Large-scale Farms Research Articles

PREVALENCE OF BOVINE MASTITIS AND THE FIRST DETECTION OF MYCOPLASMA BOVIS IN VIETNAM’S DAIRY FARMS

Mastitis still remains an economic disease in dairy farms all over the world. This study aimed to report the prevalence of this disease in large-scale farms in Vietnam, the pathogens profile, and first report the detection of Mycoplasma bovis (M. bovis) by applying conventional culture and real-time PCR (polymerase chain reaction) methods. We examined 64,802 enrolled dairy cows from six farms in Vietnam, yielding 1,874 (2.9%) total cases of clinical mastitis. The majority of the 14 pathogens were identified. Klebsiella spp. accounted for 21.0% of the total isolates. Streptococcus uberis (S. uberis), Escherichia coli (E. coli), other Streptococcus spp, and Coagulase-Negative Staphylococci (CNS), followed at 12.6, 7.6, 6.0, and 5.5 percent, respectively. The rest pathogens include Pseudomonas spp., Enterococcus faecalis, Enterobacter spp., Bacillus spp., Citrobacter spp., Pasteurella spp., Proteus spp., and Staphylococcus aureus were isolated with less than 1% each. To the best of our knowledge, this is the first report for detecting M. bovis in mastitis milk samples in Vietnam, where 35 out of 1,422 samples submitted in 2022 were M. bovis positive. Moreover, of the 35 positive cases, 11 cases had only M. bovis, while 24 cases had M. bovis and other pathogens, including 13 Enterobacteriaceae, 7 Streptococcus spp., and 4 CNS.

TOSCA – an open-source, finite-volume, large-eddy simulation (LES) environment for wind farm flows

Abstract. The growing number and growing size of wind energy projects coupled with the rapid growth in high-performance computing technology are driving researchers toward conducting large-scale simulations of the flow field surrounding entire wind farms. This requires highly parallel-efficient tools, given the large number of degrees of freedom involved in such simulations, and yields valuable insights into farm-scale physical phenomena, such as gravity wave interaction with the wind farm and farm–farm wake interactions. In the current study, we introduce the open-source, finite-volume, large-eddy simulation (LES) code TOSCA (Toolbox fOr Stratified Convective Atmospheres) and demonstrate its capabilities by simulating the flow around a finite-size wind farm immersed in a shallow, conventionally neutral boundary layer (CNBL), ultimately assessing gravity-wave-induced blockage effects. Turbulent inflow conditions are generated using a new hybrid off-line–concurrent-precursor method. Velocity is forced with a novel pressure controller that allows us to prescribe a desired average hub-height wind speed while avoiding inertial oscillations above the atmospheric boundary layer (ABL) caused by the Coriolis force, a known problem in wind farm LES studies. Moreover, to eliminate the dependency of the potential-temperature profile evolution on the code architecture observed in previous studies, we introduce a method that allows us to maintain the mean potential-temperature profile constant throughout the precursor simulation. Furthermore, we highlight that different codes do not predict the same velocity inside the boundary layer under geostrophic forcing owing to their intrinsically different numerical dissipation. The proposed methodology allows us to reduce such spread by ensuring that inflow conditions produced from different codes feature the same hub wind and thermal stratification, regardless of the adopted precursor run time. Finally, validation of actuator line and disk models, CNBL evolution, and velocity profiles inside a periodic wind farm is also presented to assess TOSCA’s ability to model large-scale wind farm flows accurately and with high parallel efficiency.

Impact of Agriculture Corporate Farm Increase Productivity Widespread Destructive Activity on Earth Democracy in India

Agricultural productivity in India can be improved by investing in agricultural research and development, improving irrigation infrastructure, promoting farm mechanization, and strengthening agricultural extension services. Agriculture is the foundation of the civilization, culture and heritage of India. It most commonly refers to corporations that are large-scale farms, market agricultural technologies in particular pesticides, fertilizers, and GMO's, have significant economic and political influence, or some combination of the three. The large-scale corporate agriculture is more efficient than peasant farming in the country. It leads to better allocative efficiency, induces higher private investment in agriculture, and results in higher output, income and exports. During 2021-22, in the countries total exports agricultural exports contributed of to the tune of US $ 50.2 billion with a 20% increase from US $ 41.3 billion in 2020-21. In FY 2023, it is projected that the Indian agriculture sector will grow at the rate 3.5%. Agriculture in India is a complex mosaic of distinct agro-ecosystems, differentiated by climatic, soil, vegetation and other natural features. About half of the Indians derive their livelihood from agriculture and allied activities. Technology and Research Corporate farming enterprises usually invest in research and development of new agricultural technologies, seeds, and farming practices. Farmers who are part of these systems can benefit from access to cutting-edge technology and knowledge that can improve productivity and efficiency. It is one of the oldest systems of the world characterized by its diversity and heterogeneity, unorganized and stressed on account of natural and anthropogenic vagaries from ‘seed to market’. Agriculture is the backbone of the Indian economy, contributing to around 16.5% of India's GDP and employing over 50% of the workforce. The Indian agriculture market is valued at USD 435.9 billion as of 2022 and is expected to reach USD 580.82 billion by 2028, growing at a CAGR of around 4.9% between 2023 and 2028. Historically, stressed natural resources due to unfavourable weather, monsoon and natural calamities resulted in crop failures leading to food shortage that made serious impacts on the civilization. Post-Independence, the Indian agriculture transformed from a food-scarce to food-exporting country primarily due to science led innovations that caused multi-fold increase in the agricultural production from 135 million tons in 1950/51 to over 1300 million tons in 2021/22 in spite of increasing abiotic and biotic stresses and depleting along with deteriorating natural resources. Agriculture is one amongst the few sectors that made progressive growth after independence and marched well with the need of the country. Success in agriculture since Independence has been the backbone of India’s success.

Cumulative effects of offshore wind farms on common guillemots (Uria aalge) in the southern North Sea - climate versus biodiversity?

Governments are under increasing pressure to reduce greenhouse gas emissions, and large-scale wind farms are being developed in marine environments worldwide. However, top predators are strongly affected by environmental change and anthropogenic activities. Common guillemots (Uria aalge, hereafter guillemots), as one of the world’s most numerous seabird species, are prone to interference with offshore wind farms (OWFs). This study assessed the cumulative impacts of all operating OWFs on guillemots in the German North Sea. These estimates were applied to quantify the possible conflicts between guillemot occurrence and current German government plans to implement large-scale OWFs. If OWFs were implemented according to the current maritime spatial plan for the German Exclusive Economic zone, they would cover 13% of the German North Sea. Guillemot numbers peak during autumn, with German North Sea offshore waters hosting approximately 90,000 individuals. Guillemot density in autumn was significantly reduced within a radius of 19.5 km around operating OWFs. Applying this disturbance distance to current installation plans, about 70% of the German North Sea would be affected, and an estimated 68% of guillemots in the German North Sea would experience habitat loss. This highlights the possible threat to guillemots in the southern North Sea if the current German government plans are implemented. The current estimates are highly relevant to decisions regarding marine spatial planning and management recommendations. Such evaluations are essential for developing sustainable scenarios including reducing the human CO2 footprint, whilst also conserving biodiversity.

Big hands holding small hands: The role of new agricultural operating entities in farmland abandonment

It is crucial to address farmland abandonment to achieve Zero Hunger according to the United Nations’ sustainable development goals. However, quantitative research on this topic is relatively lacking. Based on a large sample of panel data from the Chinese Family Database, this study applies a panel Tobit model to examine the relationship between new agricultural operating entities (NAOEs) and farmland abandonment. The results show that NAOEs—professional operators, family farms, and agricultural cooperatives—are negatively and significantly associated with the ratio of abandoned farmland areas. This effect is achieved through channels such as promoting land leasing, providing technical guidance, and facilitating the sale of agricultural products. Additionally, NAOEs benefit more from China’s central and western regions, mountainous areas, villages with better land tenure security, and households with poorer human resource endowments. These findings provide valuable insights for policymakers to ensure food security and promote sustainable development by cultivating various large-scale farming entities.

Food estate management strategy in Humbang Hasundutan Regency, North Sumatra Province

Food Estate is the concept of developing agricultural production on a wide scale, as an effort to create national food security by extensifying land as a form of large-scale agriculture that relies on the agricultural industry. Data were obtained from questionnaires through the Purposive sampling method, identification of internal and external factors can be carried out so that a food estate management strategy can be formulated using a SWOT analyst. Based on internal factors, the most important strength is the commitment of off-takers (cooperation, use of certified seeds, production targets, demplot, farm business analysis, and drip irrigation systems) with a score of 0.43, and the use of technology and increasing public knowledge about the horticultural system with a score of 0.43. While the variable that has the highest weakness is that land cannot be traded with a score of 0.42. The results of an external analysis obtained the opportunity variable with the highest value, namely the production cost borne by the off taker, and the agreed crop price between the off taker and farmers with a score of 0.44, and then external variables in the form of threats, namely pests and high rainfall with a score value of 0.42.

Envisioning prairie agroecology: Farmer visual constructions of place-based ecological agriculture in Canada

Climate change is driving new challenges for farmers around the world, provoking a sense of urgency in the search for on-farm solutions and pathways to sustainable agricultural systems. While agroecology has gained recognition as a promising option for climate resilience, it remains nascent in the Canadian Prairies—a significant agricultural region dominated by large-scale conventional agriculture. Amid the sprawling fields of grains and oilseeds primarily destined for export markets, growing farm consolidation, and increased land concentration, farmers committed to ecological principles are building a prefigurative foundation for prairie agroecology. Far from cohering into a unified definition, this article captures what agroecology on the Prairies looks like. Through a community-engaged research design and in consultation with the National Farmers Union of Canada, we explore farmers’ reflections on agroecology and provide a participatory platform for farmer-led constructions of agroecology. Through dialogue with 19 farmers of different farm sizes and production types that began in the 2021 farming season—one marked by drought and extreme heat—we use photovoice, visual elicitation interviews, and participatory video to document and mobilize visual constructions of an emerging prairie agroecology. Despite a shared vision among the farmer participants about the need for a sustainability transition through diversified farming practices, three key questions emerged about the future of prairie agroecology: (1) Can prairie agroecology scale up and out, and if so, under what conditions? (2) To what extent is prairie agroecology possible without dense, place-based social networks? and (3) What are the possibilities for prairie agroecology when the future of farming in the region is uncertain, especially given the changing farmer demographics and Canada’s settler colonial context? We explore these questions and provide reflections on key issues confronting the future of prairie agroecology.

Sustainable Innovation in the Canadian Agrifood Sector: Past, Present & Future

In order to remain globally competitive with sustainable innovations in agri-food, both the public and private sectors in Canada must increase investment and in the industry. Studies reveal that both sectors’ support for agri-food innovation has declined in recent years. To spur innovation and growth public funding should revert to previous levels, ideally reaching 0.10 per cent of GDP. Incentives such as tax relief, matching funds and enhanced protection of intellectual property rights could spur increased levels of private sector investment in innovation. In the past 50 years, innovation in agriculture has brought tremendous benefits to producers, processors and consumers. Successful innovations include genetically modified crops, large-scale cattle feeding operations and the adoption of no-till farming, which has reduced the traditional practice of summerfallowing fields. Still, with the demand for a secure global food supply and growing concerns about the environmental impacts of large-scale farming, the need for sustainable innovation in the agri-food sector is pressing. This paper offers three recommendations for policy-makers. First, public funding for agricultural research and development should be increased to prior levels. Next, the private sector needs more favourable conditions to foster investment in the agri-food industry. Last, if intellectual property rights are strengthened, innovating firms will be reassured that they can capture the economic benefits innovation creates.

Cost-Return Structure and Farmers’ Opinions on Cashew Nut Cultivation: A Comparative study of Small and Large Scale Farmers From India

Purpose: This study focuses on analysing the cost and returns associated with cashew cultivation with the aim of showcasing its profitability for small scale and large-scale farmers. Additionally, the research explores the perspectives of farmers on factors affecting cashew cultivation, such as profitability, incentives, support systems, soil quality, climate conditions, and related aspects. Method/design/approach: The researchers collected primary data from 220 cashew nut farmers and employed techniques like regression analysis, percentile analysis, and the Kolmogorov-Smirnov (KS) test to evaluate the collected data. Results and Conclusion: The results indicated that large-scale farmers enjoy advantages in terms of productivity and profitability compared to small farmers. There is a direct correlation between the size of a farm and its productivity. However, large farmers face higher costs for cultivation in contrast to small farmers. Farmers generally hold a positive view about the profitability, incentives, and support provided for cashew cultivation. However, they express concerns about the crop’s adaptability to different climates and soil conditions. Originality/value: The study contributes by highlighting that large scale farmers have an advantage in terms of productivity and profitability. It indicates the need for better policy formation in favour of small-scale farmers by allocating them additional land through appropriate amendments.

Cluster Based Pre Scaling Up of Improved Malt Barley Technologies: Evidence from West Shewa Zone, Oromia Region, Ethiopia

Malt barley is a high-opportunity cash crop, with great room for profitable expansion, particularly when connected to growing breweries. With the intention of popularizing advanced malt barley varieties (IBON174/03 and HB-1963) on a large-scale demonstration farming approach, this activity was carried out in West Shewa Zone potential areas to increase production and productivity of malt barley technologies during 2020-2022 production seasons. West Shewa Zone was purposively selected based on agro-ecological zone as the target population for this cluster farming. From the Zone potential areas, three districts were randomly selected including Ambo, Toke kutaye and Elfeta Districts. From each district, 9 kebeles and 144 host farmers participated in this cluster based on their interest and availability of adjacent farm plots. Thus, 9 clusters were formed, and 60 ha of land was covered on improved malt barley technologies. Training was given for stakeholders for 144 farmers, 44 DAs, and 16 agricultural experts who worked in selected districts on barley production and management packages. The study found that the average yield from the IBON174/03 variety was 30qt ha-1, 29qt ha-1, and 28qtha-1 at Toke kutaye, Elfeta and Ambo districts, with an overall mean grain yield of 29qtha-1. The HB-1963 variety yielded 26 qt ha-1, 24 qt ha-1 at Toke kutaye, Elfeta and Ambo districts respectively for an overall grain yield of 25 qt ha-1. Therefore, from the researchers and farmers evaluation both demonstrated malt barley varieties were recommended for the study areas and similar agro-ecologies for further demonstration and dissemination.

Performance Evaluation of Multiple Machine Learning Models in Predicting Power Generation for a Grid-Connected 300 MW Solar Farm

Integrating renewable energy sources (RES), such as photovoltaic (PV) systems, into power system networks increases uncertainty, leading to practical challenges. Therefore, an accurate photovoltaic (PV) power prediction model is required to provide essential data that supports smooth power system operation. Hence, the work presented in this paper compares and discusses the results of different machine learning (ML) techniques in predicting the power produced by the 300 MW Sakaka PV Power Plant in the north of Saudi Arabia. The validation of the presented work is performed using real-world operational data obtained from the specified solar farm. Several performance measures, including accuracy, precision, recall, F1 Score, and mean square error (MSE), are used in this work to evaluate the performance of the different ML approaches and determine the most precise prediction model. The obtained results show that the Support Vector Machine (SVM) with a Radial basis function (RBF) is the most effective approach for optimizing solar power prediction in large-scale solar farms.

Biosecurity implementation on large-scale poultry farms in Europe: A qualitative interview study with farmers

Biosecurity is an essential tool for rearing healthy animals. Biosecurity measures (BMs) are well known in poultry production, but it is difficult to assess actual implementation on farms. The aims of this qualitative study were (1) to provide an overview of biosecurity implementation according to poultry farmers in Europe; and (2) to better understand the reported reasons and potential obstacles for not implementing the measures. In seven European Union Member States, 192 farmers (118 under contract with a company and 68 independents) working in seven different categories of poultry production were interviewed on 62 BMs to determine the frequency of implementation and the reasons for non-implementation. Most of the replies (n = 7791) concerning BM implementation were reported by the farmers as “always” implemented (81%), statistically higher for breeders (87%) and layers (82%) and lower for independent farms versus farms under contract with a company (79.5% and 82.5%, respectively). Regardless the poultry production category, the most frequently implemented BMs declared by the farmers were daily surveillance of birds, rodent control and feed storage protection. Standard hygiene practices were also mentioned as high-implementation measures for most production categories, with some deficiencies, such as rendering tank disinfection after each collection and, for meat poultry, disinfection of the feed silo and bacterial control of house cleaning and disinfection between each cycle. The entry of vehicles and individuals onto poultry farms, especially during critical points of eggs collection for breeders and layers, as well as the presence of other animals, such as the “all in/all out” practice, particularly in layers and ducks, were also reported as the least commonly practiced measures. The main reasons for not implementing the measures (n = 1683 replies) were low awareness and poor knowledge of the expected benefits of biosecurity (“no known advantages” 14%, and “not useful” 12%), the lack of training (“not enough training” 5% and “advice” 7%), lack of time (19%), and financial aspects (17%). Despite the good overall biosecurity mentioned by the farmers, these findings highlight certain deficiencies, suggesting room for improvement and the need for targeted and tailored support of poultry farmers in Europe.

Principles and legal tools for equitable water resource allocation: prioritization in South Africa

ABSTRACT South Africa’s legally binding National Water Resource Strategy specifies a people-oriented prioritization for the equitable allocation of the nation’s public trust of surface and groundwater resources. This article analyses how the Inkomati–Usuthu Catchment Management Agency seeks to operationalize the three highest priorities in the Sabie Sub Catchment: the Basic Human Needs Reserve for domestic and constitutionally based productive water uses; customary water tenure in former homelands prioritized over the upstream commercial forestry and large-scale farming and the downstream Kruger National Park; and priority General Authorizations overcoming administrative injustices of current licensing. These highest priorities imply curtailment of the lowest priority, high-impact economic uses.

The influence of technology perceptions on farmers' water-saving irrigation technology adoption behavior in the North China Plain

Abstract The application and promotion of water-saving irrigation technology are of great significance for maintaining food security and the sustainable development of agricultural water resources. Based on the characteristics of integrated agricultural technologies, a binary logistic model was used to analyze the impact of technology perception on farmers' adoption behavior regarding water-saving irrigation technologies using data from surveys of 775 wheat and maize farmers in the North China Plain. The results show the following: the perceived ease of use of technology significantly contributes to farmers' water-saving irrigation technology adoption behavior, but the effect of the perceived usefulness of technology is not significant. Government regulation plays a moderating role in the impact of the perceived ease of use of technology on the adoption of water-saving irrigation technologies by farmers. In addition to the perceived ease of use of technology and technology training, large-scale farmers are influenced by government advocacy and technology subsidies, while smallholders are mainly influenced by the perceived usefulness of technology. Therefore, the focus of future work should be on improving farmers' perceptions of the ease of use of water-saving irrigation technologies, expanding the scope of technical training and technical subsidies, and strengthening government advocacy and education.

Assessment of morphological and chlorophyll content traits in Bambara groundnut (Vigna subterannea [verdc L.

Background: Bambara groundnut has promising economic potential due to its various uses such as food, medicinal and agronomic benefits. To date, there are no significant breeding efforts aimed at cultivar development and the crop remains underutilised.Aim: To characterise and identify Bambara groundnut landraces using agro-morphological and chlorophyll traits to identify breeding lines for cultivar development.Setting: The experiment was conducted in Limpopo and North West provinces (Loskop and Molelwane research farms).Methods: This study used randomised complete block design (RCBD) with three replications.Results: Analysis of variance revealed significant variations among most of the landraces used. Highly significant positive correlations were observed for most of the traits recorded. The principal component analysis (PCA) indicated that the first six principal components contributed 78.34% of the total variability among the test genotypes that were being evaluated. The biplot and dendrogram further grouped the landraces according to traits associated with them. Shannon Weaver’s diversity index showed a wide variability among the accessions in qualitative morphological traits.Conclusion: The agro-morphological traits and chlorophyll content characterisation showed significant variability within the landraces tested. These findings would be beneficial for breeders to choose the desirable traits associated with the Bambara groundnut landraces in the breeding programme for the development of new breeding population.Contribution: The identified superior landraces will be utilised by the small-scale and large-scale commercial farmers for direct cultivation and marketing, and can be used as parents in breeding programmes.

Wind turbine blade icing risk assessment considering power output predictions based on SCSO-IFCM clustering algorithm

With the expansion of large-scale wind farms, wind power penetration has surged. However, high turbine operations correlate with rising maintenance costs and failures, often due to blade icing. Blade icing in wind turbines often leads to expensive mechanical and operational emergencies. While many detection methods identify icing presence, they fall short in assessing its impact severity. By observing power changes before and after icing, we can gauge its effect. Hence, we suggest an icing risk assessment method incorporating wind power predictions (WPPs). Single prediction methods, whether physical or data-driven, have distinct strengths and limitations. Physical models are clear but may struggle with complex nonlinearities, while data-driven ones handle such complexities but lack interpretability and rely heavily on data quality. A hybrid approach merges the clarity of physical models with the flexibility of data-driven ones. Therefore, a two-stage hybrid forecasting strategy is developed to improve the accuracy of WPPs. Specifically, a four-parameter model based on power curves is constructed to find the preliminary WPPs, and an error correction model based on a multilayer perceptron is constructed to correct the WPP results. Previous research illustrates the benefits that additional feature data (beyond wind power) brings to the identification of icing failures. To fully utilize more feature information and improve icing risk assessment reliability, we propose a hybrid sand cat swarm optimization and improved fuzzy C-means clustering algorithm to determine power deviation and other feature data related to icing detection. Real-world sensor data from supervisory control and data acquisition systems are used to validate the proposed icing risk assessment method (that considers WPPs). The results indicate that the proposed method can achieve effective risk classification and provide a basis for O&M decisions affecting wind turbine equipment.

The Impact of Land Transfer-In on Crop Planting Structure and Its Heterogeneity among Farmers: Evidence from China

The crop planting structure in the world has shown a trend of “non-grain”, which will shake the foundations of global food security in the long run. As a basic and important production factor, changes in land will have an impact on farmers’ crop planting decisions. In this paper, we take China, a country that is experiencing land transfer, “non-grain” production, and farmer differentiation, as the research area, use the household survey data at the national level, and adopt the methods of Propensity Score Matching (PSM) and multiple regression models to reveal the impact of land transfer-in on the crop planting structure and its heterogeneity among farmers. The results showed that land transfer-in can drive the crop planting structure to tend to be “non-grain” in China. The research conclusion was still valid after the robustness tests of expanding the sample size, increasing the number of control variables, and introducing endogenous problem management. The heterogeneity analysis indicated that the negative impact of land transfer-in on the planting of grain crops mainly exists for large-scale farmers and farmers with agriculture as the main source of income. Based on these findings, the Chinese government should formulate targeted policies to prevent the “non-grain” tendency of crop planting structure after land transfer-in.

Influence of repeated estrus synchronization treatment on hormone secretion, growth, and development of dairy goats.

In large-scale intensive farms, dairy goats often undergo frequent estrus synchronization (ES) treatment, which may result in a decline in reproductive performance; however, the underlying mechanism remains unclear. The present study aimed to investigate the effect of pregnant mare serum gonadotropin (PMSG) and progesterone (P4)-mediated ES treatment on fertility in dairy goats, while also identifying key metabolic and endocrine mechanisms that influence reproductive performance in does subjected to repeated ES treatment. Forty-eight Saanen does were randomly assigned to two groups (24 goats each) that received ES treatments either thrice fortnightly (3-PMSG) or once (1-PMSG) simultaneously with the third ES treatment of the 3-PMSG group during the breeding season. ES treatment was performed via the intravaginal insertion of a controlled internal drug release (CIDR) device impregnated with 300 mg P4, followed by 300 IU PMSG injections 48 h before CIDR withdrawal. Blood was collected to detect the level of hormones and blood biochemical indices. Additionally, estrus rate, fecundity rate, body weight, size, and lactation performance were measured. The results showed that repeated ES treatment markedly decreased the estrus rate and fecundity rate of goats. Among the does in all groups, there was no substantial difference in follicle stimulating hormone, luteinising hormone, gonadotropin-releasing hormone, melatonin, growth hormone, PMSG, total cholesterol, total protein, and glucose levels, as well as the body weight, body size, and lactation performance. Repeated ES treatment elevated estrogen (E2) levels 36, 48, and 72 h post-CIDR removal; increased P4 upon CIDR insertion; and raised PMSG antibody levels 24, 48, and 72 h post-CIDR removal. The results suggest that elevated anti-PMSG levels are the primary reason for the decline in ES efficiency, and that high E2 and P4 levels at some time points also impair reproductive performance. These findings provide novel insights into the metabolic effects of repeated PMSG stimulation in goats, guiding future reproductive hormone use in breeding practices.

Effect of postpartum drenching on plasma parameters of cows at a large-scale dairy farm.

The aim of the present study was to explore the influence of postpartum drenching with a feed additive on the plasma concentration of biochemical parameters while factoring in prepartum rumination times (RT). One hundred and sixty-one cows were fitted with a Ruminact© HR-Tag approximately 5 days before calving. Drenching and control groups were established based on calving dates. Animals in the drenched group were treated three times (Day 1/day of calving/, Day 2, and Day 3 postpartum) using a feed additive containing calcium propionate, magnesium sulphate, yeast, potassium chloride and sodium chloride mixed in approximately 25 L of lukewarm tap water. Blood samples were collected on Days 1, 2, 3, 7 and 12. Cows with below the average RT were categorised as "low rumination" and those above it as "high rumination" animals. Drenching decreased the plasma concentrations of total protein, urea and creatinine and increased the levels of alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT) and chloride. Low rumination time prepartum resulted in higher concentrations of beta-hydroxybutyrate, total protein and activities of alkaline phosphatase and GGT, while it decreased the activity of ALT and the concentrations of calcium, magnesium, sodium and potassium. The day of lactation had an effect on all parameters except for potassium.

Managing urban development could halve nitrogen pollution in China

Halving nitrogen pollution is crucial for achieving Sustainable Development Goals (SDGs). However, how to reduce nitrogen pollution from multiple sources remains challenging. Here we show that reactive nitrogen (Nr) pollution could be roughly halved by managed urban development in China by 2050, with NH3, NOx and N2O atmospheric emissions declining by 44%, 30% and 33%, respectively, and Nr to water bodies by 53%. While rural-urban migration increases point-source nitrogen emissions in metropolitan areas, it promotes large-scale farming, reducing rural sewage and agricultural non-point-source pollution, potentially improving national air and water quality. An investment of approximately US$ 61 billion in waste treatment, land consolidation, and livestock relocation yields an overall benefit of US$ 245 billion. This underscores the feasibility and cost-effectiveness of halving Nr pollution through urbanization, contributing significantly to SDG1 (No poverty), SDG2 (Zero hunger), SDG6 (Clean water), SDG12 (Responsible consumption and production), SDG14 (Climate Action), and so on.