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Heat stress has posed a significant threat to the laying hens inside the poultry houses in the Northwest region of China. Significant non-uniformities can be found in the thermal distribution and temperature variations in summer. The ventilation system has been the primary measure to regulate the thermal environment in the poultry houses. Excellent airflow arrangement and ventilation strategies are essential for the ventilation efficiency. Still, the continuous operation of fans can inevitably generate the excessive local cold air, thereby wasting the electrical energy for the high cost of environmental control. Alternatively, intermittent ventilation can serve as an efficient way to improve ventilation effectiveness with energy saving. However, it is notably limited to applying to the summer poultry houses so far. In this study, a novel intermittent ventilation was introduced to alleviate the significant temperature fluctuations and ensure the high stability of the thermal environment in the summer poultry houses. According to the internal air temperature, the fan operations were performed on the conventional tunnel-ventilated poultry houses (control house, CH) and sidewall inlets poultry houses (experimental house, EH). Specifically, the fans were regulated, when the temperature exceeded the upper limit. Once the temperature dropped below the lower limit temperature, the fans were deactivated simultaneously, which was different from the continuous operations of fans throughout the summer. The thermal environment was monitored in the operation periods of intermittent ventilation. The environmental conditions inside the poultry houses were also evaluated. The results revealed that the average internal temperatures of experimental and control poultry houses were 25.3 and 26.5 °C, respectively, under the same external environmental temperatures; While the average relative humidity were 65.8% and 62.7%, respectively. The temperature fluctuations during the EH and CH's intermittent and continuous ventilation were 0.6 and 0.7 °C, 1.2 and 1.0 °C, respectively. The maximal difference of temperature in the horizontal direction of EH and CH were 0.3 and 5.2, 0.8 and 4.7 °C, respectively. Temperature variations were assessed in the four-hour intervals. The EH consistently demonstrated more minor temperature fluctuations than the CH when the fans were operated intermittently. The horizontal temperature difference was less than that in the continuous operation in EH. There was no difference in pressure and air velocity under the intermittent and continuous ventilation in the same number of fans. The pressure difference between the interior and the evaporative cooling pad buffer room increased from 17 to 19 Pa from the fan opposite wall to the fan. Average air velocity at the sidewall inlets and along the aisles in the EH were 3.30 and 0.49 m/s, respectively, which were higher by 1.86 and 0.12 m/s, compared with the CH. Therefore, the intermittent ventilation was suitable for the sidewall inlets, to improve the thermal environment within the poultry house significantly. There was great potential for widespread adoption in the Northwest region of China in the summer. The lifespan of the fan was extended for the maximal economic benefits. The intermittent operation times of fans should be determined according to the local climate, poultry houses’ ventilation requirements and the poultry houses’ size. This finding can provide a foundational reference for designing and adjusting the intermittent ventilation in summer poultry houses in the Northwest region of China. [ABSTRACT FROM AUTHOR]

A fuzzy adaptive control system was presented for greenhouse temperature, according to heat balance and fuzzy control. The accuracy of temperature control was improved to reduce the energy consumption of the control system in the winter greenhouse. An adaptive adjustment module was introduced for the output membership functions using the heat balance equation in the system. The membership functions of output variables were real-time adjusted with the outdoor temperature in the upper computer. The target temperature was ultimately reached to be stable in the greenhouse. At the same time, the experiment was conducted to verify the fuzzy adaptive control. The final experimental results were as follows: (1) The temperature was set to be 30, 35, 40, and 45 ℃ for the water tank of the heating fan. The temperature inside the greenhouse was then monitored for a period of time. The monitoring data was substituted into the energy balance equation to calculate the comprehensive heat transfer coefficient of the heating fan. 19 datasets showed that the comprehensive heat transfer coefficient of the heating fan was 50.50 W/(m2·℃). (2) A fuzzy adaptive control system was developed for greenhouse temperature using Python. A comparison was made on the control effects of fuzzy control, adaptive fuzzy, and threshold control. The more sensitive output response of the fuzzy adaptive control was observed at the target temperature of 20 ℃, according to the heat balance equation. The higher temperature was found in the water tank of heating fan at the beginning of the control. The overall control time was shorter at 35 min. Finally, the temperature of the temperature chamber was stabilized at (19.8 ± 0.11) ℃. There was a longer control of 39 min for the general fuzzy controller. Finally, the greenhouse temperature was stabilized at (13.5 ± 0.5) ℃, which was unable to reach the target ambient temperature. The threshold control had the shortest control time of 26 min. But there were more fluctuations to reach the target temperature until the greenhouse temperature was stabilized at (20.0 ± 0.85) ℃. (3) The ratio of heat input was calculated from the heating fan to the total energy consumption of the greenhouse using different control systems. The energy utilization rate of fuzzy adaptive control was 45.97% when the total energy consumption was 1.584 × 107 J. While the energy utilization rate of threshold control was only 20.21% when the total energy consumption was 3.301 × 107 J. Therefore, low energy consumption, high stability, and accuracy were achieved in the fuzzy adaptive control system with the heat balance equation, fully meeting the needs of temperature control in a winter greenhouse. [ABSTRACT FROM AUTHOR]

Facility agriculture is one of the most important indicators to achieve efficient and high-quality crop production in modern agriculture. Optimal environmental parameters can also be adjusted to improve crop growth, yield, and quality in the greenhouse. Therefore, environmental control and regulation technologies have been widely used to achieve efficient vegetable production. This review aims to summarize the recent research status in the field of environmental regulation in greenhouses. New approaches were also proposed for future research priorities. Greenhouse environment system was gradually shifted from the manual and timed to the threshold, feedback, and intelligent control systems, with the rapid development of artificial intelligence (AI) technology. Firstly, the main properties of different control systems were evaluated from an application perspective. Among them, the threshold control was simple and widely used, but it failed to adjust the control strategy in time following the dynamic changes of the external environment, in order to meet the needs of crops for light, water, and nutrients. The feedback control shared the stable environment through feedback regulation but was unsuitable for the complex multivariable conditions. Intelligent control was widely used to balance the interaction between different environmental factors in modern greenhouses. Afterward, the intelligent control methods were investigated for greenhouse environments, including fuzzy, decoupling, neural network, and environmental control, according to the crop phenotype parameters. Specifically, the mathematical model was independent of the controlled object in the fuzzy control, and easy to handle with nonlinear issues. However, the outline fuzzy was difficult to handle the sudden disturbances in the regulation system. In decoupling control, the appropriate control strategies were designed to transform the multiple parameters with coupling effects into a single variable. The regulation model was also constructed to integrate the multiple environmental factors and crop physiological needs. The intelligent control of the environment was realized in the development of greenhouse agriculture. The Neural networks were used to extract valuable information from a large amount of greenhouse environment data, thus providing powerful tools for the regulation models. The intelligent models mainly included single-factor, multi-factor, and multi-objective environment regulation. The data-driven method was one of the research hotspots in the intelligent regulation of greenhouse environments. However，the universality and economic benefits were the key limiting factors of regulation models. Efficient and accurate acquisition of phenotypic parameters greatly contributed to the fine management of greenhouse environments, indicating the intuitive, real-time monitoring, and dynamic regulation. However, it was still lacking in the interaction between phenotype and multiple environmental factors, which failed to apply directly in greenhouse production. In addition, the existing environmental control systems were evaluated for the light, temperature, air, ventilation, and irrigation greenhouse. Research directions were proposed to urgently improve and optimize the control system. Finally, future research and development trends were also recommended to construct the greenhouse environmental regulation, considering disturbance factors. Environmental regulation models were developed using crop growth and phenotype evaluation. A "cloud-edge-end" system of greenhouse environmental regulation was established to integrate multiple models. This finding can provide new ideas and references for the subsequent development of environmental control systems in greenhouses. [ABSTRACT FROM AUTHOR]

A single-color steel open shed has been widely used for the main structure of the building in the production of fattening lambs. However, the roof cannot resist the external solar radiation in summer, leading to the increase of temperature in the shed and the occurrence of heat stress of lambs. The objective of this study was to investigate the heat insulation performance of a single-color steel roof that was covered with the reflective film, with emphasis on the physiological and growth performance of fattening lambs. Two sheds with similar building structures were selected, where one was reformed by pasting a reflective film on a single-color steel roof (film shed), and another without reform as a control (control shed). An infrared thermal imager was used to investigate the inner surface temperature of the roof, where the radiant heat of inner surface of the roof was calculated in each stage. Temperature and humidity in both sheds were continuously and dynamically measured, together with the growth performance and physiological indexes of fattening lambs. The trial lasted 67 days from June to August, including the three experimental stages (days 1-7 in the early-stage, days 8-37 in the mid-stage, and days 38-67 in the late-stage). The results showed that: 1) The inner surface temperature of the control shed reached the highest value at 11:30, while the film covered shed reached the peak value at 14:00, indicating a delay by 2.5 hours. The radiant heat of inner surface of the roof also showed the same pattern during the whole period. The inner surface temperature of the film shed was 1.87-14.20 ℃ lower than that of the control (average 7.31 ℃), indicating the most significant decrease (P<0.05) from 9:00-16:30 every day. In addition, the radiant heat of inner surface of the roof in the film shed was 8.85% lower than that of the control, indicating the largest 18.65% decrease in the late-stage at 11:30. 2) In three stages, the ambient temperature in the film shed decreased by 0.55 ℃ on average, compared with the control, especially in the early stage from 9:00 to 13:00, reaching 1.55-1.95 ℃ (average 1.78 ℃) (P<0.05). There was no significant temperature difference between the two sheds in the rest stages (P>0.05). Also, there was a significant linear positive correlation between the ambient temperature and the inner surface temperature of the roof, as well as the radiant heat of inner surface of the roof (P < 0.01). 3) The average daily gain of lambs in the film shed increased by 10.97 % (P < 0.05). There was a significant difference in the amount of water consumption between the fattening lambs in midand late-stage of the test (P < 0.05), which was 15.58 % and 12.66 % higher than that in the control. The respiratory rate of sheep in the film shed decreased by 5.31%, 7.85 times/min lower than the control (P < 0.05) in the middle stage. In summary, the single-color steel roof pasted by the reflective film can be expected to effectively improve the thermal insulation performance of the roof, and then to improve physiological and growth performance in the fattening lambs to relieve heat stress. [ABSTRACT FROM AUTHOR]

To grasp timely and conveniently environmental information such as temperature and humidity in the greenhouse, a mobile greenhouse environment monitoring system was designed, which realized the mobile monitoring of greenhouse environmental parameters. According to the improved double-side-two-way-ranging algorithm, the distance between each base station and the tag was calculated. The NLOS error was judged by the normalized residual distribution of distance, and the improved incremental Kalman filter algorithm was used to eliminate the NLOS error, and the Chan algorithm was used to calculate the accurate tag position. The mobile greenhouse environment monitoring system was composed of a remote monitoring platform, mobile workstation, and UWB positioning module. The remote monitoring platform was responsible for displaying the location information of the mobile workstation in real-time, controlling the movement of the mobile workstation remotely, displaying and storing the environmental information uploaded by the environmental information monitoring module. Mobile workstation mainly included mobile chassis, drive module, control module, environmental information measurement module, UWB positioning label, and communication module. As the specific executor of the command, the mobile workstation was responsible for receiving and executing the mobile command issued by the monitoring platform, collecting and sending the measured temperature and humidity and other environmental parameters to the monitoring platform in real-time. The remote monitoring platform and the mobile workstation communicate timely through the wireless network. The UWB positioning module included a positioning tag, positioning base station, and a computing unit. The positioning tag was installed on the mobile workstation to mark the position of the mobile workstation in the greenhouse. The positioning base station was responsible for calculating the distance between each base station and the tag and sending it to the computing unit by serial communication. The computing unit calculated the position of the tag in the greenhouse and displays it. The software of the environmental monitoring system consisted of a position information interaction layer, environment information monitoring layer, and motion control layer. The position information interaction layer was a real-time positioning program based on windows, which displayed the position of a mobile workstation in the greenhouse. The environmental information monitoring layer was an Android-based program to collect and display environmental information measured by sensors, drawing the hourly temperature and humidity change curve. The motion control layer was an Android-based remote control program, which sent motion instructions to the mobile workstation through the remote communication protocol to control the stable and safe movement of the mobile workstation in the greenhouse. The remote control and positioning accuracy-test showed that the maximum lateral deviation of the system static positioning was 7.92 cm, the maximum longitudinal deviation was 7.98 cm, and the average value of both horizontal and longitudinal deviation was less than 5 cm. When the mobile workstation was running at a speed of 0.4 m/s, the maximum lateral deviation of dynamic positioning was 8.7 cm and the average lateral deviation was 4.7 cm. Through the stability test of environmental information collection, the average data loss rate of the collected greenhouse environmental parameters uploaded to the remote monitoring platform was 2.78%, the environmental information collection was stable. The relative errors of temperature, humidity, light intensity and carbon dioxide concentration were less than 0.63%, 0.34%, 0.70%, and 0.67%, respectively, the environmental monitoring accuracy was high. The system adopted modular hardware structure design and layered software structure design, taking into account the requirements of the system for data through flux and response speed. Combined with the remote monitoring platform, it realized remote control, precise positioning, and remote real-time monitoring of the greenhouse environment. The system could have certain reference significance for the development of remote environmental monitoring technology and greenhouse precise positioning technology. [ABSTRACT FROM AUTHOR]

Active Heat Storage and release System (AHS) is a solar thermal utilization system, which collects and stores solar energy through the water circulation in the daytime, and the energy is released at night. To improve the stability and reliability of the operation of AHS, based on the sixth generation of AHS, the circulation pipeline, water supply mode, solar energy collection board were optimized and improved. The field test lasted 87 days was done to investigate the heating effect, heating performance, control strategy of circulation, and the distribution of indoor air temperature during the heating process of improved AHS under different weather conditions. The test period was from November 24th, 2019 to February 29th, 2020. The results showed that, during the experiment time, the improved AHS was in stable operation mode, the energy-saving, and high heating efficiency, the optimization was effective. In three different weather conditions of solar radiation intensity, the average temperature in the experimental area was 2.7, 2.2, and 1.9 ℃ higher than that in the control area, and the heat collection capacity was 4.6, 3.7, and 2.6 MJ/m² respectively, heat release capacity was 4.1, 3.4, and 3.1 MJ/m² respectively. The average heat collection power was 183.1, 146.5, and 105.0 W/m² respectively, and average heat release power was 163.2, 134, and 121.1 W/m² respectively. The average heat collection efficiency of improved AHS was 56.5%, 68.2%, and 73.8% respectively and the average coefficient of performance was 3.8, 3.1, and 2.8 respectively. Compared to electric heating, the energy conservation rate of improved AHS was 73.5%, 67.1%, and 63% respectively. Compared with the sixth generation AHS, when total heat energy collected was similar, the daily average power consumption was reduced by 20%, the energy-saving efficiency was increased by 6.7%, and the coefficient of performance was increased by 0.8. The water flow rate was reduced, so the average heat collection efficiency was reduced by 10.3%. If the structure of AHS is improved in the future, the diameter of the aluminum alloy finned pipe is advised to increase to improve the heat collection efficiency. During the heating period at night, the influence of improved AHS on temperature distribution in the experimental area was very obvious, because the board was located in the north wall, and the north side of the greenhouse was closed to the lower temperature roof, the temperature difference between the north and the south in the greenhouse was large. The closer to the north wall at the same height, the temperature is higher. Under different weather conditions, the maximum average temperature difference between north and south parts in the canopy was 2.8, 2.6, and 2.4 ℃ respectively. This temperature difference was getting smaller with height because of the influence of crops on heat shielding and greenhouse shape. Through the analysis of water temperature change during the daytime, it was suggested to adopt the joint control method of temperature and time for control strategy optimization. The application and promotion of AHS could be supported by the basis of theory and experimental results in this study. [ABSTRACT FROM AUTHOR]

Natural ventilation is energy-saving and preferred in livestock buildings under suitable conditions, especially for cattle and sheep. The natural ventilated livestock buildings usually have large-openings which result in the non-uniform distribution of wind speed and pressure at the openings, which makes it difficult to determine the air inlet and outlet and challenging to estimate airflow rate in a natural ventilated livestock buildings. Thermal buoyancy and wind pressure are the driving forces of natural ventilation whose airflow rate can be estimated directly by differential pressure method, wind speed method and CFD method, or indirectly by heat balance, moisture balance, CO² balance and tracer gas method. This review paper investigates the published works on the theory of natural ventilation in livestock buildings and the methods of airflow rate estimation to obtain a better understanding on the state of art for the mechanisms and estimation methods of airflow rate of natural ventilation in livestock buildings. Furthermore, this paper summarizes the key factors affecting natural ventilation and the principles of improving accuracy in the application of estimation methods to guide ventilation measurements better, promote natural ventilation or mixed ventilation in livestock barns, and provide a basis for optimizing environmental control strategies for the environment as a whole. Finally, different estimation methods of airflow rate are compared and the research gaps need to be further improved are concluded in this paper. Up to now, it is short of an accurate and disputable method to measure airflow rate in natural ventilation. The differences among different estimation methods are generally between 10% and 300%, showing a very big variance. The estimation accuracy of different methods is affected by the factors such as the discharge coefficient, the pressure coefficient, the reliability of estimated heat and moisture production from animal, and the measuring position of sensors. Compared with other methods, the CO² balance method is widely used in the field measurements, and the result is relatively stable. However, it is highly needed to standardize the layout of sensors and the usage of the measured gas concentrations from different sensors to appropriately calculate concentration difference between indoor and outdoor, improving the accuracy of assessing CO² production from livestock buildings. The moisture balance method has a potential application in field measurements and practical situations because of its low cost of sensors and relatively good performance in estimation airflow rate. Nevertheless, it is necessary to further establish the estimation models on moisture production from house level and dynamic latent heat production from animals to improve the accuracy of moisture balance method. In addition, it is helpful to assess the reliability of the measured airflow rates and decrease the uncertainty in airflow rate estimation using multiple methods at the same time. Furthermore, the existing methods are more suitable for design assistance rather than regulating the airflow rate in real situation. It is necessary to improve the existing method or establish a new method to guide the regulation of natural ventilation directly and effectively in livestock buildings. [ABSTRACT FROM AUTHOR]

Housing environment has become a driving factor on hen health, egg quality and efficient production in intensive poultry industry. In large layer poultry housing system, an environmental index is typically used to control air conditions, including air temperature (T), relative humidity (RH) and concentration of carbon dioxide (CO2) in different season. In hot seasons, thermal environment of laying hen housing is usually assessed using the temperature humidity index (THI) via the online monitored temperature and relative humidity. However, the simple assessment cannot meet the harsh requirement of indoor air quality in a large layer house, as the stocking density increases in recent years. In this paper, a comprehensive environmental index (CEI) was proposed based on the radar map to integrate the impacts of both thermal and air quality factors, in order to systematically assess the environment comfort of the birds. A LabVIEW software system was selected to illustrate the environmental comfort using the fuzzy mathematics. Five key environmental factors, including temperature, RH, air velocity, concentration of CO2 and ammonia (NH3), were used to evaluate the environmental comfort of laying hen housing, where the their weights were normalized in a radar map. In the visualized system, early warning can be delivered when either a single factor or the CEI was over the prescribed value, and thereby a quick action can be taken to adjust the environmental conditions in the layer housing to a comfort level. A field measurement was carried out at a commercial layer breeder farm in Hebei province from January to February, and from July to August, 2019. The experimental results indicated that a good performance of the CEI can be obtained to assess the comprehensive environment in the tested house via monitoring the five environmental indexes. The specific sensors were properly settled in the henhouse. The data of environmental conditions was collected to verify, and then the maximum of five indexes were selected for later use. During the summer daytime, the CEI agreed well with the THI, indicating the positive impacts of thermal environment on the comfort of the birds, while it performed better to integrate the thermal and air quality at night time. In winter, the increase in the weight of CO2 concentration can contribute to the CEI for the comfort in layer housing system. The in situ monitoring data in the actual use demonstrated that the CEI can efficiently represent the change of comprehensive environmental comfort in the chicken house, and respond to the interaction between environmental factors in each period, especially when the air quality has an increasing influence on the comprehensive environmental comfort at night in summer and in winter. The findings can provide a promising method to systematically evaluate the housing environment via the five key factors in laying hen housing, further to improve the birds comfort via precisely controlling the air conditions in intensive poultry production. [ABSTRACT FROM AUTHOR]

In recent years, China's pig industry has gradually shifted to the northeast. Compared with the rich feed resources and land resources in Northeast China, the cold environment reduces the feed conversion efficiency and the production performance of pigs. In the winter of northern China, pig producers often face a huge problem of heat preservation when they control the environment of piggery. The aim of this study is to explore the heat preservation of piggeries in Northeast China. According to the investigation, there were four types of piggeries in Jilin Province, which were brick wall piggery, concrete wall piggery, color steel wall piggery and greenhouse piggery. The simulated piggeries with brick wall, concrete wall and color steel wall were based on the experimental piggery of Jilin Agricultural University, the simulated piggery with greenhouse was based on a piggery in a pig farm, and the simulated pig farm area was based on a pig farm area. Based on Ecotect software, this paper took a typical piggery in a large pig farm in Jilin Province as an object, and studied the light and heat environment of piggery, and the light environment of pig farm production area. The daylight factor of different heights in the piggery and the lighting situation in the production area of the pig farm were studied. The thermal insulation performances of 4 kinds of piggeries with different walls were analyzed. The results were as follows: The daylight factor of each research height of the experimental piggery was higher than 2%, which met the green building standard. The production area of the pig farm had good daylight, and the solar radiation in Great Cold Day could reach 5.38 MJ/(m²·d), and the sunshine was sufficient. The building spacing of the pig farm met the epidemic prevention standard, and there was no shelter problem. By comparing the monthly energy consumption values of 4 kinds of piggeries with different building materials, the best insulation performance of piggeries was as follow: Clay porous brick piggery, foam concrete pig piggery, color steel piggery with phenolic sandwich board, low density polyethylene film greenhouse piggery. After considering the cost, it was recommended to use cinder brick masonry piggery, fly ash aerated block piggery, polyphenylene sandwich board color steel piggery and low density polyethylene film greenhouse piggery. The daily energy consumption of empty piggery in December was tested and verified. The relative error range was 0.74%-8.62% after data comparison, which verified the reliability of the model. The simulation values of energy consumption were in good agreement with the measured values. On the one hand, it verified the correctness and rationality of setting parameters in the software. On the other hand, it showed that Ecotect software was feasible in piggery building. This paper can provide theoretical basis for exploring the light and heat environment of the northern piggery, and provide more ideas for architects to optimize the design before the implementation of the plan. [ABSTRACT FROM AUTHOR]

Heat stress seriously affects the productivity, fertility and welfare of dairy cows. It is to be expected that, in the course of the next few decades, climate conditions for raising cattle will deteriorate. In order to reduce the risks of heat stress in dairy cows, researchers have been trying to seek a reliable method to predict or evaluate heat stress, and it has been become to a hot topic in this research field to obtain an index model by combining multiple environmental factors. To avoid blindness in selecting these environmental factors, this paper systematically analyzed the temperature-humidity index, and its modified indices based on THI combined with other factors, and compared the differences among these indices in characterizing the heat stress of dairy cows. These differences relate to the thresholds of indices, environmental factors involved and heat exchanging properties, and the relationships between physiological responses of dairy cows and indices. In this paper, the problems of heat stress index of dairy cows are also discussed. The most widely used temperature-humidity index is based on thermal sensation and thermal comfort of human, but had not been actually related to cow’s living environments. Most indices linking environmental parameters to the physiological or behavioral responses of cows were established through the statistical correlation analysis process, but it did not reflect the real physical significance of the effects of environmental parameters on the process of heat exchange between animals and its environmental factors. In addition, the indices could only be well applied to the situation where they were established properly with the sufficient information for their use. We believed that THI had played an important role in the past when environmental parameters, physiology indicators and behavior responses were hard to be obtained, but the problem of THI had been existing in its application, so other direct parameters such as heat tolerance of high-yielding cows, the change of building structure and the linkage of various cooling modes should be considered when a new THI is being designed. Otherwise, the current THI will be not to meet the future production requirements of the dairy farming industry. With the application of digital technology, multi-parameter acquisition technology has been fundamentally changed, so it is necessary to develop a more reliable index of evaluating heat stress for cows to meet the needs of increasing livestock productivity and achieving welfare. Our suggestions to achieve this goal are as follows: 1) The index should be developed to incorporate more environmental parameters reflecting heat transfer mechanism. 2) The index can be applied not only in some specific climatic conditions, but also in other climatic conditions. 3) The index is to have applicable conditions and thresholds, and the thresholds of the index should be able to be dynamically adjusted to extend the scope of its application. 4) The index should be linked to animal physiological parameters and environmental factors, and consideration could be given to constructing a new index by meeting the theory of animal thermal balance. [ABSTRACT FROM AUTHOR]

Microclimate of swine house is a time-varying and nonlinear system affected by the interaction of internal production and external environment factors, and has an important effect on the pig’s growth performance and health status. Among multiple environmental factors, indoor air temperature affects the heat balance of the pig body and plays an important role to maintain the constant body temperature. Humidity influences the evaporation of the pig body and therefore a body’s thermoregulation. So, the indoor temperature and humidity are payed much attention by many researchers in the past decades in order to maintain a suitable indoor environment for pigs. Simulation of indoor microclimate is an effective way to provide a precision control strategy. Some researches on swine house environment control are conducted based on indoor air temperature and ventilation using traditional and automatic control method. However, in practice, it is difficult to realize an accurate microclimate control and prediction in a swine house due to some influences such as different regions that swine house located, seasons, raised number of pigs, and most simulations and models for swine house environment only focused on single environment factor such as temperature, humidity or airflow using computational fluid dynamics (CFD), the comprehensive interaction among the multiple factors and the energy consumptions are neglected. In this study, a thermal exchange model based on energy balance equations and a humidity variation model based on mass balance equations are developed for a closed swine house, the factors such as weather, heat dissipation, heat acquisition, building structure, building ventilation and pigs in the swine house are considered. Based on the one month's measured data of 1 minute resolution of room 2 on the south side and room 11 on the northwest corner in the swine house, some parameters of the simulation model were determined by using multivariate non-linear regression model (MNRM). Two days measured data are randomly selected to validate the model simulations from two rooms in hot summer. The energy consumptions of the two rooms are also analyzed and compared. Results show that the simulation and measurement values for both rooms agree well, the maximum temperatures error is 2.4 °C, the maximum relative error is 9.2% for the two rooms, and the coefficient of determination is 0.836 9 for room 2 and 0.786 9 for room 11. The maximum relative humidity error is 13.34% and the maximum relative error is 49.66% for the two rooms, the coefficient of determination is 0.912 for room 2 and 0.899 7 for room 11. The power consumption of room 11 is 1.5 times that of room 2 because room 11 has extra heat produced by the pigs and a sidewall as part of the west wall of the building. The dynamic microclimate models based on the energy and mass balance equations can be used for simulations of basic environment control and energy requirement in closed swine houses. [ABSTRACT FROM AUTHOR]

At present, with the continuous development of Chinese agricultural industrialization and rural urbanization, the traditional household biogas has been gradually replaced by more efficient medium and large-scale biogas system. Medium and large-scale biogas system can provide biogas as stable and clean cooking energy for rural residents depending on centralized utilization of agricultural organic wastes. It has a good impact on the indoor and outdoor environment in rural areas, and is in line with the requirements of the transformation of China’s rural energy structure. Further, it is a new trend for the development of rural energy in China. In this paper, the cost-benefit analysis method is used to quantify the economic and environmental benefits of these medium and large-scale biogas systems investigated by the author. Then, according to the internal rate of return (IRR) of each original system, these original systems is divided into three levels: the first level system-the better economic benefit (the IRR is greater than the discount rate 0.08), the second level system-the general economic benefit (the IRR is less than the discount rate 0.08, but more than 0), the tertiary level system-poor economic benefits (the IRR is less than 0). After considering the scale, benefits, conditions and the necessity of optimization of different levels of systems, the optimization measures are formulated to meet the needs of reality in different levels. The results show that: 1) The environmental benefit of the original system before optimization is generally good. Among them, carbon emission reduction is the most significant. In order of project scale from large to small (Baishuzhuang community, Nanan community, Tianma community, Shangzhai village, Shiyang village, Lianwang village, Yuepu village, Yezhao village, Xiaoguoyuan village), carbon emission reduction can reach 269 427.94, 230 788.18, 237 299.61, 231 344.26, 103 604.36, 81 050.29, 79 047.68, 90 434.88, 36 584.20 kg per year, respectively. 2) There are great differences in economic benefits before optimization, and the internal rates of return are as follows:-7%, -3%, -3%, 7%, 6%, 5%, 7%, 14%, 12%, which shows that the larger the scale is, the more uneconomical it is. 3) With the discount rate of 0.08 and the 0 as the stratified points, the original system is divided into three levels to optimize according to the internal rates of return of each system. 4) In the first-level system, the economic benefits of the two projects (Yezhao village and Xiaoguoyuan village) are already good. After optimization, the economic benefits decreased by 1.50% and 1.51%, respectively, but the carbon emission reduction increased by 112.88% and 134.43%, respectively. The overall optimization results are remarkable. 5) In the four projects (Shangzhai village, Shiyang village, Lianwang village, Yuepu village) of the second-level system, because the internal rate of return is more than 8%, the economic benefits are upgraded from general to good. In addition, the environmental benefit increased by 88.16%, 100.02%, 103.22%, 109.09%, respectively. The optimization effect is also remarkable. 6) In the third-level system (Baishuzhuang community, Nanan community, Tianma community), the internal rate of return of most projects becomes positive after optimization, and the economic benefits are upgraded from no to general, while the environmental benefit increases by 116.36%, 123.92% and 101.19%, respectively. The overall optimization results are good. 7) The main measure of optimization is to cut down the operating cost, but the reality is more complicated, so the local conditions should be adapted to local conditions, and the optimization measures should be chosen flexibly. 8) Those large-scale systems need to actively refer to the national biogas project construction plan and strictly control the cost when building it. [ABSTRACT FROM AUTHOR]

In the context of the increasing importance on environmental control in large-scale pig farming operations, more attention is being given to the research on different environmental impacts on pig health. In order to conduct variable environments for pig health experiments, a pig breeding chamber under multiple environment variable control was designed in this paper for more precise environmental control experiments. The pig breeding chamber was composed of 4 parts, the main chamber, the air mixing box, the environmental regulation executing devices, and the environmental control system. The main chamber was the living space for experimental animals. The air mixing box was used to regulate the air variables, such as temperature, relative humidity, NH3 and CO2 concentration, before the air entering the main chamber. The environmental regulation executing devices involved the fans, the air valves, the air conditioning compressor, the air heating pipe, the electromagnetic valve for NH3. Then the environmental control system read environment variables through sensors and controlled the working of all the environmental regulation executing devices to limit the environment variables in the main chamber in a setting range. Main ventilation mode of the pig breeding chamber was self-circulated. A fan working at the outlet built a negative pressure to exhaust the airflow entering the main chamber through the air mixing box and the ventilation pipe. The air flow entered the main chamber through three air inlets, dissipated in the chamber and then was exhausted from the outlet, thereby forming the air circulation. The air conditioning compressor and air heating pipe in the air mixing box could cool down or heat up the airflow respectively, and the electromagnetic valve for NH3 gas could increase NH3 concentration of the airflow. The exhaust air valve was working with the fresh air valve to reduce NH3 concentration or CO2 concentration in the chamber. The airflow in the main chamber was optimized previously by ANSYS flow field simulation. The environmental control system of the chamber was composed of environmental variable detection module, S7-200 PLC (Programmable Logical Controller), and host computer. The environment variable detection module sampled all the environmental data, such as temperature, relative humidity, air velocity, NH3 concentration, and CO2 concentration, and sent to a STM32 microcontroller every 2 seconds. The program embedded in STM32 integrated these data into one data packet and sent them to the S7-200 PLC through a serial port. The S7-200 PLC transferred the data to the host computer and simultaneously calculated out control instructions to control environmental regulation executing devices, limited the chamber’s internal environments to a setting range. Besides, the manure pump and LED lights were also controlled by the PLC to realize automatic manure cleaning and lighting timing. The host computer realized dynamic and real-time display and storage of environmental data. The running states of the executing devices were showed on the screen through WinCC monitoring software. Three tests for the pig breeding chamber were conducted, including the smoke test for air flow field, an empty chamber test and a full-loaded chamber test. The smoke test of air flow field verified the airflow pattern, which was simulated by ANSYS previously. Result showed the smoke formed a circle in the main chamber and dissipated all through the chamber without leaving any dead space. The test in the empty chamber verified the function and performance of the control system. The results of the environmental test with animals loaded showed that the control precision of temperature was limited within ±1°C, the relative humidity could be controlled within the pig comfortable range of 50%-80%, the oscillations of NH3 concentration were limited less than ±3×10-6 when the setting value of NH3 concentration was 10×10-6, and the concentration of CO2 could be controlled below 1 540×10-6 basically, which was a standard for animal health. During the full-loaded experiment, which lasted for almost 3 weeks, temperature, relative humidity, NH3 and CO2 concentrations variables inside the chamber were accurately controlled. This show the pig breeding chamber can provide an effective platform for more precise pig, especially nurseries, breeding experiments under variable environments and potentially helps improve the research method to reveal the relationship between pigs and their environments. [ABSTRACT FROM AUTHOR]

Out-of-season breeding technology for goose was proposed due to their obviously seasonality of production. Precisely time control is the most critical factor in this technology. Simultaneously, temperature and humidity control are also needed in case of heat stress. The application of the new technology brings challenges to the traditional breeding methods. Environment control in goose house was mostly artificial or semi mechanized. Manual operation was of poor real-time performance, and could not achieve the organic connection between the various environmental factors. Light, temperature, relative humidity and other environmental parameters could not be recorded real-time. When diseases or some abnormal reproduction happen, managers could not trace causes from the aspect of environment. This study therefore was conducted to develop an intelligent geese house environment monitoring system for assisting geese out-of-season breeding practices. In the system, BP neural network was utilized to construct an intelligent control model with history temperature and relative humidity data. With this model, the system could make comparison between current temperature and relative humidity inside and outside, so as to determine the number of working fans and the on-off state of cooling pad. GPRS wireless transmission module was used to transmit in-house environmental parameters. With this system, mobile terminal GSM function was also utilized to remote control the geese house equipment such as fans, illuminating lights, pumps and cooling pads. On the basic framework technology of EXT, Hibernate and Spring, a J2EE enterprise web application was built. This made it possible of remote control and real time monitoring. In addition, users could also obtain the environment conditions from mobile client or remote control the corresponding equipment. Field tests were conducted in comparison with artificial control and other commercially developed animal house monitoring systems. The system had been running for more than five months. Results showed that this system was stable and reliable during long-term operation, and could meet the requirements of light, temperature and relative humidity of out-of-season breeding. Compared with artificial control and Shanghai Fanlong controller, the control precision was improved by 5.49% and 2.83%, respectively, labor cost was cut down by 50%. Geese elimination rate was decreased by 1.09% and 0.62%, respectively. With the method of cooling pads system in summer, the RMSE between in house temperature of BP neural network (A3), artificial experience (A2), setting static operating point(A4) and the set values were 0.202, 0.494 and 0.372℃, respectively, and relative humidity was 1.745%, 3.166% and 2.621%, respectively. Under the precise control of light, geese in all three houses exhibited normal onset and level of egg laying. They began to lay eggs from May 1st, and rose to the peak level in about one month. During hot summer, there was no heat stress of geese in A3, they showed steady laying rate, while laying rate of geese in A2 and A4 showed varying degrees of decline. At the peak of egg production, all three groups maintained their laying rate between 35% and 45%. From May 1st to October 1st, the mean daily egg laying rate of A2, A3 and A4 are 24.77%, 31.18% and 27.94%, respectively, which indicated that the intelligent control system of geese house environments allowed geese to exhibit normal out-of-season production performances. [ABSTRACT FROM AUTHOR]

The main considered environmental factors affecting performance of poultry is temperature. Thermal insulation performance of building component is the key factor that affects temperature stability, which is essential to ensure the bird's well-being, maximum productivity and efficient feed utilization. Generally, laying hen houses are not equipped with heating system in winter, the temperature meets the requirements of layer hen rely on sensible heat production of layers. Bird's sensible heat production and good insulation of building component are generally sufficient to maintain the houses temperature. If the stocking density is low or poorly insulated buildings, it's difficult to meet the layer house environment requirements, including temperature, humidity and air quality. Improving thermal insulation performance of the building component would reduce heat loss and increasing stocking density could raise sensible heat production. However, ideal ventilation control system is required to ensure that aerial pollution emissions levels are within the acceptable limits and not to result in unnecessary ventilation heat losses. As such, minimum ventilation rate is particularly important. It is crucial for indoor temperature level and uniformity. Layer house minimum ventilation and air flow are crucial not only for indoor temperature and humidity, but also for temperature control uniformity. But there was a lack of information about the design theories. No information could be found in the literature that optimum relationship between thermal insulation performance of the layer house component and stocking density in laying-hen housing systems with different climatic regions in China. It was required to settle the urgent issue on how to determine the layer houses component thermal insulation performance under different climate zones, especially in the layer house building construction and environmental control fields. The objectives of this article was to analyze on minimum thermal resistance of building component in different climatic regions of China, and according the law of energy and quality conservation, to build dynamic heat balance model for layer house. A model was developed to determine the thermal insulation performance. It was important to build dynamic heat balance model in layer house, in order to maintain the temperature of the house of laying hen and to keep the healthy environment of layer hen. Those can reduce the energy consumption and construction cost, providing a guidance for laying house thermal insulation system design. In this paper, we conducted theoretical analysis and numerical calculation the building component minimum thermal resistance under the different climate regions and built steady-state heat balance theory model for layer house. Results showed that: 1) When calculated temperatures were -25 ℃ (Northeastern China), -15 ℃ (Northern and Northwestern China), -0 ℃ (South of the Yangtze River China), the minimum thermal resistance of the layer hen houses walls should not be less than 0.778, 0.972, and 0.573 m2·℃/W, and the minimum thermal resistance for the ceiling should not be less than, 0.716, 0.266, and 0.333 m2·℃/W respectively for the above mentioned three regions. 2) A-frame cage of three tiers, semi-A-frame cage of four tiers, four overlap tiers cages, six overlap tiers cages, and eight overlap tiers cages, with maximum stocking density and outdoor design temperature should not be lower than -14, -17, -19, -22, -23 ℃. As such, dynamic thermal balance of layer house can be achieved. The results of this study provided theoretical foundation for the design of insulation system for closed layer hen house. Those research results can reduce the energy consumption and construction cost and providing a theoretical basis for layer house thermal insulation design system. [ABSTRACT FROM AUTHOR]

Swine building environment plays an important role on the pig production, and it is a nonlinear, time-varying and delay system with multiple factors coupling with each other. Air temperature, humidity, harmful gases, airflow, light, dust and other factors in such an environment can affect the growth, development, reproduction of pigs. In the confined swine building, the indoor environment quality can deteriorate due to the high breeding density. The indoor air quality can be improved by appropriate ventilation control that supplies fresh air from outdoor and at the same time dissipates heat and moisture, and decreases concentrations of harmful gases. Most of the swine building environmental control systems are only based on a single environmental variable (temperature) using traditional control method. New systems based on multiple environmental variables and using precision mathematical models are needed to improve swine building environment controls. A multi-factor environmental control system with two controllers, based on the fuzzy control theory was established for the confined swine building in this paper. In this control system, a fuzzy controller was the nucleus part. A temperature fuzzy controller and a ventilation fuzzy controller were established with two input and one output variables, respectively, to achieve environmental control. In the air temperature fuzzy controller, air temperature difference and its variation rate were selected as two input variables, and a ventilation mode and a heating mode were chosen as output variables. In the ventilation fuzzy controller, differences of relative humidity and ammonia concentration were selected as input variables, and fan operation mode was selected as an output variable. To meet the requirements in different seasons, the input variables of the two controllers were first processed through fuzzification and fuzzy logic reasoning based on different control strategies and rules. Then the output variables were obtained after defuzzification processing. To solve the coupling problems between temperature and ventilation controls and optimize the control system, a dynamic temperature compensation coefficient was added. The method developed in this paper was validated using the data collected from a swine building. Different ventilation modes were simulated to get the relationship between the changing rates of air temperature, relative humidity, ammonia concentrations with fan operation time. Results showed that the maximum relative error of temperature was 5% compared with the setting value; and the indoor temperature control was achieved. The maximum relative error of relative humidity deviation from the setting value was 6.3%, which met the required relatively humidity control. The NH3 concentrations ranged from 2.0 to 3.7 mg/m3, which were less than the setting value of 9.1 mg/m3. Therefore, the fuzzy control system and strategy with multi-factor in this paper could be used to improve the swine building environmental control. [ABSTRACT FROM AUTHOR]

The CO2 concentration is required to be below 1500 mg/m3 (Environmental Quality Standards for the Livestock and Poultry Farm of China, published in 1999) in layer hen houses where the manure is disposed by powered scraper, the litters generally need to remind and the drinking device has water leak. Consequently, moisture and NH3 levels in such barns are much high. Also, air temperature is much lower in winter, because the minimum ventilation rate is large in winter. However, the manure is cleaned daily in new poultry house with manure convey belt. Meanwhile, the aerial pollutants (CO2 and NH3) are reduced and the relative humidity is decreased. Indoor air quality in this kind of poultry house is dramatically improved. A new standard of CO2 concentration and the minimum ventilation rate of layer house with manure convey belt should be reconsidered. Determining the CO2 concentration standards for the manure convey belt in layer hen houses is needed. The objectives of this work were to draw a conclusion about the CO2 concentration levels and use it as a reference to calculate the minimum ventilation rate in winter. This review summarized the recent measurements of the emission rates of aerial NH3 and the CO2 concentrations in poultry houses in which the laying hens were kept in cages. The relationship between CO2 and NH3 was also described based on the data got in the poultry houses with different manure removing way from the domestic and foreign study. In addition, the minimum ventilation rate is important for ensuring the ideal air quality in poultry house in winter. The optimum ventilation is one of the factors affecting poultry production and energy consumption. Considering the mass conservation under steady-state conditions in the layer hen building, there are 2 main sources of CO2 in poultry house, and most of the CO2 is produced by respiration processes of layer hens, if neglecting the amount of CO2 emitted from manure. The minimum temperature value for layer houses was 13 ℃ in this study. The following conclusions were drawn in this study: 1) There was a positive and significant correlation between CO2 and NH3 concentration in layer houses based on analyzing the data of previous researches. The standards of CO2 concentration and NH3 concentration were suggested to be 5000 mg/m3 and less than 15 mg/m3 respectively in the layer hen houses with manure convey belt. This condition would not reduce the hen's performance and defenses. Primary CO2 concentration standards persisted when the feces were scraped by powered scraper to a cross conveyor at the end of the barn; 2) Average NH3 concentrations in the layer house with manure convey belt was largely less than the traditional house with the scraper. Therefore, rebuilding new layer hen's building equipped with the manure convey belt is crucial not only for indoor environment, but also for ventilation system; 3) Ventilation rate was calculated using the rate of laying hen in winter based on CO2 mass balances from the literature. The constantly minimum ventilation rates were 0.40-0.50 m3/(h·kg) for the layer houses with manure convey belt. The new standards of CO2 concentration and ventilation rate were beneficial for improving indoor environment control and ventilation energy efficiency, and saving constructional costs. Furthermore, the results of this paper provide the reference for solving the contradiction between ventilation and insulation system in layer house. Also, it can improve the versatility of poultry environment and provide the support for emission studies using the new standard of the CO2 to evaluate the poultry building environment. [ABSTRACT FROM AUTHOR]

To study the digestion ability of biogas slurry in paddy field and the potential risk of water environment pollution in the process of digestion, 4 irrigation amounts of biogas slurry treatments and 2 control treatments were designed based on the location test with engineering measures in this study. The treatments included 1000 t/hm2 biogas slurry at base-tiller stage of rice combined with 120 kg/hm2 nitrogen (urea) at panicle stage of rice (BS10), and 635.29, 423.53, 211.76 t/hm2 biogas slurry at base-tiller stage respectively combined with 423.53, 282.35, 141.18 t/hm2 biogas slurry at panicle stage (300% BS, 200% BS and 100% BS). The control treatments were conventional fertilization (CF) with 180 kg/hm2 nitrogen (urea) at base-tiller stage and 120 kg/hm2 nitrogen (urea) at panicle stage, and no-fertilization treatment (CK) without fertilizer both at base-tiller stage and at panicle stage of rice. Then the changes of the total nitrogen, ammonia nitrogen and nitrate nitrogen in both field surface water and soil percolation water at 40 and 60 cm depth were monitored 1, 2, 3, 5 and 7 d after biogas slurry application during the main rice growth period. The data were analyzed by Microsoft Excel (2010) and SPSS for windows (13.0). Results showed that: 1) The key period of biogas slurry digestion in paddy field was the first 3 d after irrigation with the total nitrogen degradation rate of 46.67%-78.36% and the ammonia nitrogen degradation rate of 47.52%-85.27%. And the digestion rate at panicle fertilizer stage was greater than that at base-tillers stage. The environmental risk of surrounding water body eutrophication was bigger if runoff was generated 3 d after the irrigation. To ensure safe disposal and realize the reduction of agricultural non-point source pollution source and emissions, engineering measures should be adopted such as closing field drain or increasing ridge height by 5-10 cm to control surface runoff. 2) The potential risk of surrounding water pollution with the amount of biogas slurry digestion above the 200% BS processing (i.e., 705.88 t/hm2) was higher than the conventional fertilization treatment both at base-tillers stage and at panicle fertilizer stage. Compared with the conventional fertilization treatment, 100% BS processing (i.e., 352.94 t/hm2) had a lower potential risk of environmental pollution. Therefore, the biogas slurry digestion in paddy field should adopt the way of more irrigation times and fewer disposal amounts. 3) To resolve the pollution risk to soil percolation water from biogas slurry digestion in paddy field with engineering measures was mainly concentrated in the tillers stage, and the ammonia nitrogen pollution risk was the main risk while the nitrate pollution risk was less. The pollution was different among different water penetration depths. Research indicated that the safe disposal amount of biogas slurry at a time in tillers stage should be controlled below the amount of 211.76 t/hm2, and less than 423.53 t/hm2 in panicle fertilizer stage. These results can provide a theoretical reference for the technology of biogas slurry safe disposal in paddy field and the technology of reducing emission in agricultural non-point source pollution from source. [ABSTRACT FROM AUTHOR]