8 resultados para media economics

em eResearch Archive - Queensland Department of Agriculture


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Converting from an existing irrigation system is often seen as high risk by the land owner. The significant financial investment and the long period over which the investment runs is also complicated by the uncertainty associated with long term input costs (such as energy), crop production, and the continually evolving natural resource management rules and policy. Irrigation plays a pivotal part in the Burdekin sugarcane farming system. At present the use of furrow irrigation is by far the most common form due to the ease of use, relatively low operating cost and well established infrastructure currently in place. The Mulgrave Area Farmer Integrated Action (MAFIA) grower group, located near Clare in the lower Burdekin region, identified the need to learn about sustainable farming systems with a focus on the environment, social and economic implications. In early 2007, Hesp Faming established a site to investigate the use of overhead irrigation as an alternative to furrow irrigation and its integration with new farming system practices, including Green Cane Trash Blanketing (GCTB). Although significant environmental and social benefits exist, the preliminary investment analysis indicates that the Overhead Low Pressure (OHLP) irrigation system is not adding financial value to the Hesp Farming business. A combination of high capital costs and other offsetting factors resulted in the benefits not being fully realised. A different outcome is achieved if Hesp Farming is able to realise value on the water saved, with both OHLP irrigation systems displaying a positive NPV. This case study provides a framework to further investigate the economics of OHLP irrigation in sugarcane and it is anticipated that with additional data a more definitive outcome will be developed in the future.

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Reduced economic circumstances have moved management goals towards higher profit, rather than maximum sustainable yields in several Australian fisheries. The eastern king prawn is one such fishery, for which we have developed new methodology for stock dynamics, calculation of model-based and data-based reference points and management strategy evaluation. The fishery is notable for the northward movement of prawns in eastern Australian waters, from the State jurisdiction of New South Wales to that of Queensland, as they grow to spawning size, so that vessels fishing in the northern deeper waters harvest more large prawns. Bio-economic fishing data were standardized for calibrating a length-structured spatial operating model. Model simulations identified that reduced boat numbers and fishing effort could improve profitability while retaining viable fishing in each jurisdiction. Simulations also identified catch-rate levels that were effective for monitoring in simple within-year effort-control rules. However, favourable performance of catch-rate indicators was achieved only when a meaningful upper limit was placed on total allowed fishing effort. The methods and findings will allow improved measures for monitoring fisheries and inform decision makers on the uncertainty and assumptions affecting economic indicators.

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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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We developed a suitable diet for mass rearing of Cryptolestes ferrugineus (Stephens) populations under laboratory conditions. Recently, this pest has developed strong level of resistance to phosphine in Australia, and therefore, a significant amount of research has been directed towards its management. In total, nineteen grain-based diets, containing rolled oats, various combinations of cracked grains and flours of wheat, sorghum, maize and barley were tested. Each diet contained a small proportion of wheat germ (4.5% w/w) and torula yeast (0.5% w/w). Experiments were conducted at fixed temperature and relative humidity regimes of 30 ± 2 °C and 70 ± 2%, respectively, and replicated three times. Adults (n = 40) of a laboratory strain of C. ferrugineus were introduced into each diet, removed after 14 days and total numbers of live adult progeny were recorded. The following diets resulted in highest live progeny production: barley flour (95%) (607.67 ± 11.21) = rolled oats (75%) + cracked sorghum (20%) (597.33 ± 33.79) ≥ wheat flour (47.5%) + barley flour (47.5%) (496.67 ± 52.93) > cracked sorghum (95%) (384.00 ± 60.66). The performance of these four diets was then tested with field-collected populations of C. ferrugineus and Cryptolestes pusillus (Schonherr). The diets based on rolled oats + cracked sorghum, wheat flour + barley flour, and barley flour alone consistently produced highest progeny numbers in field-collected populations of both species, with mean progeny numbers ranging from 359.9 to 478.5. The multiplication of C. pusillus was significantly higher than C. ferrugineus on all four diets. Our findings will help in mass rearing of healthy cultures of C. ferrugineus and C. pusillus that will greatly facilitate laboratory and field research and in particular, in developing management tactics for these species.

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Options for the integrated management of white blister (caused by Albugo candida) of Brassica crops include the use of well timed overhead irrigation, resistant cultivars, programs of weekly fungicide sprays or strategic fungicide applications based on the disease risk prediction model, Brassica(spot)(TM). Initial systematic surveys of radish producers near Melbourne, Victoria, indicated that crops irrigated overhead in the morning (0800-1200 h) had a lower incidence of white blister than those irrigated overhead in the evening (2000-2400 h). A field trial was conducted from July to November 2008 on a broccoli crop located west of Melbourne to determine the efficacy and economics of different practices used for white blister control, modifying irrigation timing, growing a resistant cultivar and timing spray applications based on Brassica(spot)(TM). Growing the resistant cultivar, 'Tyson', instead of the susceptible cultivar, 'Ironman', reduced disease incidence on broccoli heads by 99 %. Overhead irrigation at 0400 h instead of 2000 h reduced disease incidence by 58 %. A weekly spray program or a spray regime based on either of two versions of the Brassica(spot)(TM) model provided similar disease control and reduced disease incidence by 72 to 83 %. However, use of the Brassica(spot)(TM) models greatly reduced the number of sprays required for control from 14 to one or two. An economic analysis showed that growing the more resistant cultivar increased farm profit per ha by 12 %, choosing morning irrigation by 3 % and using the disease risk predictive models compared with weekly sprays by 15 %. The disease risk predictive models were 4 % more profitable than the unsprayed control.

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There is an increasing requirement for more astute land resource management through efficiencies in agricultural inputs in a sugar cane production system. A precision agriculture (PA) approach can provide a pathway for a sustainable sugarcane production system. One of the impediments to the adoption of PA practices is access to paddock-scale mapping layers displaying variability in soil properties, crop growth and surface drainage. Variable rate application (VRA) of nutrients is an important component of PA. However, agronomic expertise within PA systems has fallen well behind significant advances in PA technologies. Generally, advisers in the sugar industry have a poor comprehension of the complex interaction of variables that contribute to within-paddock variations in crop growth. This is regarded as a significant impediment to the progression of PA in sugarcane and is one of the reasons for the poor adoption of VRA of nutrients in a PA approach to improved sugar cane production. This project therefore has established a number of key objectives which will contribute to the adoption of PA and the staged progression of VRA supported by relevant and practical agronomic expertise. These objectives include provision of base soils attribute mapping that can be determined using Veris 3100 Electrical Conductivity (EC) and digital elevation datasets using GPS mapping technology for a large sector of the central cane growing region using analysis of archived satellite imagery to determine the location and stability of yield patterns over time and in varying seasonal conditions on selected project study sites. They also include the stablishment of experiments to determine appropriate VRA nitrogen rates on various soil types subjected to extended anaerobic conditions, and the establishment of trials to determine nitrogen rates applicable to a declining yield potential associated with the aging of ratoons in the crop cycle. Preliminary analysis of archived yield estimation data indicates that yield patterns remain relatively stable overtime. Results also indicate the where there is considerable variability in EC values there is also significant variation in yield.