现代化生猪养殖环境测控技术现状与发展趋势

针对现代生猪规模化养殖带来的养殖场舍内环境污染对猪生长不利的问题,阐明了猪舍内温湿度、有害气体(CO、CO2、H2S、NH3)、粉尘和气流速度等环境因子对生猪健康生长的影响,及各环境因子间的相互影响、相互作用的关系;综述了国内外猪舍环境测控技术的现状,并分析了生猪养殖舍内环境测控技术的发展趋势,为我国生猪养殖业规模化、工程化、工厂化和自动化发展提供参考,推进生猪健康福利养殖。

Detection of flock movement and behaviour of broiler chickens at different feeders using image analysis

The behaviour of broiler chickens has been extensively studied as a function of stocking density and environmental conditions,but limited information was reported in the scientific literature about the effect of feeder type on birds’feeding process.The main objective of this study was to assess the effects of three different feeder types in relation to the birds’behaviour in its surroundings.The analysed feeders were:tube-type with partition grid(F1);tube-type without partition grid(F2);and automatic type with partition grid(F3).The considered variables were:occupied area(OA);activity index(AI)(flock movement);total birds presented in the area(TB);and birds effectively eating(EE).OA and AI were calculated by computational image analysis while TB and EE were manually measured.The results indicated that the feeder type could have influenced the birds’behaviour regarding to OA(R2=0.56),TB(R2=0.48),and EE(R2=0.40),but AI(R2=0.01)was not found to be directly influenced by the feeder type.A higher percentage of birds effectively eating were found in F2(86.4%),which was the one with the largest free area to access the feed.Similar average number of total birds was found in F1,but with a lower percentage of individuals effectively eating(63.3%),which means that birds were nearby this feeder performing other behaviours.Since the assessed feeders were in the same house under the same conditions,it can be suggested that not only the free area to access the feed but potentially the design of feeders could have influenced the birds’feeding preference.The real beneficial effect of the adoption of partition grid on feed trays is still uncertain,and it is also unclear whether the financial value of reduced wastage would compensate the possible reduction in feed intake.

Preliminary laboratory test on navigation accuracy of an autonomous robot for measuring air quality in livestock buildings

Air quality in many poultry buildings is less than desirable.However,the measurement of concentrations of airborne pollutants in livestock buildings is generally quite difficult.To counter this,the development of an autonomous robot that could collect key environmental data continuously in livestock buildings was initiated.This research presents a specific part of the larger study that focused on the preliminary laboratory test for evaluating the navigation precision of the robot being developed under the different ground surface conditions and different localization algorithm according internal sensors.The construction of the robot was such that each wheel of the robot was driven by an independent DC motor with four odometers fixed on each motor.The inertial measurement unit(IMU)was rigidly fixed on the robot vehicle platform.The research focused on using the internal sensors to calculate the robot position(x,y,θ)through three different methods.The first method relied only on odometer dead reckoning(ODR),the second method was the combination of odometer and gyroscope data dead reckoning(OGDR)and the last method was based on Kalman filter data fusion algorithm(KFDF).A series of tests were completed to generate the robot’s trajectory and analyse the localisation accuracy.These tests were conducted on different types of surfaces and path profiles.The results proved that the ODR calculation of the position of the robot is inaccurate due to the cumulative errors and the large deviation of the heading angle estimate.However,improved use of the gyroscope data of the IMU sensor improved the accuracy of the robot heading angle estimate.The KFDF calculation resulted in a better heading angle estimate than the ODR or OGDR calculations.The ground type was also found to be an influencing factor of localisation errors.

Wireless data management system for environmental monitoring in livestock buildings

The impact of air quality on the health,welfare and productivity of livestock needs to be considered,especially when livestock are kept in enclosed buildings.The monitoring of such environmental factors allows for the development of appropriate strategies to reduce detrimental effects of sub-optimal air quality on the respiratory health of both livestock and farmers.In 2009,an environmental monitoring system was designed,developed and tested that allowed for the monitoring of a number of airborne pollutants.One limitation of the system was the manual collection of logged data from each unit.This paper identifies limitations of the current environmental monitoring system and suggests a range of networking technologies that can be used to increase usability.Consideration is taken for the networking of environmental monitoring units,as well as the collection of recorded data.Furthermore,the design and development of a software system that is used to collate and store recorded environmental data from multiple farms is explored.In order to design such a system,simplified software engineering processes and methodologies have been utilised.The main steps taken in order to complete the project were requirements elicitation with clients,requirements analysis,system design,implementation and finally testing.The outcome of the project provided a potential prototype for improving the environmental monitoring system and analysis informing the benefit of the implementation.

Evaluating droplet distribution of spray-nozzles for dust reduction in livestock buildings using machine vision

Previous studies have demonstrated the negative effects of sub-optimal air quality on profitability,production efficiency,environmental sustainability and animal welfare.Experiments were conducted to assess potential environmental improvement techniques such as installing oil-spraying systems in piggery buildings.The developed spray system worked very well and it was easy to assemble and operate.However,before selecting the most suitable spray heads,their capacity to uniformly distribute the oily mixture and the area covered by the spray heads had to be assessed.Machine vision techniques were used to evaluate the ability of different spray heads to evenly distribute the oil/water mixture.The results indicated that the best coverage was achieved by spray head No.4 and spray head No.1 which covered 79%and 67%of the target area,respectively.Spray distribution uniformity(variance)value was the lowest for spray head No.4(0.015).Spray head No.3 had the highest variance value(0.064).As the lowest variance means higher uniformity,nozzle No.4 was identified as the most suitable spray head for dust reduction in livestock buildings.