Search Results (748)

The application of autonomous robotics in food production is still in its infancy but bears significant potential, especially in the sector of precision farming. Here we present the results of a survey conducted during the years 2022–2023 with local farmers in Northern Germany to identify the challenges that are being faced by both conventional and organic farming practices due to climate change and increased food production regulations in the EU region. Additionally, a pilot study with a medium-sized (Demeter) farm is presented, identifying the real needs and problems organic farmers face during their food production chain from seeding, weeding, and maintaining the equipment till bringing in the harvest. The results indicate a strong demand for modular, autonomous, and digitized solutions to address key challenges in agricultural production. To address these challenges we propose a novel mechanical robotic platform design that has been developed in accordance with the Fab City principles of open and local production resulting in a low-cost open-source solution. Full article

Pitahaya (Hylocereus spp.) production is increasingly affected by climatic factors, as well as by phytopathogens and abiotic stress, leading to delays in agronomic interventions and reduced productivity. The objective was to design, implement, and validate a multimodal system (CARYPAR) that enables early disease detection and agile decision-making, characterized by low latency and reduced dependence on cloud connectivity. The methodology integrates climate reanalysis from NASA POWER, biophysical remote sensing variables derived from Sentinel-1/2, and proximal computer vision captured via mobile devices using a late fusion architecture and an optimized convolutional neural network, EfficientNet-V2B0, which discriminates between optimal and pathological conditions in vegetative tissues and fruit. The results of the experimental validation carried out in 160 georeferenced units achieved an overall accuracy of 80.0% and an F1 score of 0.8645 for Bad Fruit. The McNemar test and the operational agreement with agro-industrial experts yielded a Cohen’s Kappa index of κ = 0.6831, with an inference latency reduced to 22.00 ms. It is concluded that the multimodal integration of satellite bio-environmental data with edge computer vision achieves substantial agreement with agronomic expert judgment under heterogeneous field conditions (Cohen’s κ = 0.6831), supporting its role as a decision-support tool rather than a replacement for expert assessment. Therefore, its adoption can enhance real-time irrigation management and crop protection, while contributing to traceability and sustainable resource management in agricultural regions with limited connectivity. Full article

Digital transformation is frequently argued to improve how agricultural businesses compete, coordinate, and capture value in markets, yet evidence remains limited of how regional innovation ecosystems shape farms’ digital readiness and how this readiness translates into accounting-relevant outcomes. This study addresses that gap by linking regional innovation capacity, observed farm digital readiness, and accounting performance within a single regional analytical framework. Using cross-sectional data for 180 EU NUTS2 regions (2023), we estimate a moderated mediation model with formative constructs based on harmonized secondary indicators. This study is original in shifting the analysis from the farm or firm level to the regional scale and in operationalizing digital readiness through observable uptake of precision technologies, robotics, livestock-management machinery, internet access, and management information systems. Regional innovation capacity is positively associated with farmers’ digital readiness, and digital readiness is positively associated with accounting performance in the baseline specification. The indirect pathway from innovation capacity to accounting performance via digital readiness is significant, consistent with digital readiness acting as a transmission channel through which ecosystems relate to measurable economic outcomes. Managerial composition conditions these relationships: the share of managers under 40 weakens both the ecosystem-to-digital link and the digital-to-performance link, while female managerial share shows only marginal moderation of the first stage and no significant moderation of the second. The findings provide a basis for future multilevel research and place-based policies and advisory actions aimed at strengthening digital uptake where regional innovation capacity is weaker. Full article

Precision Livestock Farming (PLF) tools are increasingly used in dairy production, but their success depends on farmers’ perceptions, needs and investment capacity. This study explores the current use of digital technologies, satisfaction levels and future expectations among Italian dairy farmers. An online questionnaire with 19 questions collected 53 complete responses between May and November 2025. Most of the farms were free-stall Holstein dairy farms located in the Po Valley and managed by relatively young and well-educated farmers, many of whom had a background in animal production. The adoption of PLF tools was widespread: management software (73.6%), automated total mixed ration (TMR) preparation (66.0%), heat stress mitigation systems (62.3%) and collar sensors (52.8%) were the most adopted technologies. Satisfaction with current tools was high, although installation costs and poor system integration were consistently identified as major constraints. Farmers expressed clear priorities for future devices, particularly early diagnosis of health problems, calving, heat, lameness, and feeding and rumination functions. The results suggest that PLF in Italian dairy systems is moving from the adoption phase to that of consolidation. However, improvements in interoperability, affordability and farmer-centred design remain essential to support a wider and more equitable spread of the technology across the sector. Full article

Smallholder poultry farming contributes enormously to rural livelihoods, food security, and nutrition in South Africa, yet the poultry industry remains constrained by limited participation and low ICT utilisation. This study investigated the socioeconomic and demographic factors influencing decisions and choices of smallholder poultry farmers towards the adoption of ICT and market engagement in Jozini Local Municipality, KwaZulu-Natal. A cross-sectional research design was used to collect primary data from respondents. Data were collected through face-to-face surveys from 162 participants, who were randomly selected. Descriptive statistics were employed to profile the use and extent of ICT, while the multivariate probit model was used to analyse the determinants of ICT adoption and market engagement. The findings revealed that most farmers own ICT tools such as mobile phones (98.15%), which they mainly use for communication purposes (98.77%) rather than for accessing production and market related information. Smallholder characteristics like age, faming experience, marital status, and household size significantly influenced farmers decisions and choices to adopt ICT and participate in markets. The study recommends improving the traditional extension through digital integration and farmer support by means of training on ICT and formal market linkages. These interventions can significantly market participation and profitability in smallholder poultry farming, stabilising rural economic development. Full article

Food waste prevention and reduction are some of the important initiatives to improve the environmental sustainability of food systems. The global agenda of the United Nations provides a framework of targets and actions against food waste to which the European Union (EU), within the “Farm to Fork” strategy, aims to contribute. In this context, evaluating the impacts of food prevention measures is of great importance for supporting policies. This LCA analyzes the impact of classic lasagna from cradle to grave, through a generic food case study, prepared by food shops in Bologna (Northern Italy). Four scenarios are simulated, comparing the impacts of some end-of-life alternatives for the management of leftover lasagna (landfilling, composting, and redistribution with the digital application of the circular start-up “Squiseat”) versus the ideal scenario where no leftover lasagna is assumed. The results show that the preparation of classic lasagna generates non-negligible impacts on the analyzed LCA categories due to some of its ingredients, such as Bolognese sauce and Parmigiano Reggiano, and their associated production processes. For this reason, it is important to prevent classic lasagna leftovers from being wasted. The comparison of the four scenarios shows that redistribution is the scenario with the lowest impacts in all the investigated impact categories, including global warming (6.24 kg CO₂ eq./kg of lasagna). The impacts are also lower than the ideal scenario due to the assumption of more sustainable means of transport. Normalization of characterized results confirms that Global Warming (GW) is only one of the most relevant impact categories in the life cycle of classic lasagna. The results have practical implications for raising awareness concerning the impacts of food production throughout the whole life cycle and the need for preserving the value of food by avoiding waste. Moreover, this study also shows that a reduction in the impact is a shared outcome that could be achieved by the joint efforts of all the stakeholders involved in the life cycle of food. In this regard, urban centers are confirmed to be important hubs of circular and more sustainable innovation. Finally, the LCA enriches the current research by investigating redistribution through the relationship of the food shop–virtual intermediate–consumer. So far, the prevalent focus of the LCA research allows us to assess the redistribution of collected surplus food from retailers and its delivery to the consumers by means of physical intermediaries and related infrastructures (e.g., food hubs, food banks, and food emporiums). Full article

Small ruminant production is vital for rural livelihoods and food security in Saudi Arabia but faces persistent constraints, including high feed costs, limited veterinary access, low reproductive efficiency, and weak extension services. To address these gaps, a Farm Service Delivery Model (FSDM) was piloted, which involved embedding trained livestock technicians into communities to deliver integrated on-farm services. This study evaluated the impact of the FSDM on 47 farms across three regions over 6–12 months. The key results showed significant improvements: flock size increased by 28%, the lambing rate per ewe doubled from 0.39 to 0.80, twin births tripled, mortality declined from 23.8% to 8.0%, and milk production more than doubled. Economic analysis revealed a benefit–cost ratio of 3.02, indicating high return on investment. Scaling the FSDM nationally could generate up to USD 4.8 billion in added meat and milk value over five years while reducing meat imports by 48%. The model aligns with Saudi Vision 2030 and offers a scalable and sustainable pathway to enhance productivity, resilience, and rural income. Policy recommendations include institutional integration, digital innovation, blended financing, and strengthened breeding programs. Full article

Agriculture faces climate change, price volatility, and policy uncertainty. Because traditional agricultural insurance instruments often prove insufficient to address these risks, the Common Agricultural Policy (CAP) has introduced additional risk-management instruments such as mutual funds. The paper applies the Business Model Stress Testing framework to assess the robustness and adaptability of a mutual fund business model. The sustainability of the mutual model depends on building trust, enabling legislation, ensuring transparent governance, diversifying funding sources, agri-tech and alignment with support measures are the most critical factors. Within the current institutional framework, the lack of cooperative tradition and management capacities, the application of mutuals is hardly feasible for Croatia. Instead of a collective risk-sharing instruments approach, the paper suggests supporting the cooperation of stakeholders from different risk layers in harnessing digital technology and AI in developing enhanced agricultural risk management. Even though such an approach could be fuzzy too, it could bring impact faster and even contribute to the relevancy of the mutual model. The paper contributes to the literature on sustainable business model innovation in agriculture that enhances farm resilience in high-risk environments. This exercise might have policy implications for transition economies seeking to operationalize innovative tools in climate risk management and rural development. Full article

Production diseases in dairy cattle impose economic and welfare burdens, yet few studies quantify costs using on-farm cases. This study aimed to estimate costs and lost revenues at the individual-animal level in 10 German dairy farms (average of 592 cows; 9694 kg marketed milk/cow/year; 32.9% culling rate). Each farm was visited for three weeks; diseased cows and calves were examined by a trained veterinarian. Diagnoses, treatments, labour times, and outcomes were recorded, and costs calculated for labour, products, veterinary and orthopaedic services, discarded milk, decreased milk yield, culling, book loss, and reduced carcass value. In total, 1272 single-animal cases were included: 68% were stand-alone diseases, 11% involved multiple diagnoses within one organ system, and 21% affected several organ systems. When several diseases occurred in the same animal, total costs and lost revenues were greater than the sum of stand-alone cases, indicating compounding effects. High-impact conditions included mastitis, claw disorders, left displaced abomasum, and multimorbidity; per-case losses ranged from €43 (digital dermatitis) to >€1200 (left displaced abomasum with complications). Labour and culling-related costs were higher than reported, and productivity losses exceeded treatment costs in many cases. Findings support farm-level decision-making, prevention, and parameterization of future dynamic models. Full article

Button mushroom (Agaricus bisporus) cultivation in India is highly seasonal due to strict microclimatic requirements and limited access to controlled environment infrastructure among smallholder farmers. This study evaluates an IoT-controlled microclimate system (Mushroom Kothi) designed to stabilize temperature, relative humidity, and ventilation during late winter to early summer transition periods. Multi-site field evaluations across distinct agro-climatic regions demonstrated improved microclimate stability, enabling extension of the viable cultivation window by approximately 1.5–2 months beyond the conventional seasonal cutoff. The system supported continuity of production, improved water-use efficiency, and reduced manual intervention without reliance on energy-intensive cooling. The findings highlight the potential of low-cost, digitally assisted microclimate stabilization to enhance seasonal resilience, resource efficiency, and ease of cultivation in smallholder mushroom farming systems. Full article

The Mediterranean mussel, Mytilus galloprovincialis, is currently facing unprecedented mass mortality events (MMEs) that threaten the economic and ecological stability of Mediterranean aquaculture. The present review gathered and analyzed current knowledge on climate change and environmental disorders that may cause MMEs in Mediterranean mussels, compromising mussel physiology and immune competence. Biological agents, which proliferate under stress conditions, can either trigger direct disease or act as co-factors in mortality. The impact of the economic loss following MMEs in mussel production in the Mediterranean Sea is also described. The main key drivers used in the analysis of the literature were “M. galloprovincialis”, “MMEs”, “environmental stressors”, “climate change”, “pathogens”, “pollutants”, “economical losses”. The One Health–One Welfare framework recognizes the inextricable interconnection between the health of human, mussel, and marine ecosystems. This approach is essential for developing holistic monitoring programs, robust risk assessment strategies, and adaptive management policies capable of ensuring the long-term sustainability of Mediterranean mussel production and the ecological stability of coastal systems. In the future, the development of integrated water monitoring systems where mussels are both farmed species and active biological sentinels is possible. The implementation of a digital monitoring system will offer a transformative strategy for mitigating MMEs in Mediterranean mussel populations. Full article

The agri-food sector is undergoing a profound transformation driven by the combined pressures of climate change, resource scarcity, policy frameworks, and evolving consumer expectations. In this context, digital and green technologies have emerged as key enablers of more sustainable, transparent, and resilient food systems. This review provides a comprehensive overview of the conceptual foundations, technological drivers, and policy frameworks shaping the digital and green transition of the agri-food sector. Digital technologies—including precision agriculture, sensing and data acquisition systems, artificial intelligence, blockchain, and data platforms—are examined in relation to their role in improving resource-use efficiency, traceability, and decision-making across the food value chain. In parallel, green technologies and sustainable practices in food production, processing, and waste management are discussed, with emphasis on resource optimization, circular economy approaches, and environmental impact reduction. This review further highlights the role of European and global policy frameworks, such as the European Green Deal and the Farm to Fork strategy, in steering technological adoption and aligning innovation with sustainability objectives. By synthesizing technological, environmental, and policy perspectives, this work underscores the importance of integrated digital–green strategies for achieving long-term sustainability, competitiveness, and resilience in agri-food systems. Full article

This Special Issue, entitled “Digital Soil Mapping for Agri-Environmental Management and Sustainability”, gathers nine studies from around the globe that illustrate how digital soil mapping (DSM) is being applied to support agri-environmental management and sustainability. Field- and farm-scale studies are emphasized, where informed decisions are essential for efficient day-to-day management and profitability. The articles highlight the integration of remote/proximal sensing, along with modern machine learning techniques, to produce high-resolution soil maps, soil fertility and nutrient management zoning, and to monitor salinity and soil moisture to inform irrigation and land management. Another key focus is improving sampling strategies and assessing prediction uncertainty and model interpretability. This collection sets future DSM priorities, including cost-effective sampling, robust uncertainty assessments, and reliable cost–benefit and risk assessment approaches that link map accuracy/uncertainty to management outcomes and economic performance. Full article

Precision Agriculture (PA) is increasingly applied to nutraceutical cropping systems, where agronomic productivity must be integrated with the stabilization of phytochemical quality and environmental sustainability. This structured narrative review synthesizes scientific evidence (primarily 2010–2025) on the use of Unmanned Aerial Vehicle (UAV)-based multispectral and thermal sensing, LiDAR-derived canopy characterization, Internet of Things (IoT) monitoring, and artificial intelligence (AI)-driven analytics in medicinal, aromatic, and functional crops. The literature indicates that PA enhances high-resolution monitoring of crop–environment interactions, supporting site-specific irrigation, nutrient management, and stress detection. Under validated conditions, these interventions are associated with improved yield stability, resource-use efficiency, and modulation of secondary metabolite accumulation. However, reported outcomes vary substantially across species, agroecological contexts, and experimental scales, and most studies remain plot-scale or pilot-scale, limiting large-scale generalization. Moringa oleifera Lam. is examined as a model species for Mediterranean and semi-arid systems. Evidence suggests that integrated spectral, structural, and environmental monitoring can support optimized irrigation scheduling, canopy uniformity, and phytochemical consistency. Nonetheless, genotype-specific calibration, multi-season validation, standardized metabolomic benchmarking, and cross-regional transferability remain significant research gaps. Overall, PA represents a scientifically promising but still maturing framework for nutraceutical agriculture. Future progress will require rigorous multi-site validation, improved model robustness, standardized sustainability metrics, and comprehensive economic assessments to ensure scalability and long-term impact. Full article

Digital Twins (DTs) have emerged within the last decade due to the adequate maturity of several key technologies contributing to the realization of real-time virtual–physical world synchronization. Advancements in sensing, connectivity, computing processing power, and artificial intelligence have contributed to the deployment of DTs in several application sectors, such as in agriculture. This work aims to provide a scoping review of recent advancements in digital twin technologies and agricultural applications. Results indicate a special focus on plant-level models, soil moisture, and machinery, while most works are based on drone imagery combined with machine learning routines. Several works use the term DTs rather loosely, often describing systems that resemble decision support tools rather than a fully synchronized virtual–physical setup. Data integration emerges as the most important bottleneck, especially when the system mixes satellite data, local sensory data, and simulation outputs. Yet it is suggested that DTs could eventually support more adaptive and resource-efficient farm management. However, the field is still missing common frameworks and long-term evaluations. Based on this review, progress depends on better data-handling pipelines, clearer definitions of operational DTs, and more attention to economic and practical constraints faced by farmers rather than just technical proofs of concept. Full article