Agricultural Supply Research Articles

Edge computing-oriented smart agricultural supply chain mechanism with auction and fuzzy neural networks

Powered by data-driven technologies, precision agriculture offers immense productivity and sustainability benefits. However, fragmentation across farmlands necessitates distributed transparent automation. We developed an edge computing framework complemented by auction mechanisms and fuzzy optimizers that connect various supply chain stages. Specifically, edge computing offers powerful capabilities that enable real-time monitoring and data-driven decision-making in smart agriculture. We propose an edge computing framework tailored to agricultural needs to ensure sustainability through a renewable solar energy supply. Although the edge computing framework manages real-time crop monitoring and data collection, market-based mechanisms, such as auctions and fuzzy optimization models, support decision-making for smooth agricultural supply chain operations. We formulated invisible auction mechanisms that hide actual bid values and regulate information flows, combined with machine learning techniques for robust predictive analytics. While rule-based fuzzy systems encode domain expertise in agricultural decision-making, adaptable training algorithms help optimize model parameters from the data. A two-phase hybrid learning approach is formulated. Fuzzy optimization models were formulated using domain expertise for three key supply chain decision problems. Auction markets discover optimal crop demand–supply balancing and pricing signals. Fuzzy systems incorporate domain knowledge into interpretable crop-advisory models. An integrated evaluation of 50 farms over five crop cycles demonstrated the high performance of the proposed edge computing-oriented auction-based fuzzy neural network model compared with benchmarks.

A baseline study on the distribution of fluoride in drinking water and its health risk assessment in Industrial areas of Sivakasi, India

Sivakasi, popularly known as "Little Japan," is a town in the southern region of Tamil Nadu. The study area has a semi-arid tropical monsoon climate. The inhabitants depend heavily on groundwater, which is used extensively for irrigation, drinking, and domestic. The present research aimed to evaluate groundwater quality in Sivakasi, focusing on fluoride levels and major ions, providing essential information on the non-carcinogenic risks posed to residents, particularly adults, and the suitability of water for both drinking and agriculture. Fluoride concentration and the most important cations and anions were analyzed in 32 groundwater samples. The major cations and anions present in field samples are in the order of abundance: Cl> SO4> HCO3> Na > Mg >Ca> K. For drinking purposes, groundwater quality varies from moderate to poor, and over 70% of groundwater tests are out of condition for agricultural water supply. Fluoride levels in the samples from the study area ranged from 0.00 to 2.60 mg/l, with an average value of 1.60 mg/l. The hazardous Quotient (HQ) value for infants ranged from 0.00 E+00 to 1.69 E+00, children from 0.00 E+00 to 1.80 E+00, and for adults from 0.00E+00 to 1.88E+00. Additionally, the adults were more susceptible to non-carcinogenic threats than infants and children. This study on groundwater quality in Sivakasi highlights risks to health from excessive fluoride levels, particularly for adults, making it important for disaster mitigation. Understanding the non-carcinogenic hazards of contaminated water can drive disaster preparedness actions and resource allocation, emphasizing the need for secure water sources and resilient water management methods in the semiarid region.

Fault Tree Analysis of Trade-Offs between Environmental Flows and Agricultural Water Productivity in the Lake Urmia Sub-Basin Using Agent-Based Modeling

The recent problems of Lake Urmia (LU) are caused by extensive and complex socio-ecological factors that require a comprehensive approach to consider the relationships between users and identify failure factors at the basin level. For this purpose, an agent-based simulation model of farmers’ social interactions and economic interests (ABM) with various support scenarios and random supervision and training by the government agent is developed to evaluate its impact on independent farmers’ decision-making in the form of a complex adaptive system. Finally, a fault tree analysis (FTA) is created in the Cara-FaultTree 4.1. software to identify scenarios that lead to the non-development technology in irrigation management (non-DTIM) in the LU sub-basin. The assessment of the impact of government supervision and training revealed that the main causes of non-DTIM in the LU basin are a lack of demands from farmers and low awareness among residents of the basin, with failure probabilities of 0.90 and 0.86, respectively. Ultimately, the failure probability of the main event (non-DTIM) was 0.50. The paths of proper training and farmers’ requirements for sustainable agricultural water supply should become more stringent. The results confirm that appropriate measures to strengthen government supervision and training, as well as raise farmers’ awareness of the importance of long-term sustainability of water resources, can lead to greater resilience in the DTIM.

How did the COVID-19 pandemic impact consumers’ food safety knowledge, attitudes and practices? A multi-country study on the omicron variant

PurposeThe COVID-19 pandemic is not a foodborne infectious disease, but it has dramatically impacted food safety practices worldwide due to its potential for transmission through contaminated surfaces and food. Accordingly, the Omicron variant seems to have affected food-related activities and behaviours and disturbed food supply networks since its appearance in November 2021. Hence, this paper aims to assess how the Omicron variant impacted food safety knowledge, attitudes and practices amongst adult consumers in five countries: Bosnia and Herzegovina, North Macedonia, Serbia, Montenegro and Russia.Design/methodology/approachThe study is based on an online survey. The questionnaire was developed and revised based on previous research on the impact of previous COVID-19 waves on food-related activities in several countries. The questionnaire was distributed through the SurveyMonkey platform from January 15 to February 25, 2022. It consisted of 29 multiple-choice and one-option questions organised into three sections. A total of 6,483 valid responses were received. Statistical Package for Social Sciences (SPSS) version 25.0 was used to analyse the survey results.FindingsAccording to the survey findings, food safety practices evolved during the Omicron wave in the studied countries. Firstly, less than half of the sample used a face mask whilst purchasing food. Secondly, regarding food safety knowledge, the survey results suggest that there is still a lack of knowledge in the studied countries. Thirdly, the survey indicates a lack of knowledge amongst the respondents regarding food safety attitudes. For instance, more than a third of the sample (34.4%) are unsure whether the COVID-19 virus can be transmitted through food. These results are surprising and alarming, especially considering that our sample has a higher education than the population of the studied countries.Research limitations/implicationsThe main limitation of this research is the sample bias. Survey participants were randomly chosen, enrolled voluntarily and not rewarded. As a result, the questionnaire was self-administered and completed exclusively by people motivated by an interest in the topic. Consequently, our survey does not represent the general population of the studied countries. People with a high degree of education and women, for example, were overrepresented in our sample.Originality/valueThis study is unique in that it is the first to gather information and analyse people’s perceptions of the effects of the Omicron variant on food safety. As a result, the findings of this survey offer a solid basis for future investigations into the impact of the pandemic on food safety in the Balkan region and Russia. This study can help further understand the changes during the COVID-19 pandemic. It provides crucial insights that can be used to guide future decision-making and policy development regarding improving food safety practices. This and other future studies will be a foundation for organisational and government readiness for future shocks, crises and pandemics. The effects of the present Ukrainian conflict on agricultural systems and supply chains throughout the globe (e.g. increased food prices) show that this is timely, urgent and highly required.

A game-theoretical approach for the adoption of government-supported blockchain application in the IoT-enabled agricultural supply chain

Establishing a reliable, cost-effective, and data-accessible supply chain is a requirement for all administrations. The significance of such a supply chain lies in its ability to strengthen national resiliency, ensure economic security, and foster sustainable growth. Governments know financial investments and subsidies in infrastructure, logistics, and technology are necessary for a robust supply chain. This paper proposes an IoT-enabled agricultural supply chain that integrates with a cooperative Nash game between two parties: telecommunications operators and agricultural enterprises. The aim is to establish cooperative decision-making procedures in advance of the integration of blockchain technology into the supply chain, which is regulated by the subsidy policy of the government. The Nash game yields a unique Nash equilibrium, indicating that both parties can engage in cooperative negotiations regarding their participation in the blockchain application to maximize their financial profits. To illustrate the efficacy of Nash collaboration in blockchain adoption, this study presents two scenarios where non-cooperative behavior is explored to analyze stakeholder responses in competitive contexts. Numerical results justify the theoretical findings and suggest Nash cooperation among stakeholders instead of competition in the blockchain-based agri-food market, which leads to a more accessible market environment that ultimately benefits consumers. Moreover, the positive and negative aspects of the deployment of the government-supported blockchain application are derived through sensitivity analyses conducted on subsidy rate, agricultural market price, subsidy amount, and blockchain market. Practical managerial implications are derived from the findings and observations to help policymakers formulate blockchain policies in agricultural supply chains supported by governments.

Decisions of dual-channel fresh agricultural product supply chains based on information sharing

PurposeThis paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.Design/methodology/approachThe two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.FindingsThe results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.Practical implicationsThe conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.Originality/valueThis paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.

Soybean Seed Coat Cracks and Green Seeds—Predisposing Conditions, Identification and Management

Seed coat cracking and green seeds threaten soybean crop production. Seed coat cracking results from a complex interplay of genetic factors, environmental stresses, and crop management practices. Green seeds, linked to water deficit, nutritional deficiencies, and environmental stresses, exhibit reduced quality and viability. The intricate relationships between seed coat integrity and seed permeability, influenced by the lignin content, porosity, and color, play a pivotal role in seed germination, storage potential, and resistance to field stresses. These issues reverberate through the soybean agricultural supply chain. Strategic interventions are crucial to address these abnormalities and ensure soybean productivity. Seed germination and vigor are reduced due to seed coat cracking and green seeds, undermining food security and necessitating additional resources for disease management. The occurrence and identification of green seeds and seeds with cracks in the seed coat were also reported by identifying the genes and QTLs (quantitative trait loci) associated with these characteristics. Herbicides, commonly used in weed management, may offer a strategic approach to mitigating seed coat cracking and green seed occurrence. Understanding the complex interactions between the genetics, environmental factors, and management practices influencing seed abnormalities is essential as global climate change intensifies. This review emphasizes the need for integrated strategies, balanced plant nutrition, and cohesive phytosanitary management to mainly alleviate seed coat cracking and greenish occurrences in soybeans and other plant species.

Comparing climate pledges and eco-taxation in a networked agricultural supply chain organisation

Abstract This paper examines the effectiveness of climate pledges and eco-taxation as strategies for mitigating climate change within a networked agricultural supply chain organisation. We utilise variational inequality techniques within a multicriteria decision-making framework and validate our theoretical findings through numerical simulations using a machine learning augmented algorithm. By employing this approach, we position the Agricultural Sector Roadmap, aimed at capping global warming at 1.5°C, within the wider agricultural sector’s climate action framework. Our results demonstrate that environmental taxation emerges as the most effective approach for addressing climate change. Eco-taxation leads to a 57.87 per cent reduction in global emissions, whereas climate pledges only account for a 20.59 per cent reduction at the same level of production. Furthermore, eco-taxation results in a 45.68 per cent greater reduction in emission intensity compared to climate pledges. In contrast to climate commitments, an eco-fiscal policy is capable of achieving the objectives established by the European Union.

Endogenous measures for stifling corruption within selected agricultural and food development projects in Benue State, North Central, Nigeria

Due to the increasing cases of failed agricultural intervention projects in Benue State, as a result of corruption and sharp practices, this study was carried out to investigate the effect of endogenous measures used for stifling corruption within selected agricultural intervention projects in Benue State, North Central, Nigeria. key players' attitudes toward stifling corruption were also studied. Agriculture is the mainstay of the Benue State populace, but regrettably, this sector has deteriorated, and it is barely an agent of development and empowerment because of the effect of corruption on it. A preliminary survey was carried out to identify and ascertain the existence of endogenous measures employed in stifling corruption in the three local government zones (A, B, and C) of Benue State. Consequently, zone ‘C’ was randomly selected. A total of 129 respondents from all of the selected agricultural intervention projects in the zone were used. Focus Group Discussions (FGD), In-depth interviews (IDIs) with key players, and structured questionnaires were used to collect data. The dimension of sharp practices in the selected agricultural development projects was more pronounced in allocating agricultural supplies to the farmers and less pronounced in bribery, influence peddling, pricing, and duty abandonment. FGD and IDIs with key players revealed that Ekaa or Okpa (oath taking), Aolode (local vigilante), Echi (protective charms), public denouncement, tying of palm frond leaves, Enumajeje (Mucuna pruriens), withdrawal of project from the community, and Onyonkpo (village cult) were the endogenous measures deployed to stifle corruption in the selected agricultural development projects. These various endogenous measures deployed by some key players of the selected agricultural development projects to curb sharp practices significantly prevented intended culprits from indulging in deviant behavior for fear of its instant judgment on culprits. It is recommended based on the findings that endogenous measures should be encouraged to complement the government's efforts and the crude aspects of the measures conflicting with natural justice should be ejected.

Evaluating barriers to blockchain technology for sustainable agricultural supply chain: A fuzzy hierarchical group DEMATEL approach

Evaluating barriers to blockchain technology for sustainable agricultural supply chain: A fuzzy hierarchical group DEMATEL approach

Decentralized Targeting of Agricultural Credit Programs: Private versus Political Intermediaries

Abstract We conduct a field experiment in India comparing two ways of delegating selection of microcredit clients among smallholder farmers to local intermediaries: a private trader (TRAIL), versus a local-government appointee (GRAIL). Selected beneficiaries in both schemes were equally likely to take up and repay loans, and experienced similar increases in borrowing and farm output. However farm profits increased and unit costs of production decreased significantly only in TRAIL. While there is some evidence of superior selection by ability and landholding in TRAIL, the results are mainly driven by greater reduction of unit production costs for TRAIL treated farmers than GRAIL treated farmers of similar ability or landholding. We develop and test a model where the TRAIL agents’ role as middlemen in the agricultural supply chain enabled and motivated them to offer treated farmers business advice, which helped them lower unit costs.

Sustainable Groundwater Management Through Micro Irrigation: A Critical Review on Challenges and Solutions

Abstract Groundwater plays a vital role in global water resources, supporting agricultural, industrial, and domestic water supply systems. However, the long-term sustainability of groundwater is increasingly threatened due to the widespread adoption of irrigation systems especially micro irrigation. Micro irrigation is a widespread agricultural technique that involves water application to crops through drip irrigation and sprinkler systems. This method has gained widespread adoption due to its ability to deliver water efficiently to crops. This review paper examines the impacts of micro irrigation on groundwater sustainability, focusing on its effects on groundwater quantity, quality, and overall sustainability. The findings reveal that micro irrigation can significantly contribute to groundwater conservation by reducing water losses. However, improper management practices, such as over-irrigation or incorrect application rates, can lead to excessive groundwater extraction, depletion of aquifers, and declining water tables. Applying fertilizers and pesticides in micro irrigation systems may lead to groundwater pollution, thereby affecting water quality and posing a risk to human health. This review article emphasizes the significance of appropriate design, installation, and upkeep of micro irrigation systems to minimize potential adverse effects on groundwater. Furthermore, regulatory frameworks, policies, and educational programs are crucial in promoting sustainable groundwater management practices in micro irrigation. The present review highlights the significance of adopting balanced water use practices, enhancing water management techniques, and implementing relevant regulations to ensure the sustainable utilization of groundwater resources in micro irrigation systems.

Improving Farmers’ Income on Online Agri-Platforms: Evidence from the Field

Problem definition: To improve the welfare of smallholder farmers, multiple countries (e.g., Ethiopia and India) have launched online agri-platforms to transform traditional markets. However, there is still mixed evidence regarding the impact of these platforms and, more generally, how they can be leveraged to enable more efficient agricultural supply chains and markets. This paper describes work conducted in close collaboration with the state government of Karnataka, India, to design, implement, and assess the impact of a new two-stage auction on the state’s online agri-platform, the United Market Platform (UMP). Methodology/results: To ensure implementability and protect farmers’ revenue, the auction design is guided by practical operational considerations, as well as semistructured interviews with a majority of the traders in the field. A new behavioral auction model informed by the field insights is developed to determine when the proposed two-stage auction can generate a higher revenue for farmers than the traditional single-stage, first-price, sealed-bid auction. The new auction mechanism was implemented on the UMP for a major market of lentils in February 2019. By the end of May 2019, commodities worth more than $6 million (USD) had been traded under the new auction. A difference-in-differences analysis demonstrates that the implementation has yielded a significant 3.6% price increase (corresponding to a 55%–94% profit gain) for over 10,000 farmers who traded in the treatment market. Managerial implications: The results from this paper offer tangible lessons on how innovative price discovery mechanisms could be enabled by online agri-platforms in resource-constrained environments. Importantly, the success of these designs critically depends on careful considerations of systemic operational and behavioral factors that affect trades in the physical markets. History: This paper has been accepted as part of the 2023 Manufacturing & Service Operations Management Practice-Based Research Competition. Funding: Financial support from the Tata Center for Technology and Design at MIT and the National Science Foundation [Grant 1452875] is gratefully acknowledged. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0437 .

Research on Blockchain-driven Agricultural Products E-commerce Supply Chain Innovation under Game Perspective

With the arrival of the big data era, digital technology has achieved an unprecedented development speed, and blockchain, as a representative of digital technology, solves the problem of mutual trust between multiple transaction subjects in different scenarios with the technological advantages of decentralisation, timestamping and non-tampering. Currently, in the agricultural products e-commerce supply chain scenario, there is the problem of credit risk of agricultural products producers and sellers. Aiming at the pain points of agricultural products e-commerce supply chain, this paper analyses from the perspective of game, through blockchain incentive mechanism, and puts forward blockchain-driven agricultural products e-commerce supply chain innovation suggestions.

Recovering farming supply chains from animal epidemics via government subsidies

In recent years, animal epidemics – such as African swine fever and bird flu – break out more frequently in both developed and developing economies, causing serious economic losses and animal product shortages. To restore animal product supply, many governments offer two agricultural subsidies to farms: (i) the culling compensating subsidy (CCS), which guarantees a floor price for culled animals, and (ii) the scaled construction subsidy (SCS), which supports large-scale farms to enhance their production capacities. We develop a three-stage Stackelberg game framework to capture the strategic interactions among the government, large- and small-scale farms. In particular, the two types of farms differ in their epidemic prevention and control capabilities and must operate under yield uncertainty. We study two cases regarding whether the government requires a minimum BS for the SCS. In each case, we analyze the equilibrium decisions of the profit-seeking farms and characterize the structure of the government’s optimal subsidy programs with an earmarked budget to maximize social welfare. Moreover, we identify the conditions under which the government should adopt the “SCS only strategy”, “CCS only strategy”, or offer the two subsidies simultaneously. Furthermore, we examine the effectiveness of the subsidy programs in terms of consumer surplus, farms payoffs, and social welfare. We show that in both cases, these programs can make the three stakeholders achieve a win–win–win situation by prioritizing a reasonable CCS according to the subsidy budget. We leverage our analyses to offer insights that can help generate policy recommendations for stakeholders in countries suffering from animal epidemics.

Barriers to Industry 4.0 technology adoption in agricultural supply chains: a Fuzzy Delphi-ISM approach

PurposeThe purpose of this study is to identify and analyze the barriers associated with the adoption of Industry 4.0 technologies in agricultural supply chains.Design/methodology/approachThe study initially identified thirteen barriers by conducting a literature review and semi-structured interviews with key stakeholders. Subsequently, these barriers were validated and modeled using an integrated Fuzzy Delphi-ISM approach. Finally, MICMAC analysis was employed to categorize the barriers into distinct clusters.FindingsThe results provide considerable insights into the hierarchical structure and complex interrelationships between the barriers as well the driving and dependence power of barriers. Lack of information about technologies and lack of compatibility with traditional methods emerged as the two main barriers which directly and indirectly influence the other ones.Research limitations/implicationsThe robust hybrid Fuzzy Delphi and ISM techniques used in this study can serve as a useful model and benchmark for similar studies probing the barriers to Industry 4.0 adoption. From a theoretical standpoint, this study expands the scope of institutional theory in explaining Industry 4.0 adoption barriers.Practical implicationsThe study is timely for the post-COVID-19 recovery and growth of the agricultural sector. The findings are helpful for policymakers and agriculture supply chain stakeholders in devising new strategies and policy interventions to prioritize and address Industry 4.0 adoption barriers.Originality/valueIt is the first comprehensive, multi-country and multi-method empirical study to comprehensively identify and model barriers to Industry 4.0 adoption in agricultural supply chains in emerging economies.

Unveiling polymorphism and protein structure prediction insights in diacylglycerol O-acyltransferase 1 and telethonin genes of Egyptian buffalo

BackgroundThe Egyptian buffalo has a sizable impact on Egypt's agricultural sector and food supply. It is regarded as the main dairy animal and an important source of red meat. This study aimed to detect the polymorphisms of the DGAT1 and TCAP genes and assess the potential impact of the discovered nsSNPs on the stability of the tertiary structure polypeptides of selected genes in Egyptian buffalo.MethodsAllele identification was made by the restriction fragment length polymorphism (RFLP), and the single nucleotide polymorphisms (SNPs) were recognized by sequencing the purified PCR products. Protein translation indicated the synonymous and non-synonymous SNPs, and the peptides' 3D tertiary structure of selected genes, as well as the effect of amino acid substitution on the protein structure, was performed using bioinformatics tools.ResultsAnalysis of the data revealed that an nsSNP was detected in a tested region of the DGAT1 gene and caused an amino acid substitution in a polypeptide that was predicted to be neutral and located in the coiled part of the protein. The analysis of the TCAP gene showed four nsSNPs that caused four substitutions located in the α-helix region. Protein prediction analysis showed that the amino acid substitutions in DGAT1 and TCAP were non-conserved with low sensitivity to variation. The non-conservative amino acid substitutions result in amino acids with new properties different from the original amino acid that change the protein's structure and function.ConclusionWe can infer that the DGAT1 and TCAP genes' SNPs may affect meat-related traits and may improve meat quality.

Discuss on the Construction of Digital Rural Revitalization Information Service Platform in the New Era

If we want to assume digital rural areas, the focus must be on industrial prosperity, adhere to quality first, green agriculture, and take the structural reform of the agricultural supply side as a guide to further promote the construction speed of modern agricultural industrial system, management system, and production system, thereby improving agricultural productivity, competitiveness, and innovation, and promoting the realization of an agricultural power. In the new era, the system engineering of digital rural projects is relatively complex. It is necessary to adopt advanced system engineering ideas and methods, arrange top-level design, institutional setting, innovative technology, talent cultivation, and optimize operation modes, in order to achieve an information service platform and achieve digital rural revitalization.

ENERGY INTENSITY OF THE POLISH AGRI-FOOD SECTOR IN THE LIGHT OF INPUT-OUTPUT TABLES

The purpose of this paper is to assess the energy intensity of production in the Polish agri-food (agribusiness) sector, split into agriculture, food industry and supply subsectors, in the light of input-output tables. The study relies on input-output tables and physical energy flow accounts. Energy plays a key role in today’s society as it affects economic growth and the standards of living, while also being at the core of international conflicts, mainly caused by its limited resources. Compared to other sectors, agribusiness demonstrates particularly high levels of energy consumption. Agriculture, which is part of it, has a large share in the consumption of fuels derived from crude oil. This paper presents the consumption of energy in each of the four aggregates of agribusiness, as well as their GDP (in PPS) and energy consumption mix (split into 6groups of energy carriers). The authors found that between2014 and2019, energy consumption in the agribusiness industry increased by ca.9% and was accompanied by ca.8% growth in GDP. The sector’s energy intensity was half more than the average level for the economy as a whole, and remained at ca.5.6TJ per EUR1million of GDP in PPS. Only the food industry was at a level of energy efficiency similar to that of the economy as a whole, whereas the agricultural supply subsector was the only one to demonstrate lower levels. Both the economy as a whole and the agribusiness sector clearly tend to reduce the share of coal and related products in the energy mix.

Information Communication and Computation Technologies (ICCT) for Agricultural and Environmental Information Systems for Society 5.0

Purpose: This paper aims to discover the dynamic landscape of Information Communication and Computation Technologies (ICCT) within agriculture and environmental information management, elucidating their evolutionary trajectory and the resonance of Society 5.0 principles in fostering innovative solutions. By scrutinizing the core technologies constituting ICCT in these sectors, it endeavours to shed light on the potential for integration within the framework of Society 5.0, contemplating both the possibilities and challenges inherent in this convergence. Methodology: This exploratory chapter delves into the evolving landscape of Society 5.0 and its pivotal emphasis on the integration of Information Communication and Computation Technologies (ICCT) to address the complex challenges in agriculture and environmental information management. Analysis/Results: The paper provides a background on the evolution of Society 5.0 and establishes the rationale for exploring the role of ICCT in advancing Agricultural and Environmental Information Systems within this transformative societal framework. The core technologies in ICCT are explored through IoT applications in precision agriculture, the transformative impact of blockchain in agricultural supply chains, and the utilization of remote sensing and Earth observation systems along with data analytics for environmental insights. The paper further investigates the integration of ICCT in Society 5.0 agricultural and environmental systems, unveiling how these technologies support smart farming practices, citizen engagement in agricultural decision-making, and sustainable resource management. Case studies highlight successful ICCT implementations in agriculture and environmental management, underscoring best practices and lessons learned. Emerging trends in ICCT for agriculture and environmental science are explored, providing insights into future developments. Originality/Value: Through the lens of case studies showcasing successful ICCT implementations, it seeks to distill key insights, while also conducting a forward-looking assessment of emerging trends and applications, thus contributing to a deeper understanding of the evolving role of ICCT in shaping sustainable agricultural and environmental information paradigms within the societal context of the future. Type of Paper: Exploratory analysis.