practical recommendations for improving the current organizational and economic mechanism of the financial and environmental audit of the functioning of agrarian enterprises. It’s confirmed that the processes of loss of soil fertility are related to the lack of systematic state regulation of prices for agricultural and industrial products. The reason lies in the lack of an economically justified mechanism for changing the agricultural production management system associated with the differentiation of forms of ownership.

Management accounting in the agricultural enterprise information system

The complexity of the relationship of modern agricultural enterprise in connection with the change in their financial and economic situation puts forward new requirements for the connection of agricultural enterprises with the information support of the activity management process. Modern conditions of the external environment of agricultural enterprises and the aggravation of price competition complicate the issue of effective management of agricultural enterprises. This problem manifests itself during a period of crisis in the national economy, especially in the activities of industrial agricultural enterprises, and they are forced to look for other ways to maintain their positions in the market. In the agricultural enterprise management system, management decisions are made based on reliable and timely information through the use of modern management, accounting, planning, analysis and control tools. Points of view on the interpretation of management accounting vary depending on the development of economic systems and the impact of economic globalization processes. The modern view of management accounting did not arise immediately, many scientists and researchers in the study of historical periods are trying to find out the main foundations and conditions for its formation. Therefore, this article clearly studies management accounting in the information system of agricultural enterprise.

Drought events in Hungary and farmers’ attitudes towards sustainable irrigation

Among the different forms of agricultural damage in Hungary, drought poses a remarkably high risk according to the reported drought events, the area affected, and the level of mitigation payments. This study explores drought damage based on the 2018–2020 data of the Hungarian Agricultural Risk Management System. Owing to eligibility criteria, slightly more than half of the members of the scheme who reported drought damage received mitigation payments, but for them, the value of compensation significantly exceeded the mitigation contribution. According to our results, most of the damaged areas were outside the impact areas of water supply systems or were within the impact area but on non-irrigated fields, which proved that irrigation could be an effective drought mitigation tool. To avoid drought damage, irrigation development is essential, and special attention should be paid to the territory of Szabolcs-Szatmár-Bereg county. This area suffered significant drought damage in the years examined, and currently the impact area of the surface water-based water supply systems is small, while the groundwater resources are already overexploited. At the same time, the risk management system should be modified to transform it into a preventive system which encourages farmers to use water retentive soil cultivation methods, appropriate cropping systems, sustainable water management, and efficient and reasonable levels of irrigation. Accordingly, fewer mitigation benefits would be paid through less drought damage. Based on questionnaire surveys, farmers are open to using water retention practices and sustainable irrigation management.

Integrated agriculture IoT based farm monitoring and management systems

Integrated agriculture IoT based farm monitoring and management systems

Integrated agriculture IoT based farm monitoring and management systems

Integrated agriculture IoT based farm monitoring and management systems

Digital monitoring of crops in grain ecosystems

In the conditions of rapid global population growth, resource depletion, and increasing demand for grains, an efficient agricultural management system becomes a crucial element for ensuring food security in Russia and worldwide. The foundation of such management is an intelligent grain production monitoring system, where diagnosing grain crop diseases serves as a critically significant subsystem. This article presents an approach based on the utilization of neural networks, specifically the U-Net architecture for semantic segmentation, adapted for the analysis and detection of helminthosporium through images of maize leaves. Quality evaluation of segmentation employs metrics like Intersection over Union (IoU) and Dice coefficient, computed from a held-out dataset, ensuring an objective assessment of results. The research demonstrates high accuracy and similarity between the model's predictions and expert annotations, while also showcasing the convergence of loss function during neural network training. A notable advantage of the proposed approach lies in the lightweight nature of the suggested architecture and the ability to utilize trained models as cores for decision support systems, including on local devices without network connectivity.

Assessment of the Impacts of Converting Natural Wetlands to Agricultural Farms. Case of Nyabugogo, Kigali City, Rwanda

The assessment of the impacts of converting natural wetlands to agricultural farms in Nyabugogo wetland was the main objective for this research. Considering the efficiency of agricultural activities management, operation and their maintenance in Kigali is essential to reduce the increasing environmental pollution, to raise production and to search for a sustainable method of environmental conservation, this research assesses the pollutant removal efficiency of agriculture such as crops and animal residues in order to enhance the sustainable agriculture development mainly physico-chemical characteristics and some biological characteristics and based on the preliminary assessment and review of existing literature on agriculture management systems for water resources and other environmental conservation concerns in Kigali, the research aims at contributing to the search of an appropriate agriculture management that is more efficient in terms of the increase in productivity, hence contributing to environmental sustainability. Six sampling sites were chosen in Nyabugogo wetland that is Nyabugogo, Karuruma, Kabuye (2 destinations), and Nyacyonga (2 destinations). Nyabugogo and Karuruma in the rural area, and Nyacyonga in the urban area, were chosen for the investigation of fecal coliforms. On the two first locations, Nyabugogo (80 cfu/100ml) and Karuruma (40 cfu/100ml), the study found low but not insignificant results. This is related to the dispersion of habitation in rural areas. Total Dissolved Solid (TDS) ranged from 178.1 mg/l to 179.9 mg/l at Site 1 (dry season) and subsequent test (rainy season) results ranged from 178 to 200 mg/l. The results showed different TDS in different test areas. The TDS was as low as 145.4 mg/l in the surface water of SP4 and as high as 179.9 mg/l in SP1, and in the second survey, the minimum value was 140.3 mg/l and the maximum value was 285 mg/l in SP3. Because the high turbidity levels seen along the river, in the Nyabugogo catchment, erosion protection measures should be implemented, including the use of terraces where there is agricultural activity and tree plantations, particularly at Nyabugogo sites. As a result, the Nyabugogo Riverbanks must be preserved. It would cut down on the quantity of sediment that ends up in waterways.

Artificial Intelligence Technology in the Agricultural Sector: A Systematic Literature Review

Due to the increasing global population and the growing demand for food worldwide as well as changes in weather conditions and the availability of water, artificial intelligence (AI) such as expert systems, natural language processing, speech recognition, and machine vision have changed not only the quantity but also the quality of work in the agricultural sector. Researchers and scientists are now moving toward the utilization of new IoT technologies in smart farming to help farmers use AI technology in the development of improved seeds, crop protection, and fertilizers. This will improve farmers’ profitability and the overall economy of the country. AI is emerging in three major categories in agriculture, namely soil and crop monitoring, predictive analytics, and agricultural robotics. In this regard, farmers are increasingly adopting the use of sensors and soil sampling to gather data to be used by farm management systems for further investigations and analyses. This article contributes to the field by surveying AI applications in the agricultural sector. It starts with background information on AI, including a discussion of all AI methods utilized in the agricultural industry, such as machine learning, the IoT, expert systems, image processing, and computer vision. A comprehensive literature review is then provided, addressing how researchers have utilized AI applications effectively in data collection using sensors, smart robots, and monitoring systems for crops and irrigation leakage. It is also shown that while utilizing AI applications, quality, productivity, and sustainability are maintained. Finally, we explore the benefits and challenges of AI applications together with a comparison and discussion of several AI methodologies applied in smart farming, such as machine learning, expert systems, and image processing.

An evidence-based relationship between technical assistance and productivity in cocoa from Tocache, Peru

Abstract The growth of small-scale Peruvian farmers is highly dependent on cocoa factor productivity. Agricultural extension programs can help to improve farm productivity using available resources. Thus, the objective of this study is to estimate the productivity of Peruvian cocoa farming and identify if frequent technical assistance impacts on farmers’ technical efficiency. The data came from a survey of 379 cocoa farmers in Tocache, San Martin (177 producers who sell through intermediaries and 202 who are cooperative members), conducted between January and June 2015. This article is supported by the interaction of two associated techniques: the production function and the technical efficiency technique based on stochastic frontier analysis (SFA). The key findings were that the estimated coefficients for labor, capital, land and fertilizer were positive to cocoa production. Our outcomes also show there is a (marginally) significant relationship between technical assistance and technical efficiency (p-value<10%). There is also a positive relationship between efficiency and other socioeconomic characteristics of being a male, having experience in cocoa cultivation and practicing non-diversification in other crops. Policymakers could consider these results to improve farm management systems and, therefore, the competitiveness of the cocoa plantations in the Peruvian Amazonia.

Digital transformation of agricultural sector in Uzbekistan: Current state, advantages and strategies

Agriculture was and still is the largest sector in economy of Uzbekistan. From the other hand, the digital economy is penetrating to all sectors of the economy, including the agriculture sector. Further development of agricultural sector through the digitalization is of great importance. In Uzbekistan, much attention is being paid to the effective use of information technology in the agricultural field. Creating and implementing an automated farm management system is one of today’s major tasks. This research aimed at analyzing the opportunities and development of agriculture in Uzbekistan using digital technologies in comparison with other well-developed countries. At the end of the paper, the conclusions are made and the recommendations are presented as a result of the research.

Nitrogen management with reinforcement learning and crop growth models

Abstract The growing need for agricultural products and the challenges posed by environmental and economic factors have created a demand for enhanced agricultural systems management. Machine learning has increasingly been leveraged to tackle agricultural optimization problems, and in particular, reinforcement learning (RL), a subfield of machine learning, seems a promising tool for data-driven discovery of future farm management policies. In this work, we present the development of CropGym, a Gymnasium environment, where a reinforcement learning agent can learn crop management policies using a variety of process-based crop growth models. As a use case, we report on the discovery of strategies for nitrogen application in winter wheat. An RL agent is trained to decide weekly on applying a discrete amount of nitrogen fertilizer, with the aim of achieving a balance between maximizing yield and minimizing environmental impact. Results show that close to optimal strategies are learned, competitive with standard practices set by domain experts. In addition, we evaluate, as an out-of-distribution test, whether the obtained policies are resilient against a change in climate conditions. We find that, when rainfall is sufficient, the RL agent remains close to the optimal policy. With CropGym, we aim to facilitate collaboration between the RL and agronomy communities to address the challenges of future agricultural decision-making.

The ground beetle Pseudoophonus rufipes gut microbiome is influenced by the farm management system

Intensive conventional farm management, characterized by high agrochemicals input, could alter the composition of microbial communities with potential negative effects on both functional traits and the ecosystem services provided. In this study, we investigated the gut microbial composition of a high ecological relevance carabid Pseudoophonus rufipes, sampled in two fields subjected to conventional and organic management practices. Carabids’ gut microbiota was analyzed via qPCR and NGS. Profound differences between the microbial composition of organic and conventional samples were detected: the abundance of Tenericutes and Proteobacteria was significant higher in organic and conventional samples, respectively. Spiroplasmataceae and Bifidobacteriaceae families were significantly more abundant in samples from organic management, while Enterococcaceae, Morganellaceae and Yersiniaceae were more abundant in samples from conventional management. The diverse gut microbial composition of insects between the two management systems is related to the pressure of environmental stressors and it may representing an important bioindication of ecological functions and services provided by a carabid species.

THEORETICAL AND METHODOLOGICAL PRINCIPLES OF ASSESSING THE EFFICIENCY OF THE USE OF AGRICULTURAL LANDS

The paper substantiates the theoretical and methodological principles of evaluating the efficiency of agricultural land use. The purpose of regulating land use and agricultural production is substantiated, the essence of which is to ensure national food security and preserve and improve agroecosystems as the most important component of the natural and economic potential of the country as a whole. In the context of the specified goal, the principles of effective use of agricultural land resources are defined. It was established that the effectiveness of the agricultural land management system at the micro level reflects a number of indicators and criteria, which are divided into economic, ecological and social. It is substantiated that the principle of rational use and protection of land resources now acquires special importance from the standpoint of maximizing the final results of economic activity of land users. It has been established that the promising areas of agricultural land use include: the development of an adaptive landscape system of agriculture that meets the needs of society, the requirements of agricultural crops, natural conditions, the level of production and the requirements of minimal risk of contamination of products and the environment; the use of resource-saving technologies based on cost reduction through minimal tillage, the use of a new generation of agricultural machines and aggregates; carrying out an inventory of agricultural lands; increasing the professionalism of workers involved in the production of agricultural products; creation of conditions for preservation and effective use of especially valuable productive agricultural lands, establishment of their boundaries; implementation of measures to restore and preserve the reclamation complex in the regions.