134 resultados para Corn. Maize


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Background: Sorghum genome mapping based on DNA markers began in the early 1990s and numerous genetic linkage maps of sorghum have been published in the last decade, based initially on RFLP markers with more recent maps including AFLPs and SSRs and very recently, Diversity Array Technology (DArT) markers. It is essential to integrate the rapidly growing body of genetic linkage data produced through DArT with the multiple genetic linkage maps for sorghum generated through other marker technologies. Here, we report on the colinearity of six independent sorghum component maps and on the integration of these component maps into a single reference resource that contains commonly utilized SSRs, AFLPs, and high-throughput DArT markers. Results: The six component maps were constructed using the MultiPoint software. The lengths of the resulting maps varied between 910 and 1528 cM. The order of the 498 markers that segregated in more than one population was highly consistent between the six individual mapping data sets. The framework consensus map was constructed using a "Neighbours" approach and contained 251 integrated bridge markers on the 10 sorghum chromosomes spanning 1355.4 cM with an average density of one marker every 5.4 cM, and were used for the projection of the remaining markers. In total, the sorghum consensus map consisted of a total of 1997 markers mapped to 2029 unique loci ( 1190 DArT loci and 839 other loci) spanning 1603.5 cM and with an average marker density of 1 marker/0.79 cM. In addition, 35 multicopy markers were identified. On average, each chromosome on the consensus map contained 203 markers of which 58.6% were DArT markers. Non-random patterns of DNA marker distribution were observed, with some clear marker-dense regions and some marker-rare regions. Conclusion: The final consensus map has allowed us to map a larger number of markers than possible in any individual map, to obtain a more complete coverage of the sorghum genome and to fill a number of gaps on individual maps. In addition to overall general consistency of marker order across individual component maps, good agreement in overall distances between common marker pairs across the component maps used in this study was determined, using a difference ratio calculation. The obtained consensus map can be used as a reference resource for genetic studies in different genetic backgrounds, in addition to providing a framework for transferring genetic information between different marker technologies and for integrating DArT markers with other genomic resources. DArT markers represent an affordable, high throughput marker system with great utility in molecular breeding programs, especially in crops such as sorghum where SNP arrays are not publicly available.

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Stay-green, an important trait for grain yield of sorghum grown under water limitation, has been associated with a high leaf nitrogen content at the start of grain filling. This study quantifies the N demand of leaves and stems and explores effects of N stress on the N balance of vegetative plant parts of three sorghum hybrids differing in potential crop height. The hybrids were grown under well-watered conditions at three levels of N supply. Vertical profiles of biomass and N% of leaves and stems, together with leaf size and number, and specific leaf nitrogen (SLN), were measured at regular intervals. The hybrids had similar minimum but different critical and maximum SLN, associated with differences in leaf size and N partitioning, the latter associated with differences in plant height. N demand of expanding new leaves was represented by critical SLN, and structural stem N demand by minimum stem N%. The fraction of N partitioned to leaf blades increased under N stress. A framework for N dynamics of leaves and stems is developed that captures effects of N stress and genotype on N partitioning and on critical and maximum SLN.

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Background and Aims: The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. Methods: The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Key Results: Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. Conclusions: This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies.

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BACKGROUND: Piperonyl butoxide (PB)-synergised natural pyrethrins (pyrethrin:PB ratio 1:4) were evaluated both as a grain protectant and a disinfestant against four Liposcelidid psocids: Liposcelis bostrychophila Badonnel, L. entomophila (Enderlein), L. decolor (Pearman) and L. paeta Pearman. These are key storage pests in Australia that are difficult to control with the registered grain protectants and are increasingly being reported as pests of stored products in other countries. Firstly, mortality and reproduction of adults were determined in wheat freshly treated at 0.0, 0.75, 1.5, 3 and 6 mg kg-1 of pyrethrins + PB (1:4) at 301C and 702% RH. Next, wheat treated at 0.0, 1.5, 3 and 6 mg kg-1 of pyrethrins + PB (1:4) was stored at 301C and 702% RH and mortality and reproduction of psocids were assessed after 0, 1.5, 3 and 4.5 months of storage. Finally, the potential of synergised pyrethrins as a disinfestant was assessed by establishing time to endpoint mortality for adult psocids exposed to wheat treated at 3 and 6 mg kg-1 of synergised pyrethrins after 0, 3, 6, 9 and 12 h of exposure. RESULTS: Synergised pyrethrins at 6 mg kg-1 provided 3 months of protection against all four Liposcelis spp., and at this rate complete adult mortality of these psocids can be achieved within 6 h of exposure. CONCLUSION: Piperonyl butoxide-synergised pyrethrins have excellent potential both as a grain protectant and as a disinfestant against Liposcelidid.

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We compared daily net radiation (Rn) estimates from 19 methods with the ASCE-EWRI Rn estimates in two climates: Clay Center, Nebraska (sub-humid) and Davis, California (semi-arid) for the calendar year. The performances of all 20 methods, including the ASCE-EWRI Rn method, were then evaluated against Rn data measured over a non-stressed maize canopy during two growing seasons in 2005 and 2006 at Clay Center. Methods differ in terms of inputs, structure, and equation intricacy. Most methods differ in estimating the cloudiness factor, emissivity (e), and calculating net longwave radiation (Rnl). All methods use albedo (a) of 0.23 for a reference grass/alfalfa surface. When comparing the performance of all 20 Rn methods with measured Rn, we hypothesized that the a values for grass/alfalfa and non-stressed maize canopy were similar enough to only cause minor differences in Rn and grass- and alfalfa-reference evapotranspiration (ETo and ETr) estimates. The measured seasonal average a for the maize canopy was 0.19 in both years. Using a = 0.19 instead of a = 0.23 resulted in 6% overestimation of Rn. Using a = 0.19 instead of a = 0.23 for ETo and ETr estimations, the 6% difference in Rn translated to only 4% and 3% differences in ETo and ETr, respectively, supporting the validity of our hypothesis. Most methods had good correlations with the ASCE-EWRI Rn (r2 > 0.95). The root mean square difference (RMSD) was less than 2 MJ m-2 d-1 between 12 methods and the ASCE-EWRI Rn at Clay Center and between 14 methods and the ASCE-EWRI Rn at Davis. The performance of some methods showed variations between the two climates. In general, r2 values were higher for the semi-arid climate than for the sub-humid climate. Methods that use dynamic e as a function of mean air temperature performed better in both climates than those that calculate e using actual vapor pressure. The ASCE-EWRI-estimated Rn values had one of the best agreements with the measured Rn (r2 = 0.93, RMSD = 1.44 MJ m-2 d-1), and estimates were within 7% of the measured Rn. The Rn estimates from six methods, including the ASCE-EWRI, were not significantly different from measured Rn. Most methods underestimated measured Rn by 6% to 23%. Some of the differences between measured and estimated Rn were attributed to the poor estimation of Rnl. We conducted sensitivity analyses to evaluate the effect of Rnl on Rn, ETo, and ETr. The Rnl effect on Rn was linear and strong, but its effect on ETo and ETr was subsidiary. Results suggest that the Rn data measured over green vegetation (e.g., irrigated maize canopy) can be an alternative Rn data source for ET estimations when measured Rn data over the reference surface are not available. In the absence of measured Rn, another alternative would be using one of the Rn models that we analyzed when all the input variables are not available to solve the ASCE-EWRI Rn equation. Our results can be used to provide practical information on which method to select based on data availability for reliable estimates of daily Rn in climates similar to Clay Center and Davis.

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Displacement of the fungus Fusarium pseudograminearum from stubble by antagonists is a potential means of biocontrol of crown rot in cereals. The role of carbon and nitrogen nutrition in interactions between the pathogen and the antagonists Fusarium equiseti, Fusarium nygamai, Trichoderma harzianum and the non-antagonistic straw fungus Alternaria infectoria was investigated. Sole carbon source utilization patterns on Biolog plates were similar among the three Fusarium species, suggesting a possible role for competition. However, carbon niche overlap was unlikely to be important in antagonism by T. harzianum. Straw medium supplemented with sugars generally reduced the inhibitory effect of antagonists on growth of F. pseudograminearum in dual culture, indicating that availability of simple carbon sources does not limit antagonism. Adding nitrogen as urea, nitrate or ammonium to straw medium had little effect on antagonism by F. equiseti and F. nygamai, but ammonium addition removed the inhibitory effect of T. harzianum on growth of F. pseudograminearum. Displacement of F. pseudograminearum from straw by all fungi in a Petri dish assay was greater when urea or nitrate was used as a nitrogen source than with ammonium. All forms of nitrogen significantly increased displacement of F. pseudograminearum from straw under simulated field conditions when straws were either inoculated with T. harzianum or exposed to resident soil microbes. However, in 2 out of 3 experiments urea and nitrate were more effective than ammonium. The results suggest that availability of nitrogen, but not carbon, is limiting the activities of antagonists of F. pseudograminearum in straw, and the way nitrogen is applied can influence the rate of displacement and mortality of the pathogen in host residues.

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Each Agrilink kit has been designed to be both comprehensive and practical. As the kits are arranged to answer questions of increasing complexity, they are useful references for both new and experienced producers of specific crops. Agrilink integrates the technology of horticultural production with the management of horticultural enterprises. REPRINT INFORMATION - PLEASE READ! For updated information please call 13 25 23 or visit the website www.deedi.qld.gov.au (Select: Queensland Industries – Agriculture link) This publication has been reprinted as a digital book without any changes to the content published in 2005. We advise readers to take particular note of the areas most likely to be out-of-date and so requiring further research: see detailed information on first page of the kit. Even with these limitations we believe this information kit provides important and valuable information for intending and existing growers. This publication was last revised in 2005. The information is not current and the accuracy of the information cannot be guaranteed by the State of Queensland. This information has been made available to assist users to identify issues involved in the production of sweet corn. This information is not to be used or relied upon by users for any purpose which may expose the user or any other person to loss or damage. Users should conduct their own inquiries and rely on their own independent professional advice. While every care has been taken in preparing this publication, the State of Queensland accepts no responsibility for decisions or actions taken as a result of any data, information, statement or advice, expressed or implied, contained in this publication.

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The project will provide enough data for a reliable and robust NIRs. It will more fully develop the in vitro method to enable less costly assessment of grains in the future. It will also provide a reliable assessment for DE which is the most expensive component of pig feed.

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Identification and analysis of allelic variation in carotenoid biosynthesis genes present in sweet corn germplasm for eye health.

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Develop a new diagnostic platform for Post Entry Plant Quarantine to support the detection of Emergency Plant Pests in the Australian Grains and Nursery Industries.

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Project Objectives: 1. Improving yield and water use efficiency of the wheat crop, the backbone of the Australia grains industry, by better matching management, variety, soil and climate. The aim is thus increasing kg grain/ha per mm evapotranspiration and kg grain/ha per mm rain. 2. Improving land and water productivity and profit by better arrangement of the components of the cropping system. This involves better allocation of farm resources (land, water, machinery, labour) and identifying strategies that account for trade-offs between profit and risk. The aim is thus improving $/ha per year and mm rain in a risk framework.

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New regional extension project for the cotton/grains farming systems on the Darling Downs and Border Rivers with CRDC and Cotton CRC based on the CRDC/Agri-Science Queensland discussion paper.

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This project focussed on the phosphorus (P) and potassium (K) status of northern cropping soils. Stores of P and K have been depleted by crop removal and limited fertiliser application, with depletion most significant in the subsoil. Soil testing strategies are confounded by slowly available mineral reserves with uncertain availability. The utility of new soil tests was assessed to measure these reserves, their availability to plants quantified and a regional sampling strategy undertaken to identify areas of greatest P and K deficit. Fertiliser application strategies for P and K have been tested and the interactions between these and other nutrients have been determined in a large field program.

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Screening new and existing breeding germplasm and cultivars for grain defect tolerance for breeding programs, evaluate new methods and technologies to screen more effectively for the barley grains defects - pre-harvest sprouting, blackpoint, kernel discolouration, and investigate genetic mechanisms involved in controlling barley grain defect tolerance.

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Soil Micro Testing for nematodes on grain farms.