Short-Term Aerial Pollutant Concentrations in a Southwestern China Pig-Fattening House

Prevalence and Haplotypes of Toxoplasma gondii in Native Village Chickens and Pigs in Peninsular Malaysia

Toxoplasma gondii is an important zoonotic foodborne parasite capable of infecting almost all warm-blooded animal species worldwide. Toxoplasmosis is usually acquired via ingestion of undercooked infected animal tissues resulting in life-threatening consequences for unborn foetus and immunocompromised individuals. A cross-sectional study was carried out to determine the prevalence of T. gondii infection, its associated risk factors in farms, and haplotypes isolated from the native village chicken and pig populations in Peninsular Malaysia. The seroprevalence of T. gondii in village chickens at the animal level was low at 7.6% (95% CI: 4.60-11.60), while at the farm level, it was 52.0% (95% CI: 31.30-72.20). For pigs, the animal-level seroprevalence of T. gondii was 3.0% (95% CI: 1.60-5.10), while the farm-level, it was 31.6% (95% CI: 12.60-56.60). The PCR-based DNA detection on meat samples from chickens (n = 250) and pork (n = 121) detected 14.0% (95% CI: 9.95-18.9) and 5.8% (95% CI: 2.4-11.6) positive, respectively. Six unique T. gondii haplotypes were isolated from the tissue samples. Multivariable logistic regression analysis showed that feeding the chickens farm-produced feeds and allowing wild animals access to pig farms were significant determinants for farm-level seropositivity. Providing hygienic and good quality feeds to chickens and increasing biosecurity in pig farms through prevention of access by wildlife may reduce the risk of transmission of T. gondii infection in the local chickens and pig farms.

Characteristics and Traceability Analysis of Microbial Assemblage in Fine Particulate Matter from a Pig House

Fine particulate matter (PM2.5) can carry numerous substances and penetrate deep into the respiratory tract due to its small particle size; associated harmful microorganisms are suspected to increase health risks for humans and animals. To find out the microbial compositions of PM2.5 in piggeries, their interaction and traceability, we collected PM2.5 samples from a piggery while continuously monitoring the environmental indicators. We also identified pathogenic bacteria and allergens in the samples using high-throughput sequencing technology. We analyzed the microbial differences of PM2.5 samples at different heights and during different times of day and investigated the microbial dynamics among the PM2.5 samples. To better understand the interaction between microorganisms and environmental factors among different microbial communities, we applied the network analysis method to identify the correlation among various variables. Finally, SourceTracker, a commonly used microbial traceability tool, was used to predict the source of airborne microorganisms in the pig house. We identified 14 potential pathogenic bacteria and 5 allergens from PM2.5 in the pig houses, of which Acinetobacter was the dominant bacterium in all samples (relative abundance > 1%), which warrants attention. We found that bacteria and fungi directly affected the the microbial community. The bacterial community mainly played a positive role in the microbial community. Environmental variables mainly indirectly and positively affected microbial abundance. In the SourceTracker analysis using fecal matter and feed as sources and PM2.5 sample as sink, we found that fecal matter made the greatest contribution to both bacterial and fungal components of PM2.5. Our findings provide important insights into the potential risks of pathogens in PM2.5 to human and animal health and their main sources.

Prediction of Ammonia Concentration in a Pig House Based on Machine Learning Models and Environmental Parameters

Accurately predicting the air quality in a piggery and taking control measures in advance are important issues for pig farm production and local environmental management. In this experiment, the NH₃ concentration in a semi-automatic piggery was studied. First, the random forest algorithm (RF) and Pearson correlation analysis were combined to analyze the environmental parameters, and nine input schemes for the model feature parameters were identified. Three kinds of deep learning and three kinds of conventional machine learning algorithms were applied to the prediction of NH₃ in the piggery. Through comparative experiments, appropriate environmental parameters (CO₂, H₂O, P, and outdoor temperature) and superior algorithms (LSTM and RNN) were selected. On this basis, the PSO algorithm was used to optimize the hyperparameters of the algorithms, and their prediction performance was also evaluated. The results showed that the R² values of PSO-LSTM and PSO-RNN were 0.9487 and 0.9458, respectively. These models had good accuracy when predicting NH₃ concentration in the piggery 0.5 h, 1 h, 1.5 h, and 2 h in advance. This study can provide a reference for the prediction of air concentrations in pig house environments.

Recent evidence for toxic effects of NH3 exposure on lung injury: Protective effects of L-selenomethionine

Ammonia (NH₃) is a common air pollutant, which poses a serious threat to farm animals. L-selenomethionine is organic selenium (Se), which can inhibit intracellular ROS generation, block ROS-dependent autophagy, promote mitochondrial energy metabolism, and enhance the body's immunity. Lung, as an important organ of the respiratory system, is highly susceptible to the toxic effects of NH₃. However, there were few studies on the mechanism of toxic effects of NH₃ on lung tissues. The aim of this study was to investigate the effect of NH₃ on the lungs in pigs and the alleviating effect of L-selenomethionine. Twenty-four Large White*Duroc*Min pigs were randomly assigned to 4 groups: control group, NH₃ group, Se group, and NH₃ +Se group. The results showed that exposure to NH₃ caused damage and inflammation in lung tissues and significantly increased blood NH₃ concentration. NH₃ induced changes of oxidative stress indexes (GSH, GSH-Px, SOD, MDA, Keap1, Nrf2, and HO-1) and expressions of energy metabolism related genes (HK1, HK2, PFK, PK, LDHA, and HIF-1α). Ultrastructure showed that mitochondrial damage and autophagosome increased significantly, and the expression levels of autophagy related genes (Beclin1, ATG5, ATG7, ATG10, and p62) changed. However, the addition of L-selenomethionine alleviated the above changes, but there was still a significant difference compared with the control group (P < 0.05). This finding can provide a new evidence for mitigation of NH₃ toxicity.

Effects of Manure Removal Frequencies and Deodorants on Ammonia and GHG Concentrations in Livestock House

In order to mitigate the concentration of NH3 and greenhouse gases (GHGs: CO2, N2O, CH4) in livestock houses, two experiments, one determining the ideal manure removal frequency by cleaning the feces from a livestock house once, twice, three, and four times a day, and one in which microbial deodorant and VenaZn deodorant were sprayed, were conducted in a rabbit breeding house. The NH3, CO2, N2O, and CH4 concentrations were monitored continuously with an Innova 1512 photoacoustic gas monitor during the experiments. The results were as follows: the manure removal frequency had a significant impact on the average concentrations of NH3, CO2, and CH4 in the rabbit house. Cleaning the feces in the rabbit breeding house two to three times a day significantly reduced the NH3 concentration, and, on the contrary, cleaning the feces four times a day increased the NH3 concentration in rabbit house; increasing the manure removal frequency significantly reduced the concentrations of CO2 and CH4 in the rabbit house. Considering the average concentrations of NH3, CO2, N2O, and CH4 in the rabbit house and economic cost, it was better to remove feces twice a day. The average NH3 and CO2 concentration declined significantly within 3 days in the summer and winter; the N2O concentration declined within 3 days in the summer but did not decline in the winter; and there was no effect on the CH4 concentration in the summer and in the winter after spraying the rabbit house with microbial deodorant. Therefore, it was better to spray microbial deodorant twice a week on Monday and Thursday to reduce the NH3, CO2, and N2O concentrations in rabbit houses. The NH3, CO2, N2O, and CH4 concentrations first showed a decreasing trend and then an increasing trend over 5 days in the summer and 7 days in the winter after VenaZn deodorant was sprayed in the rabbit house, and the NH3, CO2, N2O, and CH4 concentrations on day 3 and day 4 were significantly lower than they were on the other days.

Characteristics of PM2.5 and Its Correlation with Feed, Manure and NH3 in a Pig-Fattening House

Fine particulate matter (PM), including PM_2.5 in pig houses, has received increasing attention due to the potential health risks associated with PM. At present, most studies have analyzed PM_2.5 in Chinese pig houses utilizing natural ventilation. These results, however, are strongly affected by the internal structure and regional environment, thus limiting their applicability to non-mechanically ventilated pig houses. This experiment was carried out in an environmentally controlled pig house. The animal feeding operation and manure management in the house were typical for Southwest China. To reduce the influence of various environmental factors on PM_2.5, the temperature and humidity in the house were maintained in a relatively stable state by using an environmental control system. The concentration of PM_2.5 in the pig house was monitored, while the biological contents and chemical composition of PM_2.5 were analyzed, and feed, manure, and dust particles were scanned using an electron microscope. Moreover, bacterial and fungal contents and some water-soluble ions in PM_2.5 were identified. The results showed that the concentration of PM_2.5 in the pig house was strongly affected by pig activity, and a phenomenon of forming secondary particles in the pig house was found, although the transformation intensity was low. The concentration of PM_2.5 had negative correlations of 0.27 and 0.18 with ammonia and hydrogen sulfide, respectively. Interestingly, a stronger correlation was observed between ammonia and hydrogen sulfide and ammonia and carbon dioxide concentrations (the concentration of ammonia had stronger positive correlations with hydrogen sulfide and carbon dioxide concentrations at +0.44 and +0.59, respectively). The main potential sources of PM_2.5 production were feed and manure. We speculate that manure could contribute to the broken, rough, and angular particles that formed the pig house PM_2.5 that easily adhered to other components.

Mitigation Strategies of Air Pollutants for Mechanical Ventilated Livestock and Poultry Housing—A Review

The fast development of large-scale intensive animal husbandry has led to an increased proportion of atmospheric pollution arising from livestock and poultry housing. Atmospheric pollutants, including particulate matter (PM), ammonia (NH3), hydrogen sulfide (H2S), and greenhouse gases (GHG), as well as other hazardous materials (e.g., gases, bacteria, fungi and viruses), have significant influences upon the local atmospheric environment and the health of animals and nearby residents. Therefore, it is imperative to develop livestock and poultry housing mitigation strategies targeting atmospheric pollution, to reduce its negative effects on the ambient atmosphere and to promote sustainable agricultural production. In this paper, we summarize the various strategies applied for reducing outlet air pollutants and purifying inlet air from mechanical ventilated livestock and poultry housing. This review highlights the current state of knowledge on the removal of various atmospheric pollutants and their relative performance. The potential optimization of processes and operational design, material selection, and other technologies, such as electrostatic spinning, are discussed in detail. The study provides a timely critical analysis to fill the main research gaps or needs in this domain by using practical and stakeholder-oriented evaluation criteria.

Continuous Measurement of Ammonia at an Intensive Pig Farm in Wuhan, China

Measurements with high time resolution are necessary to capture variation patterns and to facilitate the estimation of uncertainty in ammonia inventories. Continuous real-time monitoring of ammonia was carried out in a naturally ventilated nursery pig house during two periods in winter and summer, respectively. A higher ventilation rate of about 73,799 ± 39,655 m3/h was obtained during the summer period in comparison with 1646 ± 604 m3/h in the winter. Correspondingly, ammonia level observed in summer (0.25 ± 0.10 mg/m3) was lower than that in winter (1.28 ± 0.74 mg/m3). Spatial variation of ammonia concentration was observed during the winter monitoring period. The mean ammonia emission factor was about 0.3221 ± 0.2921 g d−1 pig−1 in summer and 0.1039 ± 0.0550 g d−1 pig−1 in winter, ranging from 0.0094 to 1.9422 g d−1 pig−1 and 0.0046 to 0.2899 g d−1 pig−1, respectively. Significant correlation was found between ammonia emission and indoor temperature and relative humidity during the winter period. For the summer measurement, effects of ventilation rate and ammonia concentration on ammonia emission were significant. Prominent diurnal pattern existed for both ammonia concentration and emission, with higher emission rates during daytime. The results confirmed the existence of considerable uncertainty associated with the ammonia emission factor, acquired by snapshot measurements.