Food Supply Chain Management Research Articles

An RFID-Powered Multisensing Fusion Industrial IoT System for Food Quality Assessment and Sensing

The development in Internet of Things (IoT) have empowered revolution in almost all walks of life. Although substantial effort has been made to bring IoT in manufacturing, there is still technical challenges of providing solutions of real-time pervasive multi-sensing, quality evaluation and boundary-less information sharing, which put people at risk from deteriorated food products and food adulteration. This investigation presents an Industrial IoT-based system for food product quality assessment and prediction. This research completes the real-time food quality assessment via radio frequency identification-based multi-sensor fusion for the first time. Also, a novel concept of shelf-life prediction is proposed. The RFID-powered sensors provide a new idea for nondestructive food product and environment sensing. A five-layer architecture considering sensing, controlling, communication, interfaces, and data analysis is highlighted. A novel RFID metadata structure is first proposed to achieve multi-dimensional information traceability and global data sharing. Machine learning-based multi-sensor fusion is proposed to provide accurate quality assessment and prediction. The proposed system is implemented as a smart shelf system to demonstrate its feasibility and advantages. The system is of great significance in improving food safety, reducing food waste and providing powerful information support for food manufacturing line and supply chain management.

Review of technological advancement in food supply chain management: Comparison between USA and Africa

This review paper examines the technological advancements in food supply chain management, drawing a comparative analysis between the United States (USA) and Africa. The global food supply chain plays a critical role in ensuring the efficient and effective distribution of food products from producers to consumers. In recent years, technological innovations have revolutionized various aspects of the food supply chain, impacting areas such as production, distribution, traceability, and sustainability. The paper begins by providing an overview of the key technological trends in food supply chain management, encompassing the adoption of Internet of Things (IoT) devices, blockchain technology, artificial intelligence (AI), and data analytics. These innovations have the potential to enhance transparency, reduce waste, improve traceability, and optimize overall supply chain efficiency. A comparative analysis is then conducted, focusing on the disparities and similarities in the adoption and implementation of these technologies between the USA and Africa. The USA, as a technologically advanced region, has witnessed extensive integration of cutting-edge technologies in its food supply chain. This includes the utilization of IoT sensors for real-time monitoring, blockchain for transparent and secure transactions, and AI for predictive analytics and demand forecasting. In contrast, Africa, characterized by a diverse range of economies and infrastructural challenges, faces unique opportunities and obstacles in embracing advanced technologies in its food supply chain. The review explores initiatives and case studies that highlight the successful integration of technology in various African countries, shedding light on the potential for leapfrogging certain stages of traditional supply chain development. The discussion encompasses the role of government policies, private sector involvement, and international collaborations in shaping the technological landscape of food supply chain management in both regions. Furthermore, attention is given to the social and economic implications of technological advancements, emphasizing the need for inclusive approaches that address the specific needs of diverse communities. This review provides valuable insights into the current state of technological advancements in food supply chain management, offering a comparative perspective between the USA and Africa. By understanding the challenges and opportunities faced by each region, stakeholders can develop targeted strategies to enhance the resilience, sustainability, and inclusivity of global food supply chains in the face of evolving technological landscapes.

A cost-effective over-temperature alarm system for cold chain delivery

Managing over-temperature alarms in cold chain logistics (CCL) is crucial for temperature monitoring systems. However, existing research in this area primarily focuses on improving identification accuracy while overlooking the associated cost implications. This study addresses this gap by proposing a cost-effective over-temperature alarm system using an artificial neural network (ANN) model that integrates multi-source data (MSD). This article demonstrates that utilizing ANN and MSD leads to significantly improved recognition accuracy compared to using single-source data while keeping the cost increase to a minimum. The paper found recognition accuracy to be 97.4% with three feature values and 98.6% with six feature values. Sensitivity analyses reveal that factors such as the initial food temperature, cumulative open time, data acquisition interval, and algorithm significantly impact the recognition accuracy of the over-temperature alarm system. The location of sensors, however, has a slight effect. Furthermore, the choice of the number of feature values and the granularity of the data influences the cost of temperature management and recognition accuracy. This study provides valuable insights into the factors influencing recognition accuracy, aiding in designing cost-effective over-temperature alarm systems for food supply chain management.

Incorporating sustainability in the food supply chain: The development of a private standard of Nature Farming poultry production in Brazil

This article aims to communicate sustainability dimensions and attributes for poultry production throughout a supply chain by developing a Nature Farming (NF) system standard. Poultry production is relevant for food security and job creation, an important economic activity and a significant export item in Brazil. The NF poultry production system was implemented in the 90s as a pioneering initiative, opening space for differentiated products. However, certification of NF poultry products has yet to be established and implemented to reach consumers. The NF products are identified as organic on labels, which does not distinguish the method’s sustainability, and communication of specificities needs to be more efficient. We studied the process of establishing a private food standard with a sustainable approach, considering perceptions of the supply chain's agents. The method was a case study of a poultry company that applies NF system. The qualitative research involved interviews with 27 company managers, 23 poultry producers, seven farm assistance technicians, 11 auditors, and 12 commercial managers. The results showed innovation by introducing a Nature Farming poultry standard comprising product attributes and sustainability criteria in the dimensions: environmental, economic, and social in conjunction with two significant dimensions, which are ethical and health. Our findings indicated that Nature Farming is a specific style of agriculture that is diverse from other currents of alternative agriculture. We proposed expressions and claims about the system’s quality attributes, aiming at the clarity of communication with consumers. We concluded that the developed standard might be the basis for certification of products. This work contributes to improving food supply chain management with differentiated and sustainable processes.

Short food supply chain management with matrices of sets: a new mathematical framework to visualise preferences of consumers’ products basket

Short food supply chain management with matrices of sets: a new mathematical framework to visualise preferences of consumers’ products basket

Domestic retailing, supply chain management, and the rise of fresh food supermarkets in China

This study investigates the emergence of fresh food supermarkets and explores domestic retailers’ fresh food supply chain management in China. The study explores two aspects of supply chain management: procurement and logistics. In line with prior research, the results suggest that domestic retailers’ continuous dominance over international retailers stems from their development of supply chain management. This study demonstrates that endogenous creativity fostered the emergence of fresh food supermarkets. Additionally, it underscores the importance of focusing beyond the transplantation route and Western impact when studying supermarkets in less developed countries.

Tracking and tracing the halal food supply chain management using blockchain, RFID, and QR code

Tracking and tracing the halal food supply chain management using blockchain, RFID, and QR code

Impact of Modified Atmosphere Packaging Conditions on Quality of Dates: Experimental Study and Predictive Analysis Using Artificial Neural Networks.

Dates are highly perishable fruits, and maintaining their quality during storage is crucial. The current study aims to investigate the impact of storage conditions on the quality of dates (Khalas and Sukary cultivars) at the Tamer stage and predict their quality attributes during storage using artificial neural networks (ANN). The studied storage conditions were the modified atmosphere packing (MAP) gases (CO2, O2, and N), packaging materials, storage temperature, and storage time, and the evaluated quality attributes were moisture content, firmness, color parameters (L*, a*, b*, and ∆E), pH, water activity, total soluble solids, and microbial contamination. The findings demonstrated that the storage conditions significantly impacted (p < 0.05) the quality of the two stored date cultivars. The use of MAP with 20% CO2 + 80% N had a high potential to decrease the rate of color transformation and microbial growth of dates stored at 4 °C for both stored date cultivars. The developed ANN models efficiently predicted the quality changes of stored dates closely aligned with observed values under the different storage conditions, as evidenced by low Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) values. In addition, the reliability of the developed ANN models was further affirmed by the linear regression between predicted and measured values, which closely follow the 1:1 line, with R2 values ranging from 0.766 to 0.980, the ANN models demonstrate accurate estimating of fruit quality attributes. The study's findings contribute to food quality and supply chain management through the identification of optimal storage conditions and predicting the fruit quality during storage under different atmosphere conditions, thereby minimizing food waste and enhancing food safety.

Hunger games search optimization with deep learning model for sustainable supply chain management

The supply chain network is one of the most important areas of focus in the majority of business circumstances. Blockchain technology is a feasible choice for secure information sharing in a supply chain network. Despite the fact that maintaining security at all levels of the blockchain is difficult, cryptographic methods are commonly used in existing works. Effective supply chain management (SCM) offers various benefits to organizations, such as enhanced customer satisfaction, increased operational efficiency, competitive advantage, and cost reduction. Potential SCM for agricultural and food supply chains needs distributors, coordination and collaboration among farmers, retailers, and stakeholders. The use of technology like Block Chain (BC), sensors, and data analytics, can boost traceability and visibility, decrease waste, and ensure safety and quality throughout the supply chain. Therefore, this study develops a Hunger Games Search Optimization with Deep Learning Model for Sustainable agricultural and food Supply Chain Management (HGSODL-ASCM) technique. The fundamental goal of the HGSODL-ASCM technique is to improve decision-making processes for agricultural and food commodity production and storage in order to optimise revenue. In the provided HGSODL-ASCM technique, a bidirectional long short-term memory (Bi-LSTM) model is built to determine the amount of productivity and storage required to maximise profit. In order to boost the performance of the Bi-LSTM classification process, the HGSO algorithm has been utilized in this work. The presented HGSODL-ASCM technique can independently achieve the SCM policies via interaction with complicated and adaptive environments. A brief set of simulations were performed to ensure the improved performance of the HGSODL-ASCM technique. The simulation results demonstrated how superior the HGSODL-ASCM method is to other methods already in use.

Evolving water, energy and carbon footprints in China's food supply chain

Food-supply related activities are depleting water resources, wasting energy and aggravating climate change to feed the swelling population. How the water, energy and carbon footprints (WECFs) transfer in the entire food supply chain (FSC) and evolve driven by socioeconomic effects remains elusive. Herein, we propose adapted models of structural path analysis (SPA) and structural decomposition analysis (SDA) specifically for the FSC based on input-output analysis. Beyond evaluating the WECFs in China's FSC induced by household consumption during 2007–2017, we track their transfer through the supply chain, and unravel their key evolutionary characteristics and socioeconomic drivers. With the WECFs increasing in aggregate magnitude, their growth rates decelerate, while the urban household consumption ascends to over 70% of the total household consumption. Except the food sector itself (Agriculture and Food processing), Chemicals and Electricity and heat are the key sectors, whose dominance is weakened by the surging contribution of Transportation and Services. Chemicals → Agriculture → Food processing → Household food consumption is a critical shared path for three footprints. From supply-side perspective, the path length for WECFs is lengthening over time, with a general 5%–8% increase in the share of paths associated with second-order production layers. Increased premium food consumption imposes pressure on the WECFs, which is non-negligible besides per capita consumption effect and intensity effect. The findings inform policies required for synergetic control of WECFs along FSC and optimized decision-making on FSC management.

Review of The Application of Digital Transformation in Food Industry

In recent years, food companies have been facing various challenges related to fluctuating demand and constantly evolving customer and supplier requirements. These challenges have made it necessary for food companies to adapt to new technological advancements and implement new solutions to optimize their manufacturing systems. One such solution is digital transformation, which is a suite of technologies aimed at creating smart ecosystems that can transform industrial processes. Digital transformations are designed to exploit the potential of rapidly advancing information and communication technology (ICT) in the food industry. These include digital tools such as machine learning, artificial intelligence, blockchain, and IoT or the Internet of Things. These technologies have several applications in the food industry, ranging from food supply chain management to food safety, production, and consumption.

Repurposing Food Supply Chain Management for Viability During COVID-19: A Systematic Review

Purpose: The purpose of this study is to examine existing studies on recycled food supply chain management during the COVID-19 epidemic. Theoretical framework: The theoretical framework of the study includes research areas, research agendas, and implications for the viability during the crisis. Design/Methodology/Approach: Mendeley Desktop Software retrieved articles from ScienceDirect.com and Google Scholar. This review included 63 full papers published in 2019–2021. Findings: This review covers food waste management, food safety, insecurity, crises, wellness, food supply chains and chain management, impact on alternative and local food systems, consumption, evaluation of alternative food provision systems, scaling and food policies, proposed business models, strategies, and mechanisms, logistics, economics, and resilience building. The research agendas include refusing, reducing, reusing, repurposing, recycling, and rescaling abandoned or outmoded goods, and rescaling. Implications include food supply chain management, food network viability, impact evaluation, and nutrition risk management. Research, practical, and social implications: This study presents research themes and agendas for adaptive management to ensure viability throughout the COVID-19 outbreak and its long-term impacts. It provides insights into food waste management, food safety, security, insecurity, wellness, food supply networks, chain management, etc. Socially, it offers future studies on outbreak viability, food network vitality, effect evaluation, and nutrition risk management. Originality/Value: In view of the current COVID-19 situation, this study revises food supply chain management. Food supply chain management on a worldwide scale has been impacted by this outbreak. This situation calls for an out-of-the-box solution.

Artificial Intelligence and Deep Learning-Based System for Agri-Food Quality and Safety Detection

Deep Learning (DL) has emerged as a highly effective technique for analyzing large volumes of data across various domains, including image processing, speech recognition, and pattern recognition. Recently, DL has also found applications in the field of food science and engineering, a relatively novel area of research. This paper provides a concise introduction to DL and delves into the architecture of a typical Convolution Neural Network (CNN) structure, as well as AI and IoT (Internet of Things) data training methodologies. Our research involved an extensive review of studies that utilized DL as a computational approach to address food-related challenges, such as food recognition, calorie computation, and safety detection of various food types like fruits, potatoes, meats, and aquatic products, as well as food supply chain management and food borne illness detection. Each study examined different problems, datasets, preprocessing techniques, network architectures, and evaluation metrics, comparing their results with alternative solutions. Furthermore, we explored the role of big data in the field of food quality assurance, uncovering compelling trends. Based on our analysis, DL consistently outperforms other approaches, including manual feature extractors and traditional machine learning algorithms. The findings highlight the tremendous potential of DL as a promising technology for food safety inspections and related applications in the food industry

Towards the Smart Sustainable and Circular Food Supply Chains Through Digital Technologies

Food supply chain management has become a remarkable issue due to the increasing food waste caused by globalization and population growth. It is essential to gain understanding of the drivers of circular economy in food supply chains and investigate stimulating factors in the development of circular food supply chains. Thus, this study conducted a systematic literature review from 2008 to 2020, including an analysis of 137 articles performed on data to answer specific research questions regarding circular food supply chain drivers. Drivers for transition to circular economy in food supply chains are presented in five main categories with 22 sub-drivers. This research contributes to the existing literature by presenting a novel approach to digital transformation in smart food supply chains through the integration of Industry 4.0 technologies. The findings present potential drivers of circular economy in food supply chains for digital transformation. This study also ensures operational efficiencies by digital technologies in food supply chains that can be beneficial for practitioners.

Preface

Proceeding THE 4th INTERNATIONAL CONFERENCE ON FOOD SCIENCE AND ENGINEERING (ICFSE) 2022 11-12 October 2022, Surakarta, Indonesia ICFSE is a biannual conference held by the Department of Food Science and Technology, Faculty of Agriculture, Universitas Sebelas Maret since 2016. This event is in collaboration with partner universities and/or organizations around the world. This conference covers the field of Food Science and Engineering. It aims to drive collaboration between scholars, practitioners, private sectors, and policy makers within the field. The conference is mainly supported by the Department of Food Science and Technology, Universitas Sebelas Maret, Indonesia.This proceeding contains the papers presented in the 4th ICFSE organized in 2022. The papers involve sessions on physical modification of foods, food chemistry and analysis, instrumental techniques for food analysis, food microstructure development and characterization, food properties including thermal, chemical, and mechanical properties, rapid detection of food contamination, macronutrient, micronutrient, and functional properties, chemistry of food additives and preservatives, food processing and engineering, food packaging, sustainable food production, food waste utilization, mathematical modeling and software development for food processing purposes, application of artificial intelligence in food engineering, food supply chain management system and food nutrigenomics for health.We would like to thank all the participants attending this conference and also the committees for their contributions to this conference and its overall success. We would also like to thank the reviewers for their positive contribution to maintaining the quality of the articles presented in this proceeding.List of General Chair, Vice Chair, Organizer, Advisory Boards, Scientific Committees, Organizing Committees are available in this pdf.

STOCKPILING IN A PANDEMIC: HOW COVID-19 HAS CHANGED CONSUMER’S FOOD PURCHASING BEHAVIOUR

COVID-19 pandemic has been a massive disruption to the way of life and has forced people to adapt to new norms and changes in daily activities. The pandemic has also had a significant impact on consumer behaviour, particularly in the way people purchase food. One of the most notable changes observed is the rise in stockpiling behaviour where people are purchasing more food than they would normally need. Based on the literature review, three aspects were recognised as COVID-19 situational factors that could potentially impact consumers’ stockpiling behaviour, namely health and safety concerns, perception of current food product supply, and technological adaptation. To understand the impact of COVID-19 on consumers’ food stockpiling behaviour, this study was conducted among 400 Malaysian consumers through the distribution of questionnaires. The results found that all three factors had a positive and significant impact on consumer stockpiling behaviour. In particular, people became increasingly concerned about the pandemic and the potential for food shortages, and as they became more technologically savvy, they were more likely to purchase food products and stockpile them. This study provides valuable insights into how COVID-19 has affected consumer behaviour in relation to stockpiling food. It is a starting point for understanding how consumer behaviour has been impacted by the pandemic and how it can help shape future strategies for managing food supply and distribution. The findings of the study could be used to inform food supply chain management strategies, particularly in terms of consumer behaviour and demand for food products during the pandemic. Future research could aim to replicate the study in different locations and with larger sample sizes to further understand the impact of COVID-19 on consumer behaviour.

Blockchain enabled food supply chain management: A systematic literature review and bibliometric analysis

Blockchain enabled food supply chain management: A systematic literature review and bibliometric analysis

Blockchain in Food Supply Chain: Benefits, Challenges and Review

Abstract: Blockchain technology has the potential to revolutionize the food supply chain by increasing transparency and traceability. With blockchain, every step of the food supply chain can be recorded and verified, allowing for greater accountability and trust between suppliers, manufacturers, distributors, retailers, and consumers. This study inclines towards the study of blockchain technology in use with food supply chain management. It also mentions the advantages and barriers to use this technology. To better comprehend the development of pertinent study and shed light on the benefits, issues, and difficulties with blockchain technology, there has been a review of the literature and an logical assessment of the supply chain exploration based on blockchain. Several intermediaries, trust issues, and subpar performance are all factors in traditional supply chain operations. Supply chain operations may be disrupted utilizing blockchain technology to enhance performance, disperse governance, and automate procedures. From the standpoint of literature analysis, this study contributes to our understanding of blockchain applications in supply chain management and offers a roadmap for these applications.

Overcoming barriers to implement digital technologies to achieve sustainable production and consumption in the food sector: A circular economy perspective

Food security and waste minimisation are the main concerns for the management of food supply chains (FSC), as >33 % of global food production is wasted or lost due to mismanagement. Stakeholders must address the ongoing issues, such as resource scarcity, climate change, waste creation etc. to create an environment conducive to sustainable production and consumption (SPC) and to promote economic sustainability. Resource efficiency and waste minimization are necessary for SPC in the FSC. Technologies from the Industry 4.0 era have demonstrated their ability to address these problems effectively. However, there are barriers to the adoption of digital technology because of internal or external issues. Therefore, it is necessary to examine the challenges faced by the food industry while applying digital technology to attain SPC. The current study has adopted an integrated methodology of Best-Worst-Method (BWM)-Level Based Weight Assessment (LBWA) and Combined Compromise Solution (CoCoSo) methods to analyse the barriers in implementing digital technologies to achieve SPC in FSC. Strategic measures to overcome these barriers are suggested. The BWM-LBWA-CoCoSo technique is used for the first time in this study to evaluate the barriers and determine the most effective strategies. According to the BWM-LBWA research, “organisational barriers” are the main impediment to the adoption of digital technology for SPC in the FSC. According to CoCoSo findings, the best way to overcome the major barriers is to “focus on improving commitment from senior management towards SPC.” The study gives decision-makers information about the major barriers in utilizing advanced digital technology to achieve SPC in FSC.

Sustainable halal food supply chain management in a small rentier halal market

PurposeThere is limited knowledge of the sustainable halal food supply management in Brunei Darussalam (Brunei), although it is reputable in the halal economy and advocates the United Nations (UN) Sustainable Development Goals (SDGs). Therefore, this paper highlights issues faced in a small, rentier halal market and proposes sustainable supply chain management (SSCM) initiatives for halal-certified food companies in Brunei.Design/methodology/approachThis paper draws data from published academic research and employs a normative and narrative assessment of SSCM and halal supply chain literature.FindingsFour normative SSCM initiatives and propositions that could be implemented by Brunei halal-certified food businesses in achieving the SDGs are highlighted: responsible sourcing, environmental purchasing, sustainable packaging and green transportation.Practical implicationsThis viewpoint paper provides a basis for achieving the “Brunei Vision 2035” through a sustainable supply chain lens that may increase well-being and develop a productive and sustainable economy. It also lays a foundation for realising the SDGs, specifically Goal 12 of Sustainable Consumption and Production.Originality/valueThe dedicated attention to smaller halal markets, such as Brunei, would enrich the literature, reveal unforeseen issues or address gaps in the domains of SSCM and halal food supply chains.