Search Results (187)

The high energy consumption of conventional mixers equipped with active mixing elements necessitates the development of more efficient technologies for mixing bulk materials and feed mixtures. This study presents a gravity-driven mixing approach based on the rotation of an inclined cylindrical chamber, eliminating the need for active mixing elements. During chamber rotation, the mixture components move toward both end walls while simultaneously undergoing a circular motion along the inner cylindrical surface. This movement intensifies the mixing process and reduces energy consumption, thereby providing an energy-efficient gravity-based mixing approach that operates without active mixing elements. Laboratory experiments were conducted to determine the key physical and mechanical properties of the sapropel, organic fertilizer, and compound feed (formulation K-60-1). The measured values were as follows: velocity on an inclined steel surface, 0.65–1.21 m/s; coefficient of friction, 0.40–0.91; bulk density, 453–1166 kg/m³; and angle of repose, 36–39°. The experimental results confirmed the validity and adequacy of the developed analytical relationships. A structural and technological design of the gravity mixer was developed, and an experimental prototype was manufactured. Analytical relationships were obtained to determine the critical rotational speed of the chamber, particle movement velocity, and the power required for the mixing process. Under optimal operating conditions, the mixture uniformity reached 95.7% after 4 min of mixing. The mixer productivity was 0.95 t/h, while the specific energy consumption was 0.5 kWh/t, which is 2.5 times lower than that of conventional mixers equipped with active mixing elements. The obtained results confirm the feasibility and effectiveness of the proposed gravity-based mixing method for the preparation of feed and organomineral mixtures under the operating conditions of small-scale farms. Full article

This study presents the design, development, and evaluation of an integrated solar-powered seed sowing and fertilizer-watering system to enhance planting efficiency, improve resource utilization, and reduce labor in small-scale agriculture. The prototype features a 600-watt photovoltaic panel, DC motors, and a manual mechanical dispensing mechanism, enabling automated seed placement, water distribution, and fertilizer application in off-grid farm environments. Development was guided by a product-based design approach using locally sourced materials to ensure cost-effectiveness, maintainability, and accessibility for rural users. Field simulations and performance trials assessed charging efficiency, seed sowing accuracy, irrigation flow rate, and fertilizer dispensing precision. Results showed high consistency in operational performance, including up to 99% seed placement accuracy, efficient water delivery, and reliable fertilizer timing, with solar energy providing adequate power storage during periods of peak irradiance. Expert evaluations using a standardized instrument demonstrated strong agreement on the system’s usability, material availability, ergonomic features, modularity, and overall functional design. Findings indicate that the system can minimize manual labor, reduce operational costs, and offer a practical transition toward clean-energy–assisted mechanization in agriculture. The study concludes that integrating renewable energy into essential farm operations can contribute to sustainable productivity and recommends future enhancements through sensor integration, increased battery capacity, and adaptive control mechanisms to support wider agricultural adoption. Full article

Blueberry production has rapidly expanded over the past decade, accompanied by growing demand for efficient and accurate methods to monitor the flowering and fruiting phases of blueberry development, which has a direct impact on yield potential. Accurate determination of blueberry phenology enables growers to make data-driven decisions on freeze protection applications and harvest windows. In addition, objective phenology data of blueberry mapping populations will provide high-quality phenotype data for the discovery of genetic mechanisms regulating blueberry flowering and fruiting times. Traditional approaches, such as manual counting and visual ratings, are labor-intensive and subjective in capturing variation across genotypes. Recent progress in computer vision and deep learning has enabled automated flower detection, but most existing studies on blueberries remain restricted to narrow flowering windows or close-up images, limiting their application at the bush level and across the seasonal development. In this study, we developed BerryFlowerNet, a customized YOLO-based model to detect and count blueberry flower clusters from bud to green fruit stages. A comprehensive dataset was collected on three dates using a field phenotyping robot, covering five flowering stages. The integration of CFNet, a custom module fusing shallow spatial features, and PIoU loss improved the detection performance. Additionally, the Slicing Aided Hyper Inference algorithm was employed to address small-object detection in bush-level images. Experimental results demonstrated that BerryFlowerNet outperformed the baseline YOLO model and three additional detectors, achieving an average mAP0.5 of 0.644 across five independent training runs. The model achieved an accuracy of 0.88 when predicting blueberry flowering stages, indicating its effectiveness and accuracy. Additionally, the results of the bush-level image analysis showed the capability of the model to capture genotype-level differences in flowering dynamics. Overall, this approach offers new opportunities for growers and breeders to determine blueberry phenological development that is critical for optimizing on-farm management strategies and advancing precision phenotyping to facilitate the development of climate-resilient blueberries. Full article

Improving cultivated land use efficiency is widely regarded as a core issue in ensuring national food security. As one of the key policy instruments supporting agricultural development, agricultural subsidies are considered to play an important role in promoting cultivated land use efficiency. Using micro-survey data from 449 farm households in a typical black soil region of Heilongjiang Province, this study employs the stochastic frontier analysis (SFA) model, the fractional logit model, and the mediation effect model to explore the potential impact of agricultural subsidies on black soil cultivated land use efficiency, as well as the potential mediating pathway at farm scale. The results suggest the following conclusions: (1) Different types of agricultural subsidies appear to have heterogeneous effects on black soil cultivated land use efficiency. Specifically, producer subsidies and total agricultural subsidies appear to exhibit nonlinear relationships with black soil cultivated land use efficiency; however, within the sample range, the overall effects tend to be negative, whereas cultivated land fertility protection subsidies are also associated with lower black soil cultivated land use efficiency. (2) Farm scale appears to serve as a potential mediating pathway linking producer subsidies and total agricultural subsidies to cultivated land use efficiency. (3) Under different conditions of land fragmentation and farm scale, the mediating pathway at farm scale appears to vary. A mediating pathway is observed among highly fragmented landholdings and small-scale farmers, whereas it is not evident among low fragmentation landholdings and large-scale farmers. Based on these findings, this study suggests that the study area may consider optimizing the structure of agricultural subsidies to promote moderate-scale farming and to improve the coordination mechanism between agricultural technical training and regulatory supervision in order to enhance black soil cultivated land use efficiency. Full article

The dominant agri-food system’s well-documented failures—biodiversity loss, deepening rural inequalities, and the erosion of small-scale farming livelihoods—have elevated SSE initiatives and social innovation in the agri-food sector and bioeconomy from a niche policy concern to a structural priority. This paper examines how SSE arrangements drive meaningful transformation in agri-food chains while advancing sustainable development at local and regional scales. Through a narrative review of interdisciplinary peer-reviewed literature and key institutional sources, the paper synthesizes evidence that SSE initiatives generate transformation through three interconnected mechanisms: (a) the reconfiguration of governance structures; (b) the deepening of producer–consumer relationships through spatial proximity and relational transparency; and (c) the more equitable redistribution of value across agri-food territories. These findings suggest that place-based SSE models occupy a central—rather than peripheral—role in sustainability transitions and local development. The paper presents a structured analytical framework linking SSE practices to agri-food chain transformation and develops nine concrete policy implications for scaling and sustaining SSE innovations through coordinated collaboration among public, private, and social economy stakeholders. The findings contribute to a sharper understanding of the conditions under which SSE-driven models can foster sustainable, socially inclusive, and community-oriented agri-food systems and of why the solidarity dimension, rather than organisational form alone, is the decisive criterion for identifying genuinely transformative initiatives. Full article

Infectious pancreatic necrosis virus (IPNV), a member of the family Birnaviridae, is a major pathogen of farmed salmonids and an important model in fish virology. Despite its small genome, which encodes only five viral proteins, IPNV exhibits complex molecular processes that govern genome expression, replication, and particle assembly. Comprehensive descriptions of the molecular biology and replication cycle of IPNV were largely established in reviews published in the mid-1990s, whereas more recent reviews have primarily focused on virulence determinants, epidemiology, or host–virus interactions. This review provides an updated synthesis of available experimental knowledge on the molecular biology of IPNV by integrating classical and recent studies addressing virion architecture, genome organization, and the functions of viral proteins. Particular attention is given to the molecular events involved in the viral replication cycle, including virus entry, genome transcription, translation and replication in the cytoplasm, polyprotein processing by the viral protease, and the coordination between genome replication and virion assembly. When appropriate, experimental observations from the related Avibirnavirus infectious bursal disease virus are considered to provide additional context for molecular mechanisms conserved within the family Birnaviridae. Together, these studies outline the current understanding of the molecular processes governing IPNV replication and morphogenesis. Full article

Agriculture in dryland regions faces increasing pressure from climate variability, water scarcity, and competing urban and environmental demands. A recent basin-wide technical analysis for the Rio Grande/Rio Bravo in the United States of America (USA) and Mexico shows that consumptive water use in the river system overall is on an unsustainable path. The Middle Rio Grande Basin (MRGB) of central New Mexico (USA) exemplifies these sustainability challenges, where irrigated agriculture persists despite low precipitation, high evaporative demand, and prolonged drought. This study provides analytical spatial description of irrigated agriculture in the MRGB, examining farm size distribution, crop composition, groundwater access, and consumptive water use measured by evapotranspiration (ET) and effective ET. Using 2021 remotely sensed crops and ET data, groundwater well records, and GIS-based aggregation to the irrigator farm level, the analysis reveals a highly fragmented agricultural landscape dominated numerically by micro-scale and small farms, which together account for 55.9% of total agricultural ET. Alfalfa and other hay crops occupy nearly three-quarters of irrigated acreage and consume 74% of total ET, reflecting the prevalence of forage production. Groundwater access is highly uneven, with most wells concentrated among large farms, creating resilient disparities. The findings highlight that consumptive agricultural water use in the MRGB is diffuse rather than concentrated: non-commercial farms (<12 hectares) account for 55.9% of basin-wide ET, while commercial farms contribute only 14.4% despite occupying about one-fifth of irrigated land. This complicates water conservation efforts. Resilient management strategies must therefore engage thousands of small, largely non-commercial irrigators through mechanisms that recognize both hydrological and spatial realities. The study provides an empirical basis for designing sustainable irrigation and water-management strategies in dryland agricultural systems facing increasing climatic and institutional pressures. Full article

Collective action serves as a critical mechanism for addressing deficiencies in small-scale irrigation infrastructure and fostering a virtuous cycle of their operation and maintenance. Village leaders, as central figures in organizing and mobilizing farmers toward collective action, play a pivotal role in shaping participatory irrigation management (PIM) outcomes through their public leadership. Drawing on micro-survey data from 723 farm households across Ningxia, Shanxi, and Shandong provinces in China’s Yellow River basin, this study employed a multi-group structural equation model (SEM) to analyze the impact of public leadership on collective action in PIM. The findings indicate that: (1) public leadership is directly associated with collective action, with a direct effect of 0.530; (2) public leadership indirectly enhances collective action through mediating variables—cadre–mass relationship, institutional trust, and grassroots democracy—with an indirect effect of 0.045; and (3) the personal characteristics of village leaders moderate the influence of public leadership on collective action. Specifically, public leadership exerts a strong effect when leaders belong to the village elite, possess a least a high school education, or are not members of the village’s major clan. These insights suggest that policymakers should explicitly consider public leadership in fostering collective action within the PIM framework. Full article

Agro-ecosystem approaches are increasingly promoted as integrated solutions for sustainable land use, climate mitigation, and food security, yet concerns remain that market-based instruments may systematically exclude resource-poor smallholder farmers. Using microdata from 8894 households participating in Kenya’s long-running International Small Group and Tree Planting Program, this study examines how institutional and organizational arrangements shape access to agricultural carbon markets and associated sustainable land management practices. We document a participation paradox: farmers in the lowest income quartile exhibit significantly higher adoption than the wealthiest quartile (92.4% vs. 86.3%), challenging conventional resource-based targeting assumptions. Three distinct agro-ecosystem participation pathways are inferred using a Gaussian Mixture Model (GMM) estimated over a feature set of organizational, financial-access, and farm/household characteristics (income, farm size, financial access, crop diversity, livestock holdings, education, organizational membership, and leadership position). A Mainstream pathway (60.2%) reflects resource-driven adoption; an Innovative pathway (32.4%) is associated with high participation among low-income farmers through organizational membership, leadership, and collective action; and a Constrained pathway (7.5%) captures persistent exclusion. Organizational membership is strongly associated with high-adoption pathways, universally present among Mainstream and Innovative farmers and absent among Constrained farmers; readers should note that membership is partly definitional in the clustering procedure, so this association reflects the pathway construction as well as empirical patterns. Leadership roles are associated with substantially increased access to non-monetary benefit streams (OR = 2.13), including training, seedlings, and community infrastructure. These alternative compensation mechanisms are spatially clustered and strongly associated with enrollment, suggesting localized institutional capacity effects. Importantly, the Innovative pathway is associated with superior agro-ecosystem outcomes, including higher tree densities and a greater uptake of conservation farming practices, suggesting possible complementarities between inclusion and ecological performance. Women are overrepresented within this pathway, highlighting the equity potential of organizational channels. Overall, the findings suggest that strengthening local organizational infrastructure can simultaneously enhance land-use sustainability, climate mitigation, and livelihood inclusion. Given the cross-sectional observational design, all findings should be interpreted as associations rather than causal effects; the results offer actionable insights for designing agro-ecosystem programs that integrate governance, social equity, and ecological resilience in support of long-term food security. Full article

Under weak grid conditions, the coupling between the grid-connected converter and the grid impedance tends to bring in harmonic instability in the permanent-magnet synchronous generators (PMSGs)-based wind farm system. Although the symmetrical phase-locked loop (SPLL) can decouple the converter from the grid, it exerts an impact on the system stability. To address this issue, this paper proposes a partial impedance decoupling control method based on the SPLL. Based on a small-signal impedance model, the grid-GSC impedance decoupling mechanism of the SPLL and its adverse impact on system stability are analytically revealed. Furthermore, a partial impedance decoupling method is realized that incorporates adjustment coefficients and symmetric compensation to achieve a trade-off between damping enhancement and coupling mitigation, thus expanding the stable operating range of the PMSG-based wind farm system. Both simulation and experimental results demonstrate that the proposed strategy significantly improves system stability and maintains stable operation under grid conditions with a 10% reduction in short-circuit ratio (SCR). Full article

Based on the survey dataset of 879 farm households in China’s three northeastern provinces, this study adopts an integrated empirical framework that incorporates the ordinary least squares (OLS) model, quantile regression, and mediation effect models to examine the impact of digital agricultural technology adoption on farmers’ grain income and unravel its underlying mechanism. The results indicate that: (1) Digital agricultural technologies adoption has a significant positive effect on farmers’ grain income, and this impact gradually increases with farmers’ income levels. Meanwhile, the income-increasing effect of digital agricultural technologies exhibits a threshold effect: when farmers adopt two types of digital agricultural technologies, they can achieve growth in grain income. (2) Heterogeneity analysis reveals that, in terms of operational scale, the income-enhancing effect of digital agricultural technologies adoption is significantly stronger for medium-scale farmers than for small-scale and large-scale farmers; in terms of regional distribution, the positive effect is strongest in Jilin Province, followed by Liaoning Province, and weakest in Heilongjiang Province; in terms of crop types, the positive effect is more substantial for rice growers than for maize farmers. (3) Mechanism analysis indicates that operational scale and plot scale play mediating roles in the impact of digital agricultural technologies on farmers’ grain income, with their mediating effects of approximately 5.52% and 9.66% respectively, which further clarifies that the adoption of digital agricultural technologies expands operational scale and plot scale, enables large-scale production, and thus boosts farmers’ grain income. These findings offer empirical insights into integrating smallholder farming systems with digital agriculture and provide evidence-based support for policies aimed at promoting scaled operation and facilitating the digital transformation of grain production systems. Full article

Accurate body-weight monitoring is essential for assessing welfare in cage-free poultry. However, commercial farms continue to rely on manual weighing because of concerns regarding the accuracy and reliability of automated methods. This study developed and evaluated an Internet of things (IoT)-enabled weighing platform integrating load cells, an microcontroller, a Raspberry Pi 5, and Node-RED for data acquisition, processing, and visualization. The system recorded weight measurements at 1 Hz, detected individual weighing sessions, and applied a rolling-median filter to produce stable weight estimates. Validation was performed against a reference scale during two weighing sessions one week apart using 75 cage-free hens randomly selected from a flock of 750 Hy-Line W80 birds. Bland–Altman analysis and a linear mixed-effects model indicated a small overestimation of approximately 6–9 g, with most measurements falling within the 95% limits of agreement, while overall mean absolute percentage error remained below 3%. Improved accuracy during the second session suggests that platform stability influenced performance. Overall, the system demonstrates strong potential for continuous low-stress weight monitoring in poultry farms. Future improvements should focus on refining calibration methods, enhancing mechanical stability, and integrating bird identification and presence-detection mechanisms to further support flock management and welfare monitoring. Full article

In advancing the green transformation of the livestock industry, whether “carrots” or “sticks” prove more effective remains to be further tested. Drawing on micro-level survey data from 273 beef cattle farmers in Yunnan Province, China, this study employs farmers’ subjective evaluations of green subsidies and environmental regulation intensity to characterize corresponding policy instruments. An ordered Probit model is used to analyze the impact and underlying mechanisms of green subsidies and environmental regulations on farmers’ green production behaviors. Results indicate: (1) Both green subsidies and environmental regulations promote green production practices among beef cattle farmers, with green subsidies demonstrating stronger effects that remain robust across a series of stability tests. (2) Heterogeneity analysis reveals that both policy instruments positively influence various types of green production behaviors, with the most significant effect observed on manure resource utilization. This effect is stronger among risk-preferring farmers and those participating in cooperatives. Furthermore, green subsidies significantly promote green production behaviors among small and medium-sized farmers, while environmental regulations enhance green production behaviors across all farmer sizes, with larger farmers experiencing stronger effects. (3) Mechanism analysis indicates that green subsidies and environmental regulations primarily promote green production practices by encouraging farmers to participate in green training, build green facilities, and enhance their green awareness. (4) Further analysis reveals no synergistic effects between green subsidies and environmental regulations. The research conclusion of this study can provide a reference for optimizing policy tool combinations in regions with similar beef cattle farming structures and regional characteristics. Full article

Agriculture is particularly vulnerable to climate change, as shifting seasonal patterns disrupt farming cycles and changing rainfall patterns, along with extreme weather events, present significant challenges. From the perspectives of risk perception and risk attitudes, this study elucidates the decision-making mechanisms underlying climate adaptation behaviors among maize growers in China, providing insights to inform climate adaptation policies, land management strategies, and food security protection. This study surveyed 752 maize growers in Jilin province, China, and employed factor analysis to quantify climate risk perception and risk attitudes. Using the Probit model and moderation analysis, this study examines the impact of climate risk perception on adaptive behavior and investigates the moderating effect of risk attitude on the relationship between risk perception and climate adaptation behavior. It then explores heterogeneity across production scales and generations. (1) We categorize adaptation behaviors into three types—capital-based, labor-based, and technology-based—according to the input factors involved. Climate risk perception promotes all three types of adaptation behaviors, whereas risk aversion primarily exerts a significant inhibitory effect on technology-based adaptations. (2) Risk attitudes exert a negative moderating effect on the relationship between climate risk perception and the adaptation behaviors of maize growers. Specifically, a higher propensity for risk aversion attenuates the positive influence of risk perception on labor-based and technology-based adaptation behaviors. (3) Heterogeneity analysis reveals that the moderating effect of risk attitude is more pronounced among small-scale farmers and younger generations. In contrast, it remains statistically insignificant for large-scale operators and older-generation cohorts. Therefore, it is important to enhance farmers’ awareness of climate risks by strengthening the dissemination of meteorological information and early warnings. Technical guidance should be intensified to improve maize growers’ understanding and mastery of relevant technologies. Develop targeted land-use strategies for climate change adaptation based on maize growers’ age, farm size, and geographic location. Full article

Intensive pig production systems in China face dual challenges of heavy metal (HM) contamination and nutrient overloading from manure. However, stage-specific quantitative relationships between diet and excretion remain poorly characterized, hindering targeted mitigation. To address this, we conducted a comprehensive farm survey in the southern water network region—a major pig production hub in China—collecting 93 paired feed and manure samples from piglets, finishing pigs, and sows across 32 large-, medium-, and small-scale farms. The results revealed that essential trace elements (Cu, Zn, Fe, Mn) in feed exceeded safety guidelines by 3–19-fold, while toxic metals (As, Hg, Pb, Cd, Cr) remained below hygienic limits. Notably, Cu and Zn concentrations in manure significantly surpassed organic fertilizer standards, with piglet manure showing the highest exceedance rates (69–91%). Strong linear correlations (Pearson’s r = 0.360–0.766) were found between feed additives (Cu, Zn, As, Pb, Cd, Cr) and their excretion in manure, with Cu and Zn exhibiting the strongest relationships, especially in piglets. Feed crude protein (CP) and phosphorus (P) levels positively influenced nitrogen (N) and P excretion (r = 0.389–0.860), particularly in finishing pigs. Scenario analysis demonstrated that aligning Cu and Zn supplementation with safety guidelines could reduce HM excretion by 50–67%, while low-CP diets and precision P feeding lowered N and P losses by 10.2–10.8% and reduced feed costs by 4.1%. These findings highlight the potential of dietary interventions to mitigate environmental risks without compromising productivity, offering actionable strategies for sustainable pig production and revised feed regulations. This study provides quantitative, stage-specific evidence linking feed formulation to excretion patterns, addressing critical knowledge gaps in feed-to-manure transfer mechanisms and supporting the development of precision feeding standards and integrated manure management systems to decouple livestock intensification from environmental degradation. Full article