9 resultados para Birch.

em eResearch Archive - Queensland Department of Agriculture


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Reliability of supply of feed grain has become a high priority issue for industry in the northern region. Expansion by major intensive livestock and industrial users of grain, combined with high inter-annual variability in seasonal conditions, has generated concern in the industry about reliability of supply. This paper reports on a modelling study undertaken to analyse the reliability of supply of feed grain in the northern region. Feed grain demand was calculated for major industries (cattle feedlots, pigs, poultry, dairy) based on their current size and rate of grain usage. Current demand was estimated to be 2.8Mt. With the development of new industrial users (ethanol) and by projecting the current growth rate of the various intensive livestock industries, it was estimated that demand would grow to 3.6Mt in three years time. Feed grain supply was estimated using shire scale yield prediction models for wheat and sorghum that had been calibrated against recent ABS production data. Other crops that contribute to a lesser extent to the total feed grain pool (barley, maize) were included by considering their production relative to the major winter and summer grains, with estimates based on available production records. This modelling approach allowed simulation of a 101-year time series of yield that showed the extent of the impact of inter-annual climate variability on yield levels. Production estimates were developed from this yield time series by including planted crop area. Area planted data were obtained from ABS and ABARE records. Total production amounts were adjusted to allow for any export and end uses that were not feed grain (flour, malt etc). The median feed grain supply for an average area planted was about 3.1Mt, but this varied greatly from year to year depending on seasonal conditions and area planted. These estimates indicated that supply would not meet current demand in about 30% of years if a median area crop were planted. Two thirds of the years with a supply shortfall were El Nino years. This proportion of years was halved (i.e. 15%) if the area planted increased to that associated with the best 10% of years. Should demand grow as projected in this study, there would be few years where it could be met if a median crop area was planted. With area planted similar to the best 10% of years, there would still be a shortfall in nearly 50% of all years (and 80% of El Nino years). The implications of these results on supply/demand and risk management and investment in research and development are briefly discussed.

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Prediction of the initiation, appearance and emergence of leaves is critically important to the success of simulation models of crop canopy development and some aspects of crop ontogeny. Data on leaf number and crop ontogeny were collected on five cultivars of maize differing widely in maturity and genetic background grown under natural and extended photoperiods, and planted on seven sowing dates from October 1993 to March 1994 at Gatton, South-east Queensland. The same temperature coefficients were established for crop ontogeny before silking, and the rates of leaf initiation, leaf tip appearance and full leaf expansion, the base, optimum and maximum temperatures for each being 8, 34 and 40 degrees C. After silking, the base temperature for ontogeny was 0 degrees C, but the optimum and maximum temperatures remained unchanged. The rates of leaf initiation, appearance of leaf tips and full leaf expansion varied in a relatively narrow range across sowing times and photoperiod treatments, with average values of 0.040 leaves (degrees Cd)-1, 0.021 leaves (degrees Cd)-1, and 0.019 leaves (degrees Cd)-1, respectively. The relationships developed in this study provided satisfactory predictions of leaf number and crop ontogeny (tassel initiation to silking, emergence to silking and silking to physiological maturity) when assessed using independent data from Gatton (South eastern Queensland), Katherine and Douglas Daly (Northern Territory), Walkamin (North Queensland) and Kununurra (Western Australia).

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In recent years, there have been significant developments in climate science relevant to agriculture and natural resource management. Assessing impacts of climate variability and use of seasonal climate forecasts have become increasingly important elements in the management "toolkit" for many Australian farmers. Consideration of climate change further increases the need for improved management strategies. While climate risk extension activities have kept pace with advances in climate science, a national review of the Vocational Education and Training system in Australia in relation to "weather and climate" showed that these topics were "poorly represented" at the management level in the Australian Qualifications Framework, and needed increased emphasis. Consequently, a new Unit of Competency concerning management of climatic risk was developed and accredited to address this deficiency. The objective of the unit was to build knowledge and skills for better management of climate variability via the elements of surveying climatic and enterprise data; analysing climatic risks and opportunities; and developing climatic risk management strategies. This paper describes establishment of a new unit for vocational education that is designed to harness recent developments in applied climate science for better management of Australia's highly variable climate. The main benefits of the new unit of competency, "Developing climatic risk management strategies,"were seen as improving decisions in climate and agriculture, and reducing climate risk exposure to enhance sustainable agriculture. The educational unit is now within the scope of agricultural colleges, universities, and registered training organisations as an accredited unit.

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Approximately 30% of plant nuclear genes appear to encode proteins targeted to the plastids or endoplasmic reticulum (ER). The signals that direct proteins into these compartments are diverse in sequence, but, on the basis of a limited number of tests in heterologous systems, they appear to be functionally conserved across species. To further test the generality of this conclusion, we tested the ability of two plastid transit peptides and an ER signal peptide to target green fluorescent protein (GFP) in 12 crops, including three monocots (barley, sugarcane, wheat) and nine dicots (Arabidopsis, broccoli, cabbage, carrot, cauliflower, lettuce, radish, tobacco, turnip). In all species, transient assays following microprojectile bombardment or vacuum infiltration using Agrobacterium showed that the plastid transit peptides from tomato DCL (defective chloroplast and leaves) and tobacco RbcS [ribulose bisphosphate carboxylase (Rubisco) small subunit] genes were effective in targeting GFP to the leaf plastids. GFP engineered as a fusion to the N-terminal ER signal peptide from Arabidopsis basic chitinase and a C-terminal HDEL signal for protein retention in the ER was accumulated in the ER of all species. The results in tobacco were confirmed in stably transformed cells. These signal sequences should be useful to direct proteins to the plastid stroma or ER lumen in diverse plant species of biotechnological interest for the accumulation of particular recombinant proteins or for the modification of particular metabolic streams.

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Two field experiments using maize (Pioneer 31H50) and three watering regimes [(i) irrigated for the whole crop cycle, until anthesis, (ii) not at all (experiment 1) and (iii) fully irrigated and rain grown for the whole crop cycle (experiment 2)] were conducted at Gatton, Australia, during the 2003-04 season. Data on crop ontogeny, leaf, sheath and internode lengths and leaf width, and senescence were collected at 1- to 3-day intervals. A glasshouse experiment during 2003 quantified the responses of leaf shape and leaf presentation to various levels of water stress. Data from experiment 1 were used to modify and parameterise an architectural model of maize (ADEL-Maize) to incorporate the impact of water stress on maize canopy characteristics. The modified model produced accurate fitted values for experiment 1 for final leaf area and plant height, but values during development for leaf area were lower than observed data. Crop duration was reasonably well fitted and differences between the fully irrigated and rain-grown crops were accurately predicted. Final representations of maize crop canopies were realistic. Possible explanations for low values of leaf area are provided. The model requires further development using data from the glasshouse study and before being validated using data from experiment 2 and other independent data. It will then be used to extend functionality in architectural models of maize. With further research and development, the model should be particularly useful in examining the response of maize production to water stress including improved prediction of total biomass and grain yield. This will facilitate improved simulation of plant growth and development processes allowing investigation of genotype by environment interactions under conditions of suboptimal water supply.

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This paper reports on the use of APSIM - Maize for retrospective analysis of performance of a high input, high yielding maize crop and analysis of predicted performance of maize grown with high inputs over the long-term (>100 years) for specified scenarios of environmental conditions (temperature and radiation) and agronomic inputs (sowing date, plant population, nitrogen fertiliser and irrigation) at Boort, Victoria, Australia. It uses a high yielding (17 400 kg/ha dry grain, 20 500 kg/ha at 15% water) commercial crop grown in 2004-05 as the basis of the study. Yield for the agronomic and environmental conditions of 2004-05 was predicted accurately, giving confidence that the model could be used for the detailed analyses undertaken. The analysis showed that the yield achieved was close to that possible with the conditions and agronomic inputs of 2004-05. Sowing dates during 21 September to 26 October had little effect on predicted yield, except when combined with reduced temperature. Single year and long-term analyses concluded that a higher plant population (11 plants/m2) is needed to optimise yield, but that slightly lower N and irrigation inputs are appropriate for the plant population used commercially (8.4 plants/m2). Also, compared with changes in agronomic inputs increases in temperature and/or radiation had relatively minor effects, except that reduced temperature reduces predicted yield substantially. This study provides an approach for the use of models for both retrospective analysis of crop performance and assessment of long-term variability of crop yield under a wide range of agronomic and environmental conditions.

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This paper reports on a purposive survey study which aimed to identify needs for the development, delivery and evaluation of applied climate education for targeted groups, to improve knowledge and skills to better manage under variable climatic conditions. The survey sample consisted of 80 producers and other industry stakeholders in Australia (including representatives from consulting, agricultural extension and agricultural education sectors), with a 58% response rate to the survey. The survey included an assessment of (i) knowledge levels of the Southern Oscillation Index and sea surface temperatures, and (ii) skill and ability in interpreting weather and climate parameters. Results showed that despite many of the respondents having more than 20 years experience in their industry, the only formal climate education or training undertaken by most was a 1-day workshop. Over 80% of the applied climate skills listed in the survey were regarded by respondents as essential or important, but only 42% of educators, 30% of consultants and 28% of producers rated themselves as competent in applying such skills. Essential skills were deemed as those that would enable respondents or their clients to be better prepared for the next extended wet or dry meteorological event, and improved capability in identifying and capitalising on key decision points from climate information and a seasonal climate outlook. The complex issue of forecast accuracy is a confounding obstacle for many in the application of climate information and forecasts in management. Addressing this problem by describing forecast 'limitations and skill' can help to overcome this problem. The survey also highlighted specific climatic tactical and strategic information collated from grazing, cropping and agribusiness enterprises, and showed the value of such information from a users perspective.

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It is essential to provide experimental evidence and reliable predictions of the effects of water stress on crop production in the drier, less predictable environments. A field experiment undertaken in southeast Queensland, Australia with three water regimes (fully irrigated, rainfed and irrigated until late canopy expansion followed by rainfed) was used to compare effects of water stress on crop production in two maize (Zea mays L.) cultivars (Pioneer 34N43 and Pioneer 31H50). Water stress affected growth and yield more in Pioneer 34N43 than in Pioneer 31H50. A crop model APSIM-Maize, after having been calibrated for the two cultivars, was used to simulate maize growth and development under water stress. The predictions on leaf area index (LAI) dynamics, biomass growth and grain yield under rain fed and irrigated followed by rain fed treatments was reasonable, indicating that stress indices used by APSIM-Maize produced appropriate adjustments to crop growth and development in response to water stress. This study shows that Pioneer 31H50 is less sensitive to water stress and thus a preferred cultivar in dryland conditions, and that it is feasible to provide sound predictions and risk assessment for crop production in drier, more variable conditions using the APSIM-Maize model.

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Crop models for herbaceous ornamental species typically include functions for temperature and photoperiod responses, but very few incorporate vernalization, which is a requirement of many traditional crops. This study investigated the development of floriculture crop models, which describe temperature responses, plus photoperiod or vernalization requirements, using Australian native ephemerals Brunonia australis and Calandrinia sp. A novel approach involved the use of a field crop modelling tool, DEVEL2. This optimization program estimates the parameters of selected functions within the development rate models using an iterative process that minimizes sum of squares residual between estimated and observed days for the phenological event. Parameter profiling and jack-knifing are included in DEVEL2 to remove bias from parameter estimates and introduce rigour into the parameter selection process. Development rate of B. australis from planting to first visible floral bud (VFB) was predicted using a multiplicative approach with a curvilinear function to describe temperature responses and a broken linear function to explain photoperiod responses. A similar model was used to describe the development rate of Calandrinia sp., except the photoperiod function was replaced with an exponential vernalization function, which explained a facultative cold requirement and included a coefficient for determining the vernalization ceiling temperature. Temperature was the main environmental factor influencing development rate for VFB to anthesis of both species and was predicted using a linear model. The phenology models for B. australis and Calandrinia sp. described development rate from planting to VFB and from VFB to anthesis in response to temperature and photoperiod or vernalization and may assist modelling efforts of other herbaceous ornamental plants. In addition to crop management, the vernalization function could be used to identify plant communities most at risk from predicted increases in temperature due to global warming.