Search Results (342)

Unsafe disposal of pesticide waste remains a critical environmental and public health issue in developing agricultural systems. This study examined cocoa farmers’ disposal behaviours and their determinants across Nigeria’s major cocoa-producing regions using an explanatory sequential mixed-methods design. Quantitative data were collected from 391 farmers, followed by 23 in-depth interviews to contextualise behavioural drivers. Results showed that knowledge of pesticide risks and availability of disposal facilities significantly predicted safer disposal practices (R² = 0.469, p < 0.05), whereas age had a negative influence. Qualitative findings revealed that negative attitudes, social norms, and limited infrastructure reinforced unsafe behaviours, while membership in farmers’ associations promoted safer practices through peer learning. A joint display demonstrated convergence between structural enablers (collection cages, extension support) and behavioural factors (knowledge, attitudes, norms). The study identifies a dual challenge of systemic shortcomings and behavioural inertia, suggesting that regulatory action alone is insufficient without farmer engagement and education. Policy and extension programmes should prioritise collection infrastructure, association-based training, and Integrated Pest Management to promote sustainable pesticide waste management. These insights advance understanding of pesticide disposal behaviour and offer actionable guidance for environmental governance in low- and middle-income agricultural contexts. Full article

Horticultural facilities can boost crop yields and quality. However, their structures, costs, and resource efficiency vary significantly. Many facility operators prioritize short-term economic gains at the expense of long-term investments in energy efficiency and environmental management, ultimately leading to increased energy consumption and higher greenhouse gas emissions. A systems-based assessment of tomato production is essential for optimizing resource use. This study integrated emergy analysis (EMA) and life cycle assessment (LCA) to evaluate the sustainability of three tomato production systems: polytunnels, solar greenhouses, and glass greenhouses. The Results demonstrated that polytunnels exhibited the best environmental performance, with the lowest environmental loading ratio (ELR, 19.06) and environmental final index (EFI, 1.62). Solar greenhouses showed the best environmental composite index (ECI), outperforming others in mitigating potential environmental impacts. Glass greenhouses imposed the greatest environmental pressure (ELR, 168.51), primarily due to substantial natural gas consumption and infrastructure investment. Scenario analyses revealed that environmental performance across all systems could be significantly enhanced through shortening transport distance, extending the service life of construction materials, and managing energy use. The maximum reduction potentials for the environmental composite index (ECI)were 23.80% for polytunnels, 18.60% for solar greenhouses, and 19.90% for glass greenhouses. This study confirms that polytunnels are the most environmentally friendly option, and targeted management strategies can effectively steer facility-based agriculture toward a more sustainable trajectory. Full article

In the context of the rapid transformation of global agricultural production towards intensification and intelligence, the precise and intelligent management of horticultural crop production processes is key to enhancing resource utilization efficiency and industry profitability. Crop growth and development models, as digital representations of the interactions between environment, crops, and management, are core tools for achieving intelligent decision-making in facility production. This paper provides a comprehensive review of the advancements in intelligent management models and systems for horticultural crop growth and development. It introduces the developmental stages of horticultural crop growth models and the integration of multi-source data, systematically organizing and analyzing the modeling mechanisms of crop growth and development process models centered on developmental stages, photosynthesis and respiration, dry matter accumulation and allocation, and yield and quality formation. Furthermore, it summarizes the current status of expert decision-support system software development and application based on crop models, achieving comprehensive functionalities such as data and document management, model parameter management and optimization, growth process and environmental simulation, management plan design and effect evaluation, and result visualization and decision product dissemination. This illustrates the pathway from theoretical research to practical application of models. Addressing the current challenges related to the universality of mechanisms, multi-source data assimilation, and intelligent decision-making, the paper looks forward to future research directions, aiming to provide theoretical references and technological insights for the future development and system integration of intelligent management models for horticultural crop growth and development. Full article

Segmentation of tomato fruits under complex lighting conditions remains technically challenging, especially in low illumination or overexposure, where RGB-only methods often suffer from blurred boundaries and missed small or occluded instances, and simple multimodal fusion cannot fully exploit complementary cues. To address these gaps, we propose YOLO-MSRF, a lightweight RGB–NIR multimodal segmentation and refinement framework for robust tomato perception in facility agriculture. Firstly, we propose a dual-branch multimodal backbone, introduce Cross-Modality Difference Complement Fusion (C-MDCF) for difference-based complementary RGB–NIR fusion, and design C2f-DCB to reduce computation while strengthening feature extraction. Furthermore, we develop a cross-scale attention fusion network and introduce the proposed MS-CPAM to jointly model multi-scale channel and position cues, strengthening fine-grained detail representation and spatial context aggregation for small and occluded tomatoes. Finally, we design the Multi-Scale Fusion and Semantic Refinement Network, MSF-SRNet, which combines the Scale-Concatenate Fusion Module (Scale-Concat) fusion with SDI-based cross-layer detail injection to progressively align and refine multi-scale features, improving representation quality and segmentation accuracy. Extensive experiments show that YOLO-MSRF achieves substantial gains under weak and low-light conditions, where RGB-only models are most prone to boundary degradation and missed instances, and it still delivers consistent improvements on the mixed four-light validation set, increasing $mA{P}_{0.5}$ by 2.3 points, $mA{P}_{0.5–0.95}$ by 2.4 points, and mIoU by 3.60 points while maintaining real-time inference at 105.07 FPS. The proposed system further supports counting, size estimation, and maturity analysis of harvestable tomatoes, and can be integrated with depth sensing and yield estimation to enable real-time yield prediction in practical greenhouse operations. Full article

This study is an economic evaluation of a composting facility in southeastern Spain (applying Life Cycle Costing), a key region in European horticulture with a significant availability of agricultural biomass. Composting helps reduce dependence on inorganic fertilizers, aligning with European policies that promote the transition toward organic fertilization practices. In addition, compost enhances soil health, increases soil organic carbon, and supports climate change mitigation. Despite its agronomic and environmental benefits, and the large availability of biomass in this region, there is a notable lack of literature addressing the economic costs of composting, which is the first step in assessing the sustainability of a production process. The proposed facility (production: 9000 tonnes of compost per year) utilizes pruning residues and manure to produce high-quality organic amendments. The analysis includes infrastructure, equipment, and every operational input. Likewise, the analysis also provides socio-economic indicators such as employment generation and contribution to the regional economy. Three scenarios were evaluated based on the pruning–shredding location: at the plant, at the farm with mobile equipment, and at the farm with conventional machinery. The most cost-effective option was shredding at the farm using mobile equipment, reducing the unit cost to EUR 65.19 per tonne due to the transport of a smaller volume of prunings and, therefore, lower fuel consumption. The plant also demonstrates high productivity per square metre and generates stable employment in rural areas. Overall, the findings highlight composting as a viable and competitive strategy within circular and low-carbon agricultural systems. Full article

Blueberries (Vaccinium spp.) are highly sensitive to winter chilling fulfillment, growing degree days above 7 °C (GDD7), and water balance (WB). By integrating a climate-based natural suitability index (CNSI), three-dimensional kernel density estimation, traditional and spatial Markov chains, and optimal geographic detector analysis, this study examines the spatiotemporal evolution and driving mechanisms of blueberry climatic suitability realization in 19 major producing provinces in China during 2008–2023. Results show that CNSI exhibits a stable and moderately right-skewed distribution, with partial convergence and a narrowing interprovincial gap. Suitability realization is highest in the middle and lower Yangtze River rice-growing belt, whereas the northern dryland belt and the southern subtropical mountainous belt show persistent mismatches between climatic potential and production advantages. Markov results reveal path dependence and moderate mobility, with “low–low lock-in” and “high–high club” phenomena reinforced under neighborhood effects. GeoDetector results indicate that effective facility irrigation and fertilizer input are dominant factors explaining spatial variation in CNSI, while comprehensive transportation accessibility and agricultural labor act as stable complements. Interaction analysis suggests that multi-factor synergies, particularly irrigation-centered combinations, yield strong dual-factor enhancement and near-nonlinear enhancement. These findings highlight the importance of aligning climatic suitability with adaptive infrastructure investment and region-specific management to promote sustainable production-share advantages in China’s blueberry industry. Full article

Current scheduling strategies for energy storage batteries in agricultural parks generally overlook the issue of battery lifespan degradation, which significantly undermines the system’s economic efficiency and long-term reliability. To address this problem, this paper proposes an optimal scheduling method for integrated energy systems in agricultural parks that takes into account the operational reliability of energy storage batteries. First, a battery capacity degradation model integrating both cycle aging and calendar aging is established, and the reliability of multiple components within the energy storage system is evaluated using Monte Carlo simulation. On this basis, an optimization scheduling model aimed at minimizing the total system operating cost is developed, dynamically balancing economic performance and battery service life. Finally, the proposed method is validated through a practical case study of a facility-based agricultural industrial park. The results demonstrate that, while ensuring stable system operation, the approach effectively extends the service life of energy storage equipment by 8–9 years, reduces the average daily operating cost by 61.94 yuan, and increases the power supply reliability rate to 99.921%. Full article

This paper presents a prototype of an autonomous hydrochemical monitoring system developed for large freshwater aquaculture facilities, directly addressing the need for smart monitoring in Agriculture 4.0. The proposed solution employs low-power sensor nodes based on commercially available components and long-range LoRaWAN communication to achieve continuous, scalable, and energy-efficient water quality monitoring. Each sensor module performs on-board signal preprocessing, including anomaly detection and short-term forecasting of key hydrochemical parameters. An ecological pond dynamics model incorporating an Extended Kalman Filter is used to fuse heterogeneous sensor data with predictive estimates, thus increasing measurement reliability. High-level data analysis, long-term storage, and cross-site comparison are performed on the server side. This integration enables adaptive tracking of environmental variations, supports early detection of hazardous trends associated with fish mortality risks, and allows one to explain and justify the reasoning behind every recommended corrective action. The performance of the forecasting and filtering algorithms is evaluated, and key system characteristics—including measurement accuracy, power consumption, and scalability—are discussed. Preliminary tests of the system prototype have shown that it can predict the dissolved oxygen level with $RMSE$ = 0.104 mg/L even with a minimum set of sensors. The results demonstrate that the proposed conceptual design of the system can be used as a base for real-time monitoring and predictive assessment of hydrochemical conditions in aquaculture environments. Full article

This study presents an optimization-driven design of a wireless communications network to continuously transmit environmental variables—temperature, humidity, weight, and water usage—in poultry farms. The reference site is a four-shed facility in Quito, Ecuador (each shed $120\mathrm{m}\times 12\mathrm{m}$) with a data center located $200\mathrm{m}$ from the sheds. Starting from a calibrated log-distance path-loss model, coverage is declared when the received power exceeds the receiver sensitivity of the selected technology. Gateway placement is cast as a mixed-integer optimization that minimizes deployment cost while meeting target coverage and per-gateway capacity; a capacity-aware greedy heuristic provides a robust fallback when exact solvers stall or instances become too large for interactive use. Sensing instruments are Tekon devices using the Tinymesh protocol (IEEE 802.15.4g), selected for low-power operation and suitability for elongated farm layouts. Model parameters and technology presets inform a pre-optimization sizing step—based on range and coverage probability—that seeds candidate gateway locations. The pipeline integrates MATLAB R2024b and LpSolve 5.5.2.0 for the optimization core, Radio Mobile for network-coverage simulations, and Wireshark for on-air packet analysis and verification. On the four-shed case, the algorithm identifies the number and positions of gateways that maximize coverage probability within capacity limits, reducing infrastructure while enabling continuous monitoring. The final layout derived from simulation was implemented onsite, and end-to-end tests confirmed correct operation and data delivery to the farm’s data center. By combining technology-aware modeling, optimization, and field validation, the work provides a practical blueprint to right-size wireless infrastructure for agricultural monitoring. Quantitatively, the optimization couples coverage with capacity and scales with the number of endpoints M and candidate sites N (binaries $M+N+MN$). On the four-shed case, the planner serves 72 environmental endpoints and 41 physical-variable endpoints while keeping the gateway count fixed and reducing the required link ports from 16 to 4 and from 16 to 6, respectively, corresponding to optimization gains of up to 82% and 70% versus dense baseline plans. Definitions and a measurement plan for packet delivery ratio (PDR), one-way latency, throughput, and energy per delivered sample are included; detailed long-term numerical results for these metrics are left for future work, since the present implementation was validated through short-term acceptance tests. Full article

Cultured meat has progressed from early in vitro cell culture concepts to regulatory approvals and preliminary commercialization, with recent advancements propelled by interdisciplinary innovations in cell line engineering, serum-free media, bioreactor design, and three-dimensional (3D) assembly technologies. This review synthesizes recent developments from 2023 to 2025, utilizing peer-reviewed publications, patent analyses, regulatory frameworks, and media reports to assess global preparedness for large-scale production. Asia has emerged as a leading hub, with China, Japan, South Korea, and Singapore focusing on scaffold-based 3D cultures, bioinks, and serum-free strategies, complemented by national centers and pilot facilities. The United States leverages its technological advancements and established regulatory framework, as evidenced by recent Food and Drug Administration and United States Department of Agriculture approvals. However, potential complications related to political regional bans and legislation may arise. Europe and the UK prioritize defined media, cell optimization, and structured novel-food regulations, with early commercialization primarily in pet food. Looking ahead, the industrialization of cultured meat is anticipated to be driven by process engineering and hybrid product strategies, with initial pilot-to-demonstration facilities established in countries open to alternative food products. Premium and hybrid cultured meat products are expected to enter the market first, while whole-cut cultured meat is likely to remain a premium offering into the early 2030s. Full article

Cold pressing is a sustainable oil extraction method that operates without chemical solvents, requires relatively low energy input, and preserves bioactive compounds, making it a recognized green technology in line with circular economy principles. By enabling full utilization of raw materials and valorization of by-products, it supports resource efficiency, waste reduction, and the development of bio-based products. This study provides the first comprehensive mapping of Serbia’s small-scale cold-pressed oil producers, based on data from the Central Register of Food Business Operators, local inspectorates, agricultural fairs, and social media, classified according to NUTS 2024 statistical regions. A total of 55 producers were identified, with over 60% operating as artisanal units (≤15 t/year), typically using screw presses of 20–50 kg/h capacity. Pumpkin seed was the most common raw material (30 producers), followed by sesame (21), hazelnut (20), sunflower (19), and flaxseed (19), while niche oils such as jojoba, argan, and rosehip were produced on a smaller scale. Medium and large facilities (>15 t/year) were concentrated in Vojvodina and central Serbia, focusing on high-volume seeds like sunflower and soybean. Integration of green screw press technologies, zero-kilometer supply chains, and press cake valorization positions this sector as a driver of rural development, biodiversity preservation, and environmental sustainability, providing a strong basis for targeted policy support and process optimization. Full article

Urban residents and especially children have limited contact with nature and are not sufficiently informed about the main problems of its protection and preservation. One of the aspects of increasing the environmental awareness of urban children is to familiarize them with the specifics of agricultural production. A significant problem in organizing agricultural-themed children’s gaming complexes is the creation of an appropriate infrastructure for exhibiting natural and agricultural processes and servicing visitors. One of the possible solutions to this problem is the use of used sea containers for facilities of educational and gaming infrastructure. An important characteristic of such containers is the ability to use them both individually and in various quantitative and combinatorial ways, forming the buildings necessary for exhibiting and servicing. The use of combined container groups makes it possible to organize appropriate temporary or permanent educational and gaming complexes in free territories within cities or suburbs, bringing them as close to consumers as possible. The children’s educational and game complex with agricultural themes is a set of organizationally and spatially interconnected buildings and structures that ensure the display of agricultural production processes based on the active participation of visitors. Full article

Path planning is a critical capability for unmanned aerial vehicles (UAVs) operating in complex 2D environments such as agricultural fields or indoor facilities—scenarios where flight altitude is often constrained and safe, smooth trajectories are essential. While the sampling-based Bidirectional RRT* (BI-RRT*) algorithm offers asymptotic optimality and improved computational efficiency, it frequently generates paths that lack the curvature continuity, obstacle clearance, and low turning angles required for stable drone flight. To address these limitations, this paper proposes a bi-directional rapid exploration random tree algorithm based on cooperative expansion strategy (CE-BI-RRT*) specifically designed for UAVs path planning in cluttered 2D settings. In terms of expansion, for different environments, the algorithm successively tests the direct expansion strategy, the intelligent deflection strategy and the improved artificial potential field method, as these strategies can quickly guide the two trees to the target while avoiding obstacles. In terms of ChooseParent and Rewire, the path length, path smoothness and safety distance are comprehensively considered in the path cost function, and a rotation strategy is applied to make the path away from obstacles after rewiring, so as to realize the gradual optimization of the path. The final path is further refined using a cubic Bezier curve optimization technique to ensure smooth transitions and continuous curvature. Evaluation results confirm its search performance when benchmarked against mainstream randomized motion planning algorithms. Full article

A major milestone for the European Union in reducing the environmental impact of its economy was the announcement of the European Green Deal. This strategy emphasizes that energy is the cornerstone of sustainable economic development and that its main objective is to address climate change by reducing greenhouse gas emissions. It is clear that energy production must come primarily from renewable sources. The Polish biogas market is still small compared to neighboring countries, with around 300 biogas plants, including landfill gas recovery systems and facilities at wastewater treatment plants. However, agricultural biogas plants offer significant opportunities for growth. Both the agricultural and processing industries generate large quantities of by-products that serve as good substrates for biogas production. This article presents the characteristics of one Polish province in terms of agricultural biogas potential. It discusses the availability of substrates for biogas production, including biodegradable waste and plant- and animal-based materials. On this basis, the potential for agricultural biogas production was estimated. It was found that the main obstacle to the development of agricultural biogas plants in the Lubuskie Province is the considerable fragmentation of farms. Full article

Microalgae cultivation presents a promising pathway for sustainable agricultural development in arid environments by minimizing freshwater consumption. In Saudi Arabia, where agricultural expansion coincides with extensive coastal resources, algal biotechnology has emerged as a strategic approach to optimize resource use. This study applies a Geographic Information System (GIS)-based framework integrating the Analytic Hierarchy Process (AHP) within a Multi-Criteria Decision-Making (MCDM) approach to evaluate the suitability of coastal zones for seawater-based microalgae cultivation. Suitability assessment incorporated topography, land use, seawater accessibility, proximity to CO₂ emission sources, nutrient availability, and key environmental parameters. The analysis focused on a 24,771 km² area of interest (AOI) extending from the coastline to the nearest highway. The results indicate that 56% of the AOI is suitable for cultivation, including 4728 km² classified as highly suitable and 1606 km² as very highly suitable, predominantly located near industrial CO₂ sources and wastewater treatment facilities. Areas with lower suitability remain feasible for cultivation through targeted resource management. These findings highlight the significant potential for large-scale microalgae production in Saudi Arabia, contributing to sustainable biotechnology development and agricultural diversification under the country’s Vision 2030 strategy. Full article