Agricultural production and the ecological question

Environmental degradation is a worldwide phenomenon. It is manifested in the clearing of forests, polluted waterways, soil erosion, the loss of biodiversity, the presence of chemicals in the ecosystem and a host of other concerns. Modern agricultural practices have been implicated in much of this degradation. This chapter explores the connections between the form of agricultural production undertaken in advanced nations – so called ‘productivist’ or ‘high-tech’ farming – and environmental degradation. It is argued, first, that the entrenchment of productivist agriculture has placed considerable, and continuing, pressures on the environment and, second, that while there are both new options for a more sustainable agriculture and new policies being proposed to tackle the existing problem, the underlying basis of productivist agriculture remains largely unchallenged. The prediction is that environmental degradation will continue unabated until more dramatic (and possibly less palatable) measures are taken to alter the behaviour of producers and the trajectory of farming and grazing industries throughout the world.

Greenhouse gas emissions from sub-tropical agricultural soils after addition of organic by-products

As the cost of mineral fertilisers increases globally, organic soil amendments (OAs) from agricultural sources are increasingly being used as substitutes for nitrogen. However, the impact of OAs on the production of greenhouse gases (CO2 and N2O) is not well understood. A 60-day laboratory incubation experiment was conducted to investigate the impacts of applying OAs (equivalent to 296 kg N ha−1 on average) on N2O and CO2 emissions and soil properties of clay and sandy loam soils from sugar cane production. The experiment included 6 treatments, one being an un-amended (UN) control with addition of five OAs being raw mill mud (MM), composted mill mud (CM), high N compost (HC), rice husk biochar (RB), and raw mill mud plus rice husk biochar (MB). These OAs were incubated at 60, 75 and 90% water-filled pore space (WFPS) at 25°C with urea (equivalent to 200 kg N ha−1) added to the soils thirty days after the incubation commenced. Results showed WFPS did not influence CO2 emissions over the 60 days but the magnitude of emissions as a proportion of C applied was RB < CM < MB < HC

The psychological and economic factors that influence energy consumption habits of low-income earners

Social marketers and governments have often targeted hard to reach or vulnerable groups (Gordon et al., 2006) such as young adults and low income earners. Past research has shown that low-income earners are often at risk of poor health outcomes and diminished lifestyle (Hampson et al., 2009; Scott et al., 2012). Young adults (aged 18 to 35) are in a transition phase of their life where lifestyle preferences are still being formed and are thus a useful target for long-term sustainable change. An area of focus for all levels of government is the use of energy with an aim to reduce consumption. There is little research to date that combines both of these groups and in particular in the context of household energy usage. Research into financially disadvantaged consumers is challenging the notion that that low income consumer purchasing and usage of products and services is based upon economic status (Sharma et al., 2012). Prior research shows higher income earners view items such as televisions and computers as necessities rather than non-essential (Karlsson et al., 2004). Consistent with this is growing evidence that low income earners purchase non-essential, energy intensive electronic appliances such as multiple big screen TV sets and additional refrigerators. With this in mind, there is a need for knowledge about how psychological and economic factors influence the energy consumption habits (e.g. appliances on standby power, leaving appliances turned on, running multiple devices at one time) of low income earners. Thus, our study sought to address the research question of: What are the factors that influence young adult low-income earners energy habits?

Multiphase porous media model for heat and mass transfer during drying of agricultural products

Modelling of food processing is complex because it involves sophisticated material and transport phenomena. Most of the agricultural products such fruits and vegetables are hygroscopic porous media containing free water, bound water, gas and solid matrix. Considering all phase in modelling is still not developed. In this article, a comprehensive porous media model for drying has been developed considering bound water, free water separately, as well as water vapour and air. Free water transport was considered as diffusion, pressure driven and evaporation. Bound water assumed to be converted to free water due to concentration difference and also can diffuse. Binary diffusion between water vapour and air was considered. Since, the model is fundamental physics based it can be applied to any drying applications and other food processing where heat and mass transfer takes place in porous media with significant evaporation and other phase change.

Being Thrifty on a $100K Wage: Austerity in Family Finances

Understanding how families manage their finances represents a highly important research agenda given the recent economic climate of debt and uncertainty. To have a better understanding of the economics in domestic settings, it is very important to study the ways money and financial issues are collaboratively handled within families. Using an ethnographic approach, we studied the everyday financial practices of fifteen middle-income families. Our preliminary results show that there is a strong tendency to live frugally; that, people apply various and creative mechanisms to minimize their expenses and save money seemingly irrespectively of their income. To this end we highlight some implications for designing technologies to support household financial practices.

Impact of agricultural chemicals on the environment and human health in Asia: Are there solutions?

Modern commercial agricultural practices in Asia during the last three to four decades involving chemicals (fertilisers and pesticides) have been associated with large increases in food production never witnessed before, especially under the Green Revolution technology in South Asia. This also involves large-scale increases in commercial vegetable crops. However, the high reliance on chemical inputs to bring about these increases in food production is not without problems. A visible, parallel correlation between higher productivity, high artificial input use and environmental degradation and human ill-health is evident in many countries where commercial agriculture is widespread. In this chapter, we focus on the impact of chemical inputs, in particular the impact of pesticides on the environment and on human health in South Asia with special reference to Sri Lanka...

Bringing the farmer perspective to agricultural robots

The research reported in this paper explores autonomous technologies for agricultural farming application and is focused on the development of multiple-cooperative agricultural robots (AgBots). These are highly autonomous, small, lightweight, and unmanned machines that operate cooperatively (as opposed to a traditional single heavy machine) and are suited to work on broadacre land (large-scale crop operations on land parcels greater than 4,000m2). Since this is a new, and potentially disruptive technology, little is yet known about farmer attitudes towards robots, how robots might be incorporated into current farming practice, and how best to marry the capability of the robot with the work of the farmer. This paper reports preliminary insights (with a focus on farmer-robot control) gathered from field visits and contextual interviews with farmers, and contributes knowledge that will enable further work toward the design and application of agricultural robotics.

Export of radioactive cesium from agricultural fields under simulated rainfall in Fukushima

In this study, we investigated the impact of rainfall on runoff, soil erosion and consequently on the discharge of radioactive cesium in agricultural fields in Fukushima prefecture using a rainfall simulator. Simulated heavy rainfalls (50 mm h-1) generated significant runoff and soil erosion. The average concentration of radioactive cesium (the sum of 134Cs and 137Cs) in the runoff sediments was [similar]3500 Bq kg-1 dry soil, more than double the concentrations measured in the field soils which should be considered in studies using the 137Cs loss to estimate long-term soil erosion. However, the estimated mass of cesium discharged through one runoff event was less than 2% of the cesium inventory in the field. This suggested that cesium discharge via soil erosion is not a significant factor in reducing the radioactivity of contaminated soils in Fukushima prefecture. However, the eroded sediment carrying radioactive cesium will deposit into the river systems and potentially pose a radioactivity risk for aquatic living organisms.

Design and flight testing of an integrated solar powered UAV and WSN for greenhouse gas monitoring emissions in agricultural farms

There is an increased interest in measuring the amount of greenhouse gases produced by farming practices . This paper describes an integrated solar powered Unmanned Air Vehicles (UAV) and Wireless Sensor Network (WSN) gas sensing system for greenhouse gas emissions in agricultural lands. The system uses a generic gas sensing system for CH4 and CO2 concentrations using metal oxide (MoX) and non-dispersive infrared sensors, and a new solar cell encapsulation method to power the unmanned aerial system (UAS)as well as a data management platform to store, analyze and share the information with operators and external users. The system was successfully field tested at ground and low altitudes, collecting, storing and transmitting data in real time to a central node for analysis and 3D mapping. The system can be used in a wide range of outdoor applications at a relatively low operational cost. In particular, agricultural environments are increasingly subject to emissions mitigation policies. Accurate measurements of CH4 and CO2 with its temporal and spatial variability can provide farm managers key information to plan agricultural practices. A video of the bench and flight test performed can be seen in the following link: https://www.youtube.com/watch?v=Bwas7stYIxQ

Evaluation of a Multispectral Camera on a UAV for Agricultural Applications

Australian farmers have used precision agriculture technology for many years with the use of ground – based and satellite systems. However, these systems require the use of vehicles in order to analyse a wide area which can be time consuming and cost ineffective. Also, satellite imagery may not be accurate for analysis. Low cost of Unmanned Aerial Vehicles (UAV) present an effective method of analysing large plots of agricultural fields. As the UAV can travel over long distances and fly over multiple plots, it allows for more data to be captured by a sampling device such as a multispectral camera and analysed thereafter. This would allow farmers to analyse the health of their crops and thus focus their efforts on certain areas which may need attention. This project evaluates a multispectral camera for use on a UAV for agricultural applications.

A high-density consensus map of barley linking DArT markers to SSR, RFLP and STS loci and agricultural traits

Background: Molecular marker technologies are undergoing a transition from largely serial assays measuring DNA fragment sizes to hybridization-based technologies with high multiplexing levels. Diversity Arrays Technology (DArT) is a hybridization-based technology that is increasingly being adopted by barley researchers. There is a need to integrate the information generated by DArT with previous data produced with gel-based marker technologies. The goal of this study was to build a high-density consensus linkage map from the combined datasets of ten populations, most of which were simultaneously typed with DArT and Simple Sequence Repeat (SSR), Restriction Enzyme Fragment Polymorphism (RFLP) and/or Sequence Tagged Site (STS) markers. Results: The consensus map, built using a combination of JoinMap 3.0 software and several purpose-built perl scripts, comprised 2,935 loci (2,085 DArT, 850 other loci) and spanned 1,161 cM. It contained a total of 1,629 'bins' (unique loci), with an average inter-bin distance of 0.7 ± 1.0 cM (median = 0.3 cM). More than 98% of the map could be covered with a single DArT assay. The arrangement of loci was very similar to, and almost as optimal as, the arrangement of loci in component maps built for individual populations. The locus order of a synthetic map derived from merging the component maps without considering the segregation data was only slightly inferior. The distribution of loci along chromosomes indicated centromeric suppression of recombination in all chromosomes except 5H. DArT markers appeared to have a moderate tendency toward hypomethylated, gene-rich regions in distal chromosome areas. On the average, 14 ± 9 DArT loci were identified within 5 cM on either side of SSR, RFLP or STS loci previously identified as linked to agricultural traits. Conclusion: Our barley consensus map provides a framework for transferring genetic information between different marker systems and for deploying DArT markers in molecular breeding schemes. The study also highlights the need for improved software for building consensus maps from high-density segregation data of multiple populations.

Optimal management of agricultural systems

To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

eResearch Archive: reaching global agricultural communities

Queensland Department of Primary Industries and Fisheries Library achieved a significant breakthrough in the provision of Open Access to Australian publicly funded research with the launch of its eResearch Archive (eRA). With more than one thousand publication records, journal articles, conferences papers and research reports now available to farmers, industry representatives, academics, researchers, students and members of the public throughout the world, the archive is the first web accessible multidisciplinary science institutional repository produced by an Australian government department.