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

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

Influence of barn climate, body postures and milk yield on the respiration rate of dairy cows

The main objective of this study was to identify the influences of different climatic conditions and cow-related factors on the respiration rate (RR) of lactating dairy cows. Measurements were performed on 84 lactating Holstein Friesian dairy cows (first to eighth lactation) in Brandenburg, Germany. The RR was measured hourly or twice a day with up to three randomly chosen measurement days per week between 0700 h and 1500 h (GMT + 0100 h) by counting right thoracoabdominal movements of the cows. Simultaneously with RR measurements, cow body postures (standing vs. lying) were documented. Cows’ milk yield and days in milk were recorded daily. The ambient temperature and relative humidity of the barn were recorded every 5 min to calculate the current temperature-humidity index (THI). The data were analyzed for interactions between THI and cow-related factors (body postures and daily milk yield) on RR using a repeated measurement linear mixed model. There was a significant effect of the interaction between current THI category and body postures on RR. The RRs of cows in lying posture in the THI < 68, 68 ≤ THI < 72 and 72 ≤ THI < 80 categories (37, 46 and 53 breaths per minute (bpm), respectively) were greater than those of standing cows in the same THI categories (30, 38 and 45 bpm, respectively). For each additional kilogram of milk produced daily, an increase of 0.23±0.19 bpm in RR was observed. Including cow-related factors may help to prevent uncertainties of RR in heat stress predictions. In practical application, these factors should be included when predicting RR to evaluate heat stress on dairy farm

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

Opportunities of adopting renewable energy for the nursery industry in Australia

In Australia, the nursery and garden industry provides significant economic, cultural, social and environmental benefits to the community (NGIA, 2014). The production nurseries support a diverse array of industries and end users, including retail outlets, landscapers, cut-flower growers, orchardists, vegetable growers, interiorscapers, sustainable forestry and revegetation enterprises. Overall, the gross value of production (GVP) of the broad 'nursery, flower and turf' industry in Australia is A$1271 million, which is 17% of the total GVP of Australian horticultural industry (ABS, 2013). Amenity horticulture is currently one of the fastest growing industries in Australia (NGIA, 2009). Energy use efficiency has also become increasingly important due to the increasing cost and scarcity of energy sources and also the associated greenhouse gas (GHG) emissions causing global warming (Bundschuh and Chen, 2014; Chen and Baillie, 2009a). The horticultural sector contributes about 6% of the total agriculturalGHGemissions in Australia (Deuter, 2008). Nursery operators are thus under increasing pressure to reduce their energy and carbon footprint. By improving energy efficiency and using clean energy sources, the nursery industry can drive down their carbon footprint (Abeliotis et al., 2015; Beccaro et al., 2014; Lazzerini et al., 2014; Russo et al., 2008), and also simultaneously increase their bottom line

Uncertainty in the measurement of indoor temperature and humidity in naturally ventilated dairy buildings as influenced by measurement technique and data variability

The microclimatic conditions in dairy buildings affect animal welfare and gaseous emissions. Measurements are highly variable due to the inhomogeneous distribution of heat and humidity sources (related to farm management) and the turbulent inflow (associated with meteorologic boundary conditions). The selection of the measurement strategy (number and position of the sensors) and the analysis methodology adds to the uncertainty of the applied measurement technique. To assess the suitability of different sensor positions, in situations where monitoring in the direct vicinity of the animals is not possible, we collected long-term data in two naturally ventilated dairy barns in Germany between March 2015 and April 2016 (horizontal and vertical profiles with 10 to 5 min temporal resolution). Uncertainties related to the measurement setup were assessed by comparing the device outputs under lab conditions after the on-farm experiments. We found out that the uncertainty in measurements of relative humidity is of particular importance when assessing heat stress risk and resulting economic losses in terms of temperature-humidity index. Measurements at a height of approximately 3 m–3.5 m turned out to be a good approximation for the microclimatic conditions in the animal occupied zone (including the air volume close to the emission active zone). However, further investigation along this cross-section is required to reduce uncertainties related to the inhomogeneous distribution of humidity. In addition, a regular sound cleaning (and if possible recalibration after few months) of the measurement devices is crucial to reduce the instrumentation uncertainty in long-term monitoring of relative humidity in dairy barns. © 2017 The Author