Search Results (134)

Background/Objectives: In mandatory livestock vaccination programs, post-vaccination immunity depends on both vaccine characteristics and consistent on-farm implementation. We evaluated whether Hanwoo farm-gate prices were temporally associated with subsequent foot-and-mouth disease (FMD) structural protein (SP) antibody seropositivity, used as a population-level proxy for vaccination performance. Methods: We analyzed 75,408 individual SP antibody records from Hanwoo cattle on commercial farms (≥50 head) sampled on-farm from April 2019 to December 2022 and linked monthly seropositivity to four price metrics. A separate 2022 cohort (n = 131,805) was analyzed by multivariable logistic regression. Cross-correlations assessed price-leading lags of 0–12 months; linear and exploratory hinge models evaluated association magnitude and a candidate breakpoint. Results: Overall SP seropositivity was 96.3%. Cattle from commercial farms had higher odds of antibody negativity than those from smaller farms (adjusted odds ratio [OR] 1.15, 95% confidence interval [CI] 1.05–1.26), whereas each additional recorded vaccination was associated with lower odds (OR 0.89, 95% CI 0.88–0.90). Monthly price and the 3-month moving-average price showed their strongest associations with subsequent seropositivity at 7 and 6 months, respectively (r = 0.519 and 0.506; both p < 0.001). Month-to-month price changes were not associated with seropositivity. An exploratory hinge model identified a candidate breakpoint near KRW 6.26 million per 600 kg live animal. Conclusions: Sustained farm-gate price conditions, rather than short-term volatility, were associated with subsequent FMD post-vaccination seropositivity. Livestock price data may provide a contextual signal for targeting communication and vaccination support activities; however, this ecological association does not demonstrate price-driven behavioral change at individual farms, and the candidate breakpoint requires prospective validation. Full article

Potato (Solanum tuberosum) is a key staple crop in Kenya, where plant-parasitic nematodes are among the most damaging yield constraints for smallholder farmers. This study evaluated fluopyram-treated banana fibre paper, a biodegradable carrier for targeted delivery of ultra-low nematicide doses, under on-farm conditions in Nyandarua County over three consecutive cropping seasons across properly and poorly managed fields. Seventeen nematode genera were identified, with Helicotylenchus and Globodera (potato cyst nematode, PCN) recording the highest population densities. Fluopyram-treated banana paper significantly suppressed Globodera juvenile densities and reduced total nematode reproductive factors by ≥26% and PCN cyst multiplication factors, the effects most pronounced under poor management. No significant nematode suppression was observed under good management. Total yield in fluopyram treatment approximately doubled in well-managed plots and increased by ~50% in poorly managed plots relative to untreated controls. Fluopyram-treated plots also produced a higher proportion of large-grade tubers under proper management, improving marketable yield. These findings demonstrate that banana fibre technology can effectively manage nematode pests under variable real-world smallholder conditions, with yield benefits amplified by good agronomic practices. The technology offers a practical, climate-smart, and sustainable nematode management tool, with potential for wide adoption across sub-Saharan Africa. Full article

Climate change is increasing the frequency of heat stress events in dairy farming, adversely affecting milk production, milk composition, cow behavior, and animal health. However, many previous studies relied on distant weather-station data and low-frequency milk recording systems, limiting the assessment of short-term and delayed heat stress responses. Therefore, the aim of this study was to combine dense longitudinal data from automatic milking systems (AMS) with continuously recorded on-farm meteorological measurements to investigate the immediate and lagged effects of heat stress on Holstein dairy cows. The study included 386,587 AMS visit records from 790 cows on three commercial dairy farms in Germany, corresponding to up to 127,310 cow-day records collected between August 2022 and August 2025. Temperature–humidity index (THI) values were calculated based on dense on-farm temperature and relative humidity records and were evaluated for multiple lag periods prior to AMS recordings. Linear mixed models were applied to infer the effects of THI on production, physiological, behavioral, and milking process traits. Increasing THI was associated with reduced daily milk yield, altered milk fat and protein percentages, decreased AMS visit frequency, prolonged milking intervals, and increased milk temperature. For contemporaneous THI, an increase from THI 50 to THI 70 corresponded to model-estimated declines of −0.86 kg in daily milk yield, −0.20% in milk fat content and −0.06% in milk protein content, −0.12 daily AMS visits, and +1.14 °C in milk temperature. The strongest associations were generally observed for prompt and short-term lagged THI windows. In contrast, longer lag periods were associated with weaker and less distinct trait responses. Rather than merely confirming the established decline in milk yield under heat stress, the integrated and temporally resolved analysis revealed trait-specific response patterns across production, behavioral, physiological, health-related, and milking-process traits. In particular, milk temperature and voluntary AMS attendance showed pronounced associations with contemporaneous and short-term THI, demonstrating the value of combining AMS-derived phenotypes with high-resolution on-farm climate data for heat stress monitoring. Full article

Large-scale breeder chicken farms generate high-moisture manure, and all-in/all-out management can constrain continuous manure handling, especially during cold northern winters. This study proposed and evaluated a staged resource-recovery pathway for breeder chicken manure under all-in/all-out farm management. The pathway consisted of an implemented on-farm primary aerobic fermentation stage for rapid reduction and sanitization, an implemented centralized secondary aerobic fermentation stage for standardized organic fertilizer production, and a proposed solar-greenhouse-assisted low-temperature module for seasonal continuity support. System performance was assessed through a practice-based case evaluation using enterprise operational records, field investigations, and routine monitoring data on manure generation, process parameters, product quality, and logistics/cost indicators. The primary stage showed a relatively stable operational window across case farms, with fresh manure moisture contents of 85–90%, compost temperatures increasing from approximately 30 °C to 60 °C before declining to about 40 °C, and pH values ranging from 7.0 to 9.5, while batch duration and moisture-control pathways varied among farms. The secondary stage demonstrated standardized downstream processing capacity; the tested organic fertilizer complied with NY/T 525-2021, while the bio-organic fertilizer specifications met the benchmark requirements of NY 884-2012. The conceptual winter continuity-support module was discussed as a conceptual engineering supplement requiring future operational validation. Overall, the evaluated pathway may provide a practice-based reference for sustainable manure management, standardized fertilizer production, and circular agricultural resource recovery under intensive breeder chicken production conditions. Full article

Salmonella remains one of the most critical zoonotic pathogens in the poultry sector, linked to animal disease, foodborne illness, and the global crisis of antimicrobial resistance (AMR). Poultry acts as a major reservoir, enabling Salmonella transmission from hatchery to retail products through horizontal, vertical, and environmental routes. Despite the use of biosecurity, vaccination, antibiotics, and chemical decontamination, effective and sustainable control across the poultry value chain remains difficult, particularly in the face of rising multidrug-resistant strains and growing consumer concerns over chemical residues. Bacteriophages (phages), viruses that selectively infect and lyse bacteria, have emerged as a promising biological alternative for Salmonella control. Although many studies have reported the effectiveness of phages against bacterial species, including Salmonella, in the poultry industry, reports on their full potential to combat antimicrobial-resistant Salmonella across the entire poultry value chain remain limited. Therefore, this review synthesizes current evidence on the application of phages throughout the poultry value chain, including on-farm interventions, processing plant decontamination, and food packaging and storage. Findings from the reviewed articles indicate over a 90% reduction in Salmonella spp. in poultry farms and post-harvest meat, along with lower mortality in phage-treated groups compared to untreated groups; however, these outcomes depend on several factors (e.g., phage strains, concentrations, application methods, and environmental conditions). Laboratory, pilot, and field studies consistently demonstrate that phage preparations, especially when formulated as cocktails or combined with complementary interventions, can achieve substantial reductions in Salmonella, including antibiotic-resistant serovars, in live birds, eggs, poultry environments, and meat products. Unlike antibiotics and chemical sanitizers, phages act with high specificity, preserving beneficial microbiota and maintaining the sensory and nutritional quality of poultry products. Their safety has been supported by toxicological and genomic assessments, and several phage-based products have obtained regulatory approval, including Generally Recognized as Safe (GRAS) status for food applications in the United States. By integrating efficacy, safety, regulatory, and practical deployment data, this review highlights bacteriophages as a scientifically validated and One Health–aligned tool capable of reducing Salmonella transmission from farm to fork across the poultry value chain, thereby laying the foundation for their future adoption in the poultry industry. Phage-based interventions offer a sustainable pathway to enhance food safety, limit antimicrobial resistance (AMR) dissemination, and strengthen consumer confidence in poultry products. However, the major limitation is the emergence of phage-resistant bacterial strains, as well as the potential involvement of some phages in the transfer of resistance and virulence genes, which could raise public concern. Nevertheless, the use of phage cocktails and whole-genome sequencing, involving tools such as ResFinder and virulence finder, can facilitate the selection of safe phages for application. Full article

Aligning plant breeders’ objectives with farmers’ preferences is essential for improving the adoption of new crop varieties. This study evaluated the effectiveness of a Participatory Weighted Selection (PWS) index, previously developed from a survey of 869 Moroccan farmers, by comparing it with biophysical Participatory Variety Selection (PVS) trials conducted on 19 farms across four agroecological zones in Morocco. Novel CWR-derived lines of durum wheat, barley, and lentil were assessed alongside commercial checks, and both male and female farmers were interviewed to gather PVS preferences. The results showed no significant gender differences for the top-ranked varieties across crops, with minor variations in some zones. Jabal emerged as the preferred durum wheat variety overall, while Zagharin2 was favored in favorable zones. Furat-3 was generally preferred for barley, except in certain mountain and favorable zones, and Bakria was the top lentil variety across most sites. Farmers’ PWS responses clustered into three groups, emphasizing consistent prioritization of high yield potential, abiotic stress tolerance, and good nutritional quality. Comparison of biophysical performance with PVS and PWS revealed strong alignment for durum wheat; however, the highest yielding genotypes for barley and lentil were not always the most preferred. Overall, these results demonstrate that the PWS approach effectively captures farmers’ preferences and provides a reliable tool for guiding breeding decisions. These findings reveal that integrating PWS with on-farm biophysical and PVS evaluations provides a robust, farmer-informed framework for prioritizing genotypes and improving the relevance of breeding decisions across diverse agroecological contexts. Full article

United States (U.S.) specialty crop growers face myriad decisions regarding substrate selection as sustainability, market demands, and resource limitations influence soilless production systems. Peat is a common component in container substrates despite public concerns about its limited availability, finite supply, and associations with greenhouse gas emissions and environmental impacts, which have prompted growers to seek alternative materials. However, limited research has focused on the experiences, challenges, and research needs of U.S. specialty crop growers related to substrate transitions. The purpose of this mixed-methods study was to explore growers’ key considerations, research interests, and preferred communication methods associated with substrate transitions. An online survey and three focus groups were used to gain insights into growers’ experiences, concerns, and perceived impacts of peat replacement, research needs, and preferred communication channels. Results indicated that financial costs, peat availability, access to peat alternative substrates, and environmental considerations were the main factors influencing potential changes in substrate use. Growers identified key research priorities to assist decision-making, including (1) irrigation and nutrient management strategies, (2) the economic performance of alternative substrates, and (3) locally validated trials demonstrating system compatibility. They preferred practical communication methods for sharing results, including websites, YouTube videos, in-person meetings, on-farm demonstrations, and short podcasts accessible during routine work hours. The findings implied that research, outreach, and communication efforts tailored to growers’ operational contexts will support informed substrate transitions. 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

Climate change represents one of the most critical challenges, especially in the Mediterranean area. Using organic and localized fertilization could be an effective agroecological strategy to help mitigate the environmental impacts of climate change. Our study was carried out in an experimental field over a three-year crop succession including broccoli, sweet pepper and barley. A randomized complete block design was adopted, with two factors: (i) fertilization method (100% broadcast and 40% localized) and (ii) fertilizer type by testing: on-farm compost, two types of commercial compost and a mineral fertilizer. Environmental impacts per hectare and marketable yield were quantified using Life Cycle Assessment (LCA), considering abiotic depletion (AD), acidification (AA), eutrophication (EU), global warming potential (GWP), and photochemical oxidation (PO). The localized application of fertilizers achieved marketable yields comparable to the broadcast method, despite lower fertilizer inputs, suggesting an optimal nutrient-use efficiency. The LCA demonstrated that localized fertilization also enhanced environmental sustainability, decreasing Global Warming Potential (GWP) by 20% per hectare, compared to broadcast treatments. Moreover, considering only the fertilization phase, we observed a 59% reduction in GWP under the localized strategy. Even though localized fertilization emerges as an effective climate-smart strategy without compromising productivity, future research is recommended to assess its long-term impacts in site-specific conditions. Full article

Image-based AI offers a low-cost alternative to traditional turbidity sensors in farm ponds, yet the prevailing shift toward Vision Transformers (ViTs) critically overlooks two field realities: the chronic scarcity of annotated data (Small Data) and the strict computational limits of edge hardware. This study presents a frugal computer vision framework that challenges the need for complex architectures in environmental screening. By systematically benchmarking six deep learning models across a calibrated high-turbidity dataset (200–800 NTU, 700 images) under standardized capture conditions, we demonstrate that traditional Convolutional Neural Networks (CNNs) possess a crucial inductive bias for this task. Specifically, ResNet-50 significantly outperformed modern ViTs in both accuracy (96.3% vs. 80.0%) and data efficiency, effectively capturing spatial scattering patterns without the massive data requirements that hindered transformer convergence. Deployed on a resource-constrained Raspberry Pi 4, the CNN-based system achieved an inference latency of 46 ms, demonstrated in an initial hardware-in-the-loop field proof-of-concept (82.4% agreement under baseline, calm-weather conditions, $n=17$). This edge-native approach not only provides actionable spatial turbidity maps to guide on-farm filtration and livestock management decisions but also establishes a critical architectural baseline: under controlled capture protocols, mature CNNs consistently outperform ViTs, establishing them as the optimal architecture for frugal, small-data agricultural Internet of Things (IoT) deployments. Full article

Accurate, non-contact monitoring of rumination behavior is essential for assessing dairy cow health and welfare, as well as for optimizing feeding strategies and herd management in modern precision livestock farming. However, practical deployment in commercial barns faces challenges such as occlusions, variable lighting, and dynamic cow movements. To address this, we developed a robust, automated vision-based framework for continuous rumination monitoring. The core of our system integrates an enhanced object detection algorithm with a robust tracking module, specifically improved to capture subtle behavioral features and maintain identity under complex conditions. Evaluated on a comprehensive dataset collected from commercial settings under various lighting and occlusion scenarios, our framework achieved high detection accuracy (mAP of 96.26%) and reliable tracking performance (multi-object tracking accuracy of 99.2%). This demonstrates its suitability for real-time, on-farm deployment. The study provides a practical, end-to-end solution for fine-grained behavioral analysis in complex environments, offering a tool that can enhance welfare assessment and support decision-making in dairy farm management. The methodological approach is also adaptable to other precision livestock monitoring tasks. Full article

Livestock production significantly contributes to greenhouse gas (GHG) emissions, particularly methane (CH₄) and nitrous oxide (N₂O) originating from enteric fermentation and manure management. This study quantified the GHG emissions and cumulative carbon footprint of four commercial sheep farms (SF1, SF2, SF3, and SF4) in the Bursa region of Türkiye, with flock sizes of 200, 500, 150, and 800 adult Merino sheep (mature ewes and breeding rams), respectively. Using the IPCC Tier 2 methodology, the biogenic carbon footprint was estimated at 15.6 kg CO₂-eq per kg of boneless sheep meat. However, when indirect inputs were included, the cumulative carbon footprint reached 28.8 kg CO₂-eq for ewes and 32.3 kg CO₂-eq for breeding rams. These results indicate that indirect emissions from feed production account for the primary environmental load (49.8%), while on-farm energy-related emissions represent a minor portion (0.3%) of the total impact. The results demonstrate that while enteric fermentation (32.5%) remains a critical biological factor, the environmental burden of the feed supply chain is equally significant in intensive systems. These findings highlight that excluding indirect inputs leads to a substantial underestimation of the climate impact, suggesting that mitigation strategies must integrate nutritional optimization with enteric methane reduction to decarbonize sheep production effectively. Full article

This study targets key challenges in ameliorating the plow-layer soil of coastal saline soils. A field experiment under a wheat–maize rotation was established with six treatments: CK, control with no organic inputs; A1, 45 t ha⁻¹ organic manure; A2, 45 t ha⁻¹ organic manure + microbial inoculant; A3, 45 t ha⁻¹ organic manure + microbial inoculant + plastic-film mulching; A4, 90 t ha⁻¹ organic manure; and A5, 135 t ha⁻¹ organic manure. By applying high rates of organic manure alone or in combination with microbial inoculation and mulching, we aimed to strengthen soil water–salt regulation, improve plow-layer soil quality, and ultimately promote crop growth and yield formation. We further quantified treatment-induced shifts in soil physicochemical properties and linked them to crop growth and yield responses. The results indicated that, compared with CK, plow-layer soil organic carbon increased by 45.56% and 107.91% under A3 and A4, respectively, while soil salinity decreased by 70.57% and 67.42%. All manure-based treatments increased yield relative to CK, with the highest yields achieved under A3 and A4: wheat yield reached 7628.16 and 7888.01 kg ha⁻¹, and maize yield reached 8828.29 and 8716.01 kg ha⁻¹, respectively. Overall, high-rate organic manure—especially when integrated with microbial inoculation and plastic mulching—substantially enhanced soil fertility while alleviating salinity stress, resulting in an integrated “fertility build-up–salinity reduction–yield enhancement” amelioration effect. This technology package offers a feasible pathway for improving coastal saline farmland and stabilizing productivity under rotation systems, with strong potential for further on-farm demonstration and wider adoption. Full article

To support farmers in their transition towards sustainable agriculture, sub-Saharan Africa needs a more effective extension. Thus, effective improvements based on a clear view of current and desired extension capacity are necessary. As in the past, mostly one-sided studies have been conducted. This paper proposes a more integral approach based on both characteristics and viewpoints of both farmers and extension workers. Capacity to provide effective extension and advisory services (EAS), or extension capacity, is defined and analyzed with mixed-research methods using data from 471 Ugandan dairy farmers, from three distinct production systems and 67 extension workers. Extension capacity is determined by farmers’ satisfaction, the frequency of delivering EAS to farmers, and the perceptions of both farmers and extension workers on the use of appropriate methods to deliver EAS. Results revealed moderate satisfaction across production systems, with a pronounced negative effect of long working experiences on the frequency of delivery. Positively influencing factors for delivery frequency are intrinsic motivation and the number of in-service trainings received by extension workers. On-farm demonstrations, individual farm visits, the use of contact farmers, and farmer training are perceived as the four most effective delivery methods among dairy farmers in Uganda. Given the moderate farmer satisfaction, low frequency of delivery, and slight mismatch between the perceived effective delivery methods and those being used, the study concludes that the current extension capacity remains low. However, low-hanging fruits for improvement include increasing in-service training opportunities, employing extension workers on contractual basis and motivating extension workers. Full article

An outbreak of mastitis caused by Staphylococcus aureus occurred in a commercial dairy goat herd during kidding season, resulting in fatal gangrenous mastitis in approximately 30% of the herd. S. aureus was recovered from milk, mammary tissue, and other organs in does subjected to necropsy. The S. aureus milk culture-positive rate among does in the hospital pen was 58.3%, while whole-herd milk cultures of clinically normal mature does identified S. aureus in 15.0% with an additional 15.0% positive for coagulase-negative Staphylococcus (CNS), yielding a total culture-positive rate of 30.0%. The prevalence of CNS in subclinical animals was consistent with previous reports from U.S. dairy goats; in contrast, S. aureus isolation rates substantially exceeded previously reported prevalences. Poor milking hygiene and milking machine dysfunction were identified as major factors contributing to the spread of the S. aureus from goat to goat. California Mastitis Test (CMT) scores were significantly higher in culture-positive does compared with culture-negative animals (p < 0.05), demonstrating the value of CMT as a practical on-farm tool for early treatment decision making. Interventions focused on addressing milking hygiene and milking machine maintenance, as well as segregation and vaccination of replacement females. S. aureus dropped to undetectable in the next two kidding seasons, whereas the CNS culture rates remained unchanged, suggesting other factors may be contributing to CNS infection. This case highlights the role of subclinical intramammary infection and milking practice factors in transmission and control of contagious mastitis pathogens like S. aureus. Full article