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This paper analyzes the consumption of fruits and vegetables (FV) in Senegal by: (1) urban and rural areas; (2) FV types (African-indigenous vs non-indigenous); (3) sources of FV (imports, purchases and own-production).

The authors undertake descriptive and regression analyses on consumption of FV sourced from purchases, own-production and gifts. The data come from primary surveys in 2017/2018 of 6,328 rural and urban households in Senegal.

The analysis showed that FV are important in urban and rural food consumption. A stunning 76% of rural FV consumption is from purchases, showing the importance of FV supply chains even into and among rural areas. Only 12% of national FV consumption is from imports. Most FV consumption in rural and urban areas is now of non-indigenous FV; African-indigenous FV have a minor share.

A limitation of this paper is that it uses a cross-sectional dataset.

There are few national survey-based studies of FV consumption in Africa. This is the first to disaggregate FV consumption between primary versus secondary cities and rural towns, and rural areas close to and far from cities, in such detail regarding types and sources of FV as outlined in the findings. The regressions contribute by including determinants beyond income, including gender, employment, spatiality and education.

This study aimed to the attributes, consequences and personal values that motivate the behavior of consumers of fruits and vegetables (FV) at local markets and how these elements are associated with food safety.

This is a qualitative research that used the laddering in-depth interview technique for data collection. Fifty interviews were conducted with consumers from Minas Gerais, Brazil. From the codification of the interview content, a hierarchical value map was constructed, showing the relationships between the attributes, consequences and values involved in the consumers’ purchasing decision.

Consumers value characteristics related to the origin of the product and the way it is produced and marketed. They seek particular benefits – such as satisfaction with the purchase, care for their health/well-being and safety when consuming food – and social benefits, such as the possibility of contributing to the local economy. Issues related to hygiene, organization, exposure and handling of products were some of the concerns reported by respondents with regard to food safety.

It is worth highlighting the application of the laddering technique itself. Analyzing the predictive validity of the method, there is a propensity for biases linked to possible interference by the researcher, especially in the coding stage of the elements.

This study can be used by producers, marketing professionals and public policymakers to promote FV sold at local markets and to encourage the improvement of food safety practices.

The research points to five consumer segments according to the different motivations that guide their purchase behavior for local FV. In addition, a focus is given to food safety, revealing its importance in the investigated context.

The choice of a sales channel for fresh vegetables is an important decision a farmer can make. Typically, the farmers rely on their personal experience in directing the produce to a sales channel. This study examines how sales forecasting of fresh vegetables along multiple channels enables marginal and small-scale farmers to maximize their revenue by proportionately allocating the produce considering their short shelf life.

Machine learning models, namely long short-term memory (LSTM), convolution neural network (CNN) and traditional methods such as autoregressive integrated moving average (ARIMA) and weighted moving average (WMA) are developed and tested for demand forecasting of vegetables through three different channels, namely direct (Jaivasree), regulated (World market) and cooperative (Horticorp).

The results show that machine learning methods (LSTM/CNN) provide better forecasts for regulated (World market) and cooperative (Horticorp) channels, while traditional moving average yields a better result for direct (Jaivasree) channel where the sales volume is less as compared to the remaining two channels.

The price of vegetables is not considered as the government sets the base price for the vegetables.

The existing literature lacks models and approaches to predict the sales of fresh vegetables for marginal and small-scale farmers of developing economies like India. In this research, the authors forecast the sales of commonly used fresh vegetables for small-scale farmers of Kerala in India based on a set of 130 weekly time series data obtained from the Kerala Horticorp.

Blockchain-based traceability technology (BTT) is an emerging digital technology that claims to have the potential to fulfil the demand for traceability to safeguard fruit safety. Drawing on the technological, organisational and environmental (TOE) framework, this study aims to investigate the perceived facilitators and barriers that influence the behavioural intentions of multiple stakeholders in the Vietnamese fruit supply chain (i.e., farmers, trading enterprises and consumers) to adopt BTT.

This study utilised a qualitative approach of semi-structured in-depth interviews with 60 stakeholders in the Vietnamese fruit supply chain to achieve the research objectives. NVivo 12 was employed to analyse the collected data using content and thematic analysis.

The findings identify several perceived facilitators that motivate BTT adoption. These include trust, transparency, business performance, the formation of alliances, consumer awareness of food safety and ethical agricultural practices, fruit branding and the pivotal role of farmers' cooperatives. Meanwhile, the perceived barriers to BTT adoption include a lack of digital literacy amongst the stakeholders, poor organisational culture, the high cost of traceability-enabled products and data privacy and security governance.

This study suggests that technology awareness and perceived facilitators and barriers should be incorporated into the design and deployment of blockchain-based traceability technology in the agri-food supply chain in developing countries.

To the best of the authors' knowledge, this study is the first qualitative paper that attempts to fill the research gap of understanding the perceived facilitators and barriers that influence the intentions of multiple stakeholders in the fruit supply chain to adopt BTT in the context of a developing economy.

Cold supply chain technology is critical for extending the shelf life of perishable leafy green vegetables. This study aims to investigate the concept of managing leafy green products using cold supply chain technology and visualise the findings.

Using expert interviews and data visualisation approaches, this study examines how organisations deal with the complexity of cold supply chain processes and networks. Thematic data analysis was conducted. Two types of software were used to accomplish the research objectives. The first software used AntConc version 3.5.8 with word frequency (N-gram) analysis, whereas the second software, VOSViewer offered co-occurrence network visualisation and cluster analysis.

The findings show that the appropriate design of cold chain technology is critical in ensuring the freshness and quality of leafy green vegetables. The primary goal of managing the complexity of the cold supply chain is to achieve product freshness and energy efficiency. Regardless of the importance of energy efficiency, cold supply chains require warehouse management solutions for transportation and storage.

This study found that proper design and selection of appropriate technology in the cold supply chain have driven the companies to improve the firms’ competitive advantage while delivering the best quality of perishable leafy green food products. In addition, the freshness, quality, safety, and health of leafy green vegetables will be determined by the company’s capacity to handle long-distance transportation and select the appropriate distribution channels and storage. Warehouse management system technology was found to be secondary compared to cold chain technology, although distribution and warehousing practices are critical for supply chain performance.

This study has established the conceptual indicators based on best practices and outcomes for the cold supply chain. This study argued that cold supply chain management and performance should be monitored independently. Furthermore, the theory of technological adoption can be expanded to include product nature as a driver. Finally, this study has established cold chain best practices based on a perishable supply chain perspective. The findings of this study can promote healthy foods to solve zero hunger and achieve sustainable development goals. Although this study demonstrates that technology improves supply chain practises, cold storage and logistics benefit the most from technological advancements. In contrast, non-cold supply chains benefit from technology-driven improvements in performance.

The primary objective of this study is to investigate the application of blockchain technology (BCT) in the agri-food supply chain, focusing on traceability and food safety.

The study employed a semi-structured interview method with representatives from the cherry supply chain to evaluate their awareness and acceptance of BCT's impact. Additionally, the analytic hierarchy process (AHP) was utilized to determine digital investment priorities in supply chain strategies. By applying the supply chain operations reference (SCOR) model framework to the cherry supply chain, the study aimed to address the question “Which process model is suitable for implementing BCT in the agri-food supply chain?”

The global agri-food supply chains are characterized by significant food losses, escalating prices along the chain, and food safety risks. Concurrently, consumer concerns regarding food safety, quality and transparency are on the rise. BCT, with its ability to ensure data integrity, immutability, and seamless tracking of chain movements, presents immense potential as a secure infrastructure in the agri-food supply chain traceability.

The developed analytic framework and the study's findings can be adapted to different sectors and different sub-sectors within agri-food supply chains.

The aim of the study is to systematically map the articles published in the area of organic food value chain. Many articles have been published in various domains of organic food value chain, but no significant study has been found related to the systematic mapping of literature.

This study relies on secondary data. Articles from Scopus and Google Scholar databases between January 1, 1990, and July 10, 2021, have been considered. On the basis of inclusion criteria, 56 articles have been analysed in this systematic mapping study.

This study describes the geographical coverage, the methodologies used, sector/industry-specific context of the articles and scope the for future research. Five clusters were identified through co-occurrence analysis: (1) “organic agriculture and sustainable value chain” (2) “organic farming and food value chain,” (3) “organic value chain and sustainable development,” (4) “organic value chain and environmental impact” and (5) organic value chain and profitability.

The study considers only articles published in Scopus and Google Scholar with some specific keywords related to the value chain and organic food industry. Future studies are encouraged by considering a wide range of keywords with a larger data set.

To the best of the author's knowledge, this study is the first to have a systematic mapping of literature on the organic food value chain.

Collaboration in agricultural value chains (AVCs) has the potential to increase smallholders’ participation in international value chains and increase their benefits from participation. This scoping review explores existing collaboration models among stakeholders of AVCs in developing countries, examines enablers and constraints of collaboration and identifies policy gaps.

We systematically searched three databases, CAB Abstracts, Econlit (EBSCO) and Agricola, for studies published between 2005 and 2023 and included 59 relevant studies on AVC collaboration.

The primary motivations for collaboration are to enhance market access and improve product quality. Key outcomes of collaboration include improvements in farmers’ welfare, market participation and increased production; only a few studies consider improved risk management as an important outcome. Robust support from government and non-governmental entities is a primary enabler of collaboration. Conversely, conflicts of interest among stakeholders and resource limitations constrain collaboration possibilities. Collaboration involving high-value crops prioritizes income increases, whereas collaboration involving staple crops focuses on improving household food security.

This study may have publication bias as unsuccessful instances of collaboration are less likely to be published.

This study is unique in highlighting collaboration models’ characteristics and identifying AVC policy and programmatic areas where private firms, farmers’ groups, local governments and donor agencies can contribute.

Different external supply scenarios faced by the retailers will affect their choice of strategy when supply is disrupted and becomes far less than demand, urgently. This study focuses on analyzing both demand and supply side response strategies to meet customer demand and reduce the impact of the shortage during supply disruptions.

According to the quantity of products that the external market can provide, the external supply scenarios were divided into sufficient-type external supply and learning-type external supply. A two-echelon perishable goods supply chain was analyzed, and three kinds of contingency strategy models for downstream retailers were investigated. First, in the sufficient external supply scenario, the optimal price and transshipment quantity to maximize retailer's profits is discussed. Second, in the scenario of learning-type external supply, this study analyzes the optimal decision in three mechanisms of the hybrid strategy and their application: price priority mechanism, quantity priority mechanism and price–quantity balance mechanism. Furthermore, the influence of penalty cost and supply on the priority orders of different mechanisms was studied.

Results show that comparing the two pure strategies (pricing strategy and transshipment strategy)it was noted that the hybrid strategy produces the best results in sufficient-type external supply scenario. In the learning-type external supply scenario, a numerical study has shown the existence of three areas in case of penalty cost and supplier's capacity, and each areas has different priority orders of the three mechanisms. Under the situation of learning external supply, the retailer's optimal strategy is affected by parameters such as penalty cost and supply volume.

The main innovation of the work lies in the following: First; the external supply situation was divided into sufficiency type and learning type, which improves the external situation faced by retailers after the outbreak of emergencies, helps retailers understand the external situation, conforms to the actual situation and has certain practical application value. Second; in the context of learning external supply, there are three coping strategies for retailers, including: Price priority mechanism, Quantity priority mechanism and Pricing and transshipment balance mechanism. This will help retailers make strategic choices, make more scientific management decisions and improve the supply chain emergency management theory. Third; the demand side response was managed through the change of external supply during supply side recovery period and supply disruption. The proposed model enables managing and analyzing supply disruption efficiently and effectively via handling uncertainty by considering all aspects of decision-making process. The proposed model can be applied in various fields such as vegetable and fruit, fresh food, etc.

Due to the recent disruptions caused by COVID-19, global supply chains are stress tested. The affected supply chains have interfered with market tonnage prices for the yield of perishable products like mangoes that are highly dependent on their quality. This research, through empirical findings, thus determines and comprehends the factors influencing mango quality (size).

A framework is developed for finding the potential factors of quality building on the previous literature and studies on the available topic. The data collection included face-to-face interviews comprising 240 farmers, hired managers and preharvest contractors in India's Jangaon, Rangareddy and Yadadri Bhuvanagiri districts of Telangana state. The data analysis is done using multiple regression, and the outcomes form the basis of the design of the experiments model.

The empirical insights support that the quality of mango is affected by factors such as the number of picking cycles, the cost of fertilizer, the variety of fertilizers used, the variety of pesticides used and pesticide application frequency. The direct implications are the benefit to farmers in improving mango quality and maximizing profit per yield cycle.

To the best of the authors’ knowledge, the first research that has specifically focused on holistically improving the quality(size) of mangoes.

The findings contribute to the perishable supply chain literature, specifically to the mango study, to comprehensively showcase the factors impacting the quality of mangoes and provide guidance to farmers regarding orchard practices.