Search Results (1,340)

Sex-specific markers are important basic tools for the sex-controlled breeding of farmed fish. Here, we aimed to develop a rapid yet accurate, cost-effective method for determining the genetic sex of the Chinese hooksnout carp (Opsariichthys bidens), a freshwater fish. Using whole-genome resequencing technology, along with bulked segregant analysis (BSA) and chromosome quotient (CQ) methods, sex-specific regions were screened, and corresponding primers were designed to validate the screening results. A total of 45 sex-specific regions were successfully screened through BSA sequencing and CQ analysis, and 50 pairs of primers were designed for use in the screening verification. The Mar28 primer pair showed stable sex specificity in multiple populations of O. bidens, accurately distinguishing male from female individuals. This primer pair amplified two bands (509 and 814 bp) in males, but only one band (509 bp) in females. The genetic sex identification method established here provides a theoretical basis for studying the mechanism of sex determination in O. bidens, has implications for the monosex culture and molecular breeding of O. bidens, and has significant scientific and practical value. Full article

Body measurements are used regularly to describe phenotypes or the weight of animals. However, little data describe the age effect on the different measurements. In the present paper, 477 Bactrian camels (7–180 months old) were measured (length of the head, length and circumference of the neck, height at the withers, girth circumference, length of the front leg, and length of the body), and their growth was modeled by comparing different equations, the most convenient being the beta growth equation. In addition, the differences in body measurements of adult Bactrian camels between farms were tested by variance analysis, and multivariate analyses were used for identifying homogeneous clusters of camels according to their body measurements. The sampled animals were from different regions of the country. The significant relationships between cluster and region support the idea of racial differentiation. Body condition scoring is widely used in farm animals as an indicator of their feeding, health, and welfare status. If a body condition score is available for dromedaries, there is no specific grid for the Bactrian camel. Starting from typical examples taken from photos in different conditions, including extreme ones, a representation of a scoring system of 6 points from very emaciated (score 0) to overweight Bactrian camel (score 5) was proposed in the form of drawings from the right side, back, and three-quarter rear. To complete the drawings, a descriptive grid was built as a base for training stakeholders in relation to Bactrian camel farm management. However, the seasonal change in the fleece abundance, the variability of the humps’ shape, and the presence of crossbreeding with dromedary camels require adapting the scoring accordingly. Full article

Using a city-level panel for China (2011–2021), this paper estimates agricultural total factor productivity (TFP) with a stochastic-frontier approach and identifies the effect of digital finance through two-way fixed effects and instrumental-variable strategies. We document a statistically and economically significant negative association: a 1% increase in the digital finance index is linked to a decline of 1.5 in agricultural TFP. Evidence points to capital misallocation as the dominant channel, with the adverse effect most pronounced where agricultural capital markets are highly distorted. Heterogeneity analyses show stronger negative impacts in labor-intensive areas, non-major grain regions, and small-scale farming systems. Results are robust across alternative specifications and IV estimations. By moving from provincial aggregates to city-level variation, this study sharpens identification and uncovers within-province patterns that are invisible in coarser data. The findings highlight an important unintended consequence of digital financial expansion for agriculture and underscore a policy priority: improving the allocation and targeting of digital credit within rural economies to support productivity and sustainable development. Full article

African swine fever (ASF), caused by the African swine fever virus (ASFV), is an acute, febrile, highly contagious, and lethal disease that poses a severe threat to the global pig farming industry. Currently, no globally recognized, safe, and effective commercial ASF vaccine has been developed, making vaccination a crucial strategy for outbreak control. The ASFV structural proteins p72, p30, and p54 are key targets for vaccine development. In this study, we developed a novel baculovirus vector-based system for surface display of a recombinant protein comprising epitopes from p72, p30, and p54. Upon infection, the recombinant protein was expressed and anchored on the plasma membrane of Sf-9 cells. Purified virus analysis revealed that the Bac-recombinant protein enhanced gene delivery and transgene expression in mammalian cells compared to the Bac-Wild Type (Bac-WT). In a murine model, the Bac-recombinant protein induced significantly higher IFN-γ and IL-4 levels than Bac-p30 and the negative control. However, further evaluation in swine models is required to confirm its protective potential against ASFV. Furthermore, it also elicited a robust antibody response, generating high-titer Bac-recombinant protein-specific antibodies. Therefore, these findings suggest that the ASFV Bac-recombinant protein is a promising candidate for a vector-based vaccine. Full article

Labor shortages in seedling nurseries, particularly in manual inspection and replanting, hinder operational efficiency despite advancements in automation. This study aims to develop a cost-effective, GPU-free machine vision system to automate the detection of deficient seedlings in plug trays, specifically for small-scale nursery operations. The proposed Deficiency Detection and Replanting Positioning (DDRP) machine integrates low-cost components including an Intel RealSense Depth Camera D435, Raspberry Pi 4B, stepper motors, and a programmable logic controller (PLC). It utilizes OpenCV’s Haar cascade algorithm, HSV color space conversion, and Otsu thresholding to enable real-time image processing without GPU acceleration. The proposed Deficiency Detection and Replanting Positioning (DDRP) machine integrates low-cost components including an Intel RealSense Depth Camera D435, Raspberry Pi 4B, stepper motors, and a programmable logic controller (PLC). It utilizes OpenCV’s Haar cascade algorithm, HSV color space conversion, and Otsu thresholding to enable real-time image processing without GPU acceleration. Under controlled laboratory conditions, the DDRP-Machine achieved high detection accuracy (96.0–98.7%) and precision rates (82.14–83.78%). Benchmarking against deep-learning models such as YOLOv5x and Mask R-CNN showed comparable performance, while requiring only one-third to one-fifth of the cost and avoiding complex infrastructure. The Batch Detection (BD) mode significantly reduced processing time compared to Continuous Detection (CD), enhancing real-time applicability. The DDRP-Machine demonstrates strong potential to improve seedling inspection efficiency and reduce labor dependency in nursery operations. Its modular design and minimal hardware requirements make it a practical and scalable solution for resource-limited environments. This study offers a viable pathway for small-scale farms to adopt intelligent automation without the financial burden of high-end AI systems. Future enhancements, adaptive lighting and self-learning capabilities, will further improve field robustness and including broaden its applicability across diverse nursery conditions. Full article

The transition towards sustainable agri-food systems, as envisioned in the European Union’s Farm to Fork (F2F) Strategy, largely depends on the incorporation of technological innovations. However, existing literature has predominantly adopted confirmatory approaches focused on general benefits and barriers, without systematically addressing the conceptual and methodological tensions that arise in the implementation of policies of this magnitude. This study seeks to move beyond an incremental review, offering instead a critical and context-specific analysis. A realist review approach was employed to explore outcomes beyond average effects, guided by the central question: what works, for whom, under what conditions, and why? The selection of studies was based on conceptual relevance, including research on technological adoption within the framework of agricultural sustainability policies, even when explicit references to the F2F Strategy were absent. In addition, an epistemological quality scale was applied to weigh the evidence, distinguishing between different levels of methodological robustness, such as case studies and meta-analyses. The analysis shows that technologies such as precision agriculture and digitalization contribute to the objectives of F2F but also generate unforeseen tensions and contradictions during implementation. Conflicts emerge between environmental sustainability goals and short-term economic viability, especially among certain producer profiles. Barriers to adoption are not generic; rather, they vary according to a differentiated typology of small-scale producers, such as family farmers in peripheral EU regions or those transitioning to organic farming. Findings suggest that a strategy focused solely on technological promotion is insufficient. The main contribution of this study lies in the development of a conceptual framework to understand how technological adoption reshapes the tensions among the different pillars of the F2F Strategy, as well as the conditions under which innovation may hinder, rather than facilitate, the agroecological transition. The study concludes with policy recommendations advocating differentiated interventions tailored to the specific contexts of producers. Full article

Rural livelihood transformation is increasingly vital for achieving agricultural modernization, reducing poverty, and promoting sustainable development in developing countries. Despite growing attention to land consolidation as a tool for improving agricultural resource allocation and productivity, its role in shaping rural livelihoods remains insufficiently understood. Addressing this gap, this study investigates the impacts of China’s High-Standard Farmland Construction (HFC), the country’s flagship land consolidation policy, on farmers’ livelihoods, focusing on both income level and income structure. Using provincial panel data from 30 regions, we adopt a continuous difference-in-differences design and mediation effect model to identify the causal effects of HFC. The results indicate that HFC significantly promotes total household income. Specifically, HFC facilitates mechanized agricultural production by consolidating fragmented plots, reducing production costs, and improving crop yields, thereby increasing agricultural income. Simultaneously, mechanization substitutes for labor and releases surplus workers, who often move to off-farm employment, diversifying income sources and stabilizing household livelihoods. Heterogeneity analysis reveals that the benefits of HFC are unevenly distributed. Low-income households, central provinces, and major grain-producing areas experience the greatest gains, and moderate-scale implementation proves more effective than either small- or excessively large-scale projects. This study highlights mechanization as a key mechanism linking land consolidation to rural livelihood transformation. The findings demonstrate that well-planned and efficiently implemented HFC policies can not only enhance agricultural productivity but also foster diversified and inclusive rural livelihoods. Full article

This study proposes a scenario-based conceptual model for transforming underground parking structures into sustainable interior green spaces, directly addressing two core research dimensions: energy efficiency and user experience. The originality of the research lies in repositioning subterranean spaces—often overlooked in urban planning—as climate-responsive, multi-functional public environments. Using a site-specific case in downtown Rize, Türkiye, three design scenarios—passive green walls, active modular systems, and experimental micro-farming—were comparatively analyzed. These scenarios were assessed through AI-assisted simulations and climate-based performance evaluations in terms of environmental benefits, thermal regulation, carbon reduction, and experiential quality. Underground space leads to green design interventions, which in turn generate environmental, energy, and social benefits. The results demonstrate that passive systems provide cost-effective improvements, active modular systems achieve balanced performance, and experimental micro-farming yields the highest ecological and social benefits. The study uniquely contributes to urban sustainable design by integrating climate-adaptive strategies, biophilic design principles, and AI-supported visualization into the transformation of underground structures. This research not only advances academic discourse but also provides policy-relevant insights for local governments, developers, and communities in the context of urban renewal. Full article

Ketosis is one of the most common metabolic disorders in high-yielding dairy cows in early lactation. It has a negative impact on milk yield, reproduction, and general health of the animals. The present review aims to systematize and critically analyze current scientific data on the monitoring, diagnosis, prevention, and treatment of subclinical and clinical ketosis, with the aim of developing an applicable protocol for good veterinary medical practices (GMP). Based on the comparative analysis method of data from the literature and clinical practice, β-hydroxybutyrate (BHBA) in blood is confirmed as the gold standard for diagnosis with specificity and sensitivity above 90%. Indicators such as fat/protein (F/P) > 1.4 and NEFA > 0.4 mmol/L, as well as reduced citrate content in milk, have been evaluated as useful screening tools, although with lower diagnostic value. Despite the advantages of some indirect methods (such as F/P), critical analysis shows that they are strongly influenced by physiological status, lactation stage, and diet and cannot replace direct blood tests. Preventive approaches emphasize the importance of stable nutrition in the pre- and post-calving period, restriction of ketogenic feeds, and use of oral glucose precursors. Literature analysis shows that propylene glycol is effective, but with prolonged use it can reduce appetite. Combined antiketotic products have also been introduced, providing not only energy support but also liver protection. Particular attention has been paid to monensin (applied in the commercial product “Kexxtone”)—a polyether antibiotic with sustained release, which reduces the incidence of ketosis by over 50% and increases milk yield in the first weeks after calving. However, its high cost, antibiotic nature, and need for veterinary supervision limit its universal use. The treatment protocol is differentiated according to the clinical type: glucose I. V. and propylene glycol in type I ketosis and avoidance of glucocorticoids in suspected type II (hepatic steatosis). In the critical analysis It is noted that improper use of glucocorticoids can lead to a worsening of the condition. A structured protocol for DVMP (Dairy Veterinary Medical Practice) is proposed, which includes targeted metabolic monitoring (NEFA, BHBA, F/P); proven preventive regimens (Kexxtone, propylene glycol, balanced rations), and staged prevention and treatment according to the form of ketosis. The adaptation of good practices to the scale of the farm and the level of knowledge and skills of the staff for their correct application remains a challenge. Providing training, a standardized control log, and access to field diagnostic tools is key to the success of any protocol. Full article

Laifeng ginger (Zingiber officinale cv. Fengtoujiang) is a famous Geographical Indication (GI) ginger variety, which grows specifically in Laifeng County, Hubei, China. In recent years, it faced a serious food safety issue of lead (Pb) exceedance in the rhizomes even though the Pb content in the soil remains at a safe level. This problem severely hinders the local ginger’s market growth. In the present study, a field study across 37 Laifeng ginger farms revealed a connection between the occurrence of Pb exceedance and the choices of fertilizers. Cultivation experiments demonstrated that with more organic fertilizer (OF) applied, the Pb of rhizome effectively declined, and the branching and longitudinal growth were enhanced. The OF application facilitated Pb translocation from rhizomes to stems and leaves. Furthermore, we showed that OF improved the soil properties by altering the pH and the composition of soil microbial communities at the genus level, which was likely to be associated with reduced the Pb content in the ginger rhizomes. This research tackles the critical industry issue of Pb exceedance in Laifeng ginger, providing a basis for the fertilization of root and tuber plants with excessive heavy metal levels, and establishes a foundation for sustainable GI product development. Full article

Infectious hematopoietic necrosis virus (IHNV), a salmonid rhabdovirus, causes severe mortality exceeding 90% in both wild and farmed salmon and trout. Frequent outbreaks of IHNV highlight the urgent need for rapid detection methods to support effective prevention and control. This study developed a double-antibody sandwich ELISA (DAS-ELISA) targeting the nucleocapsid (N) protein of IHNV. Two peptides derived from the N protein—selected for their strong antigenicity, high level of conservation, and surface accessibility—were used as immunogens to generate two specific monoclonal antibodies. Following optimization, the DAS-ELISA was established using monoclonal antibody N-15 as the capture antibody and horseradish peroxidase (HRP)-conjugated antibody N-106 as the detection antibody. The results of this study demonstrated that DAS-ELISA exhibited high specificity for multiple IHNV strains and showed no cross-reactivity with IPNV, SVCV, or VHSV. The detection sensitivity of DAS-ELISA for IHNV was determined to be 10³ TCID₅₀/mL. Parallel analysis of 293 clinical samples using DAS-ELISA and WOAH reference method demonstrated a concordance rate of 92.83% (κ = 0.856). These results confirm that the established DAS-ELISA exhibits high sensitivity, specificity, broad-spectrum applicability, and repeatability. In conclusion, this DAS-ELISA provides a reliable and efficient tool for high-throughput early detection of IHNV infection in clinical settings. Full article

This study investigates the relationship between biosecurity implementation and the prevalence of ESBL-producing bacteria in Greek swine farms, revealing an alarming 82% prevalence rate, which is significantly higher than in other European nations. Our findings indicate that comprehensive biosecurity measures are more effective than focusing on priority controls alone. Notably, there was a lack of significant associations between farm size and individual biosecurity parameters, underscoring the importance of cumulative improvements across multiple measures. Moreover, we identified a critical threshold for biosecurity implementation: farms scoring less than a critical level were consistently vulnerable to ESBL contamination. Escherichia coli emerged as the dominant species among ESBL isolates, reflecting patterns seen globally. This suggests a need for targeted biosecurity strategies, as mixed species occurrences imply shared resistance pressures. Our results advocate for a paradigm shift in biosecurity practices, emphasizing holistic improvements across all measures rather than isolating specific controls. With current implementation levels averaging only 35% of recommended biosecurity practices, our findings highlight the urgent need for comprehensive interventions to mitigate antimicrobial resistance in the Greek swine industry. Full article

Antibiotic use in aquaculture has become widespread to sustain production and control bacterial diseases, but it poses significant ecological and human health risks due to residue accumulation and resistance development. This study investigated the occurrence, dominance, and combined use of sulfonamide and fluoroquinolone antibiotics in freshwater fish aquaculture ponds around Wuxi, China. Here, the term aquaculture refers specifically to the controlled farming of freshwater fish species such as carp and crucian carp in managed pond systems. A total of 80 water samples (collected exclusively from pond waters) were obtained from 40 ponds during the high intensity rearing and harvest stage of fish. Residues of enrofloxacin and sulfonamide antibiotics were analyzed using a validated LC–MS/MS method with detection limits in the low nanogram-per-liter range. Results revealed that antibiotics were ubiquitous in pond waters, with enrofloxacin emerging as the dominant compound in August, reaching concentrations of up to 2.36 µg/L. By October, sulfonamides, particularly sulfamethoxazole and sulfadiazine, became more prevalent, with a maximum sulfadiazine concentration exceeding 4 µg/L. Multivariate analyses demonstrated a clear seasonal shift in antibiotic profiles, while correlation analyses indicated limited combined use in summer but notable co-occurrence of sulfonamides in autumn. These findings underscore that antibiotic application patterns in aquaculture are strongly linked to production stages, with potential consequences for environmental safety, resistance development, and food security. Effective monitoring, stricter regulation, and alternative disease management strategies are urgently required to mitigate risks and promote sustainable aquaculture practices. Full article

The article aimed to verify the development of the productivity level of Polish agriculture after EU integration as a key determinant of agricultural income. The research in this area was concerted because the productivity of agriculture (its technical efficiency) is a specific measure of its social efficiency, as it determines the level of wealth and social welfare and, at the same time, it is a determinant of its competitiveness in the long term. At the same time, it should be noted that after integration, agricultural production in Poland was carried out under conditions of extensive restrictions resulting from the adopted principles of the common agricultural policy aimed at increasing environmental sustainability. Productivity was measured on individual farm data using the Data Envelopment Analysis (DEA) Slacks-Based Model. The results were then extrapolated to the broader collective of commodity farms in Poland and indirectly applied to the entire population. The obtained results allowed for the conclusion that, during the first years of membership, there was a systematic decrease in productivity, which was observed from 2004 to 2011. The average value of the productivity factor for the research sample decreased from 0.230 to 0.208, while for the population it decreased from 0.224 to 0.202. After then, there was a reversal in the direction of the development trend, and in the following years, an upward trend emerged. Thus, the phenomenon of convergence in agricultural productivity with other EU countries, as the main factor influencing the direction of its changes in Poland after accession to the European Union, was not confirmed. Also, in the post-integration period, there was no change in the expected directions of interaction between the main determinants of agricultural income. Indeed, the theoretically formulated and empirically verified relations between subsidies and price relations and productivity were confirmed. Using the world price index as an explanatory variable in the multiple regression model, it was possible to explain, to a large extent, the variability of the productivity of Polish agriculture. Hence the implication for policymakers is that, despite high levels of subsidisation, the market is the main determinant of productivity changes. The weak impact of the price ratio index in Poland (‘price scissors’) on productivity volatility indicates that the increase in production costs, including those related to environmental protection (sustainability), has been effectively offset. Full article

Frequent failures in wind turbines underscore the critical need for accurate and efficient online monitoring and early warning systems to detect abnormal conditions. Given the complexity of monitoring numerous components individually, subsystem-level monitoring emerges as a practical and effective alternative. Among all subsystems, the gearbox is particularly critical due to its high failure rate and prolonged downtime. However, achieving both efficiency and accuracy in gearbox condition monitoring remains a significant challenge. To tackle this issue, we present a novel adaptive condition monitoring method specifically for wind turbine gearbox. The approach begins with adaptive feature selection based on correlation analysis, through which a quantitative indicator is defined. With the utilization the selected features, graph-based data representations are constructed, and a self-supervised contrastive residual graph neural network is developed for effective data mining. For online monitoring, a health index is derived using distance metrics in a multidimensional feature space, and statistical process control is employed to determine failure thresholds. This framework enables real-time condition tracking and early warning of potential faults. Validation using SCADA data and maintenance records from two wind farms demonstrates that the proposed method can issue early warnings of abnormalities 30 to 40 h in advance, with anomaly detection accuracy and F1 score both exceeding 90%. This highlights its effectiveness, practicality, and strong potential for real-world deployment in wind turbine monitoring applications. Full article