A Taxonomy of Food Supply Chain Problems from a Computational Intelligence Perspective.

Digitalising food manufacturing

Food and drink supply chains are complex, continually changing systems, involving many participants. They present stakeholders across the food and drinks industries with considerable challenges. Delivering performance in food supply chains offers expert perspectives to help practitioners and academics to improve their supply chain operations. The Editors have identified six key challenges in managing food and drinks supply chains. Each section of the book focuses on one of these important issues. The first chapters consider the fundamental role of relationship management in supply chains. The next section discusses another significant issue: aligning supply and demand. Part three considers five different approaches to effective and efficient process management, while quality and safety management, an issue food companies need to take very seriously, is subject of the next section. Parts five and six review issues which are currently driving change in food supply chains: the effective use of new technologies and the desire to deliver food sustainably and responsibly. With expert contributions from leaders in their fields, Delivering performance in food supply chains will help practitioners and academics to understand different approaches in supply chain management, explore alternative methods and develop more effective systems. Considers the fundamental role of relationship management in supply chains including an overview of performance measurement in the management of food supply chains Discusses the alignment of supply and demand in food supply chains and reviews sales and operations planning and marketing strategies for competitive advantage in the food industry Provides an overview of the effective use of new technologies and those that will be used in the future to deliver food sustainably and reliably

Blockchain: a framework for membership and access

Improving the regional organization of food flow requires an understanding of system constraints. System transformation is necessary if the system is to include regional, independent wholesale food suppliers and to distribute food in an equitable and sustainable manner. Regional suppliers play a pivotal role in overall food system resilience, an emerging issue in wake of the numerous failures in conventional food supply chains exacerbated by COVID-19-related disruptions. Yet alternative supply chains that link local producers with towns and urban centers regionally, represent a small fraction of our nation's food suppliers. They struggle to compete with larger distribution networks that can supply products in-and out-of-season by global procurement. The upper Midwest harbors numerous local and regional food supply chains consisting of farms, processors, trucking companies, wholesalers and other firms that share a commitment to sustainability and local economic development. A constellation of challenges hamper their emergence, however, even as larger scale food supply chains flounder or fail to effectively serve communities. Informed by Donella Meadows's work on leverage points for systemic change, a collaborative, transdisciplinary and systems research effort examined conventional food supply networks and identified key opportunities for shifting food supply chain relationships. System concepts such as stock and flow, leverage points, and critical thresholds helped us to frame and identify challenges and opportunities in the current system. The second and third phase of our collaborative research effort occurred over 4 years (2013–2016) and involved twenty-six people in co-generation of knowledge as a loose-knit team. The team included farmers, supply chain practitioners, students, academic staff and faculty from multiple departments and colleges. Our primary method was to host public workshops with practitioner speakers and participants to identify dominant narratives and key concepts within discourses of different participants in distribution networks. The literature review was iterative, based on challenges, ideas and specific questions discussed at workshops. Our research exposed two meta-narratives shaping the supply chain: diversity and efficiency. In addition to these high-leverage narratives, we identified and examined five key operational thresholds in the Upper Midwest regional food system that could be leveraged to improve food flow in the region. Attention to these areas makes it possible for businesses to operate within environmental limits and develop social structures that can meet scale efficiencies necessary for economic success. We iteratively shared this co-produced knowledge with decision-makers via local food policy councils, local government, and national policy circles with the goal of supplying actionable information. This phased action research project created the environment necessary for a group of food system entrepreneurs to emerge and collaborate, poised to improve system resilience in anticipation of food system disruptions. It forms the basis for on-going research on food flow, regional resilience, and supply chain policy.

Artificial intelligence (AI) applications include pattern recognition, events predictions, optimisation and generation of recommendations, to name a few. AI works over data, for example, produced by different sub-systems that comprise a food supply chain (FSC), such as in farms, food industries, distribution centres and retail stores, collected as food product transactions occurrences or by sensoring tools, equipment and solutions across the FSC. The adoption of AI in the FSC, along with technologies, such as Industry 4.0, the Internet of Things (IoT), the GS1 labelling schemes and other emergent technologies, such as blockchain, provides a basis for integrating the food value chain by sharing FSC transactions via a distributed trustworthy platform which potentially enables the realisation of the circular food supply chain (CFSC). This chapter describes the CFSC concept, features, value propositions, requirements, the technologies and systems for supporting it, and applications of AI in food quality and supply chain optimisation.

Cutting edge technologies to end food waste

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.

Food losses and waste (FLW) reduction and mitigating climate impact in food chains are priorities in achieving sustainable development goals. However, many FLW-reducing interventions induce additional greenhouse gas (GHG) emissions, for example, from energy, fuel, or packaging. The net effect of such interventions (expressed in GHG emissions per unit of food available for consumption) is not obvious, as is illustrated in a number of case studies. We recommend that in the decision to take on FLW-reducing interventions, the trade-offs on sustainability impacts (such as GHG emissions) are taken into consideration. Since FLW induce demand and extra operations in all stages along a supply chain, adequate representation of cumulative GHG emissions along the production and supply chain, including ‘hidden parts’ of the chain, is required, which is challenging in full LCA studies. As a workaround, the case studies in this paper are based on a generic tool, the Agro-Chain greenhouse gas Emission (ACE) calculator that includes metrics and data for common food product categories and supply chain typologies. The calculator represents the structure of a generic (fresh food) supply chain and offers data sets for, amongst others, crop GHG emission factors and FLW in different stages of the production and distribution chain. Through scenario calculations with different chain parameters (describing pre and post-intervention scenarios), the net effects of an intervention on GHG emissions and FLW per unit of food sold to the consumer can be compared with little effort. In the case studies, interventions at the production stage as well as in post-harvest operations, are analyzed. Results show that post-harvest activities (especially FLW) contribute substantially to the carbon footprint of supplied food products. The FLW-reducing interventions are considered to induce additional GHG emissions. In most case studies, FLW-reducing interventions lower total GHG associated with a unit of food supplied to a client or consumer. However, in one case study, the extra emissions due to the intervention were higher than the prevented emission from lowering food losses. Consequently, in the latter case, the intervention is not an effective GHG emission reduction intervention.

Chapter 4 - Food and beverage industry supply chains

PurposeFood supply chain resilience is a critical aspect in ensuring the continuous and reliable flow of food, particularly in the face of disruptions. This study aims to address specific gaps in the existing literature by conducting a bibliometric analysis. The primary objective is to identify key areas of concern and lacunae related to disruptions and resilience within the food supply chain. The study also strives to contribute to the field by developing a comprehensive framework that evaluates the factors influencing resilience. Furthermore, the research intends to propose effective strategies for mitigating and recovering from disruptions, emphasizing the urgency of these measures in light of identified gaps in the current body of literature.Design/methodology/approachTo achieve these objectives, the authors extracted the most relevant papers from Scopus and Web of Science (WoS) databases. The analysis parameters included a comprehensive review of current food supply chain practices and an exploration of trending research topics, such as sustainability, adaptability, circular economy and agility. Notably, the study recognized the pervasive impact of COVID-19 on food supply chain disruptions, with a high occurrence in the literature. Using advanced analytics tools like VOSviewer and Biblioshiny, the research delved into the role of modern technologies, including Industry 4.0, the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML) and blockchain in addressing disruptions and enhancing resilience.FindingsThe research reveals a significant impact of the COVID-19 pandemic on food supply chain disruptions, underscoring the critical need for strategies to bolster resilience. Notably, the study identifies the pivotal role of modern technologies (Industry 4.0, IoT, AI, ML and blockchain) in mitigating disruptions and enhancing resilience in the food supply chain. The bibliometric analysis conducted through VOSviewer and Biblioshiny provides valuable insights into research trends and focal areas within the literature.Practical implicationsThe observed importance of Industry 4.0, IoT, AI, ML and blockchain implies a practical need for integrating these technologies into food supply chain operations. Moreover, the paper discusses strategies for reducing the impact caused by disruptions, providing practical guidance for resilience planning in food supply chains. Researchers can leverage the findings to direct future efforts toward areas with identified gaps and opportunities, fostering advancements in the field and offering practical insights for real-world applications.Originality/valueBy amalgamating insights from bibliometric analysis and the developed framework, this study contributes to a holistic understanding of the challenges and opportunities in fortifying the resilience of the food supply chain. The identified factors and strategies offer valuable insights for researchers and practitioners seeking to address disruptions in food supply chains. The study’s unique contribution lies in bridging theoretical perspectives with practical applications, enhancing the relevance of business-to-business/industrial supply chain theories.

In recent years, food traceability has become one of the emerging applications of Blockchain to strengthen the aspects of anticounterfeiting and quality control. This paper intends to suggest a methodology to improve traceability and transparency in food production and supply chain using Blockchain and the Internet of Things (IoT). Typical methods of the supply chain have loopholes, which are misused by antisocial groups to distribute unhygienic substandard food products. Blockchain technology guarantees the source of origin to a customer and enables traceability, tracking, and transparency which assists to increase accountability in the food production industry by confirming customer safety and protection, developing confidence, and enhancing the quality of service.KeywordsBlockchainFood productionSupply chainIoT edgeTransparencyTraceability

Connecting food supply chains

Severe injuries from product movement in the U.S. food supply chain

Global food security is under significant threat from climate change, population growth, and resource scarcity. This review examines how advanced AI-driven forecasting models, including machine learning (ML), deep learning (DL), and time-series forecasting models like SARIMA/ARIMA, are transforming regional agricultural practices and food supply chains. Through the integration of Internet of Things (IoT), remote sensing, and blockchain technologies, these models facilitate the real-time monitoring of crop growth, resource allocation, and market dynamics, enhancing decision making and sustainability. The study adopts a mixed-methods approach, including systematic literature analysis and regional case studies. Highlights include AI-driven yield forecasting in European hydroponic systems and resource optimization in southeast Asian aquaponics, showcasing localized efficiency gains. Furthermore, AI applications in food processing, such as plasma, ozone and Pulsed Electric Field (PEF) treatments, are shown to improve food preservation and reduce spoilage. Key challenges—such as data quality, model scalability, and prediction accuracy—are discussed, particularly in the context of data-poor environments, limiting broader model applicability. The paper concludes by outlining future directions, emphasizing context-specific AI implementations, the need for public–private collaboration, and policy interventions to enhance scalability and adoption in food security contexts.

The study aims to provide a comprehensive, sustainable, and technologically advanced traceability model that enhances the safety and resilience of the food supply chain in Oman. It also seeks to create a framework for enhancing safety and resilience in the supply chain. This framework will influence other regional supply chains to embrace food traceability and contribute towards global food safety and sustainability efforts. This study followed a positivist research philosophy and used the quantitative research approach. A structured questionnaire was administered online to collect data from 385 respondents. To improve the reliability of the research instrument, a pilot test was conducted. Respondents were selected using a snowball technique. The results were tested using structural equation modelling. The results showed that compliance can improve food safety performance through data accuracy and timeliness in food supply chains in Oman. It was also found that technology traceability systems can improve food safety performance through collaborative supply chain relationships in food supply chains in Oman. Additionally, the research showed that technology traceability systems, through cooperative supply chains, enhance sustainable practices. The integration of technology traceability systems and regulatory compliance are significant elements that foster cooperation and bolster food safety and sustainability. The study holds significant implications for various stakeholders within Oman’s food industry and broader applications in similar contexts. With broader implications for the global food sector, the study offers a comprehensive framework for improving Oman’s food safety and supply chain resilience. Adopting such models can result in notable gains in economic efficiency, sustainability, consumer trust, and regulatory compliance. Oman can fortify its food business and serve as a model for other nations by utilising cutting-edge technologies and encouraging cooperation among stakeholders.