969 resultados para signal quality
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NIRS calibrations for predicting the nutritional quality of feed.
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Breeding Low Chill high quality stonefruit.
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Improving avocado fruit quality and market potential by pre and post harvest factors.
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Development of improved pasture grass via chemical mutagenesis and selection of mutations in lignin genes.
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This project aims to develop high quality kikuyu pasture grass via chemical mutagenesis, followed by screening for mutations in lignin biosynthesis genes.
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Quality management strawberry, DNA genotyping.
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Queensland's hardwood plantation industry is producing increasing volumes of sawlog, veneer and poles. Wood quality can sometimes be impaired in some plantation hardwoods when the growing trees are attacked by insect borers. Susceptibility to borer damage varies with the species as well as site conditions or location. The risk model developed from this project will enable the plantation industry to match tree species with appropriate growing conditions in Queensland.
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Management of fruit quality and pest infestations of mango and mangosteen for Market access requirements.
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Honey Gold mango is a new Australian variety owned by a Queensland company, and in high demand because of very good flavour and appearance. It develops under skin browning (USB) when grown in hot areas. It appears after packing and the fruit need to be re-sorted at the markets to remove affected fruit. Production and postharvest treatments will be developed to reduce USB and increase profitability. Other production and harvest factors causing quality loss will be also be identified through a commercial downgrade analysis program in the packhouse. Grower training will reduce downgrades and improve the percentage of fruit in premium grade.
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Monitoring aflatoxin and developing improved peanut drying practices, cadmium management and web based irrigation decision support systems.
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The main aim of this project is to develop variety management packages to help tailor commercial malt and feed barley production in the Northern GRDC Region to commercial malt and feed barley specifications. Field trials are designed to give information.
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Producing management packages for new northern barley varieties. Evaluating silage barley varieties.
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Producing barley varieties that have incrased grain yield and consistent or higher energy for pigs, as well as resistance to the major diseases of barley.
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The main grade of wheat targeted for the export sponge and dough (S&D) market is Australian prime hard (APH). By association, protein should be a key parameter relating to S&D quality, specifically loaf volume (LV). Surprisingly, the project revealed a low level of correlation between total protein content and LV. It appears that protein composition may be the key to understanding S&D quality, as the glutenin Glu D1 5+10 subunit contributed to the highest LVs. The current varieties KennedyA and SunzellA, together with several breeding lines, provided a consistently high quality over a number of seasons. These varieties performed as well as, if not better than, North American S&D varieties.
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The impact of erroneous genotypes having passed standard quality control (QC) can be severe in genome-wide association studies, genotype imputation, and estimation of heritability and prediction of genetic risk based on single nucleotide polymorphisms (SNP). To detect such genotyping errors, a simple two-locus QC method, based on the difference in test statistic of association between single SNPs and pairs of SNPs, was developed and applied. The proposed approach could detect many problematic SNPs with statistical significance even when standard single SNP QC analyses fail to detect them in real data. Depending on the data set used, the number of erroneous SNPs that were not filtered out by standard single SNP QC but detected by the proposed approach varied from a few hundred to thousands. Using simulated data, it was shown that the proposed method was powerful and performed better than other tested existing methods. The power of the proposed approach to detect erroneous genotypes was approximately 80% for a 3% error rate per SNP. This novel QC approach is easy to implement and computationally efficient, and can lead to a better quality of genotypes for subsequent genotype-phenotype investigations.