994 resultados para Agricultural machinery - Traction


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Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics.

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Correlations between oil and agricultural commodities have varied over previous decades, impacted by renewable fuels policy and turbulent economic conditions. We estimate smooth transition conditional correlation models for 12 agricultural commodities and WTI crude oil. While a structural change in correlations occurred concurrently with the introduction of biofuel policy, oil and food price levels are also key influences. High correlation between biofuel feedstocks and oil is more likely to occur when food and oil price levels are high. Correlation with oil returns is strong for biofuel feedstocks, unlike with other agricultural futures, suggesting limited contagion from energy to food markets.

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Australia’s and New Zealand’s major agricultural manure management emission sources are reported to be, in descending order of magnitude: (1) methane (CH4) from dairy farms in both countries; (2) CH4 from pig farms in Australia; and nitrous oxide (N2O) from (3) beef feedlots and (4) poultry sheds in Australia. We used literature to critically review these inventory estimates. Alarmingly for dairy farm CH4 (1), our review revealed assumptions and omissions that when addressed could dramatically increase this emission estimate. The estimate of CH4 from Australian pig farms (2) appears to be accurate, according to industry data and field measurements. The N2O emission estimates for beef feedlots (3) and poultry sheds (4) are based on northern hemisphere default factors whose appropriateness for Australia is questionable and unverified. Therefore, most of Australasia’s key livestock manure management greenhouse gas (GHG) emission profiles are either questionable or are unsubstantiated by region-specific research. Encouragingly, GHG from dairy shed manure are relatively easy to mitigate because they are a point source which can be managed by several ‘close-to-market’ abatement solutions. Reducing these manure emissions therefore constitutes an opportunity for meaningful action sooner compared with the more difficult-to-implement and long-term strategies that currently dominate agricultural GHG mitigation research. At an international level, our review highlights the critical need to carefully reassess GHG emission profiles, particularly if such assessments have not been made since the compilation of original inventories. Failure to act in this regard presents the very real risk of missing the ‘low hanging fruit’ in the rush towards a meaningful response to climate change

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With Safe Design and Construction of Machinery, the author presents the results of empirical studies into this significant aspect of safety science in a very readable, well-structured format. The book contains 436 references, 17 tables, one figure and a comprehensive index. Liz Bluff addresses a complex and important, but often neglected domain in OHS – the safety of machinery – in a holistic and profound, yet evidence based analysis; with many applied cases from her studies, which make the book accessible and a pleasant lecture. Although research that led to this remarkable publication might have been primarily focused on the regulators, this book can be highly recommended to all OHS academics and practitioners. It provides an important contribution to the body of knowledge in OHS, and establishes one of the few Australian in-depth insights into the significance of machinery producers, rather than machinery users in the wider framework of risk management. The author bases this fresh perspective on the well-established European Machinery Safety guidelines, and grounds her mixed-methods research predominantly in qualitative analysis of motivation and knowledge, which eventually leads to specific safety outcomes. It should be noted that both European and Australian legal aspects are investigated and considered, as both equally apply to many machinery exporters. A detailed description of the research design and methods can be found in an appendix. Overall, the unique combination of quantitative safety performance data and qualitative analysis of safety behaviours form a valuable addition to the understanding of machinery safety. The author must be congratulated on making these complex relationships transparent to the reader through her meticulous inquiry.

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Aurizon, Australia's largest rail freight operator, is introducing the Static Frequency Converter (SFC) technology into its electric railway network as part of the Bauhinia Electrification Project. The introduction of SFCs has significant implications on the protection systems of the 50kV traction network. The traditional distance protection calculation method does not work in this configuration because of the effect that the SFC in combination with the remote grid has on the apparent impedance, and was substantially reviewed. The standard overcurrent (OC) protection scheme is not suitable due to the minimum fault level being below the maximum load level and was revised to incorporate directionality and under-voltage inhibit. Delta protection was reviewed to improve sensitivity. A new protection function was introduced to prevent back-feeding faults in the transmission network through the grid connection. Protection inter-tripping was included to ensure selectivity between the SFC protection and the system downstream.

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Weeds are a hidden foe for crop plants, interfering with their functions and suppressing their growth and development. Yield losses of ∼34 are caused by weeds among the major crops, which are grown worldwide. These yield losses are higher than the losses caused by other pests in the crops. Sustainable weed management is needed in the wake of a huge decline in crop outputs due to weed pressure. A diversity in weed management tools ensures sustainable weed control and reduces chances of herbicide resistance development in weeds. Allelopathy as a tool, can be importantly used to combat the challenges of environmental pollution and herbicide resistance development. This review article provides a recent update regarding the practical application of allelopathy for weed control in agricultural systems. Several studies elaborate on the significance of allelopathy for weed management. Rye, sorghum, rice, sunflower, rape seed, and wheat have been documented as important allelopathic crops. These crops express their allelopathic potential by releasing allelochemicals which not only suppress weeds, but also promote underground microbial activities. Crop cultivars with allelopathic potentials can be grown to suppress weeds under field conditions. Further, several types of allelopathic plants can be intercropped with other crops to smother weeds. The use of allelopathic cover crops and mulches can reduce weed pressure in field crops. Rotating a routine crop with an allelopathic crop for one season is another method of allelopathic weed control. Importantly, plant breeding can be explored to improve the allelopathic potential of crop cultivars. In conclusion, allelopathy can be utilized for suppressing weeds in field crops. Allelopathy has a pertinent significance for ecological, sustainable, and integrated weed management systems.

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Development of no-tillage (NT) farming has revolutionized agricultural systems by allowing growers to manage greater areas of land with reduced energy, labour and machinery inputs to control erosion, improve soil health and reduce greenhouse gas emission. However, NT farming systems have resulted in a build-up of herbicide-resistant weeds, an increased incidence of soil- and stubble-borne diseases and enrichment of nutrients and carbon near the soil surface. Consequently, there is an increased interest in the use of an occasional tillage (termed strategic tillage, ST) to address such emerging constraints in otherwise-NT farming systems. Decisions around ST uses will depend upon the specific issues present on the individual field or farm, and profitability and effectiveness of available options for management. This paper explores some of the issues with the implementation of ST in NT farming systems. The impact of contrasting soil properties, the timing of the tillage and the prevailing climate exert a strong influence on the success of ST. Decisions around timing of tillage are very complex and depend on the interactions between soil water content and the purpose for which the ST is intended. The soil needs to be at the right water content before executing any tillage, while the objective of the ST will influence the frequency and type of tillage implement used. The use of ST in long-term NT systems will depend on factors associated with system costs and profitability, soil health and environmental impacts. For many farmers maintaining farm profitability is a priority, so economic considerations are likely to be a primary factor dictating adoption. However, impacts on soil health and environment, especially the risk of erosion and the loss of soil carbon, will also influence a grower’s choice to adopt ST, as will the impact on soil moisture reserves in rainfed cropping systems.

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General Index Vol 13 Parts 1-6, pages 1-81

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Nitrous oxide is the foremost greenhouse gas (GHG)generated by land-applied manures and chemical fertilisers (Australian Government 2013). This research project was part of the National Agricultural Manure Management Program and investigated the potential for sorbers (i.e. specific naturally-occurring minerals) to decrease GHG emissions from spent piggery litter (as well as other manures)applied to soils. The sorbers investigated in this research were vermiculite and bentonite. Both are clays with high cation exchange capacities, of approximately 100–150 cmol/kg Faure 1998). The hypothesis tested in this study was that the sorbers bind ammonium in soil solution thereby suppressing ammonia (NH3)volatilisation and in doing so, slowing the kinetics of nitrate formation and associated nitrous oxide (N2O) emissions. A series of laboratory, glasshouse and field experiments were conducted to assess the sorbers’ effectiveness. The laboratory experiments comprised 64 vessels containing manure and sorber/manure ratios ranging from 1 : 10 to 1 : 1 incorporated into a sandy Sodosol via mixing. The glasshouse trial involved 240 pots comprising manure/sorber incubations placed 5 cm below the soil surface, two soil types (sandy Sodosol and Ferrosol) and two different nitrogen (N) application rates (50 kg N/ha and 150 kg N/ha) with a model plant (kikuyu grass). The field trial consisted of 96, 2 m · 2 m plots on a Ferrosol site with digit grass used as a model plant. Manure/ sorber mixtures were applied in trenches (5 cm below surface) to these plots at increasing sorber levels at anNloading rate of 200 kg/ha. Gas produced in all experiments was plumbed into a purpose-built automated gas analysis (N2O, NH3, CH4, CO2) system. In the laboratory experiments, the sorbers showed strong capacity to decreaseNH3 emissions (up to 80% decrease). Ammonia emissions were close to the detection limit in all treatments in the glasshouse and field trial. In all experiments, considerable N2O decreases (>40%) were achieved by the sorbers. As an example, mean N2O emission decreases from the field trial phase of the project are shown in Fig. 1a. The decrease inGHGemissions brought about by the clays did not negatively impact agronomic performance. Both vermiculite and bentonite resulted in a significant increase in dry matter yields in the field trial (Fig. 1b). Continuing work will optimise the sorber technology for improved environmental and agronomic performance across a range of soils (Vertosol, Dermosol in addition to Ferrosol and Sodosols) and environmental parameters (moisture, temperature, porosity, pH).

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Feral pigs (Sus scrofa) consume and damage crops and impact the environment through predation, competition and habitat disturbance, although supporting dietary data are lacking in agricultural landscapes. This study was undertaken to determine the relative importance of food items in the diet of feral pigs in a fragmented agricultural landscape, particularly to assist in predicting the breadth of likely impacts. Diet composition was assessed from the stomach contents of 196 feral pigs from agricultural properties in southern Queensland. Feral pigs were herbivorous, with plant matter comprising >99% of biomass consumed. Crops were consumed more frequently than non-crop species, and comprised >60% of dietary biomass, indicating a clear potential for direct economic losses. Consumption of pasture and forage species also suggests potential competition for pasture with domestic stock. There is little evidence of direct predation on native fauna, but feral pig feeding activities may impact environmental values. Seasonal differences in consumption of crop, pasture or animal food groups probably reflect the changing availability of food items. We recommend that future dietary studies examine food availability to determine any dietary preferences to assist in determining the foods most susceptible to damage. The outcomes of this study are important for developing techniques for monitoring the impacts of feral pigs, essential for developing management options to reduce feral pig damage on agricultural lands.

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Vertebrate fauna was studied over 10 years following revegetation of a Eucalyptus tereticornis ecosystem on former agricultural land. We compared four vegetation types: remnant forest, plantings of a mix of native tree species on cleared land, natural regeneration of partially cleared land after livestock removal, and cleared pasture land with scattered paddock trees managed for livestock production. Pasture differed significantly from remnant in both bird and nonbird fauna. Although 10 years of ecosystem restoration is relatively short term in the restoration process, in this time bird assemblages in plantings and natural regeneration had diverged significantly from pasture, but still differed significantly from remnant. After 10 years, 70 and 66% of the total vertebrate species found in remnant had been recorded in plantings and natural regeneration, respectively. Although the fauna assemblages within plantings and natural regeneration were tracking toward those of remnant, significant differences in fauna between plantings and natural regeneration indicated community development along different restoration pathways. Because natural regeneration contained more mature trees (dbh > 30 cm), native shrub species, and coarse woody debris than plantings from the beginning of the study, these features possibly encouraged different fauna to the revegetation areas from the outset. The ability of plantings and natural regeneration to transition to the remnant state will be governed by a number of factors that were significant in the analyses, including shrub cover, herbaceous biomass, tree hollows, time since fire, and landscape condition. Both active and passive restoration produced significant change from the cleared state in the short term.

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Reforestation will have important consequences for the global challenges of mitigating climate change, arresting habitat decline and ensuring food security. We examined field-scale trade-offs between carbon sequestration of tree plantings and biodiversity potential and loss of agricultural land. Extensive surveys of reforestation across temperate and tropical Australia (N = 1491 plantings) were used to determine how planting width and species mix affect carbon sequestration during early development (< 15 year). Carbon accumulation per area increased significantly with decreasing planting width and with increasing proportion of eucalypts (the predominant over-storey genus). Highest biodiversity potential was achieved through block plantings (width > 40 m) with about 25% of planted individuals being eucalypts. Carbon and biodiversity goals were balanced in mixed-species plantings by establishing narrow belts (width < 20 m) with a high proportion (>75%) of eucalypts, and in monocultures of mallee eucalypt plantings by using the widest belts (ca. 6–20 m). Impacts on agriculture were minimized by planting narrow belts (ca. 4 m) of mallee eucalypt monocultures, which had the highest carbon sequestering efficiency. A plausible scenario where only 5% of highly-cleared areas (<30% native vegetation cover remaining) of temperate Australia are reforested showed substantial mitigation potential. Total carbon sequestration after 15 years was up to 25 Mt CO2-e year−1 when carbon and biodiversity goals were balanced and 13 Mt CO2-e year−1 if block plantings of highest biodiversity potential were established. Even when reforestation was restricted to marginal agricultural land (<$2000 ha−1 land value, 28% of the land under agriculture in Australia), total mitigation potential after 15 years was 17–26 Mt CO2-e year−1 using narrow belts of mallee plantings. This work provides guidance on land use to governments and planners. We show that the multiple benefits of young tree plantings can be balanced by manipulating planting width and species choice at establishment. In highly-cleared areas, such plantings can sequester substantial biomass carbon while improving biodiversity and causing negligible loss of agricultural land.

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Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.