Search Results (604)

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

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 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

Variable-rate nitrogen (VR-N) application allows farmers to optimize nitrogen (N) input site-specifically within field boundaries, enhancing both economic efficiency and environmental sustainability. In this study, VR-N technology was applied to durum wheat in two small-scale commercial fields (3–4 ha each) located in distinct agro-climatic zones of Thessaly, central Greece. A real-time VR-N application algorithm was used to calculate N rates based on easily obtainable near-real-time data from unmanned aerial vehicle (UAV) imagery, tailored to the crop’s actual needs. VR-N implementation was carried out using conventional fertilizer spreaders equipped to read prescription maps. Results showed that VR-N reduced N input by up to 49.6% compared to the conventional uniform-rate N (UR-N) application, with no significant impact on wheat yield or grain quality. In one of the fields, the improved gain of VR-N when compared to UR-N was 7.2%, corresponding to an economic gain of EUR 163.8 ha⁻¹, while in the second field—where growing conditions were less favorable—no considerable VR-N economic gain was observed. Environmental benefits were also notable. The carbon footprint (CF) of the wheat crop was reduced by 6.4% to 22.0%, and residual soil nitrate (NO₃⁻) levels at harvest were 13.6% to 36.1% lower in VR-N zones compared to UR-N zones. These findings suggest a decreased risk of NO₃⁻ leaching and ground water contamination. Overall, the study supports the viability of VR-N as a practical and scalable approach to improve N use efficiency (NUE) and reduce the environmental impact of wheat cultivation which could be readily adopted by farmers. Full article

The development of a forestry carbon sink project is an important way to achieve carbon neutrality and carbon reduction, and the collective forest carbon sink project is an important part of China’s forestry carbon sink project. As the main management entity of collective forests, whether farmers are willing to produce forestry carbon sinks is directly related to the implementation effect of the project. In this paper, a partial equilibrium model of farmers’ forestry production behavior was established based on production function and utility function, and the path to enhance farmers’ willingness to produce forestry carbon sink through forestry carbon sink projects was analyzed in combination with forest ecological management theory. In terms of empirical analysis, the PSM-DID econometric model was established based on the survey data of LY in Zhejiang Province, China, and the following conclusions were drawn: (1) With the receipt of revenues from forestry carbon sequestration projects and partial cost-sharing by the government, farmers’ participation in forestry carbon sink projects can save investment in forest land management. (2) The saved forestry production costs and forestry carbon sink project subsidies can make up for the loss of farmers’ timber income, so that the net income of forestry will not be significantly reduced. (3) The forestry production factors saved by farmers can be transferred to non-agricultural sectors and increase non-agricultural net income, so that the net income of rural households participating in forestry carbon sink projects will increase. The forestry carbon sink project can improve the utility level of farmers and increase the willingness of farmers to produce forestry carbon sinks by delivering income to farmers and saving forestry production factors. This study demonstrates that a well-designed forestry carbon sink compensation mechanism, combined with an optimized allocation of production factors, can effectively enhance farmers’ willingness to participate. This insight is also applicable to countries or regions that rely on small-scale forestry operations. Full article

American adults struggle with accurately assessing the quality of their diet, with the majority overrating their diet quality. Thus, the objective of the study was to explore what individuals think about when asked to rate their diet quality. Virtual focus groups were conducted from October 2023 to April 2024, using a semi-structured interview with open-ended questions. Convenience samples of small-scale farmers, school food service directors, health clinic patients, and university students and staff in Mississippi and Arkansas participated (N = 27). Themes and subthemes from NVivo-transcribed discussions were identified and coded inductively. Four subthemes emerged for description of diet: balance, consideration for others, convenience, and location. Four subthemes emerged for quality of diet: availability/access, culture/tradition, health considerations, and making better choices. Three subthemes emerged for healthy food: composition/preparation, nourishing benefits, and taste/flavor. Three subthemes emerged for unhealthy food: addicting/overconsumption, composition/preparation, and undesirable effects. Three subthemes emerged for nutrition knowledge: audience specific, general knowledge, and ambivalence. Three subthemes emerged for food shopping: food types, family influence/preference, and planning. Factors shaping how individuals perceive their diet quality are complex with intertwining components. Understanding the complexity involved in self-perceptions of diet quality will help us better quantify perceptions and link them to measurable outcomes. Full article

This study investigates the influence of agricultural mechanization on maize productivity in Tanzania’s Ruvuma region, a major maize-producing area vital to national food security. It addresses gaps in understanding the cumulative effects of mechanization across the maize production cycle and identifies region-specific barriers to adoption among smallholder farmers. Focusing on five key stages—land preparation, planting, plant protection, harvesting, and drying—this research evaluated mechanization uptake at each stage and its relationship with yield disparities. Statistical analyses using Python libraries included regression modeling, ANOVA, and hypothesis testing to quantify mechanization–yield relationships, controlling for farm size and socioeconomic factors, revealing a strong positive correlation between mechanization and maize yields (r = 0.86; p < 0.01). Mechanized land preparation, planting, and plant protection significantly boosted productivity (β = 0.75–0.35; p < 0.001). However, harvesting and drying mechanization showed negligible impacts (p > 0.05), likely due to limited adoption by smallholders combined with statistical constraints arising from the small sample size of large-scale farms (n = 20). Large-scale farms achieved 45% higher yields than smallholders (2.9 vs. 2.0 tons/acre; p < 0.001), reflecting systemic inequities in access. These inequities are underscored by the barriers faced by smallholders, who constitute 70% of farmers yet encounter challenges, including high equipment costs, limited credit access, and insufficient technical knowledge. This study advances innovation diffusion theory by demonstrating how inequitable resource access perpetuates low mechanization uptake in smallholder systems. It underscores the need for context-specific, equity-focused interventions. These include cooperative mechanization models for high-impact stages (land preparation and planting); farmer training programs; and policy measures such as targeted subsidies for harvesting equipment and expanded rural credit systems. Public–private partnerships could democratize mechanization access, bridging yield gaps and enhancing food security. These findings advocate for strategies prioritizing smallholder inclusion to sustainably improve Tanzania’s maize productivity. Full article

Given the serious economic burden that citrus diseases impose on fruit farmers and related industries, achieving rapid and accurate disease detection is particularly crucial. In response to the challenges posed by resource-limited platforms and complex backgrounds, this paper designs and proposes a lightweight method for the identification and localization of citrus diseases based on the RT-DETR-r18 model—GYS-RT-DETR. This paper proposes an optimization method for target detection that significantly enhances model performance through multi-dimensional technology integration. First, this paper introduces the following innovations in model structure: (1) A Gather-and-Distribute Mechanism is introduced in the Neck section, which effectively enhances the model’s ability to detect medium to large targets through global feature fusion and high-level information injection.(2) Scale Sequence Feature Fusion (SSFF) is used to optimize the Neck structure to improve the detection performance of the model for small targets in complex environments. (3) The Focaler-ShapeIoU loss function is used to solve the problems of unbalanced training samples and inaccurate positioning. Secondly, the model adopts two model optimization strategies: (1) The Group_taylor local pruning algorithm is used to reduce memory occupation and the number of computing parameters of the model. (2) The feature-logic knowledge distillation framework is proposed and adopted to solve the problem of information loss caused by the structural difference between teachers and students, and to ensure a good detection performance, while realizing the lightweight character of the model. The experimental results show that the GYS-RT-DETR model has a precision of 79.1%, a recall of 77.9%, an F1 score of 78.0%, a model size of 23.0 MB, and an mAP value of 77.8%. Compared to the original model, the precision, recall, the F1 score, the mAP value, and the FPS value have improved by 3.5%, 5.3%, 5.0%, 5.3%, and 10.3 f/s, respectively. Additionally, the memory usage of the GYS-RT-DETR model has decreased by 25.5 MB compared to the original model. The GYS-RT-DETR model proposed in this article can effectively detect various citrus diseases in complex backgrounds, addressing the time-consuming nature of manual detection and improving the accuracy of model detection, thereby providing an effective theoretical basis for the automated detection of citrus diseases. Full article

The green transition of smallholder farmers is a critical component in expanding the scale of green agricultural production in China. This research investigates how Science and Technology Backyards facilitate the ecological transformation process for small-scale agricultural producers by developing a three-party evolutionary game framework that incorporates Science and Technology Backyards (STBs), smallholder farmers, and research institutions. The main findings are as follows: (1) Under specific parameter conditions, the system converges to two stable equilibrium points: (0,0,0), where none of the three parties engage in cooperation, and (1,1,1), where full participation and collaboration among all parties are achieved. (2) Science and Technology Backyards exhibit a strong tendency to avoid bearing research costs and demonstrate high sensitivity to economic returns, indicating a clear preference for profit maximization. (3) Research institutes can effectively reduce the cost of technology trials through cooperation with Science and Technology Backyards; however, excessively high trial costs significantly weaken the willingness to collaborate. This study provides a scientific basis for decision-making by stakeholders involved in Science and Technology Backyard initiatives and offers theoretical support for advancing the green transformation of smallholder farmers through the Science and Technology Backyard. Full article

The popularity of small-scale and local fruit and vegetable production has increased in recent years due to perceived economic, environmental, and social benefits. However, these operations face contamination risks that both consumers and small-scale producers may underestimate. The present study aimed to assess the microbiological and chemical hazards on fruit, vegetables, soil, and water samples from small-scale farms in north-western Portugal during pre-harvest activities. Additionally, the study investigated farmers’ non-compliance with food safety regulations and good agricultural practices (GAPs), exploring how their behaviour might contribute to the identified hazards. A before-and-after analysis of non-compliant behaviours was conducted to determine the impact of training on improving food safety practices. The analysis identified the presence of pathogenic bacteria, pesticides, flame retardant residues, nitrates, and heavy metals. Lead (Pb) concentrations exceeded EU limits in organic carrots from one producer (0.156 ± 0.043 mg/kg) and in chard from another (0.450 ± 0.126 mg/kg). Cadmium (Cd) levels were also above regulatory thresholds in bell peppers (0.023 ± 0.009 mg/kg) and organic tomatoes (0.026 ± 0.015 mg/kg) from two different producers. Elevated levels of heavy metals were detected in irrigation water from two sites, with zinc (Zn) at 0.2503 ± 0.0075 mg/L and Pb at 0.0218 ± 0.0073 mg/L. Among food samples, the most prevalent microorganisms were Pseudomonas spp. (88.2%), Bacillus cereus (76.5%), and aerobic mesophilic bacteria (100%). Phosphorus flame retardants (PFRs), particularly tris(2-butoxyethyl) phosphate (TBEP), were detected in all food and soil samples. Some EU-banned pesticides were detected in food and soil samples, but at levels below the maximum residue limits (MRLs). Chlorpyrifos (35.3%) and p,p’-DDD (23.5%) were the most detected pesticides in food samples. After the training, GAP behaviour improved, particularly that related to hygiene. However, issues related to record-keeping and soil and water analyses persisted, indicating ongoing challenges in achieving full compliance. Full article

Vegetables are commodities frequently sold in local markets and have been associated with foodborne outbreaks in short and local supply outlets worldwide. These outbreaks could potentially be mitigated through the implementation of good handling practices (GHPs) at points of sale. Numerous studies have assessed microbiological contamination in small-scale vegetable outlets in developing countries. In contrast, research on these risks in developed countries is comparatively scarce. However, with the increasing demand for vegetables, along with the increasing popularity of local markets, there is potential for an increase in foodborne outbreaks in developed countries. This study aimed to perform a microbiological assessment in local and short supply chain outlets of farmers in Portugal, as a case study, and to observe behaviors regarding GHPs in these outlets. The study was performed before and after the implementation of improved GHPs. This research employed quantitative analysis to measure the microbial load on vegetables, bench surfaces, and vendors’ hands. Additionally, a qualitative analysis was conducted to understand farmers’ behavior regarding GHPs using observational methods. Microbial hazards were detected in vegetables, on surfaces, and on hands both before and after the implementation of these practices, although the implementation of GHPs reduced the number of contaminations potentially associated with the practices used at the outlets. The results of this study highlight the importance of implementing GHPs in local and short supply chain markets for vegetables and fruits in developed countries, not only to protect consumers’ health, but also the farmers’ businesses. Full article

Accurate estimation of soil moisture content (SMC) is crucial for effective water management, enabling improved monitoring of water stress and a deeper understanding of hydrological processes. While satellite remote sensing provides broad coverage, its spatial resolution often limits its ability to capture small-scale variations in SMC, especially in landscapes with diverse land-cover types. Unmanned aerial vehicles (UAVs) equipped with hyperspectral sensors offer a promising solution to overcome this limitation. This study compares the effectiveness of Sentinel-2, Landsat-8/9 multispectral data and UAV hyperspectral data (from 339.6 nm to 1028.8 nm with spectral bands) in estimating SMC in a research farm consisting of bare soil, cropland and grassland. A DJI Matrice 100 UAV equipped with a hyperspectral spectrometer collected data on 14 field campaigns, synchronized with satellite overflights. Five machine-learning algorithms including extreme learning machines (ELMs), Gaussian process regression (GPR), partial least squares regression (PLSR), support vector regression (SVR) and artificial neural network (ANN) were used to estimate SMC, focusing on the influence of land cover on the accuracy of SMC estimation. The findings indicated that GPR outperformed the other models when using Landsat-8/9 and hyperspectral photography data, demonstrating a tight correlation with the observed SMC (R² = 0.64 and 0.89, respectively). For Sentinel-2 data, ELM showed the highest correlation, with an R² value of 0.46. In addition, a comparative analysis showed that the UAV hyperspectral data outperformed both satellite sources due to better spatial and spectral resolution. In addition, the Landsat-8/9 data outperformed the Sentinel-2 data in terms of SMC estimation accuracy. For the different land-cover types, all types of remote-sensing data showed the highest accuracy for bare soil compared to cropland and grassland. This research highlights the potential of integrating UAV-based spectroscopy and machine-learning techniques as complementary tools to satellite platforms for precise SMC monitoring. The findings contribute to the further development of remote-sensing methods and improve the understanding of SMC dynamics in heterogeneous landscapes, with significant implications for precision agriculture. By enhancing the SMC estimation accuracy at high spatial resolution, this approach can optimize irrigation practices, improve cropping strategies and contribute to sustainable agricultural practices, ultimately enabling better decision-making for farmers and land managers. However, its broader applicability depends on factors such as scalability and performance under different conditions. Full article

The recent spread of foreign animal diseases (FADs) such as foot-and-mouth disease and African swine fever emphasizes the need to conduct comprehensive surveillance to detect a potential disease introduction as soon as possible. The United States is currently free of many important FADs of swine, and many preparedness initiatives have raised awareness amongst the commercial, intensive swine industry. However, the awareness and engagement of small-scale swine farmers regarding disease surveillance and passive reporting is not well known. This scoping review was conducted to identify and characterize sources of evidence on the practices and attitudes of small-scale swine farmers and owners in the United States regarding pig health and disease management, surveillance, and veterinary care use, and secondarily to characterize information seeking and communication behaviors. Sources of evidence were found through keyword searches of online databases, citation matching, and Sustainable Agriculture Research and Education project reports. Eligibility criteria included being conducted on or with US small-scale (defined in this review as less than 1000 pigs) or non-intensive swine farms and containing information pertinent to the objectives of the review. Seventeen sources were included in the final review. Regular disease monitoring and surveillance practices were not commonly reported, and multiple sources reported little to no incidence of disease occurrence in small-scale swine farms. Reported veterinary use and access was variable, and multiple sources reported that the choice to use veterinary care was affected by its perceived cost, value, and accessibility. Future research and outreach should aim to discern key factors affecting farmer’s decisions to use a veterinarian, improve their awareness and prioritization of swine diseases, and develop small-scale appropriate disease surveillance protocols. Ultimately, this will help small-scale swine farmers to protect the health of their pigs and improve FAD surveillance in the US. Full article