Large-scale Poultry Farms Research Articles

Advanced nutrient monitoring: Cost-effective cerium ion detection with smart device integration

This research is critically important for large-scale poultry farming, where vigilant monitoring is necessary to assess nutrient levels in poultry feed. Detecting cerium in poultry feed through colorimetric techniques is crucial for evaluating nutrient intake, feed quality, animal health, and broader environmental impacts. This study significantly contributes to ongoing research and monitoring efforts, aiding in maintaining an optimal mineral balance and enhancing chicken quality and overall poultry performance. The study utilized Alizarin Red dye (AR), both individually and in combination with Eriochrome Black T (EBT), to identify the presence of cerium ions. Various experimental conditions such as pH, concentration, temperature, and specificity were thoroughly examined. The UV-Vis absorption spectra indicated that the average minimum detectable limit for cerium ions is approximately 5 ppm, with a detection range of 0.2–3 mM. Additionally, a cost-effective paper-based sensor and a portable colorimetric method for detecting cerium ions were innovatively designed. This paper-based sensor ensures precise detection at room temperature, demonstrating high sensitivity and selectivity. The detection system was integrated with smart devices, enabling the swift capture of Red, Green, and Blue (RGB) values for practical real-time applications. This integration allows for rapid on-site identification of cerium ions. The introduction of this affordable, accurate, and portable colorimetric method for monitoring cerium ions represents a promising advancement in developing accessible tools within this field.

Synergistic effects of oral inoculation with a recombinant Lactobacillus plantarum NC8 strain co-expressing interleukin-2 and interleukin-17B on the efficacy of the infectious bronchitis vaccine in chickens

Mucosal vaccination strategies are easier to implement than others in large-scale poultry farming. However, the adjuvants that are approved for veterinary use, which are predominantly aluminum- and oil-emulsion-based adjuvants, are not suitable for mucosal vaccination and carry a risk of adverse reactions. In this study, we engineered a novel Lactobacillus plantarum NC8 strain that co-expresses chicken interleukin-2 (IL-2) and IL-17B, which we designated NC8-ChIL2-17B, and evaluated its potential as an oral immunoadjuvant. The immunomodulatory properties of NC8-ChIL2-17B were evidenced by its ability to activate macrophages and inhibit the proliferation of infectious bronchitis virus (IBV) in vitro. We then confirmed its immunoadjuvant activity in vivo by orally administering NC8-ChIL2-17B along with a commercial IBV vaccine to chicks. The results indicated that NC8-ChIL2-17B enhanced the immune response elicited by the IBV vaccine and increased the levels of IBV-specific IgG and sIgA antibodies produced in response to IBV infection. Additionally, administration of NC8-ChIL2-17B promoted weight gain and beneficially modulated the gut microbiota, resulting in improved chicken performance. These findings suggest that oral administration of NC8-ChIL2-17B is a promising strategy to enhance the immune efficacy of the IBV vaccine in chickens, offering an efficacious alternative adjuvant.

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.

Quantitative Assessment of Major Biosecurity Challenges of Poultry Production in Central Ethiopia

The present study aims to assess the level of implementation of biosecurity practices of small-, medium- and large-scale poultry farms in central Ethiopia. A cross-sectional study design was implemented involving 226 poultry farms (153 small-, 53 medium- and 20 large-scale farms) in three selected areas of central Ethiopia, including Addis Ababa, Bishoftu and West of Shaggar. The results revealed a very low overall biosecurity score of 43.1% for central Ethiopia compared to the global average score of 64.3%. No significant difference (p > 0.05) in the overall biosecurity practices among the three study sites (36.1% for Addis Ababa, 49% for Bishoftu and 34.9% for West of Shaggar) was observed. Six of the eight external biosecurity components with an overall score of 40.7% as compared to the global average of 64.6% were highly disrupted and scored lower values. With regard to internal biosecurity disease management, cleaning and disinfection practices were found to be 52.6% as opposed to the global average of 64%. The poor biosecurity level among poultry farms of central Ethiopia clearly demonstrates the urgent need for the implementation of appropriate biosecurity practices through the active involvement of all stakeholders to combat the impact of various diseases and boost the productivity of the sector.

Avian influenza vaccine supply chain in Quang Ninh province, Vietnam, 2021

Highly pathogenic avian influenza (HPAI) is a zoonotic disease that can affect both poultry and humans. Since 2005, the Vietnam government has implemented a national vaccination campaign to prevent the spread of avian influenza (AI). In 2021, the first outbreak of HPAI H5N8 was reported in a chicken farm in Quang Ninh province. To understand the stakeholders linked to the AI campaign, and their roles within the vaccine supply chain, we conducted a cross-sectional study from November 2021–January 2022. We purposively selected 114 participants, including 71 poultry farmers using HPAI vaccines, 16 veterinary drug store owners, 18 commune animal health workers (CAHWs), 8 staff from the Centers for Agricultural Services (ATSCs), and one vaccine distributor who were interviewed face-to-face using a structured questionnaire. Three HPAI vaccines (H5N1 clade 1 & 2.3.2.1, H5N1 clade 2.3.4 and H5N1 clade 2.3.2.1b) were used, and they were effective against the locally circulating virus strains. Distributors stored vaccines at the required temperature and transported them in appropriate vehicles. Vaccines remained in the supply chain for 3–5 months within their 12-month shelf-life period. The free government vaccination campaign, implemented by CAHWs, and administered by the ATSCs, reached 61% of small-scale poultry farms with a 1.21% vaccine wastage rate. Large-scale poultry farms followed the national campaign but paid a fee for the vaccines. We recommend expanding the support for AI vaccination to increase the vaccination rate among large-scale poultry farms, selecting higher efficacy seed vaccines, and that smaller dose vaccine vials are available for cost-effective vaccination.

COMMERCIAL LAYING HEN PRODUCTION AND EGG VALUE CHAIN MAPPING IN NORTHERN ETH

<p><strong>Background:</strong> In Ethiopia, commercial farms have increased in farm size, and the majority of the large-scale poultry farms are concentrated around Addis Ababa the capital city of Ethiopia. <strong>Objective:</strong> To assess poultry production, map value chains and identify major production challenges in Northern Ethiopia. <strong>Methodology:</strong> A multistage sampling technique along with a proportionate sample size determination method was used to fix the sample size. Accordingly, 147, 109 and 64 poultry producers were selected from semi-intensive, small-scale, and medium-scale farms, respectively. Nine focus group discussions comprising relevant stakeholders were conducted. <strong>Result:</strong> The earlier age at first egg-laying in weeks was reported as 16.7 ± 0.93 in the medium-scale production system. A high laying percentage of 85.47 <strong>± </strong>5.01 was recorded in the medium-scale and the highest mortality 23.5 <strong>± </strong>8.8 was in semi-intensive. The price of eggs varied by about +38% in November 2019/2020 and negatively changed price by -22% in May 2019/2020. In a ranking exercise, feed cost, feed quality, product marketing, disease, predator, and lack of information and training were ranked top five. Further risk factors were ranked, accordingly, lack of vaccine, poor biosecurity measures, and management were ranked as major causes. <strong>Implication: </strong>The government and private sector should promote improving the feeding habit of the community and improve the management practice. <strong>Conclusion:</strong> The high price of feed ingredients, limited access to veterinary services, poor market linkages in the value chain, poor feeding habits, and poor extension services aggravated by a lack of awareness of producers were the most important challenges affecting commercial production.</p>

Review on Prevalence and Antimicrobial Resistance of Poultry Salmonella in Ethiopia

Salmonellosis is one of the major causes of morbidity and mortality in village and large scale poultry farms. This paper was aimed to review on the prevalence and antimicrobial resistance of poultry Salmonella in Ethiopia. The risk factors associated with Salmonella in laying hens that the presence of previous Salmonella infection, multi-age management, cage housing systems, rearing pullets on the floor, induced molting and in-line egg processing were factors associated with Salmonella infection. Among them, many isolates were S. braenderup, S. typhimurium var. copenhagen, S. anatum and S. typhimurium isolates were dominant Salmonella serotypes. Antimicrobial resistance is a global problem in general, but it might be more severe in Ethiopia where there is lack of antimicrobial resistance assessments of Salmonella and lack of rigorous regulations. During the last decade, there has been an alarming increase in the appearance of antibiotic-resistant bacteria as a result of poor management in antibiotic utilization. Poultry Salmonella are excellent examples of diseases that have decreased in prevalence in some of the developed countries or have been eradicated by application of basic management procedures or eradication programs. Every effort should be made to eradicate Salmonella and treatment should be the last option.

STUDY OF THE INFLUENCE OF THE ARRANGEMENT OF EXHAUST FANS ALONG THE LOWER LINE ON THE AERODYNAMICS OF THE POULTRY HOUSE

Coverage and outbreaks of diseases lead to considerable losses in large-scale poultry farming. New ventilation systems are essential to ensure a safe and uniform indoor environment in large enterprises, especially in the changing climate of global warming. Thus, it is necessary to improve the design of the poultry house, to search for the most effective way of arranging the supply air valves and to improve the aerodynamic parameters of the internal environment of the poultry house in the most effective way of arranging the supply air valves and improving the aerodynamic parameters of the internal environment of the poultry house. Within the framework of this study, computational hydrodynamics modelling of the lateral ventilation system in the poultry house during the winter period of the year was performed. As a result, the temperature of the 3D field, the current lines, and the pressure in the aviary were detected. Supply air valves located 200 mm above the floor were found to perform better than those conventionally installed at 400 mm. Building walls on the inside of the poultry house frame, as well as reducing the height of the floor, improve the aerodynamics of the poultry house. The practical value of the presented study is targeted at poultry farmers with large productive capacities.

Using CNN for detection of diseases

Since economic booming, people start to care more about their health including dietary structure and nutrition. Scientist announced that fish and chicken are the best meat among others based on high nutrition level and low fat percentage. However, It is proved that many diseases especially H7N9 are related to poultry farming. Those diseases not only lethal to chicken but also has certain chance to evolve to human transmittable illness. Unfortunately, industrialized large scale poultry farming increased the morbidity of the diseases which is enough for people to take concern of. After all this, the application of genetic engineering technology to poultry industry focused on increase productivity, which sadly reduce poultry healthiness. These lead to periodic poultry pandemic blast. This is endless periodic nightmare for poultry farming. Theoretically, Using image recognizing from artificial intelligent to detect diseases at first sign is possible with current research level. This paper will compare and record the changes of appearances of five common diseases and try to design an AI model to detect it. The main results are as follow: (Use convenlutional neutral network to judge whether the chickens are sick by checking the cockscomb, skin, feather and waste. Keep training the computer to correct the weight to let the accurate rate above 98%. Extract the data of the images by digitizing, and continually recognize the diseases through the help of the vets to realize back propagation to improve the accurate rate.)

Pose estimation and behavior classification of broiler chickens based on deep neural networks

Poultry behavior is an important indicator for diagnosing poultry diseases. Accurate pose estimation is the basis of poultry behavior analysis, and it provides poultry disease warning methods. On large-scale poultry farms, it is usually a farmer or veterinarian who watches the pose of the broiler chicken to determine whether they are sick. When the posture of the bird is abnormal, the breeders can address the problem promptly. Accurate tracking of birds can better estimate their posture. In this paper, pose estimation based on a deep neural network (DNN) is applied to analyze the broiler chicken’s behavior for the first time. First, the pose skeleton is constructed through the feature points of the broiler chicken, and then, it is used to track specific body parts. Furthermore, the naive bayesian model (NBM) was used to classify and identify the poses of broiler chickens. Preliminary tests revealed that we could identify chickens in standing, walking, running, eating, resting, and preening states by comparing the postures of classified broiler chickens. The test precision of behavior recognition is 0.7511 (standing), 0.5135 (walking), 0.6270 (running), 0.9361 (eating), 0.9623 (resting), and 0.9258 (preening). Our research provides a noninvasive method for broiler chicken behavior analysis, which can be used for future behavior analysis in broiler chicken farming.

Comparative study on poultry target tracking algorithms based on a deep regression network

Poultry tracking is primarily used for evaluating abnormal behaviour and predicting disease in poultry. Offline video is often used to track and record poultry behaviour. However, poultry are group-housed animals. The difficulty of accurately monitoring large-scale poultry farms lies in the automatic tracking of individual poultry. To this end, this paper demonstrates the use of a deep regression network to track single poultry based on computer vision technology. By referring to the Alexnet network, the broiler chicken area of the previous frame and the search area of the next frame were input into the convolutional layer respectively, and the coordinates of the prediction area were obtained by full-connection layer regression. The method was compared with some existing tracking algorithms. Preliminary tests revealed that when compared with MeanShift Algorithm (MS), Multitask learning Algorithm (MIL), Kernel Correlation Filter (KCF), Adaptive Correlation Filters (ACF) and tracking-learn-detection (TLD), the poultry tracking algorithm named TBroiler tracker proposed in this paper has better performance on the overlap ratio, pixel error and the failure rate. TBroiler achieved a mixed tracking performance evaluation (MTPE) of 0.730. The evaluation scores of other methods were 0.362 (MS), 0.355 (MIL), 0.434 (KCF), 0.051 (ACF), and 0.248 (TLD). In addition, the method can be further optimised to improve the overall success rate of verification.

The occurrence of the multidrug resistance (MDR) and the prevalence of virulence genes and QACs resistance genes in E. coli isolated from environmental and avian sources

Colibacillosis is a major disease affecting poultry leads to high morbidity and mortality which causing tremendous economic losses worldwide. These economic disparities are amplified among low and middle-income where sanitation and hygiene are challenged by the increasing demand for quality sources of animal protein. With a view to investigating the prevalence of virulence genes and QACs resistance genes as well as monitoring the antibiogram of E. coli strains, a total of 368 specimens were collected from diseased broiler chickens (n = 226) and environmental sources (n = 142) at large-scale poultry farms in Ismailia Governorate, Egypt. The bacteriological examination proved that E. coli prevalence was 26.76% and 50.44% in the farm environment and diseased broilers, respectively. In tandem, the isolated E. coli strains were serogrouped, determining the most common serotypes were O78, O1:H7, O91:H21 and O126. Isolates were tested for antimicrobial susceptibility against 12 antibiotics, screened for 4 virulence genes (iss, papC, eaeA, and cfaI), and screened for 3 QACs resistance genes (qacEΔ1, qacA/B, and qacC/D). All the tested strains were positive for iss and papC genes, only 20.3% of the tested strains were positive for eaeA gene, moreover, the examined strains were negative to CFAI gene. Furthermore, all the tested strains were positive for qacEΔ1, qacA/B, and qacC/D genes. In conclusion; virulence genes (iss, papC) as well as QACs resistance genes are common in avian Pathogenic E. coli and environmental strains and are mainly associated with multi-drug resistance phenomena.

A Comparative Analysis of Risk Perception and Coping Behaviors among Chinese Poultry Farmers Regarding Human and Poultry Infection with Avian Influenza.

Poultry farmers face a dual risk when mutant avian influenza (AI) virus exhibits zoonotic characteristics. A/H5N1 and A/H7N9 are two principal strains of the AI virus that have captured public attention in recent years, as they have both been reported and can infect poultry and humans, respectively. Previous studies have focused either on poultry farmers’ risk perception and biosecurity preventive behaviors (BPBs) against A/H5N1 infection with poultry, or on their risk perception and personal protective behaviors (PPBs) against human infection with A/H7N9, even though these two strains often appear simultaneously. To bridge this research gap, a survey (N = 426) was conducted in the Chinese provinces of Jiangsu and Anhui to assess risk perception and coping behaviors adopted by poultry farmers facing the dual risk of these two viral strains. Paired sample t-tests revealed that farmers’ perceived risk of poultry infection with A/H5N1 was significantly higher than their perceived risk of human infection with A/H7N9, and that their reported frequency of BPBs against A/H5N1 was significantly higher than the frequency of PPBs against A/H7N9. Moreover, farmers were less familiar with AI infection in human beings compared to that in poultry, but they felt a higher sense of control regarding human AI infection. Multivariate regression analyses showed that farm size and perceived risks of both human and poultry infection with AI were positively associated with BPBs and PPBs. The findings of this research suggest that a campaign to spread knowledge about human AI infection among poultry farmers is needed, and that a policy incentive to encourage large-scale poultry farming could be effective in improving implementation of BPBs and PPBs.

Computational Fluid Dynamics aided investigation and optimization of a tunnel-ventilated poultry house in China

Ventilation system is crucial for poultry houses to control the indoor climate and air quality. The tunnel ventilation system is widely applied for large-scale poultry buildings in China but only limited scientific researches regarding the flow pattern, temperature distribution and design criteria are available in the literature. Thanks to the fast development of computer technology, Computational Fluid Dynamics (CFD) techniques were used in present study to investigate the indoor air movement, air temperature and relatively humidity. A three-dimensional CFD model was built according to the real dimensions of a laying hen house and the model was validated by comparing the simulation results with the field measurements at 30 positions. Meanwhile, statistical analysis was performed to determine the differences between different boundary conditions regarding the agreement between measured and CFD simulated results. Optimization of air inlet configurations was performed by using the validated CFD model and it was found that the uniformity of indoor air movement could prevent excessive local convective heat losses and reduce the temperature at the end of the house. Furthermore, the air inlets placed at the middle of the side wall could significantly reduce the high temperature expected at the end of the building without using extra energy, which is especially important for large-scale poultry farms with long buildings. The performance of side-wall windows was also examined and preliminary guidance was provided to effectively regulate the indoor climate by using these windows with the help of environmental monitoring systems. The present study contributes to the understanding and design of the tunnel ventilation system used in poultry houses.

Method for detecting avian influenza disease of chickens based on sound analysis

A new audio analysis-based detection method is put forward in this paper to detect avian influenza as early as possible. Because a distinctive difference exists in the short-time auto-correlation functions of recorded chicken sound and ambient noise, the former can be extracted from the record and the latter discarded. The mel-frequency cepstral coefficients (MFCC) are determined by analysing and processing the frequency domain of the extracted chicken sound signal. The coefficients serve as distinction criteria for healthy and infected chickens. The extracted chicken sound is trained and identified with a binary-classification support vector machine (SVM). The penalty parameter and kernel function parameter of the optimal SVM are determined through 4-fold cross validation. The maximum recognition rates for the verification set are 87.25% (for polynomial kernel function), 88.1250% (for radial basis function), and 87.1250% (for S-kernel function), respectively. According to the experimental results for the testing set, the accuracy rate of the avian-influenza detection method ranged between 84% and 90%. This work shows preliminary potential for fast and efficient detection of avian-influenza in large-scale poultry farming and poultry trading markets.

A case of human infection with highly pathogenic avian influenza A (H7N9) virus through poultry processing without protection measure

Objective: To investigate the infection pattern and etiological characteristics of a case of human infection with highly pathogenic avian influenza A (H7N9) virus and provide evidence for the prevention and control of human infection with highly pathogenic avian influenza virus. Methods: Epidemiological investigation was conducted to explore the case's exposure history, infection route and disease progression. Samples collected from the patient, environments and poultry were tested by using real time reverse transcriptase-polymerase chain reaction (RT-PCR). Virus isolation, genome sequencing and phylogenetic analysis were conducted for positive samples. Results: The case had no live poultry contact history, but had a history of pulled chicken processing without taking protection measure in an unventilated kitchen before the onset. Samples collected from the patient's lower respiratory tract, the remaining frozen chicken meat and the live poultry market were all influenza A (H7N9) virus positive. The isolated viruses from these positive samples were highly homogenous. An insertion which lead to the addition of multiple basic amino acid residues (PEVPKRKRTAR/GL) was found at the HA cleavage site, suggesting that this virus might be highly pathogenic. Conclusions: Live poultry processing without protection measure is an important infection mode of "poultry to human" transmission of avian influenza viruses. Due to the limitation of protection measures in live poultry markets in Guangzhou, it is necessary to promote the standardized large scale poultry farming, the complete restriction of live poultry sales and centralized poultry slaughtering as well as ice fresh sale.

Valorisation of Waste Chicken Feathers: Green Oil Sorbent

The threat of oil pollution increases with the development of large-scale off-shore petroleum industrial activities. Recently, reducing waste materials through reuse has contributed to sustainable manufacturing in many industries. With development of large-scale poultry farming industries, the disposal of large amounts of waste chicken feathers has become a huge problem. Thus, sustainable methods for valorisation of this waste are needed. This paper examines beneficiation of waste chicken feathers via conversion into sorbents for clean-up of oil spills in water bodies to replace conventionally used synthetic adsorbents that are costly. Chicken feathers have a very high capacity for adsorption of liquid oils (up to 16.21 g of oil/g of chicken feather) at fast uptake time (10 min). The removal efficiency of oils in spills increases with increment in contact time with the sorbent. Untreated waste chicken feathers exhibited slow sorption rate for oil due to the presence of grease and other impurities on the surface of feathers. More than 85% of the oil adsorbed by chicken feathers can be recovered. Thus, waste chicken feathers show very attractive and promising adsorption/absorption properties for oil spill clean-up applications to replace polymer-based adsorbents due to their high oil absorption capacities. Both untreated and treated chicken feathers show promising potential for use as oil absorbents.

Valorisation of chicken feathers: Application in paper production

Reducing waste materials through reuse has in the recent past contributed to sustainable manufacturing in many industries. With the development of large-scale poultry farming, the treatment of large amounts of chicken feathers has become a problem and threatened its use as a renewable resource. This paper examines the use of chicken feathers in the paper making process; a process which would traditionally use wood as the raw material. The effects of combining feather fibre and wood pulp on paper performance were studied and compared to the properties of handsheets made with 100% wood pulp. With the increase of feather content, properties such as tightness, tensile index and bursting index decreased, whilst air permeability improved. There was no significant difference in water absorbency between various chicken feather/wood pulp handsheet samples however, the water absorbency started to decrease above 80% of chicken feather content. This could potentially open up a new avenue for the use of chicken feathers in applications that are meant to tolerate high humidity conditions, e.g., packaging products.

Determinants of Knowledge and Biosecurity Preventive Behaviors for Highly Pathogenic Avian Influenza Risk Among Chinese Poultry Farmers.

Biosecurity measures are the first line of defense against highly pathogenic avian influenza (HPAI) on farms. It is generally recognized that an individual's behavior can be influenced by the knowledge they possess. However, empirical study has not reported an association between poultry producers' awareness of HPAI symptoms and their actual biosecurity actions. The aim of this study is to classify knowledge items of HPAI by exploratory factor analysis (EFA) and to examine the determinants of different types of knowledge and the effect of different types of knowledge on biosecurity preventive behaviors (BPBs). The survey (n = 297) was conducted using a questionnaire to measure the level of awareness of items related to HPAI and the actual adoption of BPBs among poultry farmers in the Chinese province of Jiangsu. The EFA revealed three main types of knowledge, which were categorized as avian influenza (AI) epidemic characteristics, primary biosecurity preventive knowledge (basic biosecurity preventive knowledge against AI), and essential biosecurity preventive knowledge (crucial biosecurity preventive knowledge against infection of AI). Multivariate regression showed that only poultry farmers' awareness of essential biosecurity preventive knowledge was positively associated with their actual BPBs. Additionally, educational attainment, number of years of experience raising poultry, farming operation size, and training were associated both with BPB and most of the knowledge factors or knowledge items. Training of existing poultry farmers is probably a feasible scheme; furthermore, the training should focus on the essential biosecurity preventive knowledge. On the other hand, policy initiatives to encourage large-scale poultry farming while discouraging small-scale backyard poultry husbandry would be an effective method of improving the management standards of rural poultry farming.

Based on Embedded Distributed Control System of the Poultry House Environment

Poultry breeding environment factors such as temperature and air humidity directly affect poultry production performance for large-scale poultry farms in the demand for environmental monitoring, research and application of CAN bus technology to build a distributed multi-variable environmental monitoring system, which an embedded core from the monitoring center and the PIC microcontroller as the core component of intelligent monitoring terminal, control center real-time monitoring of collection, analysis and processing of environmental information collected from the terminal, the control requirements based on user input, combined with the results of data processing, to the terminal sends control parameters, and breeding farms to monitor more than one poultry house.