Search Results (66)

Entropy is a foundational concept across scientific domains, playing a role in understanding disorder, randomness, and uncertainty within systems. This study applies Shannon’s entropy in information theory to evaluate and manage complexity in industrial supply chain management. The purpose of the study is to propose a quantitative modeling method, employing Shannon’s entropy model as a proxy to assess the complexity in SCs. The underlying assumption is that information entropy serves as a proxy for the complexity of the SC. The research method is quantitative modeling, which is applied to four focal companies from the agrifood and metalworking industries in Southern Brazil. The results showed that companies prioritizing cost and quality exhibit lower complexity compared to those emphasizing flexibility and dependability. Additionally, information flows related to specially engineered products and deliveries show significant differences in average entropies, indicating that organizational complexities vary according to competitive priorities. The implications of this suggest that a focus on cost and quality in SCM may lead to lower complexity, in opposition to a focus on flexibility and dependability, influencing strategic decision making in industrial contexts. This research introduces the novel application of information entropy to assess and control complexity within industrial SCs. Future studies can explore and validate these insights, contributing to the evolving field of supply chain management. Full article

Computer Vision (CV) has proven to be a powerful tool for automation in agri-food industrial processes, offering high-precision solutions tailored to specific working conditions. Recent advancements in Artificial Neural Networks (ANNs) have revolutionized CV applications, enabling systems to autonomously learn and optimize tasks. However, ANN-based approaches often require complex development and lengthy training periods, making their implementation a challenge. In this study, we explore the use of the Segment Anything Model (SAM), a pre-trained neural network developed by META AI in 2023, as an alternative for industrial segmentation tasks in the table olive (Olea europaea L.) processing industry. SAM’s ability to segment objects regardless of scene composition makes it a promising tool to improve the efficiency of olive pitting machines (DRRs). These machines, widely employed in industrial processing, frequently experience mechanical inefficiencies, including the “boat error,” which arises when olives are improperly oriented, leading to defective pitting and pit splinter contamination. Our approach integrates SAM into n CV workflow to diagnose and quantify boat errors without designing or training an additional task-specific ANN. By analyzing the segmented images, we can determine both the percentage of boat errors and the size distribution of olives during transport. The results validate SAM as a feasible option for industrial segmentation, offering a simpler and more accessible solution compared to traditional ANN-based methods. Moreover, our statistical analysis reveals that improper calibration—manifested as size deviations from the nominal value—does not significantly increase boat error rates. This finding supports the adoption of complementary CV technologies to enhance olive pitting efficiency. Future work could investigate real-time integration and the combination of CV with electromechanical correction systems to fully automate and optimize the pitting process. Full article

Resilient artificial intelligence (Resilient AI) is relevant in many areas where technology needs to adapt quickly to changing and unexpected conditions, such as in the medical, environmental, security, and agrifood sectors. In the case study involving the therapeutic rehabilitation of patients with motor problems, the Resilient AI system is crucial to ensure that systems can effectively respond to changes, maintain high performance, cope with uncertainties and complex variables, and enable the dynamic monitoring and adaptation of therapy in real time. The proposed system integrates advanced technologies, such as computer vision and deep learning models, focusing on non-invasive solutions for monitoring and adapting rehabilitation therapies. The system combines the Microsoft Kinect v3 sensor with MoveNet Thunder – SinglePose, a state-of-the-art deep-learning model for human pose estimation. Kinect’s 3D skeletal tracking and MoveNet’s high-precision 2D keypoint detection together improve the accuracy and reliability of postural analysis. The main objective is to develop an intelligent system that captures and analyzes a patient’s movements in real time using Motion Capture techniques and artificial intelligence (AI) models to improve the effectiveness of therapies. Computer vision tracks human movement, identifying crucial biomechanical parameters and improving the quality of rehabilitation. Full article

The interconnection between biodiversity loss, food system and climate change is a complex issue with profound implications for global sustainability. Small ruminant farming is a crucial part of addressing these challenges as it contributes to environmental, social, and economic resilience. In Italy, sheep and goat farming is most common in marginal areas with a prevalence of pastoral systems and low mechanization levels. In the Apulia region of Southern Italy, autochthonous small ruminant breeds are at high risk of extinction, due to changing agricultural practices and market pressures. Autochthonous breeds represent valuable genetic resources, adapted to the local environment and capable of producing high-quality products. Apulia boasts an ancient dairy tradition, producing a variety of cheeses from small ruminants, such as Canestrato Pugliese, a Protected Designation of Origin, and four cheeses (Cacioricotta, Pecorino Foggiano, Scamorza di Pecora, and Caprino) recognized as Traditional Agri-Food Products by the Italian Ministry of Agriculture, Food Sovereignty and Forests. These products represent an essential element for biodiversity conservation, encompassing ecosystems, autochthonous breeds, microbial diversity, traditional farming practices, and production systems. This review surveys the main small ruminant native breeds of Apulia region, highlighting their historical significance, distinctive traits, and traditional productions, to help shape strategies for animal biodiversity conservation. Full article

The agri-food system is faced with numerous challenges of sustainability, calling for the improved evaluation of rural development projects. However, a gap exists in the comprehension of the application of both objective and subjective indicators in project selection criteria among regions. This study aims to bridge this gap by exploring, in detail, the nature and utilization of objective and subjective indicators in the Agricultural Knowledge and Innovation System (AKIS) environment in Italy. The approach entails the analysis of documents, with a focus on data relating to the AKIS initiative across regions. The comparative approach is also used to establish the priority that regions assign to indicators. The results include the use of both objective indicators, such as the number of sectors covered, and subjective ones, such as innovation and responsiveness to local needs. Besides, the comparative approach emphasizes the complexity of the AKIS initiative, with some domains tending toward objective indicators, while others tend toward subjective indicators. The study contributes to the development of a composite framework for evaluating rural development projects and emphasizes the need for further research to develop evaluation methodologies further, so that future frameworks will be standardized as well as sensitive to regional heterogeneity. Full article

The agri-food sector is going through a massive digital transformation thanks to new technologies such as the Internet of Things (IoT), big data, and Artificial Intelligence (AI). Regional disparities and implementation barriers prevent widespread uptake despite significant research advances. Drawing on bibliometric and survey data collected up to the end of 2023, this study examines global research trends and stakeholder perceptions in Andalusia (Spain) to identify challenges and opportunities in agricultural digitalization. Bibliographic analysis revealed that research has moved from early remote sensing to precision agriculture, IoT, robotics and big data, and that AI has recently taken over in predictive analytics, automation, and decision-support systems. However, our survey of Andalusian stakeholders highlighted a limited adoption of cutting-edge tools such as AI, blockchain, and predictive models due to economic constraints, technical challenges, and skepticism. Participants emphasized the importance of trust-building, as well as the use of simple tools that require minimal input and provide immediate benefits. Priorities for the responders were also improving market transparency, optimizing resource use, and system interoperability. The findings show that closing the gap between research and practice requires developing digital solutions that are user-centered, simplified, and context-adapted, especially when dealing with complex technologies like AI and predictive systems. This must be supported by targeted public policies and collaborative innovation ecosystems, all essential elements to accelerate the integration of smart agricultural technologies and align scientific innovation with real-world needs. Full article

In recent years, Out-of-Stock (OOS) occurrences have posed a persistent challenge for both retailers and manufacturers. In the context of grocery retail, an OOS event represents a situation where customers are unable to locate a specific product when attempting to make a purchase. This study analyzes the issue from the manufacturer’s perspective. The proposed system, named the “Multi-modal yield eSTimation System of in-prOmotion Commercial Key-ProductS” (MySTOCKS) platform, is a sophisticated multi-modal yield estimation system designed to optimize inventory forecasting for the agrifood and large-scale retail sectors, particularly during promotional periods. MySTOCKS addresses the complexities of inventory management in settings where Out-of-Stock (OOS) and Surplus-of-Stock (SOS) situations frequently arise, offering predictive insights into final stock levels across defined forecasting intervals to support sustainable resource management. Unlike traditional approaches, MySTOCKS leverages an advanced deep learning framework that incorporates transformer models with self-attention mechanisms and domain adaptation capabilities, enabling accurate temporal and spatial modeling tailored to the dynamic requirements of the agrifood supply chain. The system includes two distinct forecasting modules: TR1, designed for standard stock-level estimation, and TR2, which focuses on elevated demand periods during promotions. Additionally, MySTOCKS integrates Elastic Weight Consolidation (EWC) to mitigate the effects of catastrophic forgetting, thus enhancing predictive accuracy amidst changing data patterns. Preliminary results indicate high system performance, with test accuracy, sensitivity, and specificity rates approximating 93.8%. This paper provides an in-depth examination of the MySTOCKS platform’s modular structure, data-processing workflow, and its broader implications for sustainable and economically efficient inventory management within agrifood and large-scale retail environments. Full article

The circular economy (CE) offers a promising framework for sustainable resource management; however, assessing its performance remains challenging due to a lack of robust methodologies, metrics, and data. In agrifood systems, CE has the potential to improve resource efficiency and food security. However, limited research has explored CE interventions in this sector, emphasizing the need for tailored assessment tools. This study seeks to advance CE intervention evaluation in agrifood systems through a realist literature review and discussion on agrifood system assessments to bridge identified knowledge gaps. Our review reveals that most frameworks only address technical or environmental dimensions due to their measurable nature and predominance of laboratory research. This focus underscores the necessity of incorporating assessments in real-world contexts. Insights from agrifood system evaluations suggest that future research should develop holistic frameworks encompassing technical, environmental, social, and economic dimensions. A systems-thinking approach is important for understanding complex interactions among these dimensions, involving mapping, key component identification, and development of context-specific metrics adaptable to global and local settings, particularly for low- and middle-income countries. Active stakeholder collaboration throughout design, data collection, and evaluation is essential for creating relevant indicators. Integrating these elements supports a comprehensive CE assessment framework for agrifood systems. Full article

Point-of-care (PoC) devices offer a promising solution for fast, portable, and easy-to-use diagnostics. These characteristics are particularly relevant in agrifood fields like viticulture where the early detection of plant stresses is crucial to crop yield. Microfluidics, with its low reagent volume requirements, is well-suited for such applications. Self-driven microfluidic devices, which rely on capillary forces for fluid motion, offer an attractive alternative by eliminating the need for external pumps and complex fluid control systems. However, traditional microfluidic prototyping materials like polydimethylsiloxane (PDMS) present challenges due to their hydrophobic nature. This paper presents the development of a reusable, portable, capillary-driven microfluidic platform based on a PDMS-PEG (polyethylene glycol) copolymer designed for the rapid low-cost detection of abscisic acid (ABA), a key biomarker for the onset of ripening of non-climacteric fruits and drought stress in vines. By employing passive fluid transport mechanisms, such as capillary-driven sequential flow, this platform enables precise biological and chemical screenings while maintaining portability and ease of use. A simplified field-ready sample processing method is used to prepare the grapes for analysis. Full article

European policies on climate change (CC), food security (FS), and biodiversity (BD) represent the EU’s commitment to a sustainable agri-food system, highlighting the interdependence between environmental health and food security. By analyzing key drivers and indicators, the present study evaluates the effectiveness of existing measures and identifies gaps in the policy framework. A Scoping Group activity facilitated dialogue between policymakers, industry, and farmer representatives to gather feedback and strengthen the data–policy link. The results highlight progress in areas such as promoting sustainable agriculture and biodiversity, while pointing out unresolved issues like the challenges faced by smallholder farmers. The study emphasizes the need for real-time monitoring tools and tailored solutions to address the complexities of the agri-food system. It also encourages the integration of emerging technologies, such as IoT and AI, to enhance the sustainability of agricultural practices. Ultimately, the findings call for a landscape-specific approach to maximize biodiversity gains, mitigate climate impacts, and ensure food security within the broader context of the EU’s ecological and socio-economic challenges. Full article

The “agroecological transition” has emerged as a framework that aims to explain the complex changes taking place in agrifood systems. This study offers a mapping of the emergence of this framework, and aims to demonstrate that the agroecological transition can refer to different perspectives beyond the simple combination of two concepts. We carried out a bibliometric analysis of 298 articles (2012–2023), searched using the command “agroecologic* transition*”. We used VOSviewer software (version 1.6.20), which is able to reveal clusters of co-citations of the most cited authors and articles. This result, in turn, indicates the existence of different perspectives on the use of agroecological transitions. Four clusters were found: (i) “Techniques and Practices”, represented by articles that document the agroecological transition as an expression of specific agricultural techniques and practices; (ii) “Transition Theory”, which employs the emerging theory and its conceptual contributions; (iii) “Transition Criteria”, which involves the use of criteria to monitor the transition; and (iv) “Political and Social”, made up of articles that explore the political and social movement dimension of agroecology. Each of these clusters, and their approaches, contribute different interpretations of agroecology itself, indicating the emergence of a new framework capable of attributing new meanings to it. Full article

Human and planetary health are interconnected through food and agriculture. Food production and consumption patterns continue to drive the global burden of malnutrition, diet-related disease, climate change, and environmental degradation. There is an urgent need to identify pathways for transforming agrifood systems to be increasingly healthy, sustainable, and just, but conceptual frameworks necessary for visualizing these complex relationships are limited. This systematic scoping review identified existing frameworks for analyzing human and environmental outcomes of agrifood systems and evaluated their inclusion of policy and governance. Frameworks have evolved to increasingly consider the food supply chain activities and actors, the drivers that shape them, and the outcomes of these interactions. The findings of the review were used to develop a conceptual framework specific to modern industrialized agrifood systems where policy landscape is an explicit component. The framework is tailored to researchers and policymakers with the intention of providing a foundation for analyzing and communicating agrifood system issues, including identifying facilitators and barriers to effective policy, places to intervene in the system, and windows of opportunity for successful transformation. Full article

We used systems thinking (ST) to identify the critical components of beef cattle production through the lens of ecosystem services (ES), offering a holistic approach to address its adverse externalities. We identified eight critical feedback loops in beef production systems: (i) grazing and soil health, (ii) manure management and soil fertility, (iii) feed efficiency and meat production, (iv) water use and soil moisture, (v) cultural services and community engagement, (vi) energy use, (vii) carbon sequestration and climate regulation, and (viii) environmental impact. Our analysis reveals how these interconnected loops influence each other, demonstrating the complex nature of beef production systems. The dynamic hypothesis identified through the loops indicated that improved grazing and manure management practices enhance soil health, leading to better vegetation growth and cattle nutrition, which, in turn, have a positive impact on economic returns to producers and society, all of which encourage the continuation of interlinked beef and ecosystem stewardship practices. The management of beef production ES using ST might help cattle systems across the globe to contribute to 9 of the 17 different United Nations’ Sustainable Development Goals, including the “zero hunger” and “climate action” goals. We discussed the evaluation framework for agrifood systems developed by the economics of ecosystems and biodiversity to illustrate how ST in beef cattle systems could be harnessed to simultaneously achieve the intended environmental, economic, social, and health impacts of beef cattle systems. Our analysis of the literature for modeling and empirical case studies indicates that ST can reveal hidden feedback loops and interactions overlooked by traditional practices, leading to more sustainable beef cattle production outcomes. ST offers a robust framework for enhancing ES in beef cattle production by recognizing the interconnectedness of ecological and agricultural systems, enabling policymakers and managers to develop more effective and sustainable strategies that ensure the long-term health and resilience of humans and ES. Full article

Access to food products is becoming more and more complex due to population growth, climate change, political and economic instability, disruptions in the global value chain, as well as changes in consumption dynamics and food insecurity. Therefore, agri-food chains face increasingly greater challenges in responding to these dynamics, where the digitalization of agri-food systems has become an innovative alternative. However, efforts to adopt and use the technologies of the fourth industrial revolution (precision agriculture, smart agriculture, the Industrial Internet of Things, and the Internet of Food, among others) are still a challenge to improve efficiency in the links of production (cultivation), processing (food production), and final consumption, from the perspective of the implementation of Food Informatics technologies that improve traceability, authenticity, consumer confidence, and reduce fraud. This systematic literature review proposes the identification of barriers and enablers for the implementation of Food Informatics technologies in the links of the agri-food chain. The PRISMA methodology was implemented for the identification, screening, eligibility, and inclusion of articles from the Scopus and Clarivate databases. A total of 206 records were included in the in-depth analysis, through which a total of 34 barriers to the adoption of Food Informatics technologies (13 for the production link, 12 for the processing link, and 9 for the marketing link) and a total of 27 enablers (8 for the production link, 11 for the processing link, and 8 for the marketing link) were identified. Among the barriers analogous to the three links analyzed are privacy and information security and high investment and maintenance costs, while the analogous enablers are mainly government support. Full article

There is a growing consensus that the modern food system lies at the centre of the great challenges facing humanity and that urgent and profound changes are required in the way that food is produced, processed, distributed and consumed. This review analyses sustainability transitions within agrifood systems, focusing on the role of firms and industries as defined by the Sustainable Transitions Research Network (STRN). This paper conducts the first systematic literature review using bibliometric analysis to assess the current state of research on this theme. The findings reveal a significant increase in publications related to firms and industries associated with agrifood sustainability transitions. Furthermore, the focus of current research is geographically concentrated in the European Union. The review identifies four key themes in the literature, based on the co-occurrence of keywords. These are agriculture, innovation, governance, food systems and agroecology. The review identifies an increasing awareness of the role of farmers in driving sustainability transitions at the farm level. Furthermore, there is an increasing awareness of the interrelated characteristics of the agrifood system, which acknowledges the need for sustainable innovations to occur at multiple stages of the agrifood system. The review also shows that there is growing evidence that innovations can occur through disruptive as well as incremental innovation and highlights the importance of governance influencing transitions. The existing literature raises questions about alternative food networks as sustainable innovations, their potential for significant change in the established food system and the validity of their claims regarding food equity and environmental sustainability. A key theme emerging from the literature is an ecological perspective that identifies the complex biological processes and ecosystems that form an integral part of agricultural production. These findings provide a greater understanding of the current literature landscape of agrifood sustainable transitions relating to firms and industries and lay a foundation for future research. Full article