Western Macedonia, the leading power-producing region in Greece, has long depended on thermoelectric plants and lignite mining. To reach climate neutrality by 2050, Greece is undergoing a delignitization process aiming to shut down all lignite plants. This structural reconstruction of the energy model will mainly affect society, the economy, the environment, and agriculture. Strengthening efforts to support lignite-dependent areas are essential for this transition. Bioeconomy could be one of the main pillars for the post-lignite era in the Western Macedonia Region (WMR). This paper explores the gender dimension in the adoption of bioeconomy practices and innovativeness among farmers in the Region of Western Macedonia. Based on 331 structured questionnaires and a Two-Step Cluster Analysis, the research identifies five farmer clusters and then correlates the clusters with Rogers’s theory of diffusion of innovations. The findings identify a dynamic group of young female farmers leading the diffusion of innovation, emphasizing their role in promoting sustainable agricultural transitions and the need for gender-responsive policies in regional bioeconomy strategies.

European wine production is undergoing a significant transformation, with precision viticulture (PV) emerging as a vital strategy for its long-term viability. Viticulture can benefit from the integration of digital tools and smart technologies. The VTskills project responds to this shift by promoting the adoption of environmentally, socially, and economically sustainable practices in viticulture among SME actors to achieve the objectives of the Green Deal, CAP, Farm-to-Fork, and Biodiversity strategies. One of the main goals of the VTskills project is to develop new e-learning courses for HEI and VET trainees to enhance their skills and entrepreneurial activity in an innovative environment. This paper presents the VTskills e-learning platform for sustainable precision viticulture.

Accurately forecasting agricultural commodity prices is a complex and persistent problem for producers, traders, and policymakers. In this study we examine how artificial intelligence can be combined with large-scale global news data to refine daily corn price forecasts. A Long Short-Term Memory (LSTM) neural network was trained on Chicago corn futures between 2021 and 2024 to capture price dynamics, while agriculture-related news features were derived from the Global Database of Events, Language, and Tone (GDELT). Rather than sentiment polarity, the analysis shows that attention-based indicators, such as article volume, rolling intensity measures, and persistence of elevated coverage, carry stronger predictive information. These features are incorporated through a Ridge regression residual correction applied to the LSTM predictions, forming a lightweight two-stage hybrid model. While absolute forecast accuracy remains comparable to the price-only baseline (RMSE ≈ 9 ¢/bu; MAE ≈ 5.8 ¢/bu; R2 ≈ 0.99), the hybrid framework improves directional accuracy by approximately 2.4 percentage points, with gains concentrated during periods of moderate news intensity. Feature attribution results indicate that media attention intensity and persistence dominate sentiment-tone variables, which receive zero weight under regularization. Overall, the proposed framework offers a transparent, computationally efficient, and reproducible approach for integrating open global news data into short-term agricultural price forecasting.

Impact Assessment (IA) is an important process in order to help both researchers and policymakers to identify the vulnerable points of policies with final goal to improve them. For this reason, European Union introduced impact assessment, as a mandatory process in all new policies and directives. One of the main EU policies are the Rural Development Plans (RDPs), as a part of the second pillar of the Common Agricultural Policy (CAP), which are implemented in every member-state. The aim of this paper is to evaluate an impact assessment process for the rural development plan measures. This process was implemented as case study for a specific measure of the Greek RDP. The implementation of the impact assessment process refers to a sample of farms participating in the measure 121 “Modernization of agricultural holdings” in the region of Central Macedonia in Greece for the programming period of 2007–2013. From the evaluation of the IA process very useful conclusions were raised. The results will help the researchers and the policy makers to make improvements in every step of the impact assessment process.

Agricultural cooperatives are essential in mitigating climate change and food insecurity through the promotion of sustainable agricultural practices and the conservation of biodiversity. However, weaknesses in governance, economic restrictions, market pressures, and regulatory obstacles frequently hinder their efficacy. This study investigates the main factors leading to cooperative failures through qualitative analysis of twenty-three (23) expert interviews. Research demonstrates that strong governance, efficient communication, financial stability, and supportive policies are crucial for the viability of cooperatives. Leadership issues, bureaucratic inefficiencies, and market competition were seen as significant roadblocks. It is essential to tackle these difficulties via governance adjustments, economic resilience approaches, and policy advocacy to strengthen the role of cooperatives in climate change mitigation and food security.

According to the FAO, wheat, corn, and rice are staple crops that support global food security, providing 50% of the world’s dietary energy. The ability to predict accurately these key food crop agricultural commodity prices is important in stabilizing markets, supporting policymaking, and informing stakeholders’ decisions. To this aim, machine learning (ML), ensemble learning (EL), deep learning (DL), and time series methods (TS) have been increasingly used for forecasting due to the rapid development of computational power and data availability. This study presents a systematic literature review (SLR) of peer-reviewed original research articles focused on forecasting the prices of wheat, corn, and rice using machine learning (ML), deep learning (DL), ensemble learning (EL), and time series techniques. The results of the study help uncover suitable forecasting methods, such as hybrid deep learning models that consistently outperform traditional methods, and they identify important limitations in model interpretability and the use of region-specific datasets, highlighting the need for explainable and generalizable forecasting solutions. This systematic review adheres to the PRISMA 2020 reporting guidelines.

Hippophae (sea buckthorn) is a plant valued for its berries in food manufacturing and medicinal properties. Despite growing research on its benefits, consumer perceptions of sea buckthorn-based products remain underexplored. This study examines Greek consumers’ attitudes toward cereal bars enriched with sea buckthorn, developed within a project focused on high-nutritional-value foods. Key factors include awareness, taste, safety, health benefits, trust, convenience, price, appearance, quality certification, environmental friendliness, and support for small-scale farmers. Results show moderate willingness to buy due to perceived health benefits and sustainability, but marketing should address sensory profile and trust to build a robust market.

Fresh water is indisputably a vital resource in ecosystems and its scarcity threatens the economy and society. Due to climate change, economic growth and unsustainable water management, water systems have become depleted and very contaminated worldwide. The scarcity and ecological degradation of water resources have threatened the sustainability of human life, socio-economic development and ecosystem services. The key element in an efficient management is the dynamic assessment of the status of water resources. Thus, this work developed a comprehensive evaluation indicator system based on the Driver-Pressure-State-Impact-Response (DPSIR) framework, combined with the Analytic Hierarchy Process (AHP).The study offers an applied-friendly way of assessing sustainable water management in a resource-scarce environment through a stakeholder engagement approach. This facilitates assessing and reporting the state of water resources in a selected watershed in Ghana. The analysis highlights the components of climate regime and mining activities to demonstrate the greater threats to the water systems of the region. The results clearly illustrate that strengthening stakeholders’ involvement, improvement of infrastructure and implementation of the existing policies are among the higher-ranked responses that would guarantee the sustainability of water resources in the region. Furthermore, the research provides detailed information on human activities and their impacts on water systems in a quick and easy way for local stakeholders and policymakers, so as to support sustainable water management. The overall approach can be easily implemented and expanded in several water management cases.

The rapid growth of agricultural data necessitates the development of storage systems that are scalable and efficient in storing, retrieving and analyzing very large datasets. The traditional relational database management systems (RDBMSs) struggle to keep up with large-scale analytical queries due to the volume and complexity inherent in those data. This study presents the design and implementation of a scalable data warehouse (DWH) system for agricultural big data. The proposed solution efficiently integrates data and optimizes data ingestion, transformation, and query performance, leveraging a distributed architecture based on HDFS, Apache Hive, and Apache Spark, deployed on dockerized Ubuntu Linux environments. This paper highlights the reasons why a DWH is irreplaceable for big data processing, without disputing the strengths of traditional databases in transactional use cases. By detailing the architectural choices and implementation strategy, this study provides a practical framework for deploying robust DWH solutions that are useful in supporting agricultural research, market predictions and policy decision-making.

This paper investigates the efficacy of weather derivatives as a risk management tool in the agricultural sector of Naousa, Greece, focusing on tree crops sensitive to temperature variations. The specific purpose is to assess how effectively weather derivative options can mitigate financial risks for farmers by providing strategic solutions. The study assesses the strategic application of Heating Degree Days (HDD) index options and their potential to alleviate economic vulnerabilities faced by farmers due to temperatures fluctuations. Employing different strike prices in Long Call and Straddle options strategies on the HDD index, the research offers tailored risk management solutions that cater to varying risk aversions among farmers. Moreover, the study applies the Value at Risk (VaR) methodology to quantify the financial security that weather derivatives can furnish, revealing a significantly reduced probability of severe financial losses in hedged scenarios compared to no-hedge conditions. Results show that all implemented strategies effectively enhance financial outcomes compared to scenarios without hedging, highlighting the exceptional utility of weather derivatives as risk management tools in the agricultural sector. Strategy 4, which exhibits the lowest VaR, emerges as the most effective, providing substantial protection against adverse weather conditions. This research supports the notion that weather derivatives can substantially contribute to the economic sustainability of rural economies, influencing policy decisions toward enhancing financial instruments for risk management in agriculture.

This paper highlights the significance of nurturing and safeguarding minor crops as a means of achieving regional sustainable development, preserving biodiversity, and ensuring food security. Minor crops play a critical role in addressing various environmental challenges like climate change, biodiversity loss, desertification, and soil salinity. Simultaneously, they offer local farmers economic opportunities by providing income stability and resilience. To demonstrate the potential of minor crops in promoting sustainable development, a case study from Greece is presented, focusing on three crops: blackcurrant, rice, and sunflower, which bring substantial economic and environmental benefits to the region. The study assesses the economic and environmental impact of these crops across three different rural territories in Greece. Despite covering less than 4% of total agricultural land, these crops are predominantly grown in marginal, mountainous, and insular regions. By analyzing the farm-level and broader economic effects, the study determines their potential for agricultural and regional development. The results indicate that these crops are more profitable and environmentally friendly compared to their counterparts in all three cases. Additionally, they make significant contributions to the regional economies relative to their cultivated land area, supporting economic growth while conserving and enhancing agricultural land. In conclusion, this article emphasizes the crucial need to promote the cultivation and preservation of minor crops to support sustainable development, biodiversity conservation, and regional economic growth. Policymakers and agricultural practitioners should prioritize the cultivation and preservation of regional minor crops to safeguard biodiversity at the regional level and at the same time sustainable regional development.

This study examines governance strategies that facilitate sustainable regional circular bioeconomy development, culminating in a typology which enables the classification of regional government good practices supporting circular bioeconomy deployment in diverse regions within Europe. Data on regional circular bioeconomy governance models were collected through desk research and a survey, resulting in a compilation of 61 circular bioeconomy governance models. From this compilation, 20 case studies were identified and further explored to develop a typology of regional circular bioeconomy governance strategies in the EU-27. Findings reveal a strong regional commitment to expanding bioeconomies; however, managing conflicting sustainability goals remains a challenge. This paper provides a comprehensive overview of successful governance models and practices, offering valuable insights for policymakers to support the co-development and replication of effective circular bioeconomy strategies across diverse European regions.

The aim of this paper is to explore farmers’ training needs, their lack of knowledge and skills, and their willingness to participate in related training programs in the Western Macedonia Region. Summary statistics and multivariate analyses were performed for the data analysis. The results indicate a low level of knowledge about the bioeconomy and its practices. Furthermore, the findings revealed the high willingness of farmers for future adoption of the bioeconomy, and the need to create bioeconomy training programs.

This study examined Greece's Agricultural Knowledge and Innovation System (AKIS) and assessed the flow of information and linkages among eight stakeholder groups: policy, education, research, consulting, agricultural cooperatives, credit, private enterprises, and farmers. Data were collected using an online survey tool from 61 experts/representatives following an initial phone communication. The Graph Theoretical Technique was utilized to achieve the survey's objectives. The results revealed dominant and subordinated actors in the system and identified a critical pathway for information flow within AKIS. Policymakers can leverage these findings to strengthen linkages, address information gaps, and promote innovation and equitable development in the agricultural sector.

This study aims to identify the relationships between critical factors and successful Enterprise Resource Planning implementation in the agricultural processing companies of Central Macedonia’s (Greece) region. Therefore, critical factors are taken into account collectively, as aspects of ERP implementation and its life cycle. Based on that, two versions of the particular information system’s management were presented, aiming to its success in the Greek agricultural processing field. The methodology which was used in order for the purposes of this analysis to be served, was that of Partial Least Squares Structural Equation Modeling. Through the answers given, it was determined whether the importance shown to the two different versions of critical factors is related to the degree of ERP systems’ success—or not—and in which way. Based on that, two management versions of ERP system are provided but also the scientific literature regarding the Greek and Central Macedonian field, is enriched. Lastly, helpful guidelines are developed in order for professionals and managers to understand the ways in which critical factors can be taken into account so as for the successful implementation of ERP in agribusinesses -specialized in the field of agricultural products processing- to be feasible.

Short food supply chains (SFSCs) are market schemes that allow different types of value to emerge. In this work, we aimed to uncover these facets of value. To do so, we built upon two conceptual models: a Triple Layered Business Model Canvas and an eight-dimensional blueprint developed for our purposes. Then, we conducted two studies using these models as theoretical templates. In Study I, we followed a business model canvas perspective, aiming to portray the components that contribute to the generation of economic, functional, and social value produced in SFSCs. By drawing on a sample of farmers who participate in SFSCs, we developed regression models to uncover the antecedents of value. Our analysis revealed that the effectiveness of performed activities catalyses the economic value of SFSCs. In addition, the social value depends on the capacity of SFSCs to enhance local communities’ well-being and provide significant outreach. Finally, environmental value is associated with the distribution of products. In Study II, using data from a pool of experts, we assessed the importance of eight facets of value. Participants appraised economic, social, cultural, and environmental value as more important than the remaining dimensions. Our studies shed light on the dimensions of value created in SFSCs, also confirming the usefulness of business model canvases for understanding value creation processes. However, our work also offers a new framework for conceptualising supply chains’ value, distinguishing value into primary (which is produced and remains within SFSCs) and secondary (which extends beyond supply chain limits).

European Protected Areas (PAs) are facing today complex and highly diverse challenges. Farm management structures have changed over time and traditional low-intensity farming systems have become unprofitable leading to either abandonment or intensification of farming practices. These changes have contributed to the environmental degradation of biodiversity rich agricultural landscapes and the loss of cultural knowledge and traditions. The interrelations developing at various levels between agricultural land use, nature and landscape conservation, and socio-economic activities influence the sustainable development and management of PAs. The development of certification and labelling schemes for high quality agri-food products with a PA logo is a rural development process that involves multiple functions which could generate environmental improvements and positive socio-economic changes. The differentiation of the agricultural products of PAs, through labelling and information, can be a proactive market-based instrument to support the local economy, promote environmentally sound practices, raise environmental awareness, and preserve farmland biodiversity in protected areas. This paper review is an attempt to gather and analyze in depth the findings of the existing studies focusing on the relationship between the European PAs, farming systems and certification/labelling schemes of agri-food products with a PA logo. Academic research on the subject is limited but provides valuable insights. The findings can serve as a starting point for discussions and reveal opportunities for further research to better understand the interrelations and additional effects emerging from the labelling/certification of PAs’ high quality agri-food products.

This paper presents the results of a survey conducted electronically in the years 2020-2022 within the framework of the AGRICORE Horizon project. It concerned the Agri Environment-Climate Measure M10 within the Rural Development Programme 2014-2020 and aimed to quantify the impact of its effects on environmental and climatic policy implementation at a national level according to the perceptions of Polish farmers. The representativeness of the scrutinized population was checked using general data from the Polish Statistics Office. The results of our study show a positive perception of M10 by the participating farmers. The majority of them observed the income progress of their activities despite the increased workload connected with programme implementation and the increased costs associated with some of the declared activities. The innovation activities of the M10 participants were directed mainly at sustainable agriculture and protecting the environment. The respondents who did not decide to participate in M10 most frequently explained themselves by noting a lack of information about the programme, bureaucratic limitations, or doubts concerning the profitability of participation. The results of the study suggest that during the implementation of future EU agri-environmental measures, more attention should be paid to administrative and legal activities at the national level which may improve the perception of the programme.

The aim of this paper is to describe existing linkage mechanisms among the four main pillars (Education, Research, Consulting, and Private Companies) of the Agricultural Knowledge and Innovation System (AKIS) in Greece, in terms of implementation and strength level. Moreover, the study explores approaches to strengthening sustainable linkages. Data were collected from 38 AKIS actors using a structured questionnaire and indicate some interesting results: (a) strong links in most of the mechanisms between research and education; (b) Consultancy Agencies maintain stronger links with Research Organizations than other actors; (c) Private Companies maintain stronger links with Research (at lower levels); (d) there were significant differences in terms of the strength of linkage mechanisms between Educational Institutions and Consulting Agencies and (e) activities (workshops, research projects, consultancy projects), networks, and digital platforms were considered appropriate approaches for developing synergy, complementarity, and coordination among the AKIS actors. Results of this research may be used as a decision-making tool in identifying, designing, and implementing complementary interventions and institutional changes that seem likely to strengthen the AKIS in Greece and promote enhanced agricultural innovation and equitable development.