Agricultural Information Technology Research Articles

Role of Information Technology in Agriculture : A Review

Information Technology (IT) is the application of computers and telecommunications equipment to store, retrieve, transmit and manipulate data, often in the context of a business, education or other enterprise. This paper reviewed the India’s IT Industry and in addition studied the Impact of IT on the Indian Agriculture. To improve the quality of agricultural products and production using information technology that requires efficiency and information in all sectors of agriculture. Information technology support new methods and ideas for precision and healthy agriculture used computers in farm, climate or weather forecasting, use of method and materials and kind of crops. In this paper I tried to find how information technology is useful for making choices to setting goals, improve planning and produce better agriculture products and study the key elements and basic issues of information technology in agriculture.

Agricultural raw materials, information and communications technology and service exports on economic growth in twenty Sub-Saharan countries: A panel vector error correction model approach

Agricultural raw materials, information and communications technology and service exports on economic growth in twenty Sub-Saharan countries: A panel vector error correction model approach

Adoption of green production technologies by farmers through traditional and digital agro-technology promotion–An example of physical versus biological control technologies

Traditional and digital agro-technology promotion are two critical methods for disseminating agricultural technology information, which effectively encourages farmers to employ green production technologies. This paper empirically examines the effects of traditional and digital agro-technology promotion on the adoption of green production technologies by 619 apple producers in the primary apple production area of Guanzhong Plain, China, using micro-survey data. The study's findings suggest that both promotion models significantly influence the adoption of green production technologies by farmers. This conclusion remains valid after the instrumental variables approach and a series of robustness tests are implemented to address endogeneity concerns. The heterogeneity analysis revealed that the impact of the two promotion modes on the adoption behavior of green production technologies by farmers varied by scale. Specifically, digital agro-technology promotion had a greater impact on the adoption of physical control technologies by small-scale farmers, while traditional agro-technology promotion had a greater impact on the adoption of biological control technologies by large-scale households. In addition, the technological differences between traditional agrotechnology promotion and digital agrotechnology promotion result in clear complementary and substitution effects. The two modes of promotion have evident complementary effects for biological control technologies. The two modalities of promotion for physical control technologies exhibit complementary effects between social communication-type promotions and traditional agro-technology promotions, as well as substitution effects between short-video promotions and traditional agro-technology promotions.

Development of a hydroponic device using potassium Ion-Selective electrode and neural network technology

The rapid development of modern agricultural biotechnology and information technology has become a key driver of modern agricultural growth. The demand for ion detection is prevalent in all aspects of agriculture. This study details the research on an ion sensor agricultural system using potassium (K) ion-selective electrodes (ISEs). The main emphasis is on the application of artificial neural networks (ANNs) for driving ISE development of accuracy. ISEs based on solid contact with metal oxides, specifically manganese dioxide, are studied. Moreover, the design details of an ion signal acquisition device using the NI-9205 acquisition card and LabVIEW are presented. Finally, based on experimental results of nutrient solution samples, ANNs show better performance than the multiple linear regression method. The mean relative error of K-ISE detection was maintained within 4%. This study thoroughly discusses ISE technology to promote its adoption in agriculture.

Information technologies in agriculture of Northern Kazakhstan: advantages, reserves

Ensuring sustainable development of the agrarian sector of the economy requires the integrated use of digitalization technologies. The aim is to show the current trends in the application of information technologies in agriculture in Northern Kazakhstan and to determine the conditions necessary for the introduction of modern digital infrastructure. Methods - system-structural, economicstatistical, comparative analysis, mathematical and system-functional approaches to the study of the use of information and communication technologies by agribusiness of agricultural profile. Results - the authors analyzed the scope of application of digital processes in the region. The factors influencing the use of modern digital technologies in the cultivation of agricultural land have been outlined. The dependence of the application of precision farming elements on the farm size is revealed. The calculation of economic efficiency of reference and information systems of production management is presented. Measures to overcome obstacles and mitigate the limitations of digital transformation in agriculture in the northern territories of the republic are proposed. Conclusions - based on the study it is noted that the spread of digital innovations is from 18 to 55% of the total sown area. When comparing the average land size of economic entities that implement information technologies with other farms, it was found that digital solutions in crop production are primarily available to large and medium-sized agroformations that have the financial capacity and qualified specialists for digitalization. The survey of respondents allowed us to express an opinion on the influence of the size, technical equipment and economic stability of an agro-industrial enterprise on the use of modern farming systems, as well as the level of awareness of agro-entrepreneurs about new technologies. The use of digital platforms in the crop production industry is a key element that contributes to increasing the economic efficiency of the agro-industrial complex.

Challenges in Accessing Agricultural Technology Information Centre’s Services: Identifying Key Constraints in Kanpur District

Challenges in Accessing Agricultural Technology Information Centre’s Services: Identifying Key Constraints in Kanpur District

Use of Digital Technologies for the Conduct of Work in the Government System Based on the Demans of the Current Times

This article deals with the issues of ensuring the safety of the population in the residences of citizens. It is planned to implement an electronic platform that allows for quick collection and analysis of information on the technical and social condition of residential areas. These strategies focus on digital transformation in the national economy, industry, and society. In Uzbekistan, significant steps have been taken to implement modern information and communication technologies (ICT) in public administration, education, healthcare, and agriculture. One notable challenge addressed in this study is the management of carbon monoxide poisoning, fire hazards, and explosions during the heating season. The research highlights the limitations of manual data collection, including the risk of data loss, difficulty in locating information, and inefficiencies in processing critical safety data. The program processes data in less than a minute, facilitating more efficient emergency management and preventive measures. This system exemplifies the role of digital technology in enhancing public safety and optimizing government operations.

Information and communication technology in smart agriculture: A scientometric review

SummaryAgriculture has been affected by several global trends raising the concern for food security. Agri‐food demands are amplifying due to the ever‐escalating population numbers. Thus, the notion of extending the use of smart innovative technology in managing agricultural practices has emerged rapidly over the last decade. Technological innovations have contributed significantly to shape modern agriculture as smart agriculture. Smart agriculture unfolds various benefits such as increased production, real time data and production insights and remote monitoring. The rising advancements in Information and Communication Technologies (ICT) have paved the way for researchers to use these technologies in managing agricultural practices, leading to greater benefits for farmers and society. These innovations are the key to establishing agriculture as a research discipline. The purpose of this article is to conduct a scientometric analysis to study the structure and evolution of research activities in the field of smart agriculture. The scientometric analysis aims to empirically map the scientific knowledge and identify any possible challenges in the field. This study performs elementary analysis to study publication growth over the years, impact analysis to assess the leading journals, authors, and countries, and articles analysis for findings patterns among the citations over the years and among the keyword‐based clusters. There has been a considerable increase of more than 200% in the number of publications from 2011 to 2022. However, around 60% of authors have contributed with a single publication. The findings of the study reveal the research trends and hot topics for future research fronts. Deep learning, digital agriculture, object detection, blockchain, and semantic segmentation have been identified as trending topics in smart agriculture. Comprehensively, an intellectual view of the agriculture domain is presented as a scientific field in this article.

A Redactable Blockchain-Based Data Management Scheme for Agricultural Product Traceability.

With the development of agricultural information technology, the Internet of Things and blockchain have become important in the traceability of agricultural products. Sensors collect real-time data in agricultural production and a blockchain provides a secure and transparent storage medium for these data, which improves the transparency and credibility of agricultural product traceability. However, existing agricultural product traceability solutions are limited by the immutability of the blockchain, making it difficult to delete erroneous data and modify the scope of data sharing. This damages the credibility of traceability data and is not conducive to the exchange and sharing of information among enterprises. In this article, we propose an agricultural product traceability data management scheme based on a redactable blockchain. This scheme allows agricultural enterprises to encrypt data to protect privacy. In order to facilitate the maintenance and sharing of data, we introduce a chameleon hash function to provide data modification capabilities. Enterprises can fix erroneous data and update the access permissions of the data. To improve the efficiency of block editing, our scheme adopts a distributed block editing method. This method supports threshold editing operations, avoiding single-point-of-failure issues. We save records of data modifications on the blockchain and establish accountability mechanisms to identify malicious entities. Finally, in this paper we provide a security analysis of our proposed solution and verify its effectiveness through experiments. Compared with the existing scheme, the block generating speed is improved by 42% and the block editing speed is improved by 29.3% at 125 nodes.

Investigating the impact of agricultural informatization on the carbon shadow price

The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China.

Evaluating the Efficacy of Segment Anything Model for Delineating Agriculture and Urban Green Spaces in Multiresolution Aerial and Spaceborne Remote Sensing Images

Segmentation of Agricultural Remote Sensing Images (ARSIs) stands as a pivotal component within the intelligent development path of agricultural information technology. Similarly, quick and effective delineation of urban green spaces (UGSs) in high-resolution images is also increasingly needed as input in various urban simulation models. Numerous segmentation algorithms exist for ARSIs and UGSs; however, a model with exceptional generalization capabilities and accuracy remains elusive. Notably, the newly released Segment Anything Model (SAM) by META AI is gaining significant recognition in various domains for segmenting conventional images, yielding commendable results. Nevertheless, SAM’s application in ARSI and UGS segmentation has been relatively limited. ARSIs and UGSs exhibit distinct image characteristics, such as prominent boundaries, larger frame sizes, and extensive data types and volumes. Presently, there is a dearth of research on how SAM can effectively handle various ARSI and UGS image types and deliver superior segmentation outcomes. Thus, as a novel attempt in this paper, we aim to evaluate SAM’s compatibility with a wide array of ARSI and UGS image types. The data acquisition platform comprises both aerial and spaceborne sensors, and the study sites encompass most regions of the United States, with images of varying resolutions and frame sizes. It is noteworthy that the segmentation effect of SAM is significantly influenced by the content of the image, as well as the stability and accuracy across images of different resolutions and sizes. However, in general, our findings indicate that resolution has a minimal impact on the effectiveness of conditional SAM-based segmentation, maintaining an overall segmentation accuracy above 90%. In contrast, the unsupervised segmentation approach, SAM, exhibits performance issues, with around 55% of images (3 m and coarser resolutions) experiencing lower accuracy on low-resolution images. Whereas frame size exerts a more substantial influence, as the image size increases, the accuracy of unsupervised segmentation methods decreases extremely fast, and conditional segmentation methods also show some degree of degradation. Additionally, SAM’s segmentation efficacy diminishes considerably in the case of images featuring unclear edges and minimal color distinctions. Consequently, we propose enhancing SAM’s capabilities by augmenting the training dataset and fine-tuning hyperparameters to align with the demands of ARSI and UGS image segmentation. Leveraging the multispectral nature and extensive data volumes of remote sensing images, the secondary development of SAM can harness its formidable segmentation potential to elevate the overall standard of ARSI and UGS image segmentation.

ОСОБЛИВОСТІ ІНФОРМАЦІЙНО-КОМУНІКАЦІЙНИХ ТЕХНОЛОГІЙ СІЛЬСЬКОГОСПОДАРСЬКИХ ПІДПРИЄМСТВ КИТАЮ

The article analyses the peculiarities of information and communication technologies of agricultural enterprises in China. The relevance of the work is due to the increasing digitalisation of agriculture at the global level, as well as the digitalisation of the Chinese economy. In addition, the role of modern technologies is becoming the key to the development of agriculture in general. The study is based on the works of Ukrainian and Chinese scholars on the selected topic. The purpose of the study is to analyse the current features of the use of information and communication technologies in the agricultural sector on the example of Chinese agricultural enterprises. The article analyses the main features of the use of information and communication technologies in agriculture. The peculiarities of digital and electronic agriculture are identified. The features of the introduction of information and communication technologies in agriculture in China are determined. The historical patterns of the use of modern technologies in agriculture of the country are determined. The main directions and manifestations of the use of information and communication technologies by agricultural enterprises in China are considered. Special attention is paid to the importance of social networks for Chinese agricultural enterprises. The main advantages of the use of information and communication technologies by Chinese agricultural enterprises are also identified, and the role of ICT in ensuring food security is considered. The article highlights the shortcomings and problems of using modern technologies in Chinese agriculture, among which are insufficient Internet coverage and insufficient information education of employees. The results of the study demonstrate the importance of information and communication technologies for Chinese agricultural enterprises and prove their positive impact on the development of agriculture in the country as a whole. The results obtained can be used to further improve information and communication technologies in Chinese agricultural production and to improve the digitalisation of agriculture in the country.

Information and communication technologies in agriculture: a systematic literature review

Information and communication technologies in agriculture: a systematic literature review

Consumption Pattern of Information and Communication Technology in Agriculture: A Study of Jaipur District

The study was conducted in Girdharipura and Mehla villages of Jaipur district of Rajasthan. The study analyzes how ICT is used for agricultural information in rural regions and evaluates the information and relationship between various ICT tools and farmers. In this research, we used a sample size of 100 farmers with a random selection of 50 farmers from Mehla village and 50 farmers from Girdharipura village, all between the age group of 20 and 55 from June 2021 to December 2021. ICT holds huge potential in the dissemination of agriculture-related information to rural masses for their capacity building. Thus, ICT is rightly hailed as a potentially useful tool for agricultural reforms. Farmers often engage in numerous forms of media consumption and do not limit themselves to a single one. This study suggests that farmers engage in various media consumption such as electronic media, folk media & print media, and ICT tools for agriculture purposes, and weather information. Mehla village was using more electronic media than Girdharipura.

Research on Information Technology Innovation and Rural Revitalization Strategies of Agricultural Complex Teaching and Research Bases in Colleges and Universities

Abstract The construction of agricultural composite teaching and research bases plays an important role in promoting rural revitalization and strengthening agricultural education. This paper emphasizes the role of agricultural information technology innovation in rural revitalization and proposes the impact of agricultural technology innovation on the development of rural revitalization. The variables of agricultural technology innovation as well as rural revitalization are selected, the benchmark regression model is set, the local impact model is set for the seven secondary indicators under agricultural technology innovation, and the evaluation index model is constructed. Through the empirical analysis method, the model is sequentially subjected to preliminary analysis and nonlinear characterization. Benchmark regression test using the fixed-effects model, model (7) shows that agricultural technological innovation at the 1% significant level of β =2.6548, P < 0.01, indicating that agricultural technological innovation has a positive and positive impact on rural revitalization. The threshold test shows that when the level of financial activity is lower than the threshold effect of 0.0965, the coefficient of the impact of agricultural technological innovation on rural revitalization is 0.0458. The effect of agricultural technological innovation on rural revitalization is affected by the intensity of financial activity, and there is a moderating effect of economic activity on both.

E-Agricultural for Better Yield

Abstract: The advent of newer technologies had led scientists and researchers to monitor and control agricultural activities remotely by the incorporation of information and communication technology (ICT). Modern information technologies have the impact to potentially increase the agricultural productivity by transferring knowledge and information to agricultural practitioners from the rural communities. Since the present generation have knowledge and easy access to smart mobile phones so the setup of control system installed in field can be monitored and controlled by new generation giving new dimensions to agriculture also known as smart agriculture. The agriculture is playing a major role in the economy of nation developing; therefore the need for upliftment in Agriculture is very important. Smart agriculture or e-Agriculture is a one of such concepts that is playing an important role in the enhancement of processes involved in Agriculture. The major role of ICT in Agriculture is its potentiality to aid a wide access to information that will support knowledge sharing and decision making. The usage of Information and Communication Technology (ICT) in Agriculture is growing day by day and more youth are attracted towards e-agriculture for their better earnings.

TRIBAL FARMING DYNAMICS: INVESTIGATING THE INFLUENCE OF SOCIO ECONOMIC AND PSYCHOLOGICAL ATTRIBUTES ON AGRICULTURAL INFORMATION MANAGEMENT PRACTICES

Agriculture is the cornerstone of many rural communities worldwide. Tribal farmers play a vital role in preserving agricultural customs and ensuring regional food security. The efficient management of agricultural information is critical in modern farming operations, as it allows farmers to enhance production, make informed decisions, and adapt to changing environmental conditions. Information and Communication Technologies (ICTs) in agriculture include networks, mobile devices, services, and applications that aid in the processing, management, and exchange of data, information, or knowledge within the farming ecosystem. ICTs assist farmers through educational procedures in improving farming methods and techniques, increasing production efficiency and income, bettering their levels of living, and lifting the social and educational standards of rural life. The study was conducted in the Keonjhar district of Odisha. An ex-post facto research design was followed for carrying out the study. The research study was followed by both purposive and non-probability random sampling methods for the selection of district, block, gram panchayat, village, and respondents. 120 respondents were selected through disproportionate random sampling. The study revealed the relationship between some socio—economic and psychological variables and Agricultural information management behavior. From this correlation, it was observed that age is negatively correlated and other variables such as gender, education, income, family size, outward orientation, training program, and social participation are positively correlated with information-seeking sources. These variables are directly proportional to the information-seeking sources.

APPLICATION OF ADVANCED TECHNOLOGIES IN AGRICULTURAL SECTOR FOR INCREASING GROSS PRODUCTION AND EXPORTING AGRICULTURAL PRODUCTS

This scientific article examines the influence of information technologies on the agro-industrial complex (AIC) during armed conflicts, specifically using the example of the war in Ukraine. Military actions have a negative impact on agricultural activities, leading to the destruction of crops, railways, transportation blockades, and infrastructure. However, information technologies can play a crucial role in ensuring food security and supporting the AIC in the context of armed conflict.The article analyzes the utilization of information technologies such as remote sensing of Earth, geographic information systems, drones, and agricultural sensors, which can provide essential information about the state of crops, water resources, and land areas. These technologies assist farmers in planning and making informed decisions regarding optimal resource utilization and ensuring food security even during times of armed conflict. Furthermore, the article examines the effectiveness of mobile applications, electronic document management, and farm management systems in ensuring efficient production and organizing agricultural processes to maintain the sustainable functioning of the AIC during armed conflict. These technologies enable farmers and agricultural enterprise managers to conduct effective monitoring and resource management, plan farm operations, and coordinate personnel actions even in the face of military threats. Additionally, the article analyzes the ethical aspects of using information technologies in the AIC during armed conflicts. This includes issues of data confidentiality protection for farmers, ethical use of data from mobile applications, and the safeguarding of worker privacy. The impact of these technologies on society and rural development during conflicts is also explored. Overall, the article provides a comprehensive view of the use of information technologies in agriculture during armed conflict and emphasizes the necessity of developing and implementing specialized solutions that address the unique challenges and needs of the AIC in such exceptional circumstances. Research in this field can contribute to ensuring the sustainable development of agriculture and enhancing the resilience of the AIC to armed conflicts and other hazards.

Factors Influencing Intention and Behaviour of Agricultural Extension Staff Concerting Post-Covid-19 Digital Technical Guidance: A Study in Yogyakarta, Indonesia

Agriculture extension staffs are encouraged to attempt more efficient methods to enhance their competency through digital webinars or technical guidance, in Bahasa Bimbingan Teknis (Bimtek) programs. The research aims to explore factors influencing the intention and behavior of agricultural extension staff towards the Technical guidance online Ministry of Agriculture in Special Region Yogyakarta, Indonesia. This research included the Behavior Intention (BI) and Use Behavior (UB) models with significant construct. The research used the quantitative method and analyzed PLS-SEM. One hundred eighty extension staffs participated, chiefly 34-42 years old. All of the indicators passed the outer model assessment. The analysis results conclude that significant effects are Attitude to BI, Control Behavior to BI, Perceived Usefulness to BI, and Behavior Intention to UB. The perception of extension staffs about Technical guidance online can enhance their performance to continue using it in obtaining agricultural technology information, extension materials, information on agricultural policies, and the latest agricultural development programs. The insignificant constructs are Subjective Norm, Motivation, and Perceived Ease to Use. The validated research model explains 61% of the variance (R2 = 0.61) in Attitude, Perceived Usefulness, and Control Behaviour towards Behavior Intention (BI). Moreover, BI explains 8.9% of the variance (R2 = 0.089) in UB of Technical guidance online. This research found that BI and UB have Q2 values of 0.538 and 0.077. The practical implication could be applied as preliminary development planning studies to enhance the efficiency of Technical guidance online as Bank Data.

Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review

The potential benefits of applying information and communication technology (ICT) in precision agriculture to enhance sustainable agricultural growth were discussed in this review article. The current technologies, such as the Internet of Things (IoT) and artificial intelligence (AI), as well as their applications, must be integrated into the agricultural sector to ensure long-term agricultural productivity. These technologies have the potential to improve global food security by reducing crop output gaps, decreasing food waste, and minimizing resource use inefficiencies. The importance of collecting and analyzing big data from multiple sources, particularly in situ and on-the-go sensors, is also highlighted as an important component of achieving predictive decision making capabilities in precision agriculture and forecasting yields using advanced yield prediction models developed through machine learning. Finally, we cover the replacement of wired-based, complicated systems in infield monitoring with wireless sensor networks (WSN), particularly in the agricultural sector, and emphasize the necessity of knowing the radio frequency (RF) contributing aspects that influence signal intensity, interference, system model, bandwidth, and transmission range when creating a successful Agricultural Internet of Thing Ag-IoT system. The relevance of communication protocols and interfaces for presenting agricultural data acquired from sensors in various formats is also emphasized in the paper, as is the function of 4G, 3G, and 5G technologies in IoT-based smart farming. Overall, these research sheds light on the significance of wireless sensor networks and big data in the future of precision crop production