Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture

A Systematic Review of Sustainable Fresh Fruit and Vegetable Supply Chains

Fresh fruit and vegetables are crucial for human health. Their fibrous structure and high nutritional value are essential for people’s well-being. This study aims to provide a review of the current state of knowledge and practices regarding fresh fruit and vegetable supply chains (FFVSC). The reviewed papers are divided into categories according to their findings, research purposes, tools and messages used. Our objective is to guide both academics and practitioners by pointing out significant streams of research with respect to these categories. For a better understanding, these subgroups are essentially based on their common research purpose, and the tools and methods they adopted are explained. Therefore, this study sheds light on research related to FFVSCs for those who are new to this area or planning to conduct in-depth research on directions suggested by studies in this area. The related literature was classified into eight categories: namely, (1) value chain indicators of FFVSCs, (2) food-related problems/postharvest losses along FFVSCs, (3) roles of parties involved in the FFV value chain, (4) review papers, (5) technological trends in FFVSCs, (6) packaging issues of FFVSCs, (7) logistics solutions of FFVSCs, and (8) sustainable FFVSCs. Details on the tools and methods employed in these studies are summarized in Appendix B. To the best of the authors’ knowledge, the related literature lacks a comprehensive review that investigates different aspects of FFVVCs in detail. Thus, this study contributes towards a better understanding of the related literature and can be used as a guide for future studies.

Logistics and Agri-Food: Digitization to Increase Competitive Advantage and Sustainability. Literature Review and the Case of Italy

This paper examines the current challenges faced by logistics with a focus on the agri-food sector. After outlining the context, a review of the literature on the relationship between logistics and strategic management in gaining and increasing competitiveness in the agri-food sector is conducted. In particular, the flow of the paper is as follows: after examining the aforementioned managerial problem and its broader repercussions, the paper proceeds to address two main research questions. First, how and by which tools can digitization contribute to improving supply chain management and sustainability in logistics? Second, what are the main managerial and strategic implications and consequences of this for the agri-food sector in terms of efficiency, effectiveness, cost reduction, and supply chain optimization? Finally, the paper presents Italy as a case study, chosen both for its peculiar internal differences in logistical infrastructures and entrepreneurial management between Northern and Southern regions (which could be at least partially overcome with the use of new technologies and frameworks) and for the importance of the agri-food sector for the domestic economy (accounting about 25% of the country’s GDP), on which digitization should have positive effects in terms of value creation and sustainability.

Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm

Digitalization has impacted agricultural and food production systems, and makes application of technologies and advanced data processing techniques in agricultural field possible. Digital farming aims to use available information from agricultural assets to solve several existing challenges for addressing food security, climate protection, and resource management. However, the agricultural sector is complex, dynamic, and requires sophisticated management systems. The digital approaches are expected to provide more optimization and further decision-making supports. Digital twin in agriculture is a virtual representation of a farm with great potential for enhancing productivity and efficiency while declining energy usage and losses. This review describes the state-of-the-art of digital twin concepts along with different digital technologies and techniques in agricultural contexts. It presents a general framework of digital twins in soil, irrigation, robotics, farm machineries, and food post-harvest processing in agricultural field. Data recording, modeling including artificial intelligence, big data, simulation, analysis, prediction, and communication aspects (e.g., Internet of Things, wireless technologies) of digital twin in agriculture are discussed. Digital twin systems can support farmers as a next generation of digitalization paradigm by continuous and real-time monitoring of physical world (farm) and updating the state of virtual world.

Inhibitors of Industry 4.0 and Circular Economy in Manufacturing Industry Supply Chains

Circular economy (CE) and Industry 4.0 (I4.0) are clearly gaining popularity around the world because to their ability to integrate breakthrough technology with unique circular production and business models. This study conducted a systematic literature review, followed by expert intervention, to identify the 16 inhibitors hindering the implementation of a combination of CE practices and I4.0 technologies in the manufacturing industry supply chain. This paper has used ISM, Fuzzy MICMAC, and Fuzzy AHP approach to analyse the interrelationship among inhibitors and highlight the most critical of them. The findings of the paper suggest ‘missing competitive leadership and ‘lack of capital' are the most critical inhibitors, hindering the implementation of I4.0 and CE approach, depriving the manufacturing sector from enormous incentives. This one-of-a-kind original research paper is a holistic attempt to highlight the key elements of manufacturing and production supply chain. The results of the study will help the SCM companies to devise the strategies for achieving excellence.

Exploring Attractive Quality Requirements for Short Food Supply Chain Digital Platforms

Perceptions towards unsustainable supply chain practices in global, mainstream food systems are motivating a shift towards short food supply chains. Short food supply chains are developed to remove the physical and social distances between producer and consumer. Advances in digital technologies offer promise for short food supply chains, including platforms that can enable real-time data flow, create visibility, and support sustainable practices. This research aims to prioritise attractive quality requirements of short food supply chain digital platforms. The methodology consists of a literature review and Kano analysis for requirements prioritisation. The results show that the requirements span across the four Kano categories, attractive quality encompassing the largest number of requirements. The attractive quality requirements identified offer increased levels of satisfaction when present and have limited negative impact when missing. Therefore, they are considered exciting for potential users of a system. The limitations of the research and areas of future work are presented.

A Food-Circular Economy-Women Nexus: Lessons from Guelph-Wellington

Resource nexus approaches have been expanding to include additional sectors beyond standard water, energy, and food approaches. Opportunities exist by re-imagining the resource nexus approach with the framework of the United Nations Sustainable Development Goals (SDGs). Emerging research and policy themes, such as the circular economy and gender, can provide additional context to traditional nexus arrangements. To illustrate this, we analyze SDG implementation and interaction from 40 unstructured interviews from SMEs participating in Guelph-Wellington’s Seeding Our Food Future (SOFF) program, part of the wider Our Food Future (OFF) initiative led by the City of Guelph and Wellington County in Ontario, Canada. Results show that 16/17 SDGs and associated targets were present on the program. Environmental SDGs were implemented the most, followed by social and economic ones. SDGs 2, 12, and 5 had the most general implementation and direct paired interactions and were associated with the broadest number of SDGs across the project. These findings support the existence of a Food-Circular Economy-Women nexus in Guelph-Wellington’s agri-food sector. Further analysis shows that this nexus is most active in agriculture, and that women are responsible for introducing a social aspect, which addresses food security. Results can inform food system and circular economy researchers and practitioners.

Digitalization in Food Supply Chains: A Bibliometric Review and Key-Route Main Path Analysis

Technological advances such as blockchain, artificial intelligence, big data, social media, and geographic information systems represent a building block of the digital transformation that supports the resilience of the food supply chain (FSC) and increases its efficiency. This paper reviews the literature surrounding digitalization in FSCs. A bibliometric and key-route main path analysis was carried out to objectively and analytically uncover the knowledge development in digitalization within the context of sustainable FSCs. The research began with the selection of 2140 articles published over nearly five decades. Then, the articles were examined according to several bibliometric metrics such as year of publication, countries, institutions, sources, authors, and keywords frequency. A keyword co-occurrence network was generated to cluster the relevant literature. Findings of the review and bibliometric analysis indicate that research at the intersection of technology and the FSC has gained substantial interest from scholars. On the basis of keyword co-occurrence network, the literature is focused on the role of information communication technology for agriculture and food security, food waste and circular economy, and the merge of the Internet of Things and blockchain in the FSC. The analysis of the key-route main path uncovers three critical periods marking the development of technology-enabled FSCs. The study offers scholars a better understanding of digitalization within the agri-food industry and the current knowledge gaps for future research. Practitioners may find the review useful to remain ahead of the latest discussions of technology-enabled FSCs. To the authors’ best knowledge, the current study is one of the few endeavors to explore technology-enabled FSCs using a comprehensive sample of journal articles published during the past five decades.

A Bibliometric Network Analysis of Recent Publications on Digital Agriculture to Depict Strategic Themes and Evolution Structure

The agriculture sector is one of the backbones of many countries’ economies. Its processes have been changing to enable technology adoption to increase productivity, quality, and sustainable development. In this research, we present a scientific mapping of the adoption of precision techniques and breakthrough technologies in agriculture, so-called Digital Agriculture. To do this, we used 4694 documents from the Web of Science database to perform a Bibliometric Performance and Network Analysis of the literature using SciMAT software with the support of the PICOC protocol. Our findings presented 22 strategic themes related to Digital Agriculture, such as Internet of Things (IoT), Unmanned Aerial Vehicles (UAV) and Climate-smart Agriculture (CSA), among others. The thematic network structure of the nine most important clusters (motor themes) was presented and an in-depth discussion was performed. The thematic evolution map provides a broad perspective of how the field has evolved over time from 1994 to 2020. In addition, our results discuss the main challenges and opportunities for research and practice in the field of study. Our findings provide a comprehensive overview of the main themes related to Digital Agriculture. These results show the main subjects analyzed on this topic and provide a basis for insights for future research.

The Protective Effect of Digital Financial Inclusion on Agricultural Supply Chain during the COVID-19 Pandemic: Evidence from China

Financial inclusion plays a positive role in protecting agriculture during or after disaster. This paper focuses on the protective effect of digital financial inclusion on the agricultural supply chain and analyzes three mechanisms of the protective effect: financial widening, financial deepening, and financial services digitization. Based on the Gravity Equation, we conduct an empirical study using agricultural logistics and digital financial inclusion data from China. The regression results indicate that a 1% increase in the digital financial inclusion, measured by the Peking University Digital Inclusion Index, increases agricultural trade during the COVID-19 pandemic by approximately 1.6%. Furthermore, heterogeneous protective effects exist between regions in China. Digital financial inclusion is more effective in the Eastern regions in protecting the ASC than in other regions. This paper enriches the understanding of financial inclusion in helping agriculture supply chain recovery.

Applications of IoT for achieving sustainability in agricultural sector: A comprehensive review

This research aims to achieve a holistic understanding of the current IoT scenario by conducting a comparative analysis of the prevailing literature regarding IoT applications in the agricultural domain. Also, it proposes a framework for IoT adoption in the case sector. A systematic literature review was conducted with a methodology that focused on scientific articles authored in the English language that were published in peer-reviewed journals in the last five years. Initially, 179 research papers were extracted from the SCOPUS database and finally, 82 relevant articles were considered for the study which were classified into various categories and studied thoroughly. Based on a comprehensive survey of the selected articles four research questions were identified and successfully addressed. The results highlighted that research efforts pertaining to IoT applications of agriculture have matured from their initial conceptual stage and now reached the implementation phase. Also, it was observed that Machine Learning based algorithms were utilized extensively in recent research studies. For the first time, an exhaustive study has been conducted holistically to comprehend the recent advances in the field of IoT applications for the agricultural sector.

Implementing Industry 4.0 through Cleaner Production and Social Stakeholders: Holistic and Sustainable Model

Although Industry 4.0 has received much attention in recent years due to the possibility of increasing companies’ productivity, the implementation process is complex. The aim of this study is to present a holistic model for implementing Industry 4.0 based on cleaner production as a fundamental tool for the development of production systems that meet the Sustainable Development 04026-002Goals (SDGs), and social stakeholders that cooperate with this implementation process, helping to develop sustainable infrastructure, processes and technologies to increase the sustainable transformation of these companies towards Industry 4.0. The method used was literature research, and the Delphi technique was used to ask specialists to contribute with their experience to evaluate and propose improvements to the model, in the form of a consensus. The model contributes to the Sustainable Development Goals 9, 12 and 15. This holistic and sustainable model is a contribution to theory and practice, helping executives, technicians, entrepreneurs and those involved with Industry 4.0 to base the implementation process in the needs and specificities of each company, avoiding the “one fits all” models, considering the peculiarities of each company and the complexity of the implementation process in a more efficient and collaborative digital production ecosystems base, seeking to reduce inequalities, through the joint effort of social stakeholders to find ways to restore and/or improve social harmony, impacted by Industry 4.0.

Identification of Promising Smart Farm Technologies and Development of Technology Roadmap Using Patent Map Analysis

In this study, we suggest methodologies for identifying promising and vacant technologies on smart farms by analyzing patent information. Additionally, a technology roadmap for smart farms is suggested using network analysis. The database of patents related to smart farms was extracted from the United States Patent and Trademark Office (USPTO) by keyword search, and valid patents data was selected and clustered using the Latent Dirichlet Allocation (LDA) algorithm. We also conducted the technical importance analysis and trend analysis to identify promising technology topics. By developing a patent map based on a self-organizing map (SOM), we were able to identify vacant technologies among smart farm technology groups. In order to develop vacant technologies, we presented a stepwise technology roadmap by analyzing the relationship between technology elements using network analysis. The proposed procedure and analysis method provides useful insights in establishing research and development (R&D) strategies for the development of smart farm technology roadmaps.

Blockchain Software Selection as a Fuzzy Multi-Criteria Problem

Increased consumer requirements for quality, safety and traceability of goods in supply chains has accelerated the implementation of blockchain during the COVID-19 pandemic. The right choice of blockchain software is a complicated task and an important prerequisite for successful deployment. In this study, we propose a conceptual framework for group multi-criteria selection of blockchain software in fuzzy environment according to organization needs and experts’ judgements. The applicability of the new framework has been verified through an illustrative example for ranking blockchain systems. The evaluations of compared alternatives were calculated by using measurement of alternatives and ranking according to the compromise solution (MARCOS) method. The robustness of the new framework was proven by sensitivity analysis in which two (crisp and fuzzy) MARCOS models with two different sets of weighting coefficients were compared.

Application Research: Big Data in Food Industry

A huge amount of data is being produced in the food industry, but the application of big data—regulatory, food enterprise, and food-related media data—is still in its infancy. Each data source has the potential to develop the food industry, and big data has broad application prospects in areas like social co-governance, exploit of consumption markets, quantitative production, new dishes, take-out services, precise nutrition and health management. However, there are urgent problems in technology, health and sustainable development that need to be solved to enable the application of big data to the food industry.

Blockchain-Based Model to Improve the Performance of the Next-Generation Digital Supply Chain

In the era of the fourth industrial revolution, all aspects of the industrial domain are being affected by emerging technologies. Digitalization of every process is taking place or under process. One of the most important components common to every domain is the supply chain process. Organizations employ a digital supply chain to track the delivery of their products or materials. The digital supply chain is still suffering from a few issues such as no provenance, less transparency, and a trust issue. Blockchain technology, one of the emerging technologies, can be integrated with the supply chain to deal with the existing issues and to improve its performance. In this paper, a model is proposed to integrate blockchain technology with the supply chain to improve performance. The proposed model uses the combination of the Ethereum blockchain and the interplanetary file system to maintain the traceability, transparency, and trustworthiness of the supply chain.

Exploring the role of artificial intelligence in managing agricultural supply chain risk to counter the impacts of the COVID-19 pandemic

Purpose

In India, artificial intelligence (AI) application in supply chain management (SCM) is still in a stage of infancy. Therefore, this article aims to study the factors affecting artificial intelligence adoption and validate AI’s influence on supply chain risk mitigation (SCRM).

Design/methodology/approach

This study explores the effect of factors based on the technology, organization and environment (TOE) framework and three other factors, including supply chain integration (SCI), information sharing (IS) and process factors (PF) on AI adoption. Data for the survey were collected from 297 respondents from Indian agro-industries, and structural equation modeling (SEM) was used for testing the proposed hypotheses.

Findings

This study’s findings show that process factors, information sharing, and supply chain integration (SCI) play an essential role in influencing AI adoption, and AI positively influences SCRM. The technological, organizational and environmental factors have a nonsignificant negative relation with artificial intelligence.

Originality/value

This study provides an insight to researchers, academicians, policymakers, innovative project handlers, technology service providers, and managers to better understand the role of AI adoption and the importance of AI in mitigating supply chain risks caused by disruptions like the COVID-19 pandemic.

Are artificial intelligence and machine learning suitable to tackle the COVID-19 impacts? An agriculture supply chain perspective

Purpose

This article aims to model the challenges of implementing artificial intelligence and machine earning (AI-ML) for moderating the impacts of COVID-19, considering the agricultural supply chain (ASC) in the Indian context.

Design/methodology/approach

20 critical challenges were modeled based on a comprehensive literature review and consultation with experts. The hybrid approach of “Delphi interpretive structural modeling (ISM)-Fuzzy Matrice d' Impacts Croises Multiplication Applique'e à un Classement (MICMAC) − analytical network process (ANP)” was used.

Findings

The study's outcome indicates that “lack of central and state regulations and rules” and “lack of data security and privacy” are the crucial challenges of AI-ML implementation in the ASC. Furthermore, AI-ML in the ASC is a powerful enabler of accurate prediction to minimize uncertainties.

Research limitations/implications

This study will help stakeholders, policymakers, government and service providers understand and formulate appropriate strategies to enhance AI-ML implementation in ASCs. Also, it provides valuable insights into the COVID-19 impacts from an ASC perspective. Besides, as the study was conducted in India, decision-makers and practitioners from other geographies and economies must extrapolate the results with due care.

Originality/value

This study is one of the first that investigates the potential of AI-ML in the ASC during COVID-19 by employing a hybrid approach using Delphi-ISM-Fuzzy-MICMAC-ANP.

State of the Art of Urban Smart Vertical Farming Automation System: Advanced Topologies, Issues and Recommendations

The global economy is now under threat due to the ongoing domestic and international lockdown for COVID-19. Many have already lost their jobs, and businesses have been unstable in the Corona era. Apart from educational institutions, banks, privately owned institutions, and agriculture, there are signs of economic recession in almost all sectors. The roles of modern technology, the Internet of things, and artificial intelligence are undeniable in helping the world achieve economic prosperity in the post-COVID-19 economic downturn. Food production must increase by 60% by 2050 to meet global food security demands in the face of uncertainty such as the COVID-19 pandemic and a growing population. Given COVID 19’s intensity and isolation, improving food production and distribution systems is critical to combating hunger and addressing the double burden of malnutrition. As the world’s population is growing day by day, according to an estimation world’s population reaches 9.6 billion by 2050, so there is a growing need to modify the agriculture methods, technologies so that maximum crops can be attained and human effort can be reduced. The urban smart vertical farming (USVF) is a solution to secure food production, which can be introduced at any adaptive reuse, retrofit, or new buildings in vertical manners. This paper aims to provide a comprehensive review of the concept of USVF using various techniques to enhance productivity as well as its types, topologies, technologies, control systems, social acceptance, and benefits. This review has focused on numerous issues, challenges, and recommendations in the development of the system, vertical farming management, and modern technologies approach.

Agri-Food Contexts in Mediterranean Regions: Contributions to Better Resources Management

The agri-food frameworks have specific characteristics (production units with small dimensions and in great number with implications in the respective markets) that call for adjusted approaches, even more so when they are considered in Mediterranean contexts (where global warming will have relevant impacts). In fact, the Mediterranean regions and countries have particular specificities (due to their climate conditions) that distinguish them from their neighbours. This is particularly true in Europe, for example, where the southern countries present socioeconomic dynamics (associated with the respective public debt) that are different from those identified in the northern regions. From this perspective, it seems pertinent to analyse the several dimensions of the agri-food systems in the Mediterranean area. To achieve these objectives, a search was carried out on 26 December 2020 on the scientific databases Web of Science Core Collection (WoS) and Scopus for the topics “agr*-food” and “Mediterranean”. These keywords were selected after a previous literature survey and to capture the agri-food contexts in Mediterranean regions. The keyword “agr*-food” was considered in this way to allow for a wider search (including “agri-food”, “agro-food”, etc.). Considering only articles (excluding proceeding papers, book chapters, and books, because in some cases it is difficult to access the entire content of the document), 100 and 117 documents were obtained from the WoS and Scopus, respectively. After removing the duplicated studies and taking into account the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach, 137 documents were surveyed through a literature review. As main insights, several dimensions embedded in the concept of agri-food were highlighted, from those related to heritage subjects to natural assets. On the other hand, the following subtopics were identified: agri-food dynamics and sustainability, agriculture and agri-food systems, agri-chains and food consumption, and food production and composition impact on agri-chains. Stressing the gaps in the scientific literature, related to the topics here addressed, there are possibilities to better explore the several dimensions and solutions offered by the new developments associated with smart agriculture and agriculture 4.0, specifically for the Mediterranean contexts and their challenges. Finally, to complement the PRISMA methodologies, an MB2MBA2 (Methodology Based on Benchmarking of Metadata, from scientific databases, and Bibliometric Assessment and Analysis) approach is suggested to carry out systematic literature reviews, based on bibliometric analysis.

Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management

The digital transformation of supply chains should revolutionize entire management processes and improve various aspects of sustainability. In particular, the plans of Industry 4.0 aim towards a digitization of several procedures by exploiting emerging technologies such as the Internet of Things, RFID and blockchain. The purpose of this study is to highlight how order and disruption events processes can be improved with the adoption of emerging technologies and how this reflects on the improvement of sustainability aspects. The study is based on the comparison of two simulation scenarios between three actors in the cheese supply chain. In particular, a first traditional scenario “as is” is simulated without the use of new technologies and is compared to a second scenario “to be” that adopts IoT, RFID and blockchain. The results show an improvement in time performance for managing both perfect and non-compliant orders. The developed framework highlights the impact of new technologies on sustainability aspects, showing further managerial implications.

Resilience and Digitalization in Short Food Supply Chains: A Case Study Approach

The interest in short food supply chains (SFSCs) has grown significantly in the last decade, notably in respect of their potential role to achieve more sustainable food chains. However, a major barrier to achieving sustainable supply chains is the uncertainty associated with supply chain activities. Therefore, this paper aims to explore the different resilience capabilities that SFSCs possess and the potential role of digital technologies as enablers of SFSCs’ resilience. Using a case study research approach, semi-structured interviews were conducted in two SFSCs in Mexico. Collected data were analyzed using thematic analysis. Findings suggest that SFSCs possess the supply chain resilience (SC resilience) capabilities investigated here, namely flexibility, redundancy, collaboration, visibility and agility. A key finding is the importance of low-cost digital technologies (including freeware and social media) that can support flexibility, collaboration, visibility and agility. These findings raise important implications for SFSCs actors exploring opportunities to improve their collective resilience. This study expands the current literature by proposing a conceptual framework that summarizes a wide variety of strategies that support SC resilience capabilities in the context of SFSCs.

A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs

When integrating the Internet of Things (IoT) with Unmanned Aerial Vehicles (UAVs) occurred, tens of applications including smart agriculture have emerged to offer innovative solutions to modernize the farming sector. This paper aims to present a low-cost platform for comprehensive environmental parameter monitoring using flying IoT. This platform is deployed and tested in a real scenario on a farm in Medenine, Tunisia, in the period of March 2020 to March 2021. The experimental work fulfills the requirements of automated and real-time monitoring of the environmental parameters using both under- and aboveground sensors. These IoT sensors are on a farm collecting vast amounts of environmental data, where it is sent to ground gateways every 1 h, after which the obtained data is collected and transmitted by a drone to the cloud for storage and analysis every 12 h. This low-cost platform can help farmers, governmental, or manufacturers to predict environmental data over the geographically large farm field, which leads to enhancement in crop productivity and farm management in a cost-effective, and timely manner. Obtained experimental results infer that automated and human-made sets of actions can be applied and/or suggested, due to the innovative integration between IoT sensors with the drone. These smart actions help in precision agriculture, which, in turn, intensely boost crop productivity, saving natural resources.

Analyzing AgriFood-Tech e-Business Models

The agribusiness sector shows tremendous growth and sustainability prospects by exploiting the challenges of “AgriFood-Tech” business models in the digital environment, by encouraging innovation, accelerating institutional and structural change, enhancing productivity, and introducing new products and services to the market. The purpose of this study is to investigate different types of “AgriFood-Tech” digital models and analyze their role in the agribusiness and AgriFood sector. Based on relevant literature research, the authors present and discuss five indicative examples of “AgriFood-Tech” models, using the Business Model Canvas (BMC) framework. The methodology included the analysis of the components of innovative AgriFood innovative business models paradigms, such as distribution channels, key partnerships, customer selection and relationships, financial viability, and value proposition. The goal was to explore their building blocks and the required decisions that create, deliver, and capture value. Our findings highlight the importance of specific features of the models, including online sharing of information between the stakeholders, online searches of agri-products, and logistics services in the agribusiness sector.

Overinvestment in selected Central and Eastern European countries: Production and economic effects

Farms need to invest in order to earn incomes and maintain their competitive edge. However, the scale and extent of investments must be aligned with resources of other productive inputs, primarily including land, because otherwise there is risk of overinvestment. Since 2004, Central and Eastern European countries have been provided with access to investment support programs; these are non-repayable aid funds which can potentially lead to overinvestment issues. Therefore, this paper attempts to answer the question on the scale of overinvestment in the countries covered. This is all the more important since that problem has rarely been addressed in economic and agricultural research. The study presented in this paper is unique in that the research tasks are based on unpublished Farm Accountancy Data Network (FADN) microdata for 5839 selected Central and Eastern European farms provided by the European Commission’s Directorate-General for Agriculture and Rural Development (DG AGRI). Based on variables relating to the amount of productive inputs and production volumes, the authors developed their own typology of farms which includes the following categories: optimum investment levels (the growth rate of labor productivity is greater than growth in the assets-to-land ratio); relative overinvestment (while labor productivity grows, it does so at a slower rate than the assets-to-land ratio); absolute overinvestment (labor productivity declines while the assets-to-land ratio grows); underinvestment (decline in both labor productivity and the assets-to-land ratio). The authors demonstrated that members of the ‘absolute overinvestment’ group made flagrant mistakes in investment planning and implementation, whereas members of the ‘relative overinvestment’ group did record an improvement in labor productivity which ultimately can be considered a positive outcome. Underinvested farms were a very small minority in each country. In addition to filling a gap in the methodology for determining agricultural overinvestment, this paper also indicates the scale of that issue in Central and Eastern European countries. This study may be of importance both to farms (as guidelines for investment planning) and to agricultural policymakers who develop investment support programs.

Assessed versus Perceived Risks: Innovative Communications in Agri-Food Supply Chains

Food preparations, especially those based on animal products, are often accused of being responsible for the increase in food-borne infections, contributing to increased pressure on healthcare systems. The risk assessment in agri-food supply chains is of utmost importance for the food industry and for policymakers. A wrong perception of risks may alter the functioning of supply chains; thus, efforts should be devoted to communicating risks in an efficient way. We adopt a multidisciplinary approach to investigate how consumers perceive different food risks. Our analysis shows that planning effective communication strategies is very much important for efficiently informing consumers on food risks. We also comment on potential innovative ways to better organise the supply chains.

Enhancing Coffee Supply Chain towards Sustainable Growth with Big Data and Modern Agricultural Technologies

Modern agricultural technology management is nowadays crucial in terms of the economy and the global market, while food safety, quality control, and environmentally friendly practices should not be neglected. This review aims to give perspectives on applying big data analytic and modern technologies to increase the efficacy and effectiveness of the coffee supply chain throughout the process. It was revealed that several tools such as wireless sensor networks, cloud computing, Internet of Things (IoT), image processing, convolutional neural networks (CNN), and remote sensing could be implemented in and used to improve the coffee supply chain. Those tools could help in reducing cost as well as time for entrepreneurs and create a reliable service for the customer. It can be summarized that in the long term, these modern technologies will be able to assist coffee business management and ensure the sustainable growth for the coffee industry.

Smart Farming through Responsible Leadership in Bangladesh: Possibilities, Opportunities, and Beyond

Smart farming has the potential to overcome the challenge of 2050 to feed 10 billion people. Both artificial intelligence (AI) and the internet of things (IoT) have become critical prerequisites to smart farming due to their high interoperability, sensors, and cutting-edge technologies. Extending the role of responsible leadership, this paper proposes an AI and IoT based smart farming system in Bangladesh. With a comprehensive literature review, this paper counsels the need to go beyond the simple application of traditional farming and irrigation practices and recommends implementing smart farming enabling responsible leadership to uphold sustainable agriculture. It contributes to the current literature of smart farming in several ways. First, this paper helps to understand the prospect and challenges of both AI and IoT and the requirement of smart farming in a nonwestern context. Second, it clarifies the interventions of responsible leadership into Bangladesh’s agriculture sector and justifies the demand for sustainable smart farming. Third, this paper is a step forward to explore future empirical studies for the effective and efficient use of AI and IoT to adopt smart farming. Finally, this paper will help policymakers to take responsible initiatives to plan and apply smart farming in a developing economy like Bangladesh.

Distributed Ledger Technology Applications in Food Supply Chains: A Review of Challenges and Future Research Directions

The lack of transparency and traceability in food supply chains (FSCs) is raising concerns among consumers and stakeholders about food information credibility, food quality, and safety. Insufficient records, a lack of digitalization and standardization of processes, and information exchange are some of the most critical challenges, which can be tackled with disruptive technologies, such as the Internet of Things (IoT), blockchain, and distributed ledger technologies (DLTs). Studies provide evidence that novel technological and sustainable practices in FSCs are necessary. This paper aims to describe current practical applications of DLTs and IoT in FSCs, investigating the challenges of implementation, and potentials for future research directions, thus contributing to achievement of the United Nations’ Sustainable Development Goals (SDGs). Within a systematic literature review, the content of 69 academic publications was analyzed, describing aspects of implementation and measures to address the challenges of scalability, security, and privacy of DLT, and IoT solutions. The challenges of high costs, standardization, regulation, interoperability, and energy consumption of DLT solutions were also classified as highly relevant, but were not widely addressed in literature. The application of DLTs in FSCs can potentially contribute to 6 strategic SDGs, providing synergies and possibilities for more sustainable, traceable, and transparent FSCs.

Blockchain Applications in Agribusiness: A Systematic Review

Blockchain is a technology that can be applied in different sectors to solve various problems. As a complex system, agribusiness presents many possibilities to take advantage of blockchain technology. The main goal of this paper is to identify the purposes for which blockchain has been applied in the agribusiness sector, for which a PRISMA-based systematic review was carried out. The scientific literature corpus was accessed and selected from Elsevier’s Scopus and ISI of Knowledge’s Web of Science (WoS) platforms, using the PRISMA protocol procedures. Seventy-one articles were selected for analysis. Blockchain application in agribusiness is a novel topic, with the first publication dating from 2016. The technological development prevails more than blockchain applications since it has been addressed mainly in the Computer Sciences and Engineering. Blockchain applications for agribusiness management of financial, energy, logistical, environmental, agricultural, livestock, and industrial purposes have been reported in the literature. The findings suggest that blockchain brings many benefits when used in agribusiness supply chains. We concluded that the research on blockchain applications in agribusiness is only at an early stage, as many prototypes are being developed and tested in the laboratory. In the near future, blockchain will be increasingly applied across all economic sectors, including agribusiness, promoting greater reliability and agility in information with a reduced cost. Several gaps for future studies were observed, with significant value for science, industry, and society.

Blockchain and smart contract for IoT enabled smart agriculture

The agricultural sector is still lagging behind from all other sectors in terms of using the newest technologies. For production, the latest machines are being introduced and adopted. However, pre-harvest and post-harvest processing are still done by following traditional methodologies while tracing, storing, and publishing agricultural data. As a result, farmers are not getting deserved payment, consumers are not getting enough information before buying their product, and intermediate person/processors are increasing retail prices. Using blockchain, smart contracts, and IoT devices, we can fully automate the process while establishing absolute trust among all these parties. In this research, we explored the different aspects of using blockchain and smart contracts with the integration of IoT devices in pre-harvesting and post-harvesting segments of agriculture. We proposed a system that uses blockchain as the backbone while IoT devices collect data from the field level, and smart contracts regulate the interaction among all these contributing parties. The system implementation has been shown in diagrams and with proper explanations. Gas costs of every operation have also been attached for a better understanding of the costs. We also analyzed the system in terms of challenges and advantages. The overall impact of this research was to show the immutable, available, transparent, and robustly secure characteristics of blockchain in the field of agriculture while also emphasizing the vigorous mechanism that the collaboration of blockchain, smart contract, and IoT presents.

Strategic Supply Chain Planning for Food Hubs in Central Colombia: An Approach for Sustainable Food Supply and Distribution

This paper investigates the problem of sustainable rural supply and urban distribution of fresh food products in central Colombia. Paradoxically, while farmers in the countryside suffer from poverty due to the low profitability of the agricultural activity, inhabitants at urban centers pay high prices for fresh and nutritious foods. In this work, we propose a supply chain system and a business model based on food hubs located on existing (and often abandoned) public facilities in the central region of Colombia. There are many examples in which the hub strategy has facilitated trade and logistics in supply chains. However, few studies consider the particularities of the presented case. We study a business strategy through a mathematical model which considers both the sustainable and efficient operation of the food hubs and better trading conditions for farmers. We propose a variant of the competitive hub location problem adapted to this case study. We tested the model under different scenarios such as changes in the attractiveness parameters, operation costs, and profit margins. The results suggest that if hubs are able to attract farmers, the model can be both sustainable for the hub concessionaires and for the farmers.

The internet of things in the food supply chain: adoption challenges

Purpose

The food supply chain (FSC) challenges coupled with global disruptions, such as the recent coronavirus disease 2019 (COVID-19) pandemic outbreak, exacerbate its vulnerability. The Internet of things (IoT) is one of the disruptive technologies being adopted in food supply chain management (FSCM). This study aims to address the challenges of IoT adoption in the FSC by systematically analyzing the prior pertinent literature.

Design/methodology/approach

A structured literature review was used to collate a list of peer-reviewed and relevant publications. A total of 72 out of 210 articles were selected for the final evaluation.

Findings

The literature review findings suggest five themes: technical, financial, social, operational, educational and governmental related challenges. A total of 15 challenges were devised from the review related literature of IoT adoption. The study concludes with future research recommendations for scholars and practical implications for practitioners.

Research limitations/implications

While this study focuses on the overall FSC, further research should address other domains in the FSC such as cold supply chain, agriculture and perishable food to gain a better contextual understanding of the specific case.

Originality/value

The topic of IoT adoption in the FSCM is still considered emerging. Therefore, the present work contributes to the limited studies and documentation on the level of IoT implementation in the FSCM. This study should help organizations to assimilate how to adopt and manage the IoT application by addressing the factors and challenges presented in this research.

The Unknown Potential of Blockchain for Sustainable Supply Chains

The growing attention to emerging technologies has raised several doubts regarding the sustainability aspects. Among the new technologies, blockchain has laid the foundations for a revolution in the financial field but also in the energy, tourism, medical, industrial and supply chains sectors. Through a systematic literature review, 37 documents were analyzed to describe the sustainable aspects generated using blockchain in supply chains. Therefore, the results achieved provide two levels of analysis. The former highlights the impact of the adoption of blockchain in supply chains based on the three dimensions of sustainability: environmental, economic and social. The latter shows the positive and negative impacts of each form of sustainability. The purpose of the work is to summarize the current state of the art in order to propose a future development agenda based on the need to simulate and define a measurability for each dimension of sustainability. Finally, the study provides a broad overview of practical and managerial implications for entrepreneurs and researchers. On the one hand, the work shows how the use of blockchain improves the profits and reputation of companies. On the other hand, it highlights several research gaps to be investigated and considered by researchers.

Sustainability Driven by Agriculture through Digital Transformation

Economic, environmental and social sustainability is increasingly gaining the attention of academia and commitment in the policies of national economies. Global warming and climate change, weather disasters and disruptions are just some of the challenges that can drastically disrupt stable business models, and thus jeopardize sustainability. Agriculture, as an activity at the center of the value chain, is facing these problems, and, at the same time, contributes to feeding the growing world population and is responsible for conserving resources and ensuring sustainability. Process automation, data analysis and processing, control and management of agricultural operations have transformed the agricultural business and contributed to sustainability, survival and development within supply chains. This article analyzes the literature in the field of sustainability and agriculture led by digital technologies of Industry 4.0. The analysis of the research field showed the high importance of the topic in academic and national circles, given the number of published articles. Secondly, the concepts of sustainable agriculture and sustainability driven agriculture in the context of digital transformation were analyzed and it was shown that transformed agriculture can successfully cope with today’s challenges. Finally, guidelines for sustainable development driven by agriculture through the determinants of digital transformation are defined.

Digitalization and the third food regime

This article asks how the application of digital technologies is changing the organization of the agri-food system in the context of the third food regime. The academic debate on digitalization and food largely focuses on the input and farm level. Yet, based on the analysis of 280 digital services and products, we show that digital technologies are now being used along the entire food commodity chain. We argue that digital technologies in the third food regime serve on the one hand as a continuation of established information and communication technologies, thus deepening certain features of the existing food regime such as the retail sector's control over global commodity chains. On the other hand, digital technologies also introduce new forms of control and value extraction based on the use of data and pave the way for large tech companies to take over market shares in the agri-food sector. Finally, we find that multinational agri-food companies are starting to take on the business models of leading digital tech companies, for instance by developing digital platforms throughout the agri-food system. We argue that this shows that the broader economic restructuring of neoliberal capitalism towards digital capitalism is also making its way into the agri-food system.

The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems

Modern agriculture and food production systems are facing increasing pressures from climate change, land and water availability, and, more recently, a pandemic. These factors are threatening the environmental and economic sustainability of current and future food supply systems. Scientific and technological innovations are needed more than ever to secure enough food for a fast-growing global population. Scientific advances have led to a better understanding of how various components of the agricultural system interact, from the cell to the field level. Despite incredible advances in genetic tools over the past few decades, our ability to accurately assess crop status in the field, at scale, has been severely lacking until recently. Thanks to recent advances in remote sensing and Artificial Intelligence (AI), we can now quantify field scale phenotypic information accurately and integrate the big data into predictive and prescriptive management tools. This review focuses on the use of recent technological advances in remote sensing and AI to improve the resilience of agricultural systems, and we will present a unique opportunity for the development of prescriptive tools needed to address the next decade's agricultural and human nutrition challenges.

Applications of Artificial Neural Networks in Greenhouse Technology and Overview for Smart Agriculture Development

This article reviews the applications of artificial neural networks (ANNs) in greenhouse technology, and also presents how this type of model can be developed in the coming years by adapting to new technologies such as the internet of things (IoT) and machine learning (ML). Almost all the analyzed works use the feedforward architecture, while the recurrent and hybrid networks are little exploited in the various tasks of the greenhouses. Throughout the document, different network training techniques are presented, where the feasibility of using optimization models for the learning process is exposed. The advantages and disadvantages of neural networks (NNs) are observed in the different applications in greenhouses, from microclimate prediction, energy expenditure, to more specific tasks such as the control of carbon dioxide. The most important findings in this work can be used as guidelines for developers of smart protected agriculture technology, in which systems involve technologies 4.0.