Search Results (20)

Ceftiofur sodium (CFS) is a clinically significant cephalosporin widely used in the livestock and poultry industries. However, CFS that is not absorbed by animals is excreted in feces, entering the environment and contributing to the emergence of antibiotic-resistant bacteria (ARB) and antibiotic-resistant genes (ARGs). This situation poses substantial challenges to both environmental integrity and public health. Currently, research on the biodegradation of CFS is limited. In this study, we isolated a strain of Escherichia coli, designated E. coli CS-1, a Gram-negative, rod-shaped bacterium capable of utilizing CFS as its sole carbon source, from fecal samples collected from hog farms. We investigated the effects of initial CFS concentration, pH, temperature, and inoculum size on the degradation of CFS by E. coli CS-1 through a series of single-factor experiments conducted under aerobic conditions. The results indicated that E. coli CS-1 achieved the highest CFS degradation rate under the following optimal conditions: an initial CFS concentration of 50 mg/L, a pH of 7.0, a temperature of 37 °C, and an inoculum size of 6% (volume fraction). Under these conditions, E. coli CS-1 was able to completely degrade CFS within 60 h. Additionally, E. coli CS-1 exhibited significant capabilities for CFS degradation. In this study, six major degradation products of (CFS) were identified by UPLC–MS/MS: desfuroyl ceftiofur, 5-hydroxymethyl-2-furaldehyde, 7-aminodesacetoxycephalosporanic acid, 5-hydroxy-2-furoic acid, 2-furoic acid, and CEF-aldehyde. Based on these findings, two degradation pathways are proposed. Pathway I: CFS is hydrolyzed to break the sulfur–carbon (S–C) bond, generating two products. These products undergo subsequent hydrolysis and redox reactions for gradual transformation. Pathway II: The β-lactam bond of CFS is enzymatically cleaved, forming CEF-aldehyde as the primary degradation product, which is consistent with the biodegradation mechanism of most β-lactam antibiotics via β-lactam ring cleavage. Transcriptome sequencing revealed that 758 genes essential for degradation were upregulated in response to the hydrolysis and redox processes associated with CFS. Furthermore, the differentially expressed genes (DEGs) of E. coli CS-1 were functionally annotated using a combination of genomics and bioinformatics approaches. This study highlights the potential of E. coli CS-1 to degrade CFS in the environment and proposes hypotheses regarding the possible biodegradation mechanisms of CFS for future research. Full article

The Silway River has historically failed to meet safe fecal coliform levels due to improper waste disposal. The river mouth is located in General Santos City, the tuna capital of the Philippines and a leading producer of hogs, cattle, and poultry. The buildup of contaminants due to direct discharge of waste from chicken farms and existing water quality conditions has led to higher fecal matter in the Silway River. While there were technical reports in the early 2000s about poultry farming, this is the first study where fecal coliform from poultry farming was detected in the Silway River using highly sensitive protocols like qPCR. This study characterized the effect of flow velocity and physicochemical water quality parameters on chicken fecal contamination. Gene markers such as Ckmito and ND5-CD were used to detect and quantify poultry manure contamination through microbial source tracking (MST) and environmental DNA (eDNA) profiling. The results of this study showed the presence of chicken fecal bacteria in all stations along the Silway River. The results revealed that normal levels of water quality parameters such as temperature, pH, and high TSS concentrations create favorable conditions for chicken fecal coliforms to thrive. Multiple regression analysis showed that flow velocity and DO significantly affect chicken fecal contamination. A lower cycle threshold (Ct) value indicated higher concentration of the marker ND5-CD, which means higher fecal contamination. It was found that there was an inverse relationship between the Ct value and both velocity (R² = 0.55, p = 0.01) and DO (R² = 0.98, p = 0.2), suggesting that low flow velocity and low DO can lead to higher fecal contamination. Findings of fecal contamination could negatively impact water resources, the health of nearby residents, and surrounding farms and industries, as well as the health and growth of fish. Full article

The development of animal husbandry directly affects climate change and the ecological environment. This study aims to explore the relationship between carbon emissions from animal husbandry and economic growth in Inner Mongolia and to provide theoretical and countermeasure support for sustainable development. Based on the environmental Kuznets theory, the present situation of animal husbandry and economic growth in this region is analyzed. By analyzing slaughter and storage data for cow, sheep, hog, and poultry from 2000 to 2022, we calculated carbon emissions using the IPCC coefficient method. The environmental Kuznets curve is used to control variables such as human capital, government intervention, openness, technological innovation, and environmental protection expenditure. The findings show that carbon emissions from cows and sheep have risen significantly over the past 23 years, while the hog industry has remained stable. Both the number of poultry farms and their carbon emissions have declined. Economic growth is one reason for the increase in carbon emissions, while government intervention and openness have had mixed results. To ensure sustainable development, Inner Mongolia should strengthen government supervision, increase investment in environmental protection, expand opening-up, improve rural education, and promote low-carbon growth. Full article

The sustainable development of the hog industry has significant implications for agricultural development, farmers’ income, and the daily lives of residents. Precise hog supply forecasts are essential for both government to ensure food security and industry stakeholders to make informed decisions. This study proposes an integrated framework for hog supply forecast. Granger causality analysis is utilized to simultaneously investigate the causal relationships among piglet, breeding sow, and hog supply, as well as to ascertain the uncertain time lags associated with these variables, facilitating the extraction of valuable time lag features. The Seasonal and Trend decomposition using Loess (STL) is leveraged to decompose hog supply into three components, and Autoregressive Integrated Moving Average (ARIMA) and Xtreme Gradient Boosting (XGBoost) are utilized to forecast the trends, i.e., seasonality and residuals, respectively. Extensive experiments are conducted using monthly data from all the large-scale pig farms in Chongqing, China, covering the period from July 2019 to November 2023. The results demonstrate that the proposed model outperforms the other five baseline models with more than 90% reduction in Mean Squared Logarithm (MSL) loss. The inclusion of the piglet feature can enhance the accuracy of hog supply forecasts by 42.1% MSL loss reduction. Additionally, the findings reveal statistical time lag periods of 4–6 months for piglet and 11–13 months for breeding sow, with significance levels of 99%. Finally, policy recommendations are proposed to promote the sustainability of the pig industry, thereby driving the sustainable development of both upstream and downstream sectors of the swine industry and ensuring food security. Full article

Hog insurance and rural environmental protection are complementary to each other. Studying the environmental effects of hog insurance is imperative for safeguarding food safety and promoting the long-term development of the agricultural insurance industry. Informed by the risk management theory and sustainable development theory, this paper constructs a theoretical framework for the impact of policy-supported hog insurance on the green total factor productivity (GTFP) of hog farming. Utilizing panel data from China’s hog-dominant production areas spanning from 2005 to 2021, the slacks-based measures of directional distance functions (SBM-DDF) model and multiple-time-point difference-in-differences (DID) approach were used to measure GTFP and explore the effects of hog insurance on GTFP and the underlying mechanisms. The findings indicate a substantial enhancement in GTFP due to hog insurance. The conclusion drawn was robust to various tests. The mechanism is that hog insurance fosters GTFP by expanding the breeding scale, adjusting the planting–breeding structure, and promoting technological progress. Furthermore, the environmental effects of hog insurance policy are more pronounced in economically developed regions, with significant effects observed on the GTFP of free-range, small-scale, and medium-scale hog-farming households. This study contributes new evidence to the field of assessing the environmental impact of agricultural insurance policies and provides valuable insights for furthering green transformation and development in the hog insurance-supported breeding industry. Full article

Hog farm wastewater may require novel biological treatment techniques to improve efficiency and reduce costs. Previous studies combining vermifiltration with downstream hydroponics showed the need for a balanced wastewater nutrient content, particularly the nitrogen-to-phosphorus ratio. Here, a deep-water culture hydroponic system, growing lettuce as model culture, was used to remediate hog farm wastewater after an initial vermifiltration stage, aiming to produce an effluent suitable for irrigation. Supplemented vermifiltered wastewater (SVW) with added nutrients was tested against unsupplemented vermifiltered wastewater (VW) over 35 days, using a synthetic nutrient solution (NS) as a control. Supplementation was shown to improve lettuce growth, light use efficiency, and water use efficiency. Nutrient analysis over time showed a better-balanced phosphorus and nitrogen removal in SVW than in VW; in all treatments nitrogen and phosphorus content was reduced to legally acceptable levels for treated wastewater reuse in irrigation: nitrate 5 mgN L⁻¹ in VW and undetectable in SVW and NS; ammonia undetectable in all treatments; and total phosphorus 2.4 mg L⁻¹ in SVW, 0.9 mg L⁻¹ in NS and undetectable in VW. Coliforms increased in VW and SVW during hydroponic treatment, which should be solved by disinfection. Overall, combining vermifiltration with downstream hydroponic culture proved to be a promising treatment to remediate nutrients in hog farm effluent to make it suitable to be reused for irrigation. Full article

China’s large-scale hog farmers are playing an increasingly important role in promoting the stable development of the hog industry. Taking large-scale hog enterprises as samples, based on hog sales data from January 2019 to July 2022, this paper adopts a two-way fixed-effects model to test the impact, mechanism, and heterogeneity of hog futures on the production stability of large-scale hog farmers. The study found that hog futures help promote stable production of large-scale farmers. This finding still holds after a series of robustness tests. The mechanism analysis found that, first, hog futures help large-scale farmers expand their risk management factor inputs. Second, hog futures help reduce the impact of hog price risk on production. Finally, hog futures help stabilize farmers’ production expectations. The moderating effects analysis found that the stabilizing effect of hog futures will enhance as farmers’ share of hog farming operations increases. Heterogeneity analysis found that when hog prices fluctuate negatively, hog futures help promote the stable production of large-scale farmers. When hog prices fluctuate positively, the production stabilization effect of hog futures is not obvious. Therefore, hog enterprises should be encouraged to participate in hog futures hedging transactions to promote stable hog production. Full article

The drastic fluctuations in pork prices directly affect the sustainable development of pig farming, agriculture, and feed processing industries, reducing people’s happiness and sense of gain. Although there have been extensive studies on pork price prediction and early warning in the literature, some problems still need further study. Based on the monthly time series data of pork prices and other 11 influencing prices (variables) such as beef, hog, piglet, etc., in China from January 2000 to November 2023, we have established a project pursuit auto-regression (PPAR) and a hybrid PPAR (H-PPAR) model. The results of the PPAR model study show that the monthly pork prices in the lagged periods one to three have an important impact on the current monthly pork price. The first lagged period has the largest and most positive impact. The second lagged period has the second and a negative impact. We built the H-PPAR model using the 11 independent variables (prices), including the prices of corn, hog, mutton, hen’s egg, and beef in lagged period one, the piglet’s price in lagged period six, and by deleting non-important variables. The results of the H-PPAR model show that the hog price in lagged period one is the most critical factor, and beef price and the other six influencing variables are essential factors. The model’s performance metrics show that the PPAR and H-PPAR models outperform approaches such as support vector regression, error backpropagation neural network, dynamic model average, etc., and possess better suitability, applicability, and reliability. Our results forecast the changing trend of the monthly pork price and provide policy insights for administrators and pig farmers to control and adjust the monthly pork price and further enhance the health and sustainable development of the hog farming industry. Full article

In the pursuit of establishing a more environmentally sustainable and low-carbon hog farming system, the accurate quantification of emissions of greenhouse gas emanating from these systems, especially within the context of China, becomes imperative. Here, drawing insights from a life cycle approach, exhaustive field surveys, and context-specific analyses, we establish an emission measurement index system tailored to hog farming enterprises in China’s Shaanxi Province. Using this methodology, we probed the emission profiles and characteristics of three emblematic hog farming enterprises in the region. Our key findings are as follows: (1) The carbon dioxide emissions per kilogram of pork, factoring in feed cultivation, processing, and transportation, for Pucheng Xinliu Science and Technology, Baoji Zhengneng Farming, and Baoji Zhenghui Farming were quantified as 0.80298 kg, 1.52438 kg, and 0.81366 kg, respectively. (2) Presently, the methane emission coefficient due to enteric fermentation in large-scale hog farms in Shaanxi surpasses the default value set by the Intergovernmental Panel on Climate Change (IPCC). There appears to be a consistent underestimation of enteric methane emissions from live pigs in the province, as gauged against the IPCC metrics. Notably, the emission factor for fattening pigs averaged 2.61823 kgCH₄/head/year, while that for breeding pigs stood at 2.96752 kgCH₄/head/year. (3) When examining methane and nitrous oxide outputs from manure across various production stages, we observed that emissions from lactating pigs significantly outweigh those from other stages. Interestingly, nitrous oxide emissions from breeding pigs during fattening, finishing, and gestation remained nearly the same, regardless of the manure treatment method. (4) Under the management protocols followed by Pucheng and Baoji, the total carbon emissions from an individual fattening pig amounted to 328.5283 kg and 539.2060 kg, respectively, whereas for breeding pigs, these values were 539.2060 kg and 551.6733 kg, respectively. Further calculations showed that the average carbon footprint CF of large-scale pig farms in China was 3.6281 kgCO₂/kg pork. In conclusion, optimizing feed cultivation and transportation logistics, promoting integrated breeding and rearing practices, refining feed formulation, and advancing manure management practices can collaboratively attenuate greenhouse gas emissions. Such synergistic approaches hold promise for steering the hog industry towards a greener, low-carbon, and sustainable trajectory. Full article

This research delves into the intricacies of decision-making processes underpinning the willingness to upgrade technology within the burgeoning domain of intelligent pig farming in China, employing the UTAUT model to scrutinize how various determinants sway upgrade willingness and the ensuing behavioral modification. By applying the UTAUT model to intelligent pig farming, the inquiry evaluates the impact of performance expectations, effort expectations, social influence, and contributory factors on upgrade willingness and behavior, with data amassed from assorted novel agricultural management entities in China. The findings unveil that performance and effort expectations, social influence, and contributory factors have a favorable influence on upgrade willingness, while contributory factors, alongside the augmentation of upgrade willingness, positively affect upgraded behavior. This inquiry underscores the multifaceted interaction of factors guiding technological upgrade verdicts in intelligent pig farming, furnishing invaluable insights for comprehending technology adoption in agriculture. It lays a groundwork for devising strategies to spur technological advancements, harboring potential for wider applications across varied agricultural vistas. Full article

Animal diseases are a serious threat to animal husbandry production and diet health, and effective prevention and control measures need to be explored. This study investigates the factors influencing the adoption of biosecurity prevention and the control behaviours of hog farmers towards African swine fever and provides appropriate recommendations. Using research data from Sichuan, Hubei, Jiangsu, Tianjin, Liaoning, Jilin, and Hebei, we employed a binary logistic model to empirically analyse these factors. Regarding individual farmer characteristics, male farmers emphasised biosecurity prevention and control in farms, with higher education actively influencing the adoption of prevention and control measures. Farmers who received technical training were actively inclined to adopt such behaviours. Furthermore, the longer the duration of farming, the more probable the farmers were to neglect biosecurity prevention and control. However, the bigger and more specialised the farm, the more inclined they were to adopt prevention and control behaviours. With respect to disease prevention and control awareness, the more risk-averse the farmers were, the more they actively adopted epidemic prevention behaviours. As the awareness of epidemic risk increased, the farmers tended to adopt active epidemic prevention behaviours by reporting suspected outbreaks. The following policy recommendations were made: learning about epidemic prevention and improving professional skills; large-scale farming, specialised farming; and timely dissemination of information to raise risk awareness. Full article

China’s African swine fever (ASF) outbreak, which started in 2018, has had a huge and far-reaching impact on China’s hog industry, and it has not been completely eliminated so far. This article analyzes the impact of the ASF epidemic on the costs and technical efficiency of hog production in China based on data from the China Agricultural Product Cost–Benefit Compilation (2012–2021) using a stochastic frontier trans-log production function model. The results show that, after the outbreak of the ASF epidemic in China, feed costs, medical and epidemic prevention costs, and other costs of hog production in China increased significantly; the technical efficiency of China’s hog production decreased significantly; large-scale hog farms were the most responsive to and greatly affected by the ASF epidemic; and there are regional differences in the impact of the ASF epidemic on technical efficiency of hog production. Future policies should focus on strengthening the R&D investment and technology promotion capacity of hog production, developing moderate-scale farming, and enhancing regional cooperation to improve technical efficiency of hog production. Full article

Hydrogen sulfide (H₂S) from hog operations contributes to noxious odors in the surrounding environment and can be life-threatening. There is, however, limited understanding of what influences H₂S emissions from these farms. Emissions of H₂S were measured periodically over the course of two years at hog finisher farms in humid mesothermal (North Carolina, NC, USA) and semi-arid (Oklahoma, OK, USA) climates. Emissions were determined using an inverse dispersion backward Lagrangian stochastic model in conjunction with line-sampled H₂S concentrations and measured turbulence. Daily emissions at the two lagoons were characterized by low emissions on most days with occasional days of high emissions. Mean annual area-specific emissions were much lower for the NC lagoon (1.32 µg H₂S m⁻² s⁻¹ ± 0.07 µg H₂S m⁻² s⁻¹) than the OK lagoon (6.88 µg H₂S m⁻² s⁻¹ ± 0.13 µg H₂S m⁻² s⁻¹). Mean annual hog-specific emissions for the NC lagoon were 0.75 g H₂S hd⁻¹ d⁻¹ while those for the OK lagoon were 1.92 g H₂S hd⁻¹ d⁻¹. Emissions tended to be higher during the afternoon, likely due to higher mean winds. Daily H₂S emissions from both lagoons were greatest during the first half of the year and decreased as the year progressed and a reddish color (indicating high populations of purple sulfur bacteria (PSB)) appeared in the lagoon. The generally low emissions at the NC lagoon and higher emissions at the OK lagoon were likely a result of the influence of wind on mixing the lagoon and not the presence of PSB. Full article

In recent decades, pigs and pork have been the central elements of Chinese agricultural systems, food security, and diet. China’s rapid income growth has induced a significant change in food consumption patterns, and hog production has received utmost attention from both, the Chinese government and the public. While the impact of Farmer Field Schools (FFS) on crop cultivation has been widely studied, few studies have examined the impact of FFS on hog production. This study uses data collected from 222 hog farmers in Beijing to examine the impact of FFS on the productivity of hog production, focusing on its three main indicators: feed conversion ratio and the mortality of sows and piglets. We found that farms that participated in FFS programs significantly improved the feed conversion ratio of hog production, particularly in small scale hog farms. On average, FFS reduced the feed conversion ratio for herd sizes of 1000, 500, and 200 by 6.8%, 10.7%, and 14.0%, respectively. We did not find evidence that farms that participated in FFS programs had a significant impact on minimizing the mortality of sows and piglets. This study suggests that the knowledge training model of the FFS program could also work in fields other than crop cultivation. Furthermore, we suggest that more attention could be paid to extension services diffusing knowledge of vaccination and disinfection in hog FFS programs. Full article

Mathematical models have many uses. When input data is limited, simple models are required. This occurs in pasture agriculture when managers typically only have access to temperature and rainfall values. A simple pasture growth model was developed that requires only latitude and daily maximum and minimum temperature and rainfall. The accuracy of the model was validated using ten site-years of measured pasture growth at a site under continuous stocking where management controlled the height of grazing (HOG) and a site under rotational stocking at a West Virginia University farm (WVU). Relative forage growth, expressed as a fraction of maximum growth observed at the sites, was reasonably accurate. At the HOG site constant bias in relative growth was not different from zero. There was a year effect due to the weather station used for predicting growth at HOG being 1.8 km from the pasture. However, the error was only about 10-percent. At the WVU site constant bias for relative growth was not different from zero and year effect was eliminated when adjusted for nitrogen status of the treatments. This simple model described relative pasture growth within 10-percent of average for a given site, environment, and management using only daily weather inputs that are readily available. Using predictions of climate change impact on temperature and rainfall frequency and intensity this model can be used to predict the impact on pasture growth. Full article