Fresh Produce Supply Chain Research Articles

Minimization of losses in postharvest of fresh produce supply chain

PurposeGlobalization and population explosion have worsened postharvest losses (PHL) in developing countries. This study looks to identify numerous controllable variables to reduce these losses and make the fresh produce supply chain more efficient.Design/methodology/approachThe study employs the interpretive structural modelling (ISM) technique to develop a hierarchical model to comprehend the intricate relationships between the variables influencing PHL. These variables are further classified based on the relative levels of importance in terms of their driving and dependence powers.FindingsThe findings of this research provide variables for enterprises operating in fresh food supply chains to understand the specific risks that that supply chain faces and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the supply chain to aid implementation of PHL mitigation measures. The study highlights the importance of devising policies, legislation and efforts to regulate and curtail PHL across the global food supply chain.Research limitations/implicationsThe efficiency of the food supply chain contributes not only to economic sustainability but also to broader goals such as food security, better utilisation of global resources and sustainability in the supply chain.Social implicationsIt also highlights the significance of well-informed government policies, laws and regulations in successfully controlling and reducing PHL.Originality/valueThis study compares factors contributing to PHL in the fresh produce supply chain and emphasises the stakeholders’ critical role in alleviating these losses. It also highlights the significance of well-informed government policies, laws and regulations in successfully controlling and reducing PHL.

Adoption challenges of environmental monitoring practices: case study of temperature data loggers in selected Australian vegetable supply chains

Temperature monitoring across cold chain practices is an integral component of fresh produce supply chains. Numerous temperature data loggers (TDLs) are available to reduce the significant amount of food loss and waste (FLW) (equivalent to around 50%) in vegetable supply chains; however, its widespread adoption remains a challenge for the actors along the chain. This study seeks to understand the adoption of TDLs within selected Australian vegetable supply chains to address the challenge of FLW. Three representative cases of vegetable supply chains were purposively selected, including growers, packers, transporters, distribution centres along with technology providers, and industry experts. Data were collected through semi-structured interviews and analysed utilising thematic analysis. The findings indicate that members of vegetable supply chains recognise temperature management as one of the key factors for preserving quality and extending shelf life of their produce; however, they are not proactively seeking to utilise TDLs in their supply chain operations. Resistance to adoption of TDLs is deeply rooted in product-based challenges such as cost and compatibility, and process-based challenges including information sharing and product mixing. Additionally, presence of an individual’s undesirable behavioural aspects such as status-quo bias and responsibility shirking as well as prevailing social norms within the industry influence the adoption of TDLs.

Study on Optimizing Inventory to Minimize Waste in the Fresh Produce Supply Chain

Abstract: The increasing demand for fresh produce, particularly greens, presents unique challenges in inventory management due to their short shelf life and susceptibility to spoilage. Inefficient management often results in significant waste, leading to financial losses for retailers and increased environmental burdens from the disposal of spoiled goods. Despite various strategies being employed in the agri-food sector, gaps remain in understanding how to optimize inventory levels to minimize waste at the retails level while maintaining high service levels for customers. This research aims to develop an inventory management model tailored to fresh produce that can mitigate these issues by balancing stock availability and minimizing wastage, particularly in large retail shops. To address the research problem, a mixed-integer linear programming (MILP) model was developed, focusing on three service levels—90%, 92%, and 95%—to evaluate the trade-offs between customer satisfaction and total inventory costs. The model incorporates key constraints, including stock balance, shelf-life limitations, and demand satisfaction. The model was validated using actual data, including stock, sales, and wastage records for the month of August, 2024. The objective function aimed to minimize total costs, encompassing holding costs, wastage, and lost revenue. The findings indicate that higher service levels, while reducing stockouts, significantly increase costs due to excess inventory and waste. The most cost-effective solution was observed at the 90% service level, which balanced waste reduction and customer satisfaction. The study also emphasizes the importance of integrating total cost reduction and minimize wastage. Future work should focus on incorporating consumer behavior patterns and extending the model to multi-echelon inventory systems, which include both distribution centers and retail outlets, to capture a more holistic view of the supply chain.

Supply chain network equilibrium with outsourcing for fresh agricultural products under stochastic demands

Abstract Accepted by: M. Zied Babai This paper examines a supply chain network focusing on the distribution of fresh agricultural products, incorporating outsourcing and stochastic demands considerations. Initially, we establish a generalized Nash equilibrium model with stochastic demands among fresh produce firms. Subsequently, we transform this model into a mixed complementarity system using the Karush–Kuhn–Tucker conditions. Utilizing the Fischer–Burmeister function, we further convert the mixed complementarity system into a set of nonlinear equations, amenable to solution via GAMS software. We conduct numerical experiments and perform sensitivity analysis on key parameters. Our findings suggest that higher subsidy rates incentivize firms towards production outsourcing, particularly benefiting low-income farmers, thereby potentially increasing profits. Moreover, market fluctuations play a pivotal role in ensuring the stability and profitability of firms, with moderate fluctuations presenting opportunities for fresh enterprises to adapt, innovate and capitalize on evolving market conditions. These results offer valuable insights for effective management of fresh produce supply chains.

The improvement strategy of fresh produce supply chain resilience based on extenics.

Nowadays, the world is in turmoil, climate and environmental problems are prominent, the import and export of fresh agricultural products are restricted, etc. The impact of the growing demand for fresh agricultural products and healthy lifestyle choices, and fresh agricultural products are essential for people's daily life, which are perishable, fragile, seasonal, and other unstable factors. Therefore, when the fresh produce supply chain faces various pressures and difficulties, how to enhance the resilience of the supply chain against various problems and risks with flexible and multi-dimensional strategies and methods has become the focus of extensive attention. This kind of problem is a typical contradictory problem, and previous studies have failed to achieve good results. In this paper, based on extenics, we are able to one-dimensionalise the multi-dimensional contradictory problems and multi-dimensionalise the one-dimensional contradictory problems to solve such problems in a scientific and effective way. Firstly, taking fresh agricultural products supply chain enterprise M as the research object, we constructed the fresh agricultural products supply chain enterprise toughness system and identified the toughness state of each index. Secondly, we found the low-evaluation toughness indexes that need to be solved and constructed a extension model of incompatible problems of enterprise toughness. Thirdly, we analysed the objectives and conditions of toughness incompatible problems of fresh agricultural products supply chain enterprises numerically and quantitatively, and then, with the objective of toughness improvement, we analyzed the correlation of the condition basic-elements of incompatible problems and carried out extension transformations. Again, the objectives and conditions of the incompatible problems of fresh produce supply chain enterprises are analysed numerically and quantitatively, and with toughness enhancement as the objective, the correlation analysis and extension transformation of the condition basic-elements of the incompatible problems are implemented to generate the set of toughness enhancement strategies that can solve the incompatible problems in a multidimensional and scientific way. Finally, the optimal toughness enhancement strategies are selected through the superiority evaluation and composed into a new strategy to enhance the toughness of the fresh produce supply chain. Combined with extenics calculations and screening, a new strategy for supply chain resilience enhancement of fresh agricultural products was finally formed. The existing problems are solved from six aspects: product supply type, product demand, product supply efficiency, human resource quantity, production and processing equipment, and logistics guarantee ability. It provides a certain reference significance for the fresh agricultural products supply chain toughness enhancement, and helps enterprises to strengthen their competitiveness and sustainability through the enhancement of toughness.

An Operations Optimisation Model for Fresh Food Produce Supply Chain Considering Time-Varying Freshness and Consumer Utility

An Operations Optimisation Model for Fresh Food Produce Supply Chain Considering Time-Varying Freshness and Consumer Utility

Opportunities for Prediction Models to Reduce Food Loss and Waste in the Postharvest Chain of Horticultural Crops

Significant losses occur in the fresh produce supply chain, spanning from the harvest to postharvest stages, with considerable wastage during production and consumption. Developing predictive models for overall postharvest losses is crucial to inform growers and industry stakeholders, facilitating better decision-making and resource management. These models play a pivotal role in supporting governments, as well as global food and agricultural organizations, in their efforts to alleviate poverty and ensure food and nutrition security for the growing human population. This review discusses opportunity targets for predicting total postharvest losses and addresses strategies for effective waste management with the aim of promoting sustainable agricultural production and enhancing global food security.

Optimizing traceability scheme in a fresh product supply chain considering product competition in blockchain era

Fresh product traceability plays an integral role in ensuring food safety. Recently, many firms have introduced blockchain technology (BCT) for product traceability to guarantee product authenticity and consumer rights. However, introduction of the new technology has also intensified the competition among fresh products. Meanwhile, previous studies on traceability strategies only considered the impact of traceability cost and ignored the issue of increased product competition in blockchain era. Driven by these problems, we build a game-theoretical model to analyze the optimization of traceability schemes for both low-end fresh products (LEFP) and high-end fresh products (HEFP) in a fresh product supply chain (FPSC) in a competitive environment. Moreover, this paper investigates the impact of power structure on traceability schemes and identifies the conditions under which one scheme outperforms the others. We find that the cost per unit of product input has no effect on the traceability decision of the FPSC. Nonetheless, the introduction of BCT increases the number of consumers who choose LEFP and raises the selling price and wholesale price of corresponding products. Finally, from the supply chain perspective, it is best to adopt the same traceability scheme for both products. This study sheds light on the use of BCT in traceability can provide enhanced product authenticity and consumer rights while increasing product competition and demonstrates the significance of traceability schemes in the FPSC.

Dormancy of pathogenic bacteria in the fresh produce supply chain

The increased consumption of fresh produce in the last decades has led to an escalation in the number of associated foodborne outbreaks. Various stressful conditions along the fresh produce supply chain can induce bacteria to enter a dormancy state, such as the persistence state and the viable but nonculturable (VBNC) state. Bacteria can develop an increased tolerance to a range of environmental stresses in the dormancy state and return to their normal growing state when conditions become favorable, leading to foodborne illnesses. This review will explore how bacteria contaminate fresh produce along the supply chain and the conditions that can promote the formation of dormant cells. Additionally, various options for detecting and eradicating dormant bacterial cells in the fresh produce supply chain will be discussed.

Fresh product supply chain coordination using vendor managed inventory and consignment with revenue sharing over a finite planning horizon

Fresh product supply chain coordination using vendor managed inventory and consignment with revenue sharing over a finite planning horizon

Implementing Ireland’s Food Vision 2030 within the Fresh Produce Sector: An Investigation of the Barriers and Enablers Using Systems Thinking Principles

The Irish Food Vision 2030 (IFV 2030) seeks to restructure Ireland’s agricultural food system to deliver long-term social, economic, and environmental sustainability in keeping with its commitment to the European Green Deal and the 2030 Sustainable Development Goals. This study investigates the effectiveness of the IFV 2030 in delivering on this commitment across the fresh produce supply chain in Ireland using a combination of data collected from stakeholders through a survey and systems thinking principles. A review of the literature and Foucault’s genealogical methods guided the development of the survey. Systems thinking principles were used to review the IFV 2030 and assess its capacity to deliver large-scale change for a sustainable Irish food system. Barriers to change were identified, including historical patterns of behaviour between EU and Irish policymakers that have repeatedly hindered progress towards large-scale change events. The results demonstrate that successful, long-term change will depend on the involvement and incentives of stakeholders within the supply chain. Continuous stakeholder engagement is required through a bottom-up organisational and supply chain approach to deliver long-term sustainability within the fresh produce sector. Using a systems thinking lens brings benefits through transdisciplinary collaboration and fosters the multiple stakeholder perspectives needed to deliver new ideas and solutions.

Determining the optimal food hub location in the fresh produce supply chain

Purpose Using recent US regional data associated with food system operations, this study aims at building optimization and econometric models to incorporate varying influential factors on food hub location decisions and generate effective facility location solutions. Design/methodology/approach Mathematical optimization and econometric models have been commonly used to identify hub location decisions, and each is associated with specific strengths to handle uncertainty. This paper develops an optimization model and a hurdle model of the US fresh produce sector to compare the hub location solutions between these two modeling approaches. Findings Econometric modeling and mathematical optimization are complementary approaches. While there is a divergence between the results of the optimization model and the econometric model, the optimization solution is largely confirmed by the econometric solution. A combination of the results of the two models might lead to improved decision-making. Practical implications This study suggests a future direction in which model development can move forward, for example, to explore and expose how to make the existing modeling techniques easier to use and more accessible to decision-makers. Social implications The models and results provide information that is currently limited and is useful to help inform sustainable decisions of various stakeholders interested in the development of regional food systems, regional infrastructure investment and operational strategies for food hubs. Originality/value This study sheds light on how the application of complementary modeling approaches improves the effectiveness of facility location solutions. This study offers new perspectives on elaborating key features to encompass facility location issues by applying interdisciplinary approaches.

An OGSM-based multi-objective optimization model for partner selection in fresh produce supply chain considering carbon emissions

Incorporating partner selection with environmental commitment is recognized as a crucial aspect of green development in fresh produce supply chains. This paper presents a multi-objective programming (MOP) model for partner selection considering carbon emissions based on the ‘Objectives, Goals, Strategies, Measures’ (OGSM) framework. The OGSM serves as a strategic scheme to identify the long-term green development vision of a supply chain, ensuring that the activities of supply chain partners are aligned with common goals. Driven by the OGSM design, the MOP model is formulated with three conflicting objective functions to maximize profit, minimize carbon emission, and maximize the quality of fresh produce. The model helps decision-makers address decisions on partner selection with determined logistics volumes, transportation modes and packaging types under carbon emission constraints. To tackle the NP-hard problem, we develop an effective hybrid meta-heuristic algorithm called ɛ-NSGA, which complements the advantages of the ɛ-constraint method and NSGA-II (Non-dominated Sorting Genetic Algorithm-II). The experimental results based on parameter calibration of the Taguchi method and the Kruskal–Wallis test demonstrate that the proposed ɛ-NSGA outperforms other four heuristic algorithms in terms of the performance indices of GD (Generational Distance), spacing, IGD (Inverted Generational Distance), and HV (Hyper Volume). The implementation of the OGSM-MOP together with ɛ-NSGA in a real-world apple supply chain illustrates the effectiveness and practicality of the model. Finally, managerial insights into the utilization of the model are discussed and suggestions for decision-making to fulfill corporate environmental obligations are provided.

Fresh produce supply chain network design and management using swarm intelligence: A case study of Egypt

Fresh produce supply chain network design and management using swarm intelligence: A case study of Egypt

Research on dynamic pricing and coordination model of fresh produce supply chain based on differential game considering traceability goodwill

This study aims to solve the current pricing and coordination problems in the fresh produce supply chain by proposing a dynamic pricing and coordination differential game model based on traceability goodwill to optimize the operational efficiency and profitability of the supply chain. Freshness and traceability are critical consumer trust and brand value factors incorporated into the dynamic pricing and coordination model in the agricultural supply chain. The research methodology of this paper integrates critical factors such as supply chain cost and market demand to construct a comprehensive differential game model. It also highlights the motivation of dynamic pricing strategy and coordination mechanism based on traceability goodwill. Through traceability goodwill, operating companies can better assess and manage product quality and improve consumer trust in agricultural products, thus enhancing brand value. The dynamic pricing strategy based on traceability goodwill can flexibly adjust prices according to changes in the quality characteristics of agricultural products and market demand, realizing a dynamic balance between supply and demand. On the other hand, the mutual cost-sharing and coordination mechanism promotes the synergy between the various links of the supply chain. It improves overall efficiency through cooperation coo, coordination, and other means. The validity and reliability of the model are verified through numerical simulation experiments. The numerical simulation results show that the dynamic pricing and coordination model based on traceability will significantly improve supply chain efficiency and profitability compared with the traditional model. Specifically, the interests of supply chain participants are balanced, and the overall supply chain operational efficiency is improved. The main contribution of this study is to propose a dynamic pricing and coordination model based on traceability goodwill and verify its superiority through numerical simulation experiments. This study provides a valuable reference for fresh agricultural products supply chain management and offers new ideas for improving supply chain efficiency and profitability.

Towards a risk-based food safety management system in the fresh produce supply chain in Da Nang, Viet Nam

Food safety has emerged as a paramount concern for both Vietnamese consumers and the government. However, limited data are available on food safety management systems in Viet Nam. This study identified significant gaps in good agricultural and hygienic practices along the fresh produce chain (farmers and traditional wholesalers/market sellers) in the region of Da Nang, Viet Nam. This was achieved through a survey on good agricultural and hygienic practices for farmers (n = 100) and sellers (n = 100), which researchers further supplemented by microbiological analysis for E. coli, Salmonella spp., and Listeria monocytogenes on leafy greens, water in contact with produce and contact surfaces (hands). The results indicated that 86.0 % of farmers and 54.0 % of sellers received food safety training in the last 3 years; and women dominated both vegetable cultivation but also trading. Farm-level deficiencies included inadequate handwashing practices, lack of documentation for manure application schedules, improper washing and drying of harvest tools, failure to keep containers elevated off the ground, improper storage of vegetables, and inadequate covering of containers, with respectively 34.0 %, 30.3 %, 12.1 %, 41.7 % and 7.9 % of farmers executing the practice as prescribed by the WHO/FAO ‘5 keys of growing safer fruits and vegetables’. As for sellers, the most dominant gaps (<50.0 % compliance) were the way of handwashing and the practice of keeping containers elevated off the ground before, during, and after harvesting. The microbiological analysis confirmed that, in a total of 36 fresh produce samples including mustard greens, cucumber, lettuce, and crown daisy, the number of samples positive for E. coli, Salmonella spp., and L. monocytogenes were 12, 2, and 10 respectively. Samples of hands and the irrigation water showed high contamination with E. coli. Based on identified gaps, risk communication tools were developed and distributed amongst farmers, sellers, and Da Nang food safety management authority (governmental organisation performing inspections in the traditional food markets). As intervention, two farmers and two sellers were trained in safe agricultural practices for the cultivation of fresh vegetables (managerial intervention) and instructed to use tap water as irrigation water instead of uncontrolled surface water (technological intervention). A post-assessment was conducted, including redoing the survey on good practices and microbiological analysis. The outcome of these interventions showed positive results in terms of good agricultural and hygienic practices resulting in improved hygiene levels and safety of the fresh produce. The findings from this research have the potential to provide a model for the development of a science-based risk management strategy in alternative food chains or geographic areas in emerging countries.

Social Sustainability Risk Assessment of Fresh Produce Supply Chain in China under Computer Technology and Digital Transformation

This paper investigates the social sustainability risks in China’s fresh produce supply chain amid ongoing digital transformation. As computer technologies reshape supply chain operations, understanding and mitigating associated social risks become paramount. This research aims to provide a comprehensive assessment of these risks, examining factors such as data and cyber security, inequality, and ethical sourcing concerns. Ten social risk criteria are identified through literature review and expert opinion. In a Sichuan case study, by integrating hybrid methodology Fuzzy Failure Modes and Effects Analysis (FMEA) and Fuzzy VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje), Data Privacy and Security Risks (SR1) stands out as the most critical risk criterion in the supply chain with the highest Q value, followed by Ethical Use of Technology (SR4) and Digital Dependency (SR5). This paper offers insights into how stakeholders can navigate the intersection of digitalization and social sustainability to foster more resilient and equitable fresh produce supply chains.

Physiological Processes Affecting Postharvest Quality of Fresh Fruits and Vegetables

Fresh fruits and vegetables are integral components of a balanced diet, providing essential nutrients and contributing to human health. However, the postharvest quality of these perishable commodities is greatly influenced by various physiological processes that occur after harvest. This article reviews the key physiological processes affecting postharvest quality, including respiration, transpiration, ripening, senescence, and enzymatic activity. Understanding these processes is crucial for optimizing postharvest handling practices to extend shelf life, maintain quality attributes such as texture, flavor, color, and nutritional content, and minimize losses. Strategies to manage these physiological processes, including temperature and humidity control, modified atmosphere packaging, and the use of postharvest treatments, are discussed. Additionally, emerging technologies and innovative approaches for enhancing postharvest quality and extending the storage life of fresh fruits and vegetables are highlighted. By elucidating the complex interplay of physiological factors influencing postharvest quality, this review aims to provide valuable insights for researchers, practitioners, and stakeholders involved in the fresh produce supply chain, ultimately contributing to the promotion of food security and sustainability.

Microbiological quality of irrigation water on highly diverse fresh produce smallholder farms: elucidating environmental routes of contamination.

To evaluate the microbiological safety, potential multidrug-resistant bacterial presence and genetic relatedness (DNA fingerprints) of Escherichia coli isolated from the water-soil-plant nexus on highly diverse fresh produce smallholder farms. Irrigation water (n=44), soil (n=85), and fresh produce (n=95) samples from six smallholder farms with different production systems were analysed for hygiene indicator bacterial counts and the presence of shigatoxigenic E. coli and Salmonella spp. using standard microbiological methods. Identities of isolates were confirmed using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), and the genetic relatedness of the E. coli isolates determined using enterobacterial repetitive intergenic consensus polymerase chain reaction (ERIC-PCR) analysis. Irrigation water E. coli levels ranged between 0 and 3.45 log MPN/100 ml-1 with five farms having acceptable levels according to the World Health Organization limit (3 log MPN/100 ml-1). Fresh produce samples on four farms (n=65) harboured E. coli at low levels (<1 log CFU/g-1) except for one sample from kale, spring onion, green pepper, onion, and two tomato samples, which exceeded international acceptable limits (100 CFU/g-1). Only one baby carrot fresh produce sample tested positive for Salmonella spp. Of the 224 samples, E. coli isolates were identified in 40% (n=90) of all water, soil, and fresh produce types after enrichment. Additionally, the DNA fingerprints of E. coli isolates from the water-soil-plant nexus of each respective farm clustered together at high similarity values (>90%), with all phenotypically characterized as multidrug-resistant. The clustering of E. coli isolated throughout the water-soil-plant nexus, implicated irrigation water in fresh produce contamination. Highlighting the importance of complying with irrigation water microbiological quality guidelines to limit the spread of potential foodborne pathogens throughout the fresh produce supply chain.

An analysis of Strategies for Adopting Blockchain Technology in Fresh Product Supply Chain Under Freshness Misreporting

The application of blockchain technology can inhibit producers' freshness misrepresentation in fresh produce supply chains. In this paper, we consider consumers with fresh produce freshness information traceability preference. In a fresh produce supply chain with a single producer and a single seller, the seller's blockchain application decision is studied, the Stackelberg game models of the supply chain members in the two scenarios of the producer misrepresenting freshness and the seller applying blockchain are constructed, and the changes of the equilibrium solutions before and after the application of blockchain technology are analysed. The theoretical proofs and numerical simulation studies show that when the transaction cost is at a certain level, the sellers should choose to apply blockchain technology to improve their own revenue, and the level of applying blockchain technology is affected by the consumer's retrospective preference and the cost coefficient of blockchain technology.