Constructing better piggery buildings by identifying factors contributing to improved thermal control under hot climatic conditions

External and internal air temperatures were measured continuously for one year (between January 1999 and December 1999) in 48 piggery buildings in South Australia using self contained data-loggers with built-in sensors. Data was consolidated to correspond with the four seasons. Regression values between the external and internal temperatures were calculated for individual buildings for each season. Data was also collected on major housing features, including configuration of the buildings and management factors employed in them. The information collected was then analysed to quantify the effects of housing and management factors on the resulting environmental control using a multi-factorial statistical model. The overall mean air temperatures in all buildings corresponding to the four seasons were; 24°C (summer), 20°C (autumn), 18°C (winter), 21°C (spring) across all buildings. The regression values between external and internal temperatures were affected by the season, type of insulation material used in the buildings, the availability of extra heating or cooling equipment, height of buildings, roof pitch (angle), type of ridge ventilation control employed, stocking density, age of buildings and number of pigs housed per building. The effects of housing and management factors on thermal control capacity of buildings were quantified. These findings should aid the construction of better designed livestock buildings resulting in improved welfare and production efficiency in piggery buildings

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

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

Feeding behaviour of broiler chickens: a review on the biomechanical characteristics

Feed related costs are the main drivers of profitability of commercial poultry farms, and good nutrition is mainly responsible for the exceptional growth rate responses of current poultry species. So far, most research on the poultry feeding behaviour addresses the productivity indices and birds' physiological responses, but few studies have considered the biomechanical characteristics involved in this process. This paper aims to review biomechanical issues related to feed behaviour of domestic chickens to address some issues related to the feed used in commercial broiler chicken production, considering feed particle size, physical form and the impact of feeders during feeding. It is believed that the biomechanical evaluation might suggest a new way for feed processing to meet the natural feeding behaviour of the birds

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

On-farm energy use in the grain and horticultural industries

Agriculture and the related primary industry requires energy as an important input. Energy is needed to a differing extent in all the stages of the agri-food chain. In this paper, on-farm energy use in the grain and horticultural industries is evaluated. It is found that the energy use varies significantly with the farm enterprises and also the farming systems, including irrigation and heating/cooling methods. The total direct on-farm energy use for grain grown under dryland conditions with no tillage may be as low as 0.35 GJ/ha, while for horticultural products, the direct on-farm energy use may reach up to 20000 GJ/ha for tomatoes grown in greenhouses. The large variation of energy uses may indicate the significant opportunities for reducing energy use in these industries

On-farm energy use in the dairy industries

Dairying is one of largest agricultural industries in Australia. This paper reviews the on-farm energy use in various dairy operations. It is found that the total direct on-farm energy needed to produce one kilogram of milk varies between 0.41-0.83 MJ/kg milk in Australia. This is in comparison with 0.19-2.47 MJ/kg milk overseas. The differences in energy uses are mainly due to different farming systems and technologies adopted and also different analysis methods employed. The large variation of energy uses indicates the significant opportunities for reducing energy use

An assessment of direct on-farm energy use for high value grain crops grown under different farming practices in Australia

Several studies have quantified the energy consumption associated with crop production in various countries. However, these studies have not compared the energy consumption from broad range of farming practices currently in practice, such as zero tillage, conventional tillage and irrigated farming systems. This study examines direct on-farm energy use for high value grain crops grown under different farming practices in Australia. Grain farming processes are identified and “typical” farming operation data are collected from several sources, including published and unpublished literature, as well as expert interviews. The direct on-farm energy uses are assessed for 27 scenarios, including three high value grain crops―wheat, barley and sorghum―for three regions (Northern, Southern and Western Australia) under three farming conditions with both dryland (both for conventional and zero-tillage) and irrigated conditions. It is found that energy requirement for farming operations is directly related to the intensity and frequency of farming operations, which in turn is related to tillage practices, soil types, irrigation systems, local climate, and crop types. Among the three studied regions, Western Australia requires less direct on-farm energy for each crop, mainly due to the easily workable sandy soils and adoption of zero tillage systems. In irrigated crops, irrigation energy remains a major contributor to the total on-farm energy demand, accounting for up to 85% of total energy use

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