59 resultados para lamb crop


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This is part of a GRDC funded project led by Dr Jeremy Whish of CSIRO Ecosystem Sciences. The project aims to build a root-lesion nematode module into the crop growth simulation program APSIM (Agricultural Production Systems Simulator). This will utilise existing nematode and crop data from field, glasshouse and laboratory research led by Dr John Thompson. New data will be collected to validate and extend the model.

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This project aims to develop integrated irrigation and nutrition management strategies under limited water for irrigators currently investing in overhead irrigation systems (CPLM) to minimize the learning lag in their use and optimize crop and economic performance.

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This project developed a novel approach to integrating enhanced gene mapping technologies with crop modelling to enhance the rate of improvement in sorghum yield.

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Validation of new Indian seasonal climate forecasting products. In the Indian state of Andhra Pradesh (AP) kharif crops are heavily dependent on summer monsoon rains, where the timing and intensity of the rains affects crop yield. The majority of farms in AP are small and marginal, making them very vulnerable to yield reductions. Farmers also lack access to relevant information that might enable them to respond to seasonal conditions. Enabling farmers to utilise seasonal climate forecasting would allow them to respond to seasonal variability. To do this, farmers need a forecasting system that indicates a specific management strategy for the upcoming season, and effective and timely communication of the forecast information. Current agro-meteorological advisories in AP are issued on a bi-weekly basis, and they are relevant to an agro-climatic zone scale which may not be sufficiently relevant at a village level. Also, the information in the advisories may not be necessarily packaged in way relevant to cropping decisions by farmers. The objectives of this project are to evaluate the skill of seasonal climate forecasts to be issued for the 2008 monsoon season, to assess crop management options in response to seasonal scenarios that capture the range of seasonal climatic variability, to develop and evaluate options for effective communication and adoption of climate forecasts and agricultural advisories, and to synthesise and report on options for future research investments into seasonal climate forecasting.

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A comprehensive analysis was conducted using 48 sorghum QTL studies published from 1995 to 2010 to make information from historical sorghum QTL experiments available in a form that could be more readily used by sorghum researchers and plant breeders. In total, 771 QTL relating to 161 unique traits from 44 studies were projected onto a sorghum consensus map. Confidence intervals (CI) of QTL were estimated so that valid comparisons could be made between studies. The method accounted for the number of lines used and the phenotypic variation explained by individual QTL from each study. In addition, estimated centimorgan (cM) locations were calculated for the predicted sorghum gene models identified in Phytozome (JGI GeneModels SBI v1.4) and compared with QTL distribution genome-wide, both on genetic linkage (cM) and physical (base-pair/bp) map scales. QTL and genes were distributed unevenly across the genome. Heterochromatic enrichment for QTL was observed, with approximately 22% of QTL either entirely or partially located in the heterochromatic regions. Heterochromatic gene enrichment was also observed based on their predicted cM locations on the sorghum consensus map, due to suppressed recombination in heterochromatic regions, in contrast to the euchromatic gene enrichment observed on the physical, sequence-based map. The finding of high gene density in recombination-poor regions, coupled with the association with increased QTL density, has implications for the development of more efficient breeding systems in sorghum to better exploit heterosis. The projected QTL information described, combined with the physical locations of sorghum sequence-based markers and predicted gene models, provides sorghum researchers with a useful resource for more detailed analysis of traits and development of efficient marker-assisted breeding strategies.

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Growing legume fallow crops has proven to be an important factor in reducing the yield decline effect in sugarcane production. Legumes can also provide a direct economic benefit to sugarcane farmers by providing a source of nitrogen. Further, in some instances, income can flow from the sale, of grain or seed. The following case study provides an insight into the changes made by Russell Young, a sugarcane farmer situated in the Rita Island area of the Burdekin district. The case study focuses on the economics of the old farming system versus a new farming system. The old farming system is based on the conventional farming practices previously used by the Young family in 2002 compared to the 2006 farming system which involves a reduction in tillage practices and use of a Soybean rotational crop for seed production. A whole-of-farm was used to assess the impact of the new farming system on farm profitability. A whole-of-farm economic analysis looks at the impact of a change in farming practice across the whole business, rather than focusing on one single component. This case study is specific to an individual grower’s situation and is not representative of all situations. When evaluating a farming system change, it is important to have a detailed plan.

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Dairy farms located in the subtropical cereal belt of Australia rely on winter and summer cereal crops, rather than pastures, for their forage base. Crops are mostly established in tilled seedbeds and the system is vulnerable to fertility decline and water erosion, particularly over summer fallows. Field studies were conducted over 5 years on contrasting soil types, a Vertosol and Sodosol, in the 650-mm annual-rainfall zone to evaluate the benefits of a modified cropping program on forage productivity and the soil-resource base. Growing forage sorghum as a double-crop with oats increased total mean annual production over that of winter sole-crop systems by 40% and 100% on the Vertosol and Sodosol sites respectively. However, mean annual winter crop yield was halved and overall forage quality was lower. Ninety per cent of the variation in winter crop yield was attributable to fallow and in-crop rainfall. Replacing forage sorghum with the annual legume lablab reduced fertiliser nitrogen (N) requirements and increased forage N concentration, but reduced overall annual yield. Compared with sole-cropped oats, double-cropping reduced the risk of erosion by extending the duration of soil water deficits and increasing the time ground was under plant cover. When grown as a sole-crop, well fertilised forage sorghum achieved a mean annual cumulative yield of 9.64 and 6.05 t DM/ha on the Vertosol and Sodosol, respectively, being about twice that of sole-cropped oats. Forage sorghum established using zero-tillage practices and fertilised at 175 kg N/ha. crop achieved a significantly higher yield and forage N concentration than did the industry-standard forage sorghum (conventional tillage and 55 kg N/ha. crop) on the Vertosol but not on the Sodosol. On the Vertosol, mean annual yield increased from 5.65 to 9.64 t DM/ha (33 kg DM/kg N fertiliser applied above the base rate); the difference in the response between the two sites was attributed to soil type and fertiliser history. Changing both tillage practices and N-fertiliser rate had no affect on fallow water-storage efficiency but did improve fallow ground cover. When forage sorghum, grown as a sole crop, was replaced with lablab in 3 of the 5 years, overall forage N concentration increased significantly, and on the Vertosol, yield and soil nitrate-N reserves also increased significantly relative to industry-standard sorghum. All forage systems maintained or increased the concentration of soil nitrate-N (0-1.2-m soil layer) over the course of the study. Relative to sole-crop oats, alternative forage systems were generally beneficial to the concentration of surface-soil (0-0.1 m) organic carbon and systems that included sorghum showed most promise for increasing soil organic carbon concentration. We conclude that an emphasis on double-or summer sole-cropping rather than winter sole-cropping will advantage both farm productivity and the soil-resource base.

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The wheat grain industry is Australia's second largest agricultural export commodity. There is an increasing demand for accurate, objective and near real-time crop production information by industry. The advent of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite platform has augmented the capability of satellite-based applications to capture reflectance over large areas at acceptable pixel scale, cost and accuracy. The use of multi-temporal MODIS-enhanced vegetation index (EVI) imagery to determine crop area was investigated in this article. Here the rigour of the harmonic analysis of time-series (HANTS) and early-season metric approaches was assessed when extrapolating over the entire Queensland (QLD) cropping region for the 2005 and 2006 seasons. Early-season crop area estimates, at least 4 months before harvest, produced high accuracy at pixel and regional scales with percent errors of -8.6% and -26% for the 2005 and 2006 seasons, respectively. In discriminating among crops at pixel and regional scale, the HANTS approach showed high accuracy. The errors for specific area estimates for wheat, barley and chickpea were 9.9%, -5.2% and 10.9% (for 2005) and -2.8%, -78% and 64% (for 2006), respectively. Area estimates of total winter crop, wheat, barley and chickpea resulted in coefficient of determination (R(2)) values of 0.92, 0.89, 0.82 and 0.52, when contrasted against the actual shire-scale data. A significantly high coefficient of determination (0.87) was achieved for total winter crop area estimates in August across all shires for the 2006 season. Furthermore, the HANTS approach showed high accuracy in discriminating cropping area from non-cropping area and highlighted the need for accurate and up-to-date land use maps. The extrapolability of these approaches to determine total and specific winter crop area estimates, well before flowering, showed good utility across larger areas and seasons. Hence, it is envisaged that this technology might be transferable to different regions across Australia.

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Sorghum is a food and feed cereal crop adapted to heat and drought and a staple for 500 million of the world’s poorest people. Its small diploid genome and phenotypic diversity make it an ideal C4 grass model as a complement to C3 rice. Here we present high coverage (16-45 × ) resequenced genomes of 44 sorghum lines representing the primary gene pool and spanning dimensions of geographic origin, end-use and taxonomic group. We also report the first resequenced genome of S. propinquum, identifying 8 M high-quality SNPs, 1.9 M indels and specific gene loss and gain events in S. bicolor. We observe strong racial structure and a complex domestication history involving at least two distinct domestication events. These assembled genomes enable the leveraging of existing cereal functional genomics data against the novel diversity available in sorghum, providing an unmatched resource for the genetic improvement of sorghum and other grass species.

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Echinochloa colona is the most common grass weed of summer fallows in the grain-cropping systems of the subtropical region of Australia. Glyphosate is the most commonly used herbicide for summer grass control in fallows in this region. The world's first population of glyphosate-resistant E. colona was confirmed in Australia in 2007 and, since then, >70 populations have been confirmed to be resistant in the subtropical region. The efficacy of alternative herbicides on glyphosate-susceptible populations was evaluated in three field experiments and on both glyphosate-susceptible and glyphosate-resistant populations in two pot experiments. The treatments were knockdown and pre-emergence herbicides that were applied as a single application (alone or in a mixture) or as part of a sequential application to weeds at different growth stages. Glyphosate at 720 g ai ha−1 provided good control of small glyphosate-susceptible plants (pre- to early tillering), but was not always effective on larger susceptible plants. Paraquat was effective and the most reliable when applied at 500 g ai ha−1 on small plants, irrespective of the glyphosate resistance status. The sequential application of glyphosate followed by paraquat provided 96–100% control across all experiments, irrespective of the growth stage, and the addition of metolachlor and metolachlor + atrazine to glyphosate or paraquat significantly reduced subsequent emergence. Herbicide treatments have been identified that provide excellent control of small E. colona plants, irrespective of their glyphosate resistance status. These tactics of knockdown herbicides, sequential applications and pre-emergence herbicides should be incorporated into an integrated weed management strategy in order to greatly improve E. colona control, reduce seed production by the sprayed survivors and to minimize the risk of the further development of glyphosate resistance.

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Climatic variability in dryland production environments (E) generates variable yield and crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement seeks broadly adapted genotypes to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in response to average local environmental conditions. This process does not search the full spectrum of potential G × M × E combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional, broad adaptation approach) of exploiting specific adaptation arising from G × M × E. We present an in-silico analysis for sorghum production in Australia using the APSIM sorghum model. Crop design (G × M) is optimised for subsets of locations within the production region (specific adaptation) and is compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic subregions that have frequencies of major environment types substantially different from that for the entire production region show greatest advantage for specific adaptation. Although the specific adaptation approach confers yield and production risk advantages at industry scale, even greater benefits should be achievable with better predictors of environment-type likelihood than that conferred by location alone.

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There is limited understanding about how insect movement patterns are influenced by landscape features, and how landscapes can be managed to suppress pest phytophage populations in crops. Theory suggests that the relative timing of pest and natural enemy arrival in crops may influence pest suppression. However, there is a lack of data to substantiate this claim. We investigate the movement patterns of insects from native vegetation (NV) and discuss the implications of these patterns for pest control services. Using bi-directional interception traps we quantified the number of insects crossing an NV/crop ecotone relative to a control crop/crop interface in two agricultural regions early in the growing season. We used these data to infer patterns of movement and net flux. At the community-level, insect movement patterns were influenced by ecotone in two out of three years by region combinations. At the functional-group level, pests and parasitoids showed similar movement patterns from NV very soon after crop emergence. However, movement across the control interface increased towards the end of the early-season sampling period. Predators consistently moved more often from NV into crops than vice versa, even after crop emergence. Not all species showed a significant response to ecotone, however when a response was detected, these species showed similar patterns between the two regions. Our results highlight the importance of NV for the recruitment of natural enemies for early season crop immigration that may be potentially important for pest suppression. However, NV was also associated with crop immigration by some pest species. Hence, NV offers both opportunities and risks for pest management. The development of targeted NV management may reduce the risk of crop immigration by pests, but not of natural enemies.