Search Results (779)

Implementing nature-based solutions (NbSs) for wildfire risk management and other hazards has been challenging in emerging economies due to the high costs, the lack of immediate returns on investment, and stringent inclusion criteria set by organizations like the IUCN and domain experts. To address these challenges, this exploratory study proposes a new concept: green/blue initiatives. These initiatives represent intermediate steps, encompassing small-scale, community-driven activities that can evolve into recognized NbSs over time. To explore this concept, experiences related to wildfire prevention in the Biobío region of Chile were analyzed through primary and secondary source reviews. The analysis identified three initiatives qualifying as green/blue initiatives: (1) goat grazing in Santa Juana to reduce fuel loads, (2) a restoration prevention farm model in Florida called Faro de Restauración Mahuidanche and (3) the Conservation Landscape Strategy in Nonguén. They were examined in detail using data collected from site visits and interviews. In contrast to Chile’s prevailing wildfire policies, which focus on costly, large-scale fire suppression efforts, these initiatives emphasize the importance of reframing wildfire as a manageable ecological process. Lastly, the challenges and enabling factors for adopting green/blue initiatives are discussed, highlighting their potential to pave the way for future NbS implementation in central Chile. Full article

The synchronous reference frame phase-locked loop (SRF-PLL) is widely employed for grid synchronization in wind farms. However, it may exhibit oscillations under voltage sags or improper parameter settings. These oscillations may compromise the secure integration of large-scale wind power. Therefore, mitigating the oscillations of the SRF-PLL is crucial for ensuring stable and reliable operation. To this end, this paper investigates the underlying oscillation mechanism of the SRF-PLL from local and global perspectives. By taking into account the grid voltage and control parameters, it is revealed that oscillations of the SRF-PLL can be triggered by grid voltage sags and/or the improper control parameters. More specifically, from the local perspective, the SRF-PLL exhibits distinct qualitative behaviors around its stable equilibrium points under different grid voltage amplitudes. As a result, when grid voltage sags occur, the SRF-PLL may exhibit multiple oscillation modes and experience a prolonged transient response. Furthermore, from the global viewpoint, the large-signal analysis reveals that the SRF-PLL has infinitely many asymmetrical convergence regions. However, the sizes of these asymmetrical convergence regions shrink significantly under low grid voltage amplitude and/or small control parameters. In this case, even if the parameters in the small-signal model of the SRF-PLL are well-designed, a small disturbance can shift the operating point into other regions, resulting in undesirable oscillations and a sluggish dynamic response. The validity of the theoretical analysis is further supported by experimental verification. Full article

Background/Objectives: Staphylococcus aureus is a major pathogen of concern in raw milk due to its potential to cause foodborne illness and its increasing antimicrobial resistance (AMR). In Romania, data on the occurrence and resistance patterns of S. aureus in raw sheep milk from traditional farming systems remain limited. This study investigated the presence and antimicrobial resistance of S. aureus in 106 raw sheep milk samples collected from traditional farms in the Banat region of western Romania. Methods: Coagulase-positive staphylococci (CPS) were enumerated using ISO 6888-1:2021 protocols. Isolates were identified at the species level using the Vitek 2 system and molecularly confirmed via PCR targeting the 16S rDNA and nuc genes. Methicillin resistance was assessed by detecting the mecA gene. Antimicrobial susceptibility was determined using the Vitek 2 AST-GP79 card. Results: CPS were detected in 69 samples, with S. aureus confirmed in 34.9%. The mecA gene was identified in 13.5% of S. aureus isolates, indicating the presence of methicillin-resistant S. aureus (MRSA). Resistance to at least two antimicrobials was observed in 97.3% of isolates, and 33 strains (89.2%) met the criteria for multidrug resistance (MDR). The most frequent MDR phenotype involved resistance to lincomycin, macrolides, β-lactams, tetracyclines, and aminoglycosides. Conclusions: The high prevalence of S. aureus, including MRSA and MDR strains, in raw sheep milk from traditional farms represents a potential public health risk, particularly in regions where unpasteurized dairy consumption persists. These findings underscore the need for enhanced hygiene practices, prudent antimicrobial use, and AMR monitoring in small-scale dairy systems. Full article

Postharvest losses amongst small-scale farmers in developing countries are high due to inadequate resources and infrastructure. Among the various affected crops, tomatoes are particularly vulnerable; however, studies on postharvest losses of most fruits and vegetables are limited. Therefore, this study aimed to assess postharvest tomato losses under different production systems within the small-scale supply chain using the indirect assessment (questionnaires and interviews) and direct quantification of losses. Farmers reported tomato losses due to insects (82.35%), cracks, bruises, and deformities (70.58%), and diseases (64.71%). Chemical sprays were the main form of pest and disease control reported by all farmers. The direct quantification sampling data revealed that 73.07% of the tomatoes were substandard at the farm level, with 47.92% and 25.15% categorized as medium-quality and poor-quality, respectively. The primary contributors to the losses were decay (39.92%), mechanical damage (31.32%), and blotchiness (27.99%). Postharvest losses were significantly higher under open-field production systems compared to closed tunnels. The fungi associated with decay were mainly Geotrichum, Fusarium spp., and Alternaria spp. These findings demonstrate the main drivers behind postharvest losses, which in turn highlight the critical need for intervention through training and support, including the use of postharvest loss reduction technologies to enhance food security. Full article

Non-agricultural business activity of farmers is crucial not only for stabilizing farm income but also for the multifunctional development of rural areas. Capturing changes in the level and nature of this activity supports the development of sustainable agricultural and rural policy. In this context, this study aimed to identify the scale and types of non-agricultural business activity and to recognize the main determinants of such business activities undertaken by farmers in Poland between 2002 and 2022. Sectoral-level data from the Agricultural Censuses and cyclical studies of the structure of farms and household budgets were used to approximate underlying motivations for running non-agricultural business (opportunity vs. necessity entrepreneurship). The findings indicate that, in Poland, the impact of regressive factors remains strong, pushing farmers to take on additional business activity due to the large share of small and very small farms. However, during the 21st century, a gradual spread of opportunity entrepreneurship among Polish farmers has been observed. This study highlights the rationale for supporting non-agriculture business activity motivated by progressive factors to increase the income resilience of farmer households and the sustainable development of agriculture. The article indicates the need for further research on the motives for undertaking non-agricultural economic activities by farmers and the impact of this activity on the allocation of farm resources. Full article

This paper examines the farming systems and operational structures in the Region of Western Macedonia (RWM), Greece and constructs a typology of farms based on structural, operational, and socio-economic characteristics. Agriculture remains a vital pillar of the regional economy, particularly in the context of RWM’s ongoing transition to a post-lignite development model. Using farm-level data from the 2018 Farm Accountancy Data Network (FADN), Principal Component Analysis (PCA) identified four latent dimensions of farm heterogeneity—income and productivity, asset base, land size, and labour structure. Hierarchical and K-means cluster analysis revealed three distinct farm types: (1) medium-sized, high-efficiency farms with moderate reliance on subsidies (30% of the sample); (2) small-scale, family farms with modest productivity and limited capitalisation (48%); and (3) large, asset-rich farms exhibiting structural inefficiencies and lower output per hectare (22%). These findings highlight structural vulnerabilities, particularly the predominance of undercapitalised smallholdings, and provide a data-driven foundation for Thdesigning differentiated policies that support farm resilience, generational renewal, and sustainable rural development. Full article

There is still a need to develop scenarios and models aimed at substituting fuelwood and reducing the use of fossil fuels such as liquefied petroleum gas (LPG), on which low-income rural households in the Global South often depend. The use of these fuels for cooking and heating in domestic and productive activities poses significant health and environmental risks. This study validated, in three different phases, the sustainability of a model for the production and use of biogas from the treatment of swine-rearing wastewater (WWs) on a community farm: (i) A Multi-Criteria Analysis (MCA), incorporating environmental, social/health, technical, and economic criteria, identified the main weighted criterion to C8 (use of small-scale technologies and low-cost access), with a score of 0.44 points, as well as the Tubular biodigester (Tb) as the most suitable option for the study area, scoring 8.1 points. (ii) Monitoring of the Tb over 90 days showed an average biogas production of 2.6 m³ d⁻¹, with average correlation 0.21 m³ Biogas kg Biomass⁻¹. Using the experimental biogas production rate (k = 0.0512 d⁻¹), the process was simulated with the BgMod model, achieving an average deviation of only 10.4% during the final production phase. (iii) The quantification of benefits demonstrated significant reductions in firewood use: in Scenario S1 (kitchen energy needs), biogas replaced 83.1% of firewood, while in Scenario S2 (citronella essential oil production), the substitution rate was 24.1%. In both cases, the avoided emissions amounted to 0.52 tons of CO_2eq per month. Finally, this study proposes a synthesised, community-based rural biogas framework designed for replication in regions with similar socio-environmental, technical, and economic conditions. Full article

The construction and development of digital infrastructure have emerged as a crucial indicator of national competitiveness, which holds significant importance in driving the sustained growth of the national economy and the comprehensive advancement of society. This paper explores the impact of digital infrastructure on farm households’ scale management, aiming to reveal the role and potential of digital technology in agricultural modernization. Additionally, it seeks to offer a scientific foundation for the government to formulate agricultural policies and advance agricultural modernization. Using the OLS (Ordinary Least Squares) model, moderating effect model, and other methods, this study investigates how digital infrastructure affects farm households’ scale management based on micro-level research data of 2510 farm households from the CRRS (China Rural Revitalization Survey). The following conclusions are drawn: Firstly, the enhancement of digital infrastructure can motivate farm households to expand the land management area and increase the unit output of land. Secondly, farm households’ digital literacy positively moderates the effect of digital infrastructure on their land unit output; moreover, digital skills training for farm households exhibits a positive moderating effect on the influence of digital infrastructure on their management area. Finally, there is a heterogeneity in the impact of digital infrastructure on farm households’ scale management. Specifically, the promotion of farm households’ scale management is stronger in plain areas and weaker in hilly and mountainous areas; stronger for middle-aged and older and small-scale farm households; and weaker for youth groups and large-scale farm households. Based on this, this paper suggests increasing the investment in digital infrastructure construction, improving farm households’ digital literacy, carrying out digital skills training, and formulating differentiated regional policies for reference. Full article

The salinization of agricultural soils is a serious threat to farming and ecological balance in arid and semi-arid regions. Accurate estimation of soil water-soluble ions (calcium, carbonate, magnesium, and sulfate) is necessary for correct monitoring of soil salinization and sustainable land management. Hyperspectral ground-based data are valuable in soil salinization monitoring, but the acquisition cost is high, and the coverage is small. Therefore, this study proposes a two-stage deep learning framework with multispectral remote-sensing images. First, the wavelet transform is used to enhance the Transformer and extract fine-grained spectral features to reconstruct the ground-based hyperspectral data. A comparison of ground-based hyperspectral data shows that the reconstructed spectra match the measured data in the 450–998 nm range, with R² up to 0.98 and MSE = 0.31. This high similarity compensates for the low spectral resolution and weak feature expression of multispectral remote-sensing data. Subsequently, this enhanced spectral information was integrated and fed into a novel multiscale self-attentive Transformer model (MSATransformer) to invert four water-soluble ions. Compared with BPANN, MLP, and the standard Transformer model, our model remains robust across different spectra, achieving an R² of up to 0.95 and reducing the average relative error by more than 30%. Among them, for the strongly responsive ions magnesium and sulfate, R² reaches 0.92 and 0.95 (with RMSE of 0.13 and 0.29 g/kg, respectively). For the weakly responsive ions calcium and carbonate, R² stays above 0.80 (RMSE is below 0.40 g/kg). The MSATransformer framework provides a low-cost and high-accuracy solution to monitor soil salinization at large scales and supports precision farmland management. Full article

Small-scale farms deserve attention and support because they play crucial and important roles. Apart from ensuring provision of food security, they also provide other economic, environmental, and social–cultural benefits. In the United States of America, these farms are agriculturally, culturally, and geographically different. They have varied needs that trigger an array of distinct biophysical, socioeconomic, and institutional challenges. The effects of these challenges are exacerbated by economic uncertainty, technological advancements, climate change, and other environmental concerns. To provide ideal services to the small-scale farm audience, it is necessary to understand these challenges and opportunities that can be leveraged to enhance their productivity and profitability. This article reviews the challenges faced by small-scale farming in the United States of America. It then reviews possible pathways to enhance their productivity and profitability. The review revealed that U.S. small-scale farms face several challenges. They include accessing farmland, credit and capital, lack of knowledge and skills, and technology adoption. Others are difficulties to insure, competition from corporations, and environmental uncertainties associated with climate change. The paper then reviews key pathways to enhance small-scale farmers’ capacities and resilience with a positive impact on their productivity and profitability. They are enhanced cooperative extension services, incentivization, strategic marketing, annexing technology, and government support, among others. Based on the diversity of farms and their needs, responses should be targeted towards individual needs. Since small-scale farm products have an effect on human health and dietary patterns, strategies to increase productivity should be linked to nutrition and health. Full article

The common octopus (Octopus vulgaris) supports one of the most valuable small-scale fisheries in Portugal, particularly in the Algarve region, with substantial socioeconomic implications. This species holds significant potential for human consumption due to its low lipid content, favorable fatty acid profile, high-quality protein, and essential microelements. This study aimed to provide a comprehensive characterization of octopus specimens landed in two key Algarve fishing areas—Barlavento/Windward (Alvor Harbour) and Sotavento/Leeward (Fuzeta Harbour). We assessed their nutritional value, focusing on protein quality, lipid indexes, trace minerals, and essential vitamins, as well as overall safety and quality. All regulated contaminants and additional potential risks were also evaluated, yielding fully satisfactory safety results. The research was conducted within the framework of the European Sea2See project, which aims to enhance consumer trust and acceptance of sustainably harvested or farmed seafood in Europe. Our findings demonstrate that Algarve octopus is a nutritionally rich seafood product, promoting cardiovascular health and general well-being. Full article

The high cost of mushroom spawn remains a critical constraint to economically viable mushroom cultivation, particularly for small-scale farmers. This study investigated four spawn types, including stick (giant mimosa stalks, GMS), sawdust, sorghum, and liquid culture as inoculum sources for 10 edible mushroom species. The results indicated that GMS stick spawn provides excellent conditions for the mycelial growth of seven species, outperforming other spawn types in terms of colonization rate and pinhead formation. Mushrooms grown on GMS substrate demonstrated rapid development, with full colonization occurring within 11 to 26 days and pinhead initiation between 18 and 47 days, depending on the species. Among the mushroom species tested, Schizophyllum commune exhibited the fastest growth, reaching full colonization in 11 days and forming pinheads after 18 days of inoculation. In comparison, Auricularia polytricha showed the slowest development. Economically, GMS spawn was the most cost-effective at 0.074 USD per unit, significantly lower than sawdust (0.24 USD), sorghum (0.29 USD), and potato dextrose broth (PDB; 2.80 USD). The conversion from PDB with GMS could reduce industrial inoculum costs from 35,000 USD to 600 USD annually. These findings demonstrate the potential of GMS as an effective, low-cost, and sustainable spawn option that can enhance mycelial growth and support eco-friendly farming practices. Full article

Small-scale fisheries and aquaculture play a crucial role in securing food, income, and nutrition for millions, especially in the Global South. Rural small-scale aquaculture (SSA) is characterized by limited investment and technical training among farmers, diversification and dispersion of farms over large areas, reduced access to competitive markets for inputs and products, and family labor. Small-scale integrated circular aquaponic (ICAq) systems, in which systems’ component outputs are transformed into component inputs, have significant potential to increase circularity and promote economic development, especially in a rural context. We offer an integrated and comprehensive approach centered on aquaponics or aquaponic farming for small-scale aquaculture units. It aims to identify and describe a series of circular processes and causal links that can be implemented based on deep study in SSA and ICAq. Circular processes to treat by-products in ICAq include components like composting, vermicomposting, aerobic and anaerobic digestion, silage, and insect production. These processes can produce ICAq inputs such as seedling substrates, plant fertilizers, bioenergy, or feed ingredients. In addition, the plant component can supply therapeutic compounds. Further research on characterization of aquaponic components outputs and its quantifications, the impact of using circular inputs generated within the ICAq, and the technical feasibility and economic viability of circular processes in the context of SSA is needed. Full article

This study provides a comprehensive panorama of wastewater treatment on swine farms in Pará de Minas, MG, focusing on the performance of the anaerobic digester technologies adopted. Considering the economic and environmental importance of swine production, wastewater treatment is critical for mitigating environmental impacts while providing renewable energy opportunities. Data compilation from the Minas Gerais Institute of Agriculture (IMA), technical visits, and physicochemical analyses were conducted. Our results indicate that the region has significant potential to increase biogas production by expanding the number of plants and improving the efficiency of existing systems. Investments in scalable technological solutions tailored for small-scale operations are essential to enhance both wastewater treatment and biogas generation. This study demonstrates the potential for new business opportunities within the biogas value chain in Brazilian agribusiness. Full article

Reproductive efficiency is a critical determinant of productivity and profitability in sheep farming. Traditional selection methods have largely relied on phenotypic traits and historical reproductive records, which are often limited by subjectivity and delayed feedback. Recent advancements in artificial intelligence (AI), including video tracking, wearable sensors, and machine learning (ML) algorithms, offer new opportunities to identify behavior-based indicators linked to key reproductive traits such as estrus, lambing, and maternal behavior. This review synthesizes the current research on AI-powered behavioral monitoring tools and proposes a conceptual model, ReproBehaviorNet, that maps age- and sex-specific behaviors to biological processes and AI applications, supporting real-time decision-making in both intensive and semi-intensive systems. The integration of accelerometers, GPS systems, and computer vision models enables continuous, non-invasive monitoring, leading to earlier detection of reproductive events and greater breeding precision. However, the implementation of such technologies also presents challenges, including the need for high-quality data, a costly infrastructure, and technical expertise that may limit access for small-scale producers. Despite these barriers, AI-assisted behavioral phenotyping has the potential to improve genetic progress, animal welfare, and sustainability. Interdisciplinary collaboration and responsible innovation are essential to ensure the equitable and effective adoption of these technologies in diverse farming contexts. Full article