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

GranoScan: an AI-powered mobile app for in-field identification of biotic threats of wheat

Capitalizing on the widespread adoption of smartphones among farmers and the application of artificial intelligence in computer vision, a variety of mobile applications have recently emerged in the agricultural domain. This paper introduces GranoScan, a freely available mobile app accessible on major online platforms, specifically designed for the real-time detection and identification of over 80 threats affecting wheat in the Mediterranean region. Developed through a co-design methodology involving direct collaboration with Italian farmers, this participatory approach resulted in an app featuring: (i) a graphical interface optimized for diverse in-field lighting conditions, (ii) a user-friendly interface allowing swift selection from a predefined menu, (iii) operability even in low or no connectivity, (iv) a straightforward operational guide, and (v) the ability to specify an area of interest in the photo for targeted threat identification. Underpinning GranoScan is a deep learning architecture named efficient minimal adaptive ensembling that was used to obtain accurate and robust artificial intelligence models. The method is based on an ensembling strategy that uses as core models two instances of the EfficientNet-b0 architecture, selected through the weighted F1-score. In this phase a very good precision is reached with peaks of 100% for pests, as well as in leaf damage and root disease tasks, and in some classes of spike and stem disease tasks. For weeds in the post-germination phase, the precision values range between 80% and 100%, while 100% is reached in all the classes for pre-flowering weeds, except one. Regarding recognition accuracy towards end-users in-field photos, GranoScan achieved good performances, with a mean accuracy of 77% and 95% for leaf diseases and for spike, stem and root diseases, respectively. Pests gained an accuracy of up to 94%, while for weeds the app shows a great ability (100% accuracy) in recognizing whether the target weed is a dicot or monocot and 60% accuracy for distinguishing species in both the post-germination and pre-flowering stage. Our precision and accuracy results conform to or outperform those of other studies deploying artificial intelligence models on mobile devices, confirming that GranoScan is a valuable tool also in challenging outdoor conditions.

Unleashing the Potential of Digitalization in the Agri-Food Chain for Integrated Food Systems

Digitalization transforms many industries, especially manufacturing, with new concepts such as Industry 4.0 and the Industrial Internet of Things. However, information technology also has the potential to integrate and connect the various steps in the supply chain. For the food industry, the situation is ambivalent: It has a high level of automatization, but the potential of digitalization is so far not used today. In this review, we discuss current trends in information technology that have the potential to transform the food industry into an integrated food system. We show how this digital transformation can integrate various activities within the agri-food chain and support the idea of integrated food systems. Based on a future-use case, we derive the potential of digitalization to tackle future challenges in the food industry and present a research agenda.

Digital Twins in Agriculture: Orchestration and Applications

Digital Twins have emerged as an outstanding opportunity for precision farming, digitally replicating in real-time the functionalities of objects and plants. A virtual replica of the crop, including key agronomic development aspects such as irrigation, optimal fertilization strategies, and pest management, can support decision-making and a step change in farm management, increasing overall sustainability and direct water, fertilizer, and pesticide savings. In this review, Digital Twin technology is critically reviewed and framed in the context of recent advances in precision agriculture and Agriculture 4.0. The review is organized for each step of agricultural lifecycle, edaphic, phytotechnologic, postharvest, and farm infrastructure, with supporting case studies demonstrating direct benefits for agriculture production and supply chain considering both benefits and limitations of such an approach. Challenges and limitations are disclosed regarding the complexity of managing such an amount of data and a multitude of (often) simultaneous operations and supports.

Exploring the application of ICTs in decarbonizing the agriculture supply chain: A literature review and research agenda

The contemporary agricultural supply chain necessitates the integration of information and communication technologies to effectively mitigate the multifaceted challenges posed by climate change and rising global demand for food products. Furthermore, recent developments in information and communication technologies, such as blockchain, big data analytics, the internet of things, artificial intelligence, cloud computing, etc., have made this transformation possible. Each of these technologies plays a particular role in enabling the agriculture supply chain ecosystem to be intelligent enough to handle today's world's challenges. Thus, this paper reviews the crucial information and communication technologies-enabled agriculture supply chains to understand their potential uses and contemporary developments. The review is supported by 57 research papers from the Scopus database. Five research areas analyze the applications of the technology reviewed in the agriculture supply chain: food safety and traceability, security and information system management, wasting food, supervision and tracking, agricultural businesses and decision-making, and other applications not explicitly related to the agriculture supply chain. The study also emphasizes how information and communication technologies can help agriculture supply chains and promote agriculture supply chain decarbonization. An information and communication technologies application framework for a decarbonized agriculture supply chain is suggested based on the research's findings. The framework identifies the contribution of information and communication technologies to decision-making in agriculture supply chains. The review also offers guidelines to academics, policymakers, and practitioners on managing agriculture supply chains successfully for enhanced agricultural productivity and decarbonization.

Behavioral decision-making of government, agricultural product producers, and consumers on agricultural product quality and safety regulation in a digital environment

The quality and safety of agricultural products are related to people's lives and health, economic development, and social stability, and have always been a hot issue of concern to the government and society. The rapid development of digital traceability technology in the digital environment has brought new opportunities for the supervision of agricultural product quality and safety, but the frequent occurrence of agricultural product safety incidents in recent years has exposed many problems such as the lack of governmental supervision, unstandardized production process of enterprises, and weak consumer awareness. To improve the cooperation efficiency of stakeholders and ensure the quality and safety of agricultural products, this paper proposes a dynamic model based on evolutionary game theory. The model incorporates the government, agricultural product producers, and farmers, and evaluates the stability and effectiveness of the system under different circumstances. The results of the study show that there are multiple evolutionary stabilization strategies in the tripartite evolutionary game model of agricultural product quality and safety supervision, and there are corresponding evolutionary stabilization conditions. There are several factors affecting the stability of the system, the most important of which are government regulation, severe penalties for agricultural product producers, and incentives. When these factors reach a certain threshold, the stakeholder cooperation mechanism can establish an evolutionarily stable strategy. This study contributes to the understanding of the operational mechanism of stakeholder cooperation in agricultural product quality and safety regulation in the digital environment and provides decision support and policy recommendations for stakeholders to promote the sustainable development and optimization of agricultural product quality and safety regulation.

Intelligent Biosensors Promise Smarter Solutions in Food Safety 4.0

Food safety is closely related to human health. However, the regulation and testing processes for food safety are intricate and resource-intensive. Therefore, it is necessary to address food safety risks using a combination of deep learning, the Internet of Things, smartphones, quick response codes, smart packaging, and other smart technologies. Intelligent designs that combine digital systems and advanced functionalities with biosensors hold great promise for revolutionizing current food safety practices. This review introduces the concept of Food Safety 4.0, and discusses the impact of intelligent biosensors, which offer attractive smarter solutions, including real-time monitoring, predictive analytics, enhanced traceability, and consumer empowerment, helping improve risk management and ensure the highest standards of food safety.

Achieving resilience through knowledge management practices and risk management culture in agri-food supply chains

The problems with the current food distribution system are laid forth in this study. Getting high-quality agricultural and food products to consumers is the goal of what is known as the "agri-food supply chain." Agri-food supply chain knowledge exchange and risk management culture are being studied, as is the effect of supply chain management methods on business success. We are seeing an increase in the regularity of supply chain interruptions. The recent supply chain interruptions and their associated consequences highlight the necessity for robust supply systems. The primary goal of this research is to examine the interplay between critical antecedents of the agri-food supply chain; supply chain resilience (including risk management culture); supply chain connectivity, visibility, collaboration, and agility; and the effect these factors have on supply chain resilience and, ultimately, firm performance. With the same foundational elements and backing from the literature, an empirical model has been suggested. From September 2020 to June 2021, 245 random samples were collected throughout Indonesia for this investigation. The suggested model and the interdependencies among the crucial antecedents have been verified using partial least squares-structural equation modeling (PLS-SEM). Findings from this study support the notion that agri-food supply chains benefit from increased emphasis on traceability, transparency, information sharing, and a culture of risk management. One major takeaway from this study is that by adopting the suggested methodology, businesses may build and strengthen their supply chain resilience capabilities by institutionalizing a risk management culture, raising employee risk awareness, and holding regular risk assessment drills. The study also suggests that businesses that want to strengthen their supply chains can do so by adopting information and communications technologies and visibility tools to improve their supply chain connectivity and visibility, allowing them to respond to and recover from disruptions in the supply chain more quickly. The model is validated using data from Indonesia's industrial sector. In order to establish supply chain resilience, the suggested model provides a comprehensive perspective that defines the interconnections between key antecedents. We conclude with some thoughts and suggestions for further study.

A review of supply chain quality management practices in sustainable food networks

Supply chain quality management practices are necessary to improve processes, meet consumer quality needs, and enhance supply chain quality management performance in sustainable food networks. Food supply chain quality management and associated practices are considerably studied in global food systems, less so for alternative food networks. There are salient differences between global food systems and alternative food networks, which may reflect on the applicable supply chain quality management practices in the food systems and networks. This paper reviews the literature on supply chain quality management practices, with a focus on alternative food networks. A systematic literature review methodology is adopted, resulting in the analysis of seventy-eight papers, identifying a total of one hundred and three supply chain quality management practices. The identified supply chain quality management practices were analysed in relation to their link to a) place, production, and producer and b) link to (bio)processes. Emerging themes from the analysis are discussed, and some areas of future research were put forward.

Exploring Sustainable Development Pathways for Agri-Food Supply Chains Empowered by Cross-Border E-Commerce Platforms: A Hybrid Grounded Theory and DEMATEL-ISM-MICMAC Approach

As cross-border e-commerce platforms become increasingly integrated into the agricultural supply chain, the establishment of a sustainable supply chain ecosystem is of paramount importance. This study, grounded in the platform theory and the supply chain ecosystem theory, combines the grounded theory and the DEMATEL-ISM-MICMAC model to thoroughly analyze the complex mechanisms driving sustainable development. Utilizing the grounded theory, we construct a system of driving factors comprising five primary indicators and eighteen secondary indicators. The hybrid model reveals the interrelationships, significance, system hierarchy, and dependence-driving relationships among these factors. Notably, the driving factor system is categorized into a six-level hierarchical structure, encompassing profound elements, such as policy optimization and digital empowerment, as well as surface-level factors, such as simplification of customs procedures and consumer demand forecasting. Based on the analysis results, this research proposes a set of pathways to achieve the sustainability of the supply chain. These strategies involve improving cross-border agricultural e-commerce policy frameworks, enhancing digital-driven supply-demand coordination, strengthening logistics infrastructure and transparency, and cultivating brand influence. The study's findings not only enrich the relevant theories but also provide practical guidance for the coordinated advancement of economic, social, environmental, and resilient development. Furthermore, they are conducive to advancing the United Nations Sustainable Development Goals.

Research on the Influencing Factors of Sustainable Supply Chain Development of Agri-Food Products Based on Cross-Border Live-Streaming E-Commerce in China

The organization and coordination of cross-border e-commerce platforms in agricultural product trading are continuously increasing, and the involvement of digital platforms has driven the integration and development of cross-border agricultural product supply chains with live-streaming e-commerce, effectively facilitating the comprehensive development of producers, sellers, and professional service providers within the ecosystem. However, despite the growing importance of this integration model in the market, there are still numerous unresolved issues from a supply chain perspective, and existing research provides relatively limited guidance on the effective operation of this integrated supply chain model. To address this gap in theoretical research, this study first delves into the essence and fundamental characteristics of sustainable cross-border agricultural product supply chains in the context of live streaming. Secondly, employing grounded theory as the primary research method and combining platform theory and ecosystem theory, an influencing factor system and an impact model for the development of sustainable cross-border agricultural product supply chains in the context of live streaming are constructed to gain a more comprehensive understanding of the complexity of this integrated supply chain model. Finally, from the perspectives of government agencies and practitioners, development pathways for sustainable cross-border agricultural product supply chains in the context of live-streaming e-commerce are proposed, aiming to enhance existing research and provide decision-making support for relevant stakeholders in formulating development strategies. The findings of this study contribute to expanding the research perspective on the ecosystem of live-streaming e-commerce and sustainable cross-border agricultural product supply chains, providing theoretical support for the establishment and operation of sustainable cross-border agricultural product supply chains in the context of live streaming. Additionally, it offers important references for promoting the sustainable development of live-streaming e-commerce and cross-border agricultural product supply chains, facilitating industry upgrading, global agricultural trade, and achieving mutually beneficial outcomes.

Tactile-Sensing Technologies: Trends, Challenges and Outlook in Agri-Food Manipulation

Tactile sensing plays a pivotal role in achieving precise physical manipulation tasks and extracting vital physical features. This comprehensive review paper presents an in-depth overview of the growing research on tactile-sensing technologies, encompassing state-of-the-art techniques, future prospects, and current limitations. The paper focuses on tactile hardware, algorithmic complexities, and the distinct features offered by each sensor. This paper has a special emphasis on agri-food manipulation and relevant tactile-sensing technologies. It highlights key areas in agri-food manipulation, including robotic harvesting, food item manipulation, and feature evaluation, such as fruit ripeness assessment, along with the emerging field of kitchen robotics. Through this interdisciplinary exploration, we aim to inspire researchers, engineers, and practitioners to harness the power of tactile-sensing technology for transformative advancements in agri-food robotics. By providing a comprehensive understanding of the current landscape and future prospects, this review paper serves as a valuable resource for driving progress in the field of tactile sensing and its application in agri-food systems.

Blockchain-Based Frameworks for Food Traceability: A Systematic Review

With the rise of globalization and technological competition, the food supply chain has grown more complex due to the multiple players and factors involved in the chain. Traditional systems fail to offer effective and reliable traceability solutions considering the increasing requirement for accountability and transparency in the food supply chain. Blockchain technology has been claimed to offer the food industry a transformative future. The inherent features of blockchain, including immutability and transparency, create a dependable and secure system for tracking food products across the whole supply chain, ensuring total control over their traceability from the origin to the final consumer. This research offers a comprehensive overview of multiple models to understand how the integration of blockchain and other digital technologies has transformed the food supply chain. This comprehensive systematic review of blockchain-based food-supply-chain frameworks aimed to uncover the capability of blockchain technology to revolutionize the industry and examined the current landscape of blockchain-based food traceability solutions to identify areas for improvement. Furthermore, the research investigates recent advancements and investigates how blockchain aligns with other emerging technologies of Industry 4.0 and Web 3.0. Blockchain technology plays an important role in improving food traceability and supply-chain operations. Potential synergies between blockchain and other emerging technologies of Industry 4.0 and Web 3.0 are digitizing food supply chains, which results in better management, automation, efficiencies, sustainability, verifiability, auditability, accountability, traceability, transparency, tracking, monitoring, response times and provenance across food supply chains.

Bioactive compounds for human and planetary health

Bioactive compounds found in edible plants and foods are vital for human and planetary health, yet their significance remains underappreciated. These natural bioactives, as part of whole diets, ingredients, or supplements, can modulate multiple aspects of human health and wellness. Recent advancements in omic sciences and computational biology, combined with the development of Precision Nutrition, have contributed to the convergence of nutrition and medicine, as well as more efficient and affordable healthcare solutions that harness the power of food for prevention and therapy. Innovation in this field is crucial to feed a growing global population sustainably and healthily. This requires significant changes in our food system, spanning agriculture, production, distribution and consumption. As we are facing pressing planetary health challenges, investing in bioactive-based solutions is an opportunity to protect biodiversity and the health of our soils, waters, and the atmosphere, while also creating value for consumers, patients, communities, and stakeholders. Such research and innovation targets include alternative proteins, such as cellular agriculture and plant-derived protein; natural extracts that improve shelf-life as natural preservatives; upcycling of agricultural by-products to reduce food waste; and the development of natural alternatives to synthetic fertilizers and pesticides. Translational research and innovation in the field of natural bioactives are currently being developed at two levels, using a systems-oriented approach. First, at the biological level, the interplay between these compounds and the human host and microbiome is being elucidated through omics research, big data and artificial intelligence, to accelerate both discovery and validation. Second, at the ecosystem level, efforts are focused on producing diverse nutrient-rich, flavorful, and resilient, yet high-yield agricultural crops, and educating consumers to make informed choices that benefit both their health and the planet. Adopting a system-oriented perspective helps: unravel the intricate and dynamic relationships between bioactives, nutrition, and sustainability outcomes, harnessing the power of nature to promote human health and wellbeing; foster sustainable agriculture and protect the ecosystem. Interdisciplinary collaboration in this field is needed for a new era of research and development of practical food-based solutions for some of the most pressing challenges humanity and our planet are facing today.

Blockchain technology for sustainable supply chains: a network cluster analysis and future research propositions

Achieving the sustainable goals of the United Nations requires improving supply chain sustainability (SSC). Blockchain technology (BCT) has attracted attention on a global level with the ability to transform supply chain management and sustainability efforts. Recognizing this, this study investigates how BCT plays a role in SSC. The current study looks into the importance of BCT in order to move supply networks towards sustainability by performing bibliometric analysis, and network cluster analysis. Through the literature review, the current literature was analyzed and future research directions were concluded. We begin our study by selecting 297 papers on the relevant subjects by applying various filters to the Web of Science (WoS) database. Influential individuals, journals, and organizations in this field were identified using bibliometric analysis. A network analysis was performed to identify influential co-author, and keywords, and for page rank, and cluster analysis. The network analysis was revealed ten distinct study clusters, and ten propositions were suggested from the analysis of these clusters. Additionally, a conceptual framework for the research was proposed, which can advise managers, practitioners, and researcher communities on the key trends and topics in this emerging research domain. Furthermore, to guide research scholars in this field, 33 future research directions were suggested.

The Aspects of Artificial Intelligence in Different Phases of the Food Value and Supply Chain

The types of artificial intelligence, artificial intelligence integration to the food value and supply chain, other technologies embedded with artificial intelligence, artificial intelligence adoption barriers in the food value and supply chain, and solutions to overcome these barriers were analyzed by the authors. It was demonstrated by the analysis that artificial intelligence can be integrated vertically into the entire food supply and value chain, owing to its wide range of functions. Different phases of the chain are affected by developed technologies such as robotics, drones, and smart machines. Different capabilities are provided for different phases by the interaction of artificial intelligence with other technologies such as big data mining, machine learning, the Internet of services, agribots, industrial robots, sensors and drones, digital platforms, driverless vehicles and machinery, and nanotechnology, as revealed by a systematic literature analysis. However, the application of artificial intelligence is hindered by social, technological, and economic barriers. These barriers can be overcome by developing the financial and digital literacy of farmers and by disseminating good practices among the participants of the food supply and value chain.

Identifying barriers to big data analytics adoption in circular agri-food supply chains: a case study in Turkey

Big data analytics (BDA), along with the resource efficiency and sustainability perspectives of a circular economy, supports the transition to circular agri-food supply chains (AFSCs), contributing to a country's achievement of the United Nations' Sustainable Development Goals. However, there is still limited research demonstrating the importance and awareness of BDA implementation in circular AFSCs in developing countries. As a result of the barriers to BDA adoption in these regions, circular AFSCs in developing countries are still in their infancies. This study sought to identify the barriers to BDA adoption in circular AFSCs in Turkey using a Delphi-based Pythagorean fuzzy analytic hierarchy process. The proposed method removes the potential for bias and produces consensus among managers of companies in various AFSCs in Turkey. The findings of this study show that the most impactful barriers to BDA are technical, economic and social, followed by environmental and organisational. The most crucial sub-barriers to BDA adoption are "lack of trust, privacy and security", "lack of financial resources" and "lack of skilled human resources". This research can guide industry managers and policymakers in the development of strategies for overcoming barriers to BDA adoption in circular AFSCs in developing nations.

"How sweet are your strawberries?": Predicting sugariness using non-destructive and affordable hardware

Global soft fruit supply chains rely on trustworthy descriptions of product quality. However, crucial criteria such as sweetness and firmness cannot be accurately established without destroying the fruit. Since traditional alternatives are subjective assessments by human experts, it is desirable to obtain quality estimations in a consistent and non-destructive manner. The majority of research on fruit quality measurements analyzed fruits in the lab with uniform data collection. However, it is laborious and expensive to scale up to the level of the whole yield. The "harvest-first, analysis-second" method also comes too late to decide to adjust harvesting schedules. In this research, we validated our hypothesis of using in-field data acquirable via commodity hardware to obtain acceptable accuracies. The primary instance that the research concerns is the sugariness of strawberries, described by the juice's total soluble solid (TSS) content (unit: °Brix or Brix). We benchmarked the accuracy of strawberry Brix prediction using convolutional neural networks (CNN), variational autoencoders (VAE), principal component analysis (PCA), kernelized ridge regression (KRR), support vector regression (SVR), and multilayer perceptron (MLP), based on fusions of image data, environmental records, and plant load information, etc. Our results suggest that: (i) models trained by environment and plant load data can perform reliable prediction of aggregated Brix values, with the lowest RMSE at 0.59; (ii) using image data can further supplement the Brix predictions of individual fruits from (i), from 1.27 to as low up to 1.10, but they by themselves are not sufficiently reliable.

Determinants of reduction of food loss and waste in Indian agri-food supply chains for ensuring food security: A multi-stakeholder perspective

With a rising population and increasing concern for food security, food loss and waste (FLW) has become a critical challenge to global sustainability. This paper, drawing on multi-stakeholder theory, aims to empirically identify the key determinants influencing the reduction of FLW in Indian agri-food supply chains (AFSCs) for ensuring food security. A structured questionnaire was used to collect responses from the various stakeholders of the AFSC and then the exploratory factor analysis technique was used to summarize the items into underlying determinants of reduction of FLW in Indian AFSC for ensuring food security. The results of this study reveal that (1) government support, (2) supply chain partnerships, (3) technological support, (4) consumer attitude and (5) top management commitment are the key determinants in the given context. All the stakeholders of AFSC must be aware of these key determinants affecting the reduction of FLW. They must work collaboratively to make a difference by preventing and managing FLW as it is everyone's responsibility to work towards food security.

Optimizing the Agricultural Supply Chain through E-Commerce: A Case Study of Tudouec in Inner Mongolia, China

E-commerce has the potential to address problems in the agricultural supply chain and support the implementation of rural revitalization strategies. Previous research has largely focused on the business models of rural e-commerce platforms, but has not examined the mechanisms by which they can optimize and reconfigure the agricultural supply chain. This study aims to fill this gap through a case study of Tudouec, a potato e-commerce platform in Inner Mongolia, China. The study employs a single-case study method and utilizes data from interviews, fieldwork, and secondary sources. The findings show that Tudouec is a multi-functional platform offering technical support, warehousing, logistics, supply chain finance, and insurance, among other services. It not only serves as a multi-channel information management platform, but also enhances supply chain capabilities through the interaction of information flow with capital and material flows. This rural e-commerce model addresses the limitations of traditional agricultural models and promotes poverty reduction and rural revitalization. The study's main contribution is in demonstrating the potential for the Tudouec model to be applied to other agricultural products and in other developing countries.

Blockchain technology for sustainable development: a systematic literature review

Purpose

Blockchain technology (BCT) is one of the latest disruptive innovations, brought along with-it immense scope of diverse applications contributing towards sustainable development (SD). The consistent increase in the publications reveal that the application of BCT for SD has become popular among researchers and practitioners in past few years, in turn, urged for a systematic literature review (SLR) to get an insight into the research journey travelled so far and setting directions for future research in this area. Therefore, this study aims to identify, map and synthesize the available literature on application of BCT for SD.

Design/methodology/approach

The automatic and manual search resulted into 1,277 studies from Scopus and Web of Science database. Further applying inclusion and exclusion criterion resulted in bringing out total of 157 studies, which were termed as primary studies. Based on the results of descriptive analysis, conducted through Bibliometric and VOSviewer software, the characteristics of BCT and its key capabilities, contributing towards shaping the recent SD literature, were critically examined. Identified research themes for clustering primary studies were aligned with United Nations Sustainability Development Goals (UNSDG). A mind-map was also prepared on the basis of thematic classification of primary studies.

Findings

The research themes “business practice and economic sustainability”, “agriculture and food security” and “business practice and environment sustainability” were found to be the focal points of scholarly attention. Synthesis and analysis of primary studies resulted into classification of research gaps under four categories – theoretical foundation, methodological limitation, research themes and technology implementation challenges. The study was concluded by sensitizing and sanitizing the concrete research questions for future research.

Research limitations/implications

The research findings shall be a roadmap for research scholars, academicians and practitioners to comprehend the present state of knowledge in the domain of “BCT application for SD” and decide upon adopting the future course of action to attain the UNSDGs by the year 2030.

Originality/value

To the best of the authors’ knowledge, the current study is the first attempt in its own sense to analyse and synthesize the available literature on “attaining SD through BCT” using SLR approach.

Blockchain-Based Supply Chain Systems, Interoperability Model in a Pharmaceutical Case Study

The main purpose of supply chain systems based on blockchain technology is to take advantage of technology innovations to ensure that a tracked asset's audit trail is immutable. However, the challenge lies in tracking the asset among different blockchain-based supply chain systems. The model proposed in this paper has been designed to overcome the identified challenges. Specifically, the proposed model enables: (1) the asset to be tracked among different blockchain-based supply-chain systems; (2) the tracked asset's supply chain to be cryptographically verified; (3) a tracked asset to be defined in a standardized format; and (4) a tracked asset to be described with several different standardized formats. Thus, the model provides a great advantage in terms of interoperability between different blockchain-driven supply chains over other models in the literature, which will need to replicate the information in each blockchain platform they operate with, while giving flexibility to the platforms that make use of it and maintain the scalability of those logistic platforms. This work aims to examine the application of the proposed model from an operational point of view, in a scenario within the pharmaceutical sector.

A critical analysis of the integration of blockchain and artificial intelligence for supply chain

The integration between blockchain and artificial intelligence (AI) has gained a lot of attention in recent years, especially since such integration can improve security, efficiency, and productivity of applications in business environments characterised by volatility, uncertainty, complexity, and ambiguity. In particular, supply chain is one of the areas that have been shown to benefit tremendously from blockchain and AI, by enhancing information and process resilience, enabling faster and more cost-efficient delivery of products, and augmenting products' traceability, among others. This paper performs a state-of-the-art review of blockchain and AI in the field of supply chains. More specifically, we sought to answer the following three principal questions: Q1-What are the current studies on the integration of blockchain and AI in supply chain?, Q2-What are the current blockchain and AI use cases in supply chain?, and Q3-What are the potential research directions for future studies involving the integration of blockchain and AI? The analysis performed in this paper has identified relevant research studies that have contributed both conceptually and empirically to the expansion and accumulation of intellectual wealth in the supply chain discipline through the integration of blockchain and AI.

Construction and application of computerized risk assessment model for supply chain finance under technology empowerment

This study seeks to assist small and medium enterprises break free of the constraints of the conventional financing model and lessen the supply chain finance risks they face. First, the supply chain financial business model and credit risk are analyzed, followed by a discussion of the application principle of blockchain in the control of supply chain financial credit risk. The next topic up for discussion is the emancipation of individuals and the application of financial technology toward the management of financial risk in supply chains. In the final stage of the development of the computerized risk assessment model, the Fuzzy Support Vector Machine (FSVM) is optimized, and the effectiveness and efficiency of risk classification are enhanced by introducing a variable penalty factor C. To test the efficacy of the C-FSVM risk assessment model, the Chinese auto sector is used as the study's object. According to the results of the study, the C-FSVM model has a classification accuracy of 96.35% for the entire sample, 96.45% for credible firms, and 95.34% for default enterprises. The training time of the C-FSVM model is 473.9s, which is far lower than the SVM and FSVM models' training times of 1631.6s and 1870.2s. In summary, the C-FSVM supply chain financial risk assessment model is effective and has great application value in banking practice.

Sensor-Driven Human-Robot Synergy: A Systems Engineering Approach

Knowledge-based synergistic automation is a potential intermediate option between the opposite extremes of manual and fully automated robotic labor in agriculture. Disruptive information and communication technologies (ICT) and sophisticated solutions for human-robot interaction (HRI) endow a skilled farmer with enhanced capabilities to perform agricultural tasks more efficiently and productively. This research aspires to apply systems engineering principles to assess the design of a conceptual human-robot synergistic platform enabled by a sensor-driven ICT sub-system. In particular, this paper firstly presents an overview of a use case, including a human-robot synergistic platform comprising a drone, a mobile platform, and wearable equipment. The technology framework constitutes a paradigm of human-centric worker-robot logistics synergy for high-value crops, which is applicable in operational environments of outdoor in-field harvesting and handling operations. Except for the physical sub-system, the ICT sub-system of the robotic framework consists of an extended sensor network for enabling data acquisition to extract the context (e.g., worker's status, environment awareness) and plan and schedule the robotic agents of the framework. Secondly, this research explicitly presents the underpinning Design Structure Matrix (DSM) that systematically captures the interrelations between the sensors in the platform and data/information signals for enabling synergistic operations. The employed Systems Engineering approach provides a comprehensible analysis of the baseline structure existing in the examined human-robot synergy platform. In particular, the applied DSM allows for understanding and synthesizing a sensor sub-system's architecture and enriching its efficacy by informing targeted interventions and reconfiguring the developed robotic solution modules depending on the required farming tasks at an orchard. Human-centric solutions for the agrarian sector demand careful study of the features that the particular agri-field possesses; thus, the insight DSM provides to system designers can turn out to be useful in the investigation of other similar data-driven applications.

Construction of rice supply chain supervision model driven by blockchain smart contract

The outbreak of the COVID-19 and the Russia Ukraine war has had a great impact on the rice supply chain. Compared with other grain supply chains, rice supply chain has more complex structure and data. Using digital means to realize the dynamic supervision of rice supply chain is helpful to ensure the quality and safety of rice. This study aimed to build a dynamic supervision model suited to the circulation characteristics of the rice supply chain and implement contractualization, analysis, and verification. First, based on an analysis of key information in the supervision of the rice supply chain, we built a dynamic supervision model framework based on blockchain and smart contracts. Second, under the logical framework of a regulatory model, we custom designed three types of smart contracts: initialization smart contract, model-verification smart contract, and credit-evaluation smart contract. To implement the model, we combined an asymmetric encryption algorithm, virtual regret minimization algorithm, and multisource heterogeneous fusion algorithm. We then analyzed the feasibility of the algorithm and the model operation process. Finally, based on the dynamic supervision model and smart contract, a prototype system is designed for example verification. The results showed that the dynamic supervision model and prototype system could achieve the real-time management of the rice supply chain in terms of business information, hazard information, and personnel information. It could also achieve dynamic and credible supervision of the rice supply chain's entire life cycle at the information level. This new research is to apply information technology to the digital management of grain supply chain. It can strengthen the digital supervision of the agricultural product industry.

Integrating artificial intelligence into a talent management model to increase the work engagement and performance of enterprises

The purpose of the paper is to create a multidimensional talent management model with embedded aspects of artificial intelligence in the human resource processes to increase employees' engagement and performance of the enterprise. The research was implemented on a sample of 317 managers/owners in Slovenian enterprises. Multidimensional constructs of the model include several aspects of artificial intelligence implementation in the organization's activities related to human resource management in the field of talent management, especially in the process of acquiring and retaining talented employees, appropriate training and development of employees, organizational culture, leadership, and reducing the workload of employees, employee engagement and performance of the enterprise. The results show that AI supported acquiring and retaining a talented employees, AI supported appropriate training and development of employees, appropriate teams, AI supported organizational culture, AI supported leadership, reducing the workload of employees with AI have a positive effect on performance of the enterprise and employee engagement. The results will help managers or owners create a successful work environment by implementing artificial intelligence in the enterprise, leading to increased employee engagement and performance of the enterprise. Namely, our results contribute to the efficient implementation of artificial intelligence into an enterprise and give owners or top managers a broad insight into the various aspects that must be taken into account in business management in order to increase employee engagement and enterprise's competitive advantage.

Internet technology and green productivity in agriculture

The high-quality development of agriculture requires not only sustainable growth of agricultural productivity but also green agricultural production. Internet technology has played an essential role in agricultural production and marketing in China over the past decades. This paper estimates provincial agricultural green growth in China from 1997 to 2019 and decomposes it into technological progress (TP) and efficiency changes (EC) based on the Luenberger productivity indicator method. Then an econometric model is employed to analyze the impact of the Internet on the growth of agricultural green productivity and each sub-component, and moderating role of farmer education in such effect. The empirical results indicated that annual average growth rate of agricultural green productivity in China is 1.33% from 1997 to 2019, and technological progress dominates its growth. The development of Internet technology has a significant positive impact on agricultural green productivity and its decomposition. Farmer education has strengthened the effect of Internet technology on agricultural green productivity and its decomposition TP and EC.

Blockchain as enabling factor for implementing RFID and IoT technologies in VMI: a simulation on the Parmigiano Reggiano supply chain

Blockchain has recently been associated to Supply Chain Management to solve several problems and change operations management processes. The study proposes to analyse three different scenarios of the Parmigiano Reggiano supply chain considering blockchain technology as an enabler for the use of other technologies such as RFID and the Internet of Things (IoT) and for the exploitation of the Vendor Managed Inventory (VMI) strategy. The study is based on the evaluation of three agent-based simulation scenarios, a traditional "as is" scenario, a second "to be" scenario implementing emerging technologies including blockchain, and a third “to be” scenario that combines the second one with the VMI optimization strategy. The results show how the combined adoption of these technologies improves the procurement process and customer satisfaction. Findings highlight the impacts that the different scenarios have on the supply chain operations in a quantitative way and allows to evaluate the changes in supply chain processes. By employing emerging technologies, order management activities are more automated and time to order and lead time order preparation are reduced. However, to achieve these performances, other data capture tools such as RFID and IoT are needed. Finally, the introduction of the VMI strategy, when enabled by blockchain technology, improves the procurement performances and significantly reduces unfilled orders.

The Operation Mode of Agricultural Supply Chain Finance Using Blockchain

With the rapid development of agriculture, modern agriculture has achieved remarkable results. Agriculture is the foundation of China's national economy, and the Party Central Committee has always insisted on solving the "three rural issues" as the top priority of the work of the whole party. However, China's agricultural foundation is weak, and the problem of unbalanced supply and demand structure of agricultural products still exists in agricultural development. With the development of blockchain, the application basis in the agricultural value chain has been established. At present, the research on the application of agricultural value chain financing is still in progress, but it is still in the initial stage. The integration of agricultural finance blockchain is low, and there are a series of problems. Extending blockchain technology to the financial area of agricultural value chains can help overcome the information barriers to traditional agricultural value chain financing and improve access to information resources for traditional agricultural value chains. The high cost of these value chains and inadequate financial management mechanisms remove bottlenecks in financing agricultural development. In this paper, we study the operation model and revenue distribution model of agricultural value chains using blockchain, analyze examples, and finally identify the basic elements of agricultural value chain financing based on sectoral chain technology. It provides theoretical support for the financing decision and production decision of each member of the agricultural supply chain, and it is hoped that the content and conclusions of the study can provide methodological reference and theoretical guidance for agricultural supply chain enterprises.

Sustainable food cold chain logistics: From microenvironmental monitoring to global impact

Food cold chain logistics (FCCL) is a systematic engineering process involving the use of a low-temperature environment to maintain the quality and safety of perishable food and reduce food loss and waste (FLW). From a mechanism perspective, FCCL must balance resource costs for a required level of food quality and safety with the costs of greenhouse gas (GHG) emissions. In the context of global warming, the sustainability trade-off between FLW and environmental impact has recently become an important topic in research on efficient, green FCCL. This is mainly reflected in technological innovation, management optimization, and policy responses. With a focus on three levels (micro, meso, macro), this review analyzes current research areas and the gaps and challenges of FCCL in microenvironmental monitoring, life cycle assessment (LCA), and global impact. Future trends pertaining to FCCL in technology, management, and industry and sustainable development are also summarized. Future trends involving sustainable FCCL must be intelligent, systematic, and low carbon. Industry empowerment through next-generation information technologies (e.g., IoT, AI, big data, blockchain) will promote the multidimensional perception, real-time information transmission, and sustainable control of microenvironmental monitoring, as well as support LCA management transformation from fragmentation to system integration. From a macro level, due to the serious global loss of perishable food, the FCCL scale demand is growing greatly, causing a huge environmental burden. Global cooperation, low-carbon consensus, and appropriate policies will become the basis for promoting sustainable FCCL development.

Analysing key barriers to Industry 4.0 for sustainable supply chain management

This study aims to define the adoption barriers to Industry 4.0 for sustainable supply chain and define their causalities and, dependencies, hierarchical levels of these barriers. Firstly, a framework for critical barriers to Industry 4.0 for sustainable supply chain management is created with literature review and experts for the first time. Then an integrated approach of Grey DEMATEL – ANP is proposed to analyze the adoption barriers to Industry 4.0 in sustainable supply chain management. The proposed method determines the cause-effect relationship among barriers, the strength of interactions, and the relative weights of critical barriers to Industry 4.0 in a sustainable supply chain. The results show that uncertainty about economic benefits, resistance to change, and lack of infrastructure and tools for Industry 4.0 in the Sustainable supply chain are crucial barriers to implementing Industry 4.0 technologies in SSC. This study can help decision-makers and managers define the barriers and provide the theoretical guideline to implement Industry 4.0 technologies across the sustainable supply chain successfully.

Uncovering dimensions of the impact of blockchain technology in supply chain management

Supply chains around the globe are faced with difficulties and disruptions due to the worldwide pandemic situation and digital solutions are needed. There is significant research interest in the implementation of blockchain technology (BCT) for supply chain management (SCM). A challenge that remains is analyzing the interactions of BCT in different areas of SCM. This study aims to identify the influential dimensions of the impact of BCT adoption in SCM and to discuss the synergetic and counter-synergetic effects between these dimensions. Advantages, disadvantages, and constraints of adopting BCT in the SCM context are explored through a systematic literature review, which provides the foundation for identifying the dimensions of impact. The interactions between these dimensions are conceptually discussed. This study introduces three dimensions of the impact of implementing BCT in SCM: ‘operations and processes’, ‘supply chain relationships’, and ‘innovation and data access’. These dimensions are interrelated and have overlapping areas within them, which leads to synergetic and counter-synergetic effects. The overlaps and synergies of the three dimensions of impact are illustrated, and the virtuous and vicious cycles of BCT adoption in SCM cases are highlighted. This study assists scholars and practitioners by clarifying the synergetic relationships within the dimensions of the impact of BCT in SCM and by providing considerations to prevent undesirable effects and expand desired ones.

Blockchain Adoption to Secure the Food Industry: Opportunities and Challenges

With the growth in food products’ usage, ensuring their quality and safety has become progressively difficult. Specifically, food traceability turns out to be a very critical task for retailers, sellers, consumers, surveillance authorities, and other stakeholders in the food supply chain system. There are requirements for food authenticity verification (correct declaration of cultivation, origin, and variety), quality checks (e.g., justification for higher prices), and preventing food products from fraudsters in the food industry. The ubiquitous and promising technology of blockchain ensures the traceability of food trade networks with high potential and handles the aforementioned issues. Blockchain makes the food industry more transparent at all levels by storing data immutably and enabling quick tracking across the stages of the food supply chain. Hence, commodities, stakeholders, and semi-finished food items can be recognized significantly faster. Motivated by these facts, in this paper, we present an in-depth survey of state-of-the-art approaches to the food industry’s security, food traceability, and food supply chain management. Further, we propose a blockchain-based secure and decentralized food industry architecture to alleviate security and privacy aspects and present a comprehensive solution taxonomy for a blockchain-based food industry. Then, a comparative analysis of existing approaches with respect to various parameters, i.e., scalability, latency, and food quality, is presented, which facilitates the end-user in selecting approaches based on the merits over other approaches. Finally, we provide insights into the open issues and research challenges with concluding remarks.

The Antecedents of Willingness to Adopt and Pay for the IoT in the Agricultural Industry: An Application of the UTAUT 2 Theory

This paper aims to examine the factors influencing the willingness of Bangladeshi farmers to adopt and pay for the Internet of Things (IoT) in the agricultural sector by applying the theoretical framework of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2). To this end, the study employed a quantitative research methodology and obtained data from 345 farmers from the northern districts of Bangladesh. Using a cross-sectional survey design and convenience sampling method, a study of premium fruit growers was undertaken to assess IoT use in agriculture, and the primary survey data were analyzed using the Structural Equation Modeling (SEM) approach via AMOS 26. The study confirmed that effort expectancy, performance expectancy, facilitating condition, hedonic motivation, government support, price value, personal innovativeness, and trust influence the willingness of Bangladeshi farmers to adopt the IoT. Additionally, predictors such as trust and willingness to adopt were observed to influence the willingness to pay for the IoT, while the construct ‘performance expectancy’ produced no effect. The study also revealed that the willingness to adopt moderates the association between performance expectancy, price value, and willingness to pay for the IoT. This research has novel implications because it investigates the behavior of rural customers with respect to innovation adoption, which in this case is the IoT in agriculture. It outlines precise reasons for the willing adoption of the IoT in agriculture, which will, in turn, assist marketers of IoT technology in the design of appropriate marketing strategies to increase acceptance in rural areas. Using the proposed model that incorporates farmers’ willingness to pay, this empirical study takes the first step in examining whether farmers in a developing economy such as Bangladesh will adopt and pay for the IoT.

Integration of Innovative Technologies in the Agri-Food Sector: The Fundamentals and Practical Case of DNA-Based Traceability of Olives from Fruit to Oil

Several socio-economic problems have been hidden by the COVID-19 pandemic crisis. Particularly, the agricultural and food industrial sectors have been harshly affected by this devastating disease. Moreover, with the worldwide population increase and the agricultural production technologies being inefficient or obsolete, there is a great need to find new and successful ways to fulfill the increasing food demand. A new era of agriculture and food industry is forthcoming, with revolutionary concepts, processes and technologies, referred to as Agri-food 4.0, which enables the next level of agri-food production and trade. In addition, consumers are becoming more and more aware about the origin, traceability, healthy and high-quality of agri-food products. The integration of new process of production and data management is a mandatory step to meet consumer and market requirements. DNA traceability may provide strong approach to certify and authenticate healthy food products, particularly for olive oil. With this approach, the origin and authenticity of products are confirmed by the means of unique nucleic acid sequences. Selected tools, methods and technologies involved in and contributing to the advance of the agri-food sector are presented and discussed in this paper. Moreover, the application of DNA traceability as an innovative approach to authenticate olive products is reported in this paper as an application and promising case of smart agriculture.

A bibliometric and thematic approach to agriculture 4.0

Researchers are developing digital solutions for agriculture. Humanity has perfected agriculture throughout history because this activity is fundamental to our existence. The agricultural sector is currently incorporating new technologies from other areas. This phenomenon is agriculture 4.0. However, a challenge to research is the integration of technologies from different knowledge fields, and this has caused theoretical and practical difficulties. Thus, our purpose with this study has been to understand the core agriculture 4.0 research themes. We have used a bibliometric analysis, and guided the data collection by the PRISMA protocol. VosViewer and Bibliometrix software generated the results. We found two main research fronts, one focussed on agriculture 4.0 development, and another on the impacts of agriculture 4.0, which may be positive or negative. We found 21 main keywords or topics researched in agriculture 4.0 related to these research fronts. These themes are within five different axes. We managed to establish a good understanding of the topics around agriculture 4.0. Future studies could focus on the responsible development of digital solutions for agriculture. This is because the social, environmental, and economic impacts of these new solutions may be positive or negative. We conclude that digital agriculture is the node technologies integration for the automation of agricultural activities.

•

There are two main research fronts.

•

Agriculture 4.0 can have both positive and negative impacts.

•

Agricultural development, food supply, and climate change are high centrality and density themes.

•

Crops, remote sensing, and precision agriculture are motor themes.

•

Agriculture, digital agriculture, and agricultural robots are basic themes.

Modeling and Analyzing the Impact of the Internet of Things-Based Industry 4.0 on Circular Economy Practices for Sustainable Development: Evidence From the Food Processing Industry of China

The Industry 4.0 concept proposes that new cutting-edge technologies, such as the Internet of Things (IoT), will grow. The acceptance of IoT in the circular economy (CE) is still in its infancy, despite its enormous potential. In the face of growing environmental affairs, IoT based Industry 4.0 technologies are altering CE practices and existing business models, according to the World Economic Forum. This research investigates the function of IoT-based Industry 4.0 in circular CE practices, as well as their impact on economic and environmental performance, which in turn influences overall organizational performance. China-based enterprises provide information for the study, which includes data from 300 companies. Utilizing a structural equation modeling framework known as partial least squares structural equation modeling (PLS-SEM). The major findings are presented in the study: (I) the IoT significantly improves the activities of the CE; (II) the IoT significantly improves the practices of the CE; and (III) the IoT meaningfully advances the practices of CE (green manufacturing, circular design, remanufacturing, and recycling). Moreover, the findings shows that environmentally friendly business practices help enhance environmental performance of firm, while also stimulating their economic performance; and improved environmental performance has a significant positive influence on firm performance. This research lays the groundwork for contributing nations/companies to attain economic and long-term sustainability goals at the same time by incorporating IoT-based Industry 4.0 technology into CE practices.

Sustainable supply chain visibility assessment and proposals for improvements using fuzzy logic

Purpose

Visibility management is essential to sustainable supply chains (SSCs), allowing the ability to see the chain end-to-end, with opportunities to derive benefits, including competitive advantage. Central to visibility management is visibility assessment and identification of areas for improvement. This paper aims to propose a method of assessing visibility in SSCs and the generation of proposals for improvement.

Design/methodology/approach

A hierarchically structured assessment template is developed that comprises of dimensions, factors and attributes of visibility in SSCs. The template permits the use of linguistic variables. A fuzzy logic approach is adopted to calculate visibility levels and generate improvement areas based on linguistic data captured through the template. An industry-based case study is used to illustrate the process.

Findings

This study reveals that visibility can be measured straightforwardly using the method developed in this paper. It is found that automation and contextual factors can significantly impact visibility levels, so also is sustainability awareness and practices adopted.

Originality/value

This paper describes a visibility assessment model that incorporates linguistic variables, fuzzy logic and the use of an adaptable visibility assessment template. The assessment model can identify potential inhibitors of visibility for SSC under study.

Sustainability in the Civil Construction Sector Supported by Industry 4.0 Technologies: Challenges and Opportunities

The civil construction sector is under pressure to make construction processes more sustainable, that is, aligned with economic, social, and environmental sustainability. Thus, the research question considers: How do Industry 4.0 Technologies help civil construction face challenges and identify new opportunities to become sustainable? The general objective of this work is to offer a current overview of publications that associate the civil construction sector; Industry 4.0 Technologies and sustainability, and identify the challenges and opportunities of the Industry 4.0 Technologies set to contribute to sustainability achievement. The research method was a bibliographic review combined with bibliometric analysis in SCOPUS databases. The results show that civil construction faces the challenge of reducing the consumption of natural resources, ensuring safe work, and optimizing processes, especially handwork. However, the insertion of Industry 4.0 Technologies into civil construction has allowed sensors, robots, modelling and simulation systems, artificial intelligence, and drones to have their productivity, efficiency, safety, strategic and environmental management enhanced. Furthermore, Industry 4.0 Technologies can contribute to civil construction through innovative, sustainable, and technological solutions focused on the flow of work, which can provide growth through the balance of costs/benefits in the management of projects and works. Thus, it is expected that this article will contribute to discussions around the possibility of construction becoming sustainable with the support of Industry 4.0 Technologies.

From resilience to satisfaction: Defining supply chain solutions for agri-food SMEs through quality approach

Since it is an important human need and many organizations are involved in the value chain, the agricultural food supply chain is exposed to various risks that arise naturally or through human actions. This study aims to develop the application of a quality function deployment approach to increase the resilience of the food supply chain by understanding customer needs and logistical risks in the food supply chain. In-depth studies with empirical analysis were conducted to determine the importance of customer needs, food supply chain risks, and actions to improve supply chain resilience of SMEs in the agri-food industry. The result shows that the top three customer needs are "attractive, bright color", "firm texture" and "fresh smell". The top three risks in the agri-food supply chain are "improper storage," "Harvest Failure" and "Human Resource Risks" and the top three resilience actions are "continuous training," "preventive maintenance," and "supply chain forecasting." The implications of this study are to propose an idea that broadens the perspective of supply chain resilience in the agri-food industry by incorporating the needs of customers in considering how to mitigate the existing risks to the satisfaction of customers, and it also highlights the relatively low skill and coordination of the workforce in agri-food supply chains.

Business Models for the Internet of Services: State of the Art and Research Agenda

The relevance of the Internet of Services (IoS) comes from the global reach of the Internet into everyone’s home and daily activities and from the move from a manufacturing-based economy to a service-based economy. The IoS is seen as a new ecosystem where service providers and consumers explore their business networks for service provision and consumption. The scientific literature refers to IoS as an important cornerstone for Industry 4.0 and Future Internet; thus, it becomes relevant to study how IoS interacts with business models. Nevertheless, there is a lack of clarity on such an intersection. Moreover, a systematic review of IoS-based business models is still missing. This paper aims to make a systematic review of IoS-based business models and their application fields. We included studies from Scopus and Web of Science databases, we excluded duplicated papers and short conference versions of the later full paper journal publications. Twenty-three different studies are presented, categorized in the sub-areas of IoS, and then by the fields of applications. The main finding highlights the opportunities of IoS applications in different fields, offering directions for future research on this new arena.

Food system resilience thinking: from digital to integral

The current food system is directly influenced by the increase in environmental problems and nutritional inequality globally. Financial and political collapses, health crises, excessive urbanization, and rapid industrialization are some of the principal factors threatening the food supply's security. The food system needs a profound transformation to avoid ecosystem destabilization and a global food crisis. Concerning this transformation, we are certain that the first step for a successful food system change is global resilience thinking. To reach an integrated food system, we proposed introducing the resilient concept linked with other known concepts, such as circular economy and sustainability. A resilient food system can recover over time, ensuring the supply of sustainable and quality food and access to all. This would mean redesigning the value chains in the food system, re-educating consumers to implement a healthier diet, and introducing technology such as digital innovation. Re-evaluating these relevant points, redesigning the focus of the food system, not only for economic efficiency but also including significant trade-offs, or valuing other services in the food system, are essential to reaching the desired resilience. © 2021 Society of Chemical Industry.

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.