68 resultados para production systems


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Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.

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To work with a major industry production/marketing unit to develop new pineapple varieties with good plant vigour, high yields and post-harvest attributes and eating quality equal to or better than the standard industry varieties 73-50 and MD2 under commercial production systems. The project uses previously developed germplasm as parental material.

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Developing a National Banana Plant Protection Program four key strategic areas have been identified which each address a number of key strategic objectives. Taken together they address the key strategic objectives as outlined in the strategic plan. The four key strategic areas of the Plant Protection Program are: 1. Resistant Varieties and Consumer Choice; 2. Safeguarding Production and Markets; 3. Sustainable Production Systems; 4. Building Science and Communication.

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Executive summary. In this report we analyse implementation costs and benefits for agricultural management practices, grouped into farming systems. In order to do so, we compare plot scale gross margins for the dominant agricultural production systems (sugarcane, grazing and banana cultivation) in the NRM regions Wet Tropics, Burdekin Dry Tropics and Mackay Whitsundays. Furthermore, where available, we present investment requirements for changing to improved farming systems. It must be noted that transaction costs are not captured within this project. For sugarcane, this economic analysis shows that there are expected benefits to sugarcane growers in the different regions through transitions to C and B class farming systems. Further transition to A-class farming systems can come at a cost, depending on the capital investment required and the length of the investment period. Obviously, the costs and benefits will vary for each individual grower and will depend on their starting point and individual property scenario therefore each circumstance needs to be carefully considered before making a change in management practice. In grazing, overall, reducing stocking rates comes at a cost (reduced benefits). However, when operating at low utilisation rates in wetter country, lowering stocking rates can potentially come at a benefit. With win-win potential, extension is preferred to assist farmer in changing management practices to improve their land condition. When reducing stocking rates comes at a cost, incentives may be applicable to support change among farmers. For banana cultivation, the results indicate that the transition to C and B class management practices is a worthwhile proposition from an economic perspective. For a change from B to A class farming systems however, it is not worthwhile from a financial perspective. This is largely due to the large capital investment associated with the change in irrigation system and negative impact in whole of farm gross margin. Overall, benefits will vary for each individual grower depending on their starting point and their individual property scenario. The results presented in this report are one possible set of figures to show the changes in profitability of a grower operating in different management classes. The results in this report are not prescriptive of every landholder. Landholders will have different costs and benefits from transitioning to improved practices, even if similar operations are practiced, hence it is recommended that landholders that are willing to change management undertake their own research and analysis into the expected costs and benefits for their own soil types and property circumstances.

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This report details the results of research into organic production of prawns in Australia. This has involved activities and experiments over two years at several sites and using a multidisciplinary approach. This includes farm trials at an inland demonstration prawn farm which solely utilises saline bore water, sample collection from two commercial prawn farms in coastal regions of south-eastern Queensland, replicated feed trials at one of DPI&F’s aquaculture research stations, specified feed manufacture at the laboratories of University of Queensland, and packaging and product storage trials and food analyses at two of DPI&F’s food technology laboratories. This work was designed to investigate and assist in the possible adoption of organic procedures by the Australian prawn farming industry. The import from Asia of cheaply produced prawns has forced all Australian prawn farmers to review their marketing procedures. Additionally investors are becoming increasingly concerned at the prospects for the expansion of this industry in Australia. Since the competition of seafood products in the marketplace is increasing on a global basis, alternate products are being investigated by those wishing to maintain and/or grow their market share. The premium paid for organic food products would hopefully provide an economic incentive for farmers to convert to organic production systems, with an added advantage that the standards that apply have beneficial implications also for the social and environmental practices of industry.

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Age at puberty is an important component of reproductive performance in beef cattle production systems. Brahman cattle are typically late-pubertal relative to Bos taurus cattle and so it is of economic relevance to select for early age at puberty. To assist selection and elucidate the genes underlying puberty, we performed a genome-wide association study (GWAS) using the BovineSNP50 chip (similar to 54 000 polymorphisms) in Brahman bulls (n = 1105) and heifers (n = 843) and where the heifers were previously analysed in a different study. In a new attempt to generate unbiased estimates of single-nucleotide polymorphism (SNP) effects and proportion of variance explained by each SNP, the available data were halved on the basis of year and month of birth into a calibration and validation set. The traits that defined age at puberty were, in heifers, the age at which the first corpus luteum was detected (AGECL, h(2) = 0.56 +/- 0.11) and in bulls, the age at a scrotal circumference of 26 cm (AGE26, h(2) = 0.78 +/- 0.10). At puberty, heifers were on average older (751 +/- 142 days) than bulls (555 +/- 101 days), but AGECL and AGE26 were genetically correlated (r = 0.20 +/- 0.10). There were 134 SNPs associated with AGECL and 146 SNPs associated with AGE26 (P < 0.0001). From these SNPs, 32 (similar to 22%) were associated (P < 0.0001) with both traits. These top 32 SNPs were all located on Chromosome BTA 14, between 21.95 Mb and 28.4 Mb. These results suggest that the genes located in that region of BTA 14 play a role in pubertal development in Brahman cattle. There are many annotated genes underlying this region of BTA 14 and these are the subject of current research. Further, we identified a region on Chromosome X where markers were associated (P < 1.00E-8) with AGE26, but not with AGECL. Information about specific genes and markers add value to our understanding of puberty and potentially contribute to genomic selection. Therefore, identifying these genes contributing to genetic variation in AGECL and AGE26 can assist with the selection for early onset of puberty.

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The availability and quality of irrigation water has become an issue limiting productivity in many Australian vegetable regions. Production is also under competitive pressure from supply chain forces. Producers look to new technologies, including changing irrigation infrastructure, exploring new water sources, and more complex irrigation management, to survive these stresses. Often there is little objective information investigating which improvements could improve outcomes for vegetable producers, and external communities (e.g. meeting NRM targets). This has led to investment in inappropriate technologies, and costly repetition of errors, as business independently discover the worth of technologies by personal experience. In our project, we investigated technology improvements for vegetable irrigation. Through engagement with industry and other researchers, we identified technologies most applicable to growers, particularly those that addressed priority issues. We developed analytical tools for ‘what if’ scenario testing of technologies. We conducted nine detailed experiments in the Lockyer Valley and Riverina vegetable growing districts, as well as case studies on grower properties in southern Queensland. We investigated root zone monitoring tools (FullStop™ wetting front detectors and Soil Solution Extraction Tubes - SSET), drip system layout, fertigation equipment, and altering planting arrangements. Our project team developed and validated models for broccoli, sweet corn, green beans and lettuce, and spreadsheets for evaluating economic risks associated with new technologies. We presented project outcomes at over 100 extension events, including irrigation showcases, conferences, field days, farm walks and workshops. The FullStops™ were excellent for monitoring root zone conditions (EC, nitrate levels), and managing irrigation with poor quality water. They were easier to interpret than the SSET. The SSET were simpler to install, but required wet soil to be reliable. SSET were an option for monitoring deeper soil zones, unsuitable for FullStop™ installations. Because these root zone tools require expertise, and are labour intensive, we recommend they be used to address specific problems, or as a periodic auditing strategy, not for routine monitoring. In our research, we routinely found high residual N in horticultural soils, with subsequently little crop yield response to additional nitrogen fertiliser. With improved irrigation efficiency (and less leaching), it may be timely to re-examine nitrogen budgets and recommendations for vegetable crops. Where the drip irrigation tube was located close to the crop row (i.e. within 5-8 cm), management of irrigation was easier. It improved nitrogen uptake, water use efficiency, and reduced the risk of poor crop performance through moisture stress, particularly in the early crop establishment phases. Close proximity of the drip tube to the crop row gives the producer more options for managing salty water, and more flexibility in taking risks with forecast rain. In many vegetable crops, proximate drip systems may not be cost-effective. The next best alternative is to push crop rows closer to the drip tube (leading to an asymmetric row structure). The vegetable crop models are good at predicting crop phenology (development stages, time to harvest), input use (water, fertiliser), environmental impacts (nutrient, salt movement) and total yields. The two immediate applications for the models are understanding/predicting/manipulating harvest dates and nitrogen movements in vegetable cropping systems. From the economic tools, the major influences on accumulated profit are price and yield. In doing ‘what if’ analyses, it is very important to be as accurate as possible in ascertaining what the assumed yield and price ranges are. In most vegetable production systems, lowering the required inputs (e.g. irrigation requirement, fertiliser requirement) is unlikely to have a major influence on accumulated profit. However, if a resource is constraining (e.g. available irrigation water), it is usually most profitable to maximise return per unit of that resource.

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Development of new agricultural industries in northern Australia is seen as a way to provide food security in the face of reduced water availability in existing regions in the south. This report aims to identify some of the possible economic consequences of developing a rice industry in the Burdekin region, while there is a reduction of output in the Riverina. Annual rice production in the Riverina peaked at 1.7 M tonnes, but the long-term outlook, given climate change impacts on that region and government water buy-backs, is more likely to be less than 800,000 tonnes. Growers are highly efficient water users by international standards, but the ability to offset an anticipated reduction in water availability through further efficiency gains is limited. In recent years growers in the Riverina have diversified their farms to a greater extent and secondary production systems include beef, sheep and wheat. Production in north Queensland is in its infancy, but a potentially suitable farming system has been developed by including rice within the sugarcane system without competition and in fact contributing to the production of sugar by increasing yields and controlling weeds. The economic outcomes are estimated a large scale, dynamic, computable general equilibrium (CGE) model of the world economy (Tasman Global), scaled down to regional level. CGE models mimic the workings of the economy through a system of interdependent behavioural and accounting equations which are linked to an input-output database. When an economic shock or change is applied to a model, each of the markets adjusts according to the set of behavioural parameters which are underpinned by economic theory. In this study the model is driven by reducing production in the Riverina in accordance with relationships found between water availability and the production of rice and replacement by other crops and by increasing ride production in the Burdekin. Three scenarios were considered: • Scenario 1: Rice is grown using the fallow period between the last ratoon crop of sugarcane and the new planting. In this scenario there is no competition between rice and sugarcane • Scenario 2: Rice displaces sugarcane production • Scenario 3: Rice is grown on additional land and does not compete with sugarcane. Two time periods were used, 2030 and 2070, which are the conventional time points to consider climate change impacts. Under scenario 1, real economic output declines in the Riverina by $45 million in 2030 and by $139 million in 2070. This is only partially offset by the increased real economic output in the Burdekin of $35 million and $131 million respectively.

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Research into the genetics of whole herd profitability has been a focus of the Beef Cooperative Research Centre for Beef Genetic Technologies over the past decade and it has been identified that measures of male reproduction may offer a potential indirect means of selecting for improved female reproduction. This paper describes the experimental design and provides a descriptive analysis of an array of male traits in Brahman and Tropical Composite genotypes managed under the medium to high stress, semi-extensive to extensive production systems of northern Australia. A total of 1639 Brahman and 2424 Tropical Composite bulls with known pedigrees, bred and raised in northern Australia, were evaluated for a comprehensive range of productive and reproductive traits. These included blood hormonal traits (luteinising hormone, inhibin and insulin-like growth factor-I); growth and carcass traits (liveweight, body condition score, ultrasound scanned 12-13th rib fat, rump P8 fat, eye muscle area and hip height); adaptation traits (flight time and rectal temperature); and a bull breeding soundness evaluation (leg and hoof conformation, sheath score, length of everted prepuce, penile anatomy, scrotal circumference, semen mass activity, sperm motility and sperm morphology). Large phenotypic variation was evident for most traits, with complete overlap between genotypes, indicating that there is likely to be a significant opportunity to improve bull fertility traits through management and bull selection.

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Peanut (Arachis hypogaea L.) is an economically important legume crop in irrigated production areas of northern Australia. Although the potential pod yield of the crop in these areas is about 8 t ha(-1), most growers generally obtain around 5 t ha(-1), partly due to poor irrigation management. Better information and tools that are easy to use, accurate, and cost-effective are therefore needed to help local peanut growers improve irrigation management. This paper introduces a new web-based decision support system called AQUAMAN that was developed to assist Australian peanut growers schedule irrigations. It simulates the timing and depth of future irrigations by combining procedures from the food and agriculture organization (FAO) guidelines for irrigation scheduling (FAO-56) with those of the agricultural production systems simulator (APSIM) modeling framework. Here, we present a description of AQUAMAN and results of a series of activities (i.e., extension activities, case studies, and a survey) that were conducted to assess its level of acceptance among Australian peanut growers, obtain feedback for future improvements, and evaluate its performance. Application of the tool for scheduling irrigations of commercial peanut farms since its release in 2004-2005 has shown good acceptance by local peanuts growers and potential for significantly improving yield. Limited comparison with the farmer practice of matching the pan evaporation demand during rain-free periods in 2006-2007 and 2008-2009 suggested that AQUAMAN enabled irrigation water savings of up to 50% and the realization of enhanced water and irrigation use efficiencies.

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During the post-rainy (rabi) season in India around 3 million tonnes of sorghum grain is produced from 5.7 million ha of cropping. This underpins the livelihood of about 5 million households. Severe drought is common as the crop grown in these areas relies largely on soil moisture stored during the preceding rainy season. Improvement of rabi sorghum cultivars through breeding has been slow but could be accelerated if drought scenarios in the production regions were better understood. The sorghum crop model within the APSIM (Agricultural Production Systems sIMulator) platform was used to simulate crop growth and yield and the pattern of crop water status through each season using available historical weather data. The current model reproduced credibly the observed yield variation across the production region (R2=0.73). The simulated trajectories of drought stress through each crop season were clustered into five different drought stress patterns. A majority of trajectories indicated terminal drought (43%) with various timings of onset during the crop cycle. The most severe droughts (25% of seasons) were when stress began before flowering and resulted in failure of grain production in most cases, although biomass production was not affected so severely. The frequencies of drought stress types were analyzed for selected locations throughout the rabi tract and showed different zones had different predominating stress patterns. This knowledge can help better focus the search for adaptive traits and management practices to specific stress situations and thus accelerate improvement of rabi sorghum via targeted specific adaptation. The case study presented here is applicable to other sorghum growing environments. © 2012 Elsevier B.V.

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Reproduction records from 2137 cows first mated at 2 years of age and recorded through to 8.5 years of age were used to study the genetics of early and lifetime reproductive performance from two genotypes (1020 Brahman and 1117 Tropical Composite) in tropical Australian production systems. Regular ultrasound scanning of the reproductive tract, coupled with full recording of mating, calving and weaning histories, allowed a comprehensive evaluation of a range of reproductive traits. Results showed components traits of early reproductive performance had moderate to high heritabilities, especially in Brahmans. The heritability of lactation anoestrous interval in 3-year-old cows was 0.51 +/- 0.18 and 0.26 +/- 0.11 for Brahman and Tropical Composite, respectively. Heritabilities of binary reproductive output traits (conception rate, pregnancy rate, calving rate and weaning rate) from first and second matings were generally moderate to high on the underlying scale. Estimates ranged from 0.15 to 0.69 in Brahman and 0.15 to 0.34 in Tropical Composite, but were considerably lower when expressed on the observed scale, particularly for those traits with high mean levels. Heritabilities of lifetime reproduction traits were low, with estimates of 0.11 +/- 0.06 and 0.07 +/- 0.06 for lifetime annual weaning rate in Brahman and Tropical Composite, respectively. Significant differences in mean reproductive performance were observed between the two genotypes, especially for traits associated with anoestrus in first-lactation cows. Genetic correlations between early-in-life reproductive measures and lifetime reproduction traits were moderate to high. Genetic correlations between lactation anoestrous interval and lifetime annual weaning rate were -0.62 +/- 0.24 in Brahman and -0.87 +/- 0.32 in Tropical Composite. The results emphasise the substantial opportunity that exists to genetically improve weaning rates in tropical beef cattle breeds by focusing recording and selection on early-in-life female reproduction traits, particularly in Brahman for traits associated with lactation anoestrus.

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Farming systems frameworks such as the Agricultural Production Systems simulator (APSIM) represent fluxes through the soil, plant and atmosphere of the system well, but do not generally consider the biotic constraints that function within the system. We designed a method that allowed population models built in DYMEX to interact with APSIM. The simulator engine component of the DYMEX population-modelling platform was wrapped within an APSIM module allowing it to get and set variable values in other APSIM models running in the simulation. A rust model developed in DYMEX is used to demonstrate how the developing rust population reduces the crop's green leaf area. The success of the linking process is seen in the interaction of the two models and how changes in rust population on the crop's leaves feedback to the APSIM crop modifying the growth and development of the crop's leaf area. This linking of population models to simulate pest populations and biophysical models to simulate crop growth and development increases the complexity of the simulation, but provides a tool to investigate biotic constraints within farming systems and further moves APSIM towards being an agro-ecological framework.

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Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here we consider how changes in climate and atmospheric carbon dioxide (CO2) concentrations will affect drought ET frequencies in sorghum and wheat systems of Northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat. This article is protected by copyright. All rights reserved.

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In this study, we investigated the extent and physiological bases of yield variation due to row spacing and plant density configuration in the mungbean Vigna radiata (L.) Wilczek variety “Crystal” grown in different subtropical environments. Field trials were conducted in six production environments; one rain-fed and one irrigated trial each at Biloela and Emerald, and one rain-fed trial each at Hermitage and Kingaroy sites in Queensland, Australia. In each trial, six combinations of spatial arrangement of plants, achieved through two inter-row spacings of 1 m or 0.9 m (wide row), 0.5 m or 0.3 m (narrow row), with three plant densities, 20, 30 and 40 plants/m2, were compared. The narrow row spacing resulted in 22% higher shoot dry matter and 14% more yield compared to the wide rows. The yield advantage of narrow rows ranged from 10% to 36% in the two irrigated and three rain-fed trials. However, yield loss of up to 10% was also recorded from narrow rows at Emerald where the crop suffered severe drought. Neither the effects of plant density, nor the interaction between plant density and row spacing, however, were significant in any trial. The yield advantage of narrow rows was related to 22% more intercepted radiation. In addition, simulations by the Agricultural Production Systems Simulator model, using site-specific agronomy, soil and weather information, suggested that narrow rows had proportionately greater use of soil water through transpiration, compared to evaporation resulting in higher yield per mm of soil water. The long-term simulation of yield probabilities over 123 years for the two row configurations showed that the mungbean crop planted in narrow rows could produce up to 30% higher grain yield compared to wide rows in 95% of the seasons.