68 resultados para production systems


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Abstract The paper evaluates the effect of future climate change (as per the CSIRO Mk3.5 A1FI future climate projection) on cotton yield in Southern Queensland and Northern NSW, eastern Australia by using of the biophysical simulation model APSIM (Agricultural Production Systems sIMulator). The simulations of cotton production show that changes in the influential meteorological parameters caused by climate change would lead to decreased future cotton yields without the effect of CO2 fertilisation. By 2050 the yields would decrease by 17 %. Including the effects of CO2 fertilisation ameliorates the effect of decreased water availability and yields increase by 5.9 % by 2030, but then decrease by 3.6 % in 2050. Importantly, it was necessary to increase irrigation amounts by almost 50 % to maintain adequate soil moisture levels. The effect of CO2 was found to have an important positive impact of the yield in spite of deleterious climate change. This implies that the physiological response of plants to climate change needs to be thoroughly understood to avoid making erroneous projections of yield and potentially stifling investment or increasing risk.

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SummaryThis scoping study assesses the contribution that woody biomass could make to feedstock supply for an aviation biofuel industry in Queensland. The inland 600?900 mm rainfall zone, including the Fitzroy Basin region, is identified as an area that is particularly worthy of closer study as it has potential for supply of woody biomass from existing native regrowth (brigalow and other species) as well as from new plantings. New analyses carried out for this study of Corymbia citriodora subsp. variegata trials suggest biomass plantings could produce harvestable yield of aboveground dry mass of about 85 t ha?1 over a 10-year rotation at relatively low-rainfall (600?750 mm mean annual precipitation) sites and about 115 t ha?1 at medium-rainfall (750?900 mm) sites. Estimates of productivity for native regrowth suggest potential productivity should be around 40 t ha?1 during the initial decade after clearing when systems are managed for bioenergy rather than grazing. In this paper, potential production systems are described, and sustainability issues are briefly considered. It is concluded that more detailed studies focused particularly on biomass production would be worthwhile, and further research requirements are briefly discussed.

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Previous studies of greenhouse gas emissions (GHGE) from beef production systems in northern Australia have been based on models of ‘steady-state’ herd structures that do not take into account the considerable inter-annual variation in liveweight gain, reproduction and mortality rates that occurs due to seasonal conditions. Nor do they consider the implications of flexible stocking strategies designed to adapt these production systems to the highly variable climate. The aim of the present study was to quantify the variation in total GHGE (t CO2e) and GHGE intensity (t CO2e/t liveweight sold) for the beef industry in northern Australia when variability in these factors was considered. A combined GRASP–Enterprise modelling platform was used to simulate a breeding–finishing beef cattle property in the Burdekin River region of northern Queensland, using historical climate data from 1982–2011. GHGE was calculated using the method of Australian National Greenhouse Gas Inventory. Five different stocking-rate strategies were simulated with fixed stocking strategies at moderate and high rates, and three flexible stocking strategies where the stocking rate was adjusted annually by up to 5%, 10% or 20%, according to pasture available at the end of the growing season. Variation in total annual GHGE was lowest in the ‘fixed moderate’ (~9.5 ha/adult equivalent (AE)) stocking strategy, ranging from 3799 to 4471 t CO2e, and highest in the ‘fixed high’ strategy (~5.9 ha/AE), which ranged from 3771 to 7636 t CO2e. The ‘fixed moderate’ strategy had the least variation in GHGE intensity (15.7–19.4 t CO2e/t liveweight sold), while the ‘flexible 20’ strategy (up to 20% annual change in AE) had the largest range (10.5–40.8 t CO2e/t liveweight sold). Across the five stocking strategies, the ‘fixed moderate’ stocking-rate strategy had the highest simulated perennial grass percentage and pasture growth, highest average rate of liveweight gain (121 kg/steer), highest average branding percentage (74%) and lowest average breeding-cow mortality rate (3.9%), resulting in the lowest average GHGE intensity (16.9 t CO2e/t liveweight sold). The ‘fixed high’ stocking rate strategy (~5.9 ha/AE) performed the poorest in each of these measures, while the three flexible stocking strategies were intermediate. The ‘fixed moderate’ stocking strategy also yielded the highest average gross margin per AE carried and per hectare. These results highlight the importance of considering the influence of climate variability on stocking-rate management strategies and herd performance when estimating GHGE. The results also support a body of previous work that has recommended the adoption of moderate stocking strategies to enhance the profitability and ecological stability of beef production systems in northern Australia.

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Many rainfed wheat production systems are reliant on stored soil water for some or all of their water inputs. Selection and breeding for root traits could result in a yield benefit; however, breeding for root traits has traditionally been avoided due to the difficulty of phenotyping mature root systems, limited understanding of root system development and function, and the strong influence of environmental conditions on the phenotype of the mature root system. This paper outlines an international field selection program for beneficial root traits at maturity using soil coring in India and Australia. In the rainfed areas of India, wheat is sown at the end of the monsoon into hot soils with a quickly receding soil water profile; in season water inputs are minimal. We hypothesised that wheat selected and bred for high yield under these conditions would have deep, vigorous root systems, allowing them to access and utilise the stored soil water at depth around anthesis and grain-filling when surface layers were dry. The Indian trials resulted in 49 lines being sent to Australia for phenotyping. These lines were ranked against 41 high yielding Australian lines. Variation was observed for deep root traits e.g. in eastern Australia in 2012, maximum depth ranged from 118.8 to 146.3 cm. There was significant variation for root traits between sites and years, however, several Indian genotypes were identified that consistently ranked highly across sites and years for deep rooting traits.

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The parasitic weed Orobanche crenata inflicts major damage on faba bean, lentil, pea and other crops in Mediterranean environments. The development of methods to control O. crenata is to a large extent hampered by the complexity of host-parasite systems. Using a model of host-parasite interactions can help to explain and understand this intricacy. This paper reports on the evaluation and application of a model simulating host-parasite competition as affected by environment and management that was implemented in the framework of the Agricultural Production Systems Simulator (APSIM). Model-predicted faba bean and O. crenata growth and development were evaluated against independent data. The APSIM-Fababean and -Parasite modules displayed a good capability to reproduce effects of pedoclimatic conditions, faba bean sowing date and O. crenata infestation on host-parasite competition. The r(2) values throughout exceeded 0.84 (RMSD: 5.36 days) for phenological, 0.85 (RMSD: 223.00 g m(-2)) for host growth and 0.78 (RMSD: 99.82 g m(-2)) for parasite growth parameters. Inaccuracies of simulated faba bean root growth that caused some bias of predicted parasite number and host yield loss may be dealt with by more flexibly simulating vertical root distribution. The model was applied in simulation experiments to determine optimum sowing windows for infected and non-infected faba bean in Mediterranean environments. Simulation results proved realistic and testified to the capability of APSIM to contribute to the development of tactical approaches in parasitic weed control.

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To improve the sustainability and environmental accountability of the banana industry there is a need to develop a set of soil health indicators that integrate physical, chemical and biological soil properties. These indicators would allow banana growers, extension and research workers to improve soil health management practices. To determine changes in soil properties due to the cultivation of bananas, a paired site survey was conducted comparing soil properties under conventional banana systems to less intensively managed vegetation systems, such as pastures and forest. Measurements were made on physical, chemical and biological soil properties at seven locations in tropical and sub-tropical banana producing areas. Soil nematode community composition was used as a bioindicator of the biological properties of the soil. Soils under conventional banana production tended to have a greater soil bulk density, with less soil organic carbon (C) (both total C and labile C), greater exchangeable cations, higher extractable P, greater numbers of plant-parasitic nematodes and less nematode diversity, relative to less intensively managed plant systems. The organic banana production systems at two locations had greater labile C, relative to conventional banana systems, but there was no significant change in nematode community composition. There were significant interactions between physical, chemical and nematode community measurements in the soil, particularly with soil C measurements, confirming the need for a holistic set of indicators to aid soil management. There was no single indicator of soil health for the Australian banana industry, but a set of soil health indicators, which would allow the measurement of soil improvements should include: bulk density, soil C, pH, EC, total N, extractable P, ECEC and soil nematode community structure.

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Brassicaceae plants have the potential as part of an integrated approach to replace fumigant nematicides, providing the biofumigation response following their incorporation is not offset by reproduction of plant-parasitic nematodes on their roots. Forty-three Brassicaceae cultivars were screened in a pot trial for their ability to reduce reproduction of three root-knot nematode isolates from north Queensland, Australia: M. arenaria (NQ1), M. javanica (NQ2) and M. arenaria race 2 (NQ5/7). No cultivar was found to consistently reduce nematode reproduction relative to forage sorghum, the current industry standard, although a commercial fodder radish (Raphanus sativus) and a white mustard (Sinapis alba) line were consistently as resistant to the formation of galls as forage sorghum. A second pot trial screened five commercially available Brassicaceae cultivars, selected for their biofumigation potential, for resistance to two nematode species, M. javanica (NQ2) and M. arenaria (NQ5/7). The fodder radish cv. Weedcheck, was found to be as resistant as forage sorghum to nematode reproduction. A multivariate cluster analysis using the resistance measurements, gall index, nematode number per g of root and multiplication for two nematode species (NQ2 and NQ5/7) confirmed the similarity in resistance between the radish cultivar and forage sorghum. A field trial confirmed the resistance of the fodder radish cv. Weedcheck, with a similar reduction in the number of Meloidogyne spp. juveniles recovered from the roots 8 weeks after planting. The use of fodder radish cultivars as biofumigation crops to manage root-knot nematodes in tropical vegetable production systems deserves further investigation.

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To examine healthy slaughter-age cattle and sheep on-farm for the excretion of Salmonella serovars in faeces and to identify possible risk factors using a questionnaire. The study involved 215 herds and flocks in the four eastern states of Australia, 56 with prior history of salmonellosis. Production systems examined included pasture beef cattle, feedlot beef cattle, dairy cattle, prime lambs and mutton sheep and animals were all at slaughter age. From each herd or flock, 25 animals were sampled and the samples pooled for Salmonella culture. All Salmonella isolated were serotyped and any Salmonella Typhimurium isolates were phage typed. Questionnaires on each production system, prepared in Epi Info 6.04, were designed to identify risk factors associated with Salmonella spp excretion, with separate questionnaires designed for each production system. Salmonellae were identified in all production systems and were more commonly isolated from dairies and beef feedlots than other systems. Statistical analysis revealed that dairy cattle were significantly more likely to shed Salmonella in faeces than pasture beef cattle, mutton sheep and prime lambs (P < 0.05). A wide diversity of Salmonella serovars, all of which have been isolated from humans in Australia, was identified in both cattle and sheep. Analysis of the questionnaires showed access to new arrivals was a significant risk factor for Salmonella excretion on dairy properties. For beef feedlots, the presence of large numbers of flies in the feedlot pens or around stored manure were significant risk factors for Salmonella excretion. Dairy cattle pose the highest risk of all the slaughter-age animals tested. Some of the identified risk factors can be overcome by improved management practices, especially in relation to hygiene.

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Dairy farms in subtropical Australia use irrigated, annually sown short-term ryegrass (Lolium multiflorum) or mixtures of short-term ryegrass and white (Trifolium repens) and Persian (shaftal) (T. resupinatum) clover during the winter-spring period in all-year-round milk production systems. A series of small plot cutting experiments was conducted in 3 dairying regions (tropical upland, north Queensland, and subtropical southeast Queensland and northern New South Wales) to determine the most effective rate and frequency of application of nitrogen (N) fertiliser. The experiments were not grazed, nor was harvested material returned to the plots, after sampling. Rates up to 100 kg N/ha.month (as urea or calcium ammonium nitrate) and up to 200 kg N/ha every 2 months (as urea) were applied to pure stands of ryegrass in 1991. In 1993 and 1994, urea, at rates up to 150 kg N/ha.month and to 200 kg N/ha every 2 months, was applied to pure stands of ryegrass; urea, at rates up to 50 kg N/ha.month, was also applied to ryegrass-clover mixtures. The results indicate that applications of 50-85 kg N/ha.month can be recommended for short-term ryegrass pastures throughout the subtropics and tropical uplands of eastern Australia, irrespective of soil type. At this rate, dry matter yields will reach about 90% of their potential, forage nitrogen concentration will be increased, there is minimal risk to stock from nitrate poisoning and there will be no substantial increase in soil N. The rate of N for ryegrass-clover pastures is slightly higher than for pure ryegrass but, at these rates, the clover component will be suppressed. However, increased ryegrass yields and higher forage nitrogen concentrations will compensate for the reduced clover component. At application rates up to 100 kg N/ha.month, build-up of NO3--N and NH4+-N in soil was generally restricted to the surface layers (0-20 cm) of the soil, but there was a substantial increase throughout the soil profile at 150 kg N/ha.month. The build-up of NO3--N and NH4+-N was greater and was found at lower rates on the lighter soil compared with heavy clays. Generally, most of the soil N was in the NO3--N form and most was in the top 20 cm.

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Measurement or accurate simulation of soil temperature is important for improved understanding and management of peanuts (Arachis hypogaea L.), due to their geocarpic habit. A module of the Agricultural Production Systems Simulator Model (APSIM), APSIM-soiltemp, which uses input of ambient temperature, rainfall and solar radiation in conjunction with other APSIM modules, was evaluated for its ability to simulate surface 5 cm soil temperature in 35 peanut on-farm trials conducted between 2001 and 2005 in the Burnett region (25°36'S to 26°41'S, 151°39'E to 151°53'E). Soil temperature simulated by the APSIM-soiltemp module, from 30 days after sowing until maturity, closely matched the measured values (R2 ≥ 0.80)in the first three seasons (2001-04). However, a slightly poorer relationship (R2 = 0.55) between the observed and the simulated temperatures was observed in 2004-05, when the crop was severely water stressed. Nevertheless, over all the four seasons, which were characterised by a range of ambient temperature, leaf area index, radiation and soil water, each of which was found to have significant effects on soil temperature, a close 1:1 relationship (R2 = 0.85) between measured and simulated soil temperatures was observed. Therefore, the pod zone soil temperature simulated by the module can be generally relied on in place of measured input of soil temperature in APSIM applications, such as quantifying climatic risk of aflatoxin accumulation.

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Grazing is a major land use in Australia's rangelands. The 'safe' livestock carrying capacity (LCC) required to maintain resource condition is strongly dependent on climate. We reviewed: the approaches for quantifying LCC; current trends in climate and their effect on components of the grazing system; implications of the 'best estimates' of climate change projections for LCC; the agreement and disagreement between the current trends and projections; and the adequacy of current models of forage production in simulating the impact of climate change. We report the results of a sensitivity study of climate change impacts on forage production across the rangelands, and we discuss the more general issues facing grazing enterprises associated with climate change, such as 'known uncertainties' and adaptation responses (e.g. use of climate risk assessment). We found that the method of quantifying LCC from a combination of estimates (simulations) of long-term (>30 years) forage production and successful grazier experience has been well tested across northern Australian rangelands with different climatic regions. This methodology provides a sound base for the assessment of climate change impacts, even though there are many identified gaps in knowledge. The evaluation of current trends indicated substantial differences in the trends of annual rainfall (and simulated forage production) across Australian rangelands with general increases in most of western Australian rangelands ( including northern regions of the Northern Territory) and decreases in eastern Australian rangelands and south-western Western Australia. Some of the projected changes in rainfall and temperature appear small compared with year-to-year variability. Nevertheless, the impacts on rangeland production systems are expected to be important in terms of required managerial and enterprise adaptations. Some important aspects of climate systems science remain unresolved, and we suggest that a risk-averse approach to rangeland management, based on the 'best estimate' projections, in combination with appropriate responses to short-term (1-5 years) climate variability, would reduce the risk of resource degradation. Climate change projections - including changes in rainfall, temperature, carbon dioxide and other climatic variables - if realised, are likely to affect forage and animal production, and ecosystem functioning. The major known uncertainties in quantifying climate change impacts are: (i) carbon dioxide effects on forage production, quality, nutrient cycling and competition between life forms (e.g. grass, shrubs and trees); and (ii) the future role of woody plants including effects of. re, climatic extremes and management for carbon storage. In a simple example of simulating climate change impacts on forage production, we found that increased temperature (3 degrees C) was likely to result in a decrease in forage production for most rangeland locations (e. g. -21% calculated as an unweighted average across 90 locations). The increase in temperature exacerbated or reduced the effects of a 10% decrease/increase in rainfall respectively (-33% or -9%). Estimates of the beneficial effects of increased CO2 (from 350 to 650 ppm) on forage production and water use efficiency indicated enhanced forage production (+26%). The increase was approximately equivalent to the decline in forage production associated with a 3 degrees C temperature increase. The large magnitude of these opposing effects emphasised the importance of the uncertainties in quantifying the impacts of these components of climate change. We anticipate decreases in LCC given that the 'best estimate' of climate change across the rangelands is for a decline (or little change) in rainfall and an increase in temperature. As a consequence, we suggest that public policy have regard for: the implications for livestock enterprises, regional communities, potential resource damage, animal welfare and human distress. However, the capability to quantify these warnings is yet to be developed and this important task remains as a challenge for rangeland and climate systems science.

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Bemisia tabaci, biotype B, commonly known as the silverleaf whitefly (SLW) is an alien species that invaded Australia in the mid-90s. This paper reports on the invasion ecology of SLW and the factors that are likely to have contributed to the first outbreak of this major pest in an Australian cotton cropping system, population dynamics of SLW within whitefly-susceptible crop (cotton and cucurbit) and non-crop vegetation (sowthistle, Sonchus spp.) components of the cropping system were investigated over four consecutive growing seasons (September-June) 2001/02-2004/05 in the Emerald Irrigation Area (EIA) of Queensland, Australia. Based on fixed geo-referenced sampling sites, variation in spatial and temporal abundance of SLW within each system component was quantified to provide baseline data for the development of ecologically sustainable pest management strategies. Parasitism of large (3rd and 4th instars) SLW nymphs by native aphelinid wasps was quantified to determine the potential for natural control of SLW populations. Following the initial outbreak in 2001/02, SLW abundance declined and stabilised over the next three seasons. The population dynamics of SLW is characterised by inter-seasonal population cycling between the non-crop (weed) and cotton components of the EIA cropping system. Cotton was the largest sink for and source of SLW during the study period. Over-wintering populations dispersed from weed host plant sources to cotton in spring followed by a reverse dispersal in late summer and autumn to broad-leaved crops and weeds. A basic spatial source-sink analysis showed that SLW adult and nymph densities were higher in cotton fields that were closer to over-wintering weed sources throughout spring than in fields that were further away. Cucurbit fields were not significant sources of SLW and did not appear to contribute significantly to the regional population dynamics of the pest. Substantial parasitism of nymphal stages throughout the study period indicates that native parasitoid species and other natural enemies are important sources of SLW mortality in Australian cotton production systems. Weather conditions and use of broad-spectrum insecticides for pest control are implicated in the initial outbreak and on-going pest status of SLW in the region.

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Because of the variable and changing environment, advisors and farmers are seeking systems that provide risk management support at a number of time scales. The Agricultural Production Systems Research Unit, Toowoomba, Australia has developed a suite of tools to assist advisors and farmers to better manage risk in cropping. These tools range from simple rainfall analysis tools (Rainman, HowWet, HowOften) through crop simulation tools (WhopperCropper and YieldProphet) to the most complex, APSFarm, a whole-farm analysis tool. Most are derivatives of the APSIM crop model. These tools encompass a range of complexity and potential benefit to both the farming community and for government policy. This paper describes, the development and usage of two specific products; WhopperCropper and APSFarm. WhopperCropper facilitates simulation-aided discussion of growers' exposure to risk when comparing alternative crop input options. The user can readily generate 'what-if' scenarios that separate the major influences whilst holding other factors constant. Interactions of the major inputs can also be tested. A manager can examine the effects of input levels (and Southern Oscillation Index phase) to broadly determine input levels that match their attitude to risk. APSFarm has been used to demonstrate that management changes can have different effects in short and long time periods. It can be used to test local advisors and farmers' knowledge and experience of their desired rotation system. This study has shown that crop type has a larger influence than more conservative minimum soil water triggers in the long term. However, in short term dry periods, minimum soil water triggers and maximum area of the various crops can give significant financial gains.

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When exposed to hot (22-35 degrees C) and dry climatic conditions in the field during the final 4-6 weeks of pod filling, peanuts (Arachis hypogaea L.) can accumulate highly carcinogenic and immuno-suppressing aflatoxins. Forecasting of the risk posed by these conditions can assist in minimizing pre-harvest contamination. A model was therefore developed as part of the Agricultural Production Systems Simulator (APSIM) peanut module, which calculated an aflatoxin risk index (ARI) using four temperature response functions when fractional available soil water was <0.20 and the crop was in the last 0.40 of the pod-filling phase. ARI explained 0.95 (P <= 0.05) of the variation in aflatoxin contamination, which varied from 0 to c. 800 mu g/kg in 17 large-scale sowings in tropical and four sowings in sub-tropical environments carried out in Australia between 13 November and 16 December 2007. ARI also explained 0.96 (P <= 0.01) of the variation in the proportion of aflatoxin-contaminated loads (>15 mu g/kg) of peanuts in the Kingaroy region of Australia during the period between the 1998/99 and 2007/08 seasons. Simulation of ARI using historical climatic data from 1890 to 2007 indicated a three-fold increase in its value since 1980 compared to the entire previous period. The increase was associated with increases in ambient temperature and decreases in rainfall. To facilitate routine monitoring of aflatoxin risk by growers in near real time, a web interface of the model was also developed. The ARI predicted using this interface for eight growers correlated significantly with the level of contamination in crops (r=095, P <= 0.01). These results suggest that ARI simulated by the model is a reliable indicator of aflatoxin contamination that can be used in aflatoxin research as well as a decision-support tool to monitor pre-harvest aflatoxin risk in peanuts.

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Global trends in human population and agriculture dictate that future calls made on the resources (physical, human, financial) and systems involved in producing food will be increasingly more demanding and complex. Both plant breeding and improved agronomy lift the potential yield of crops, a key component in progressing farm yield, so society can reasonably expect both agronomy as a science and agronomists as practitioners to contribute to the successful delivery of necessary change. By reflecting on current trends in agricultural production (diversification, intensification, integration, industrialisation, automation) and deconstructing a futuristic scenario of attempting agricultural production on Mars, it seems the skills agronomists will require involve not only the mandatory elements of their discipline but also additional skills that enable engagement with, even leadership of, teams who integrate (in sum or part) engineering, (agri-)business, economics and operational management, and build the social capital required to create and maintain a diverse array of enhanced and new ethical production systems and achieve increasing efficiencies within them.