Breeding Low Chill high quality stonefruit

Breeding Low Chill high quality stonefruit.

Improving avocado fruit quality and market potential by pre and post harvest factors

Improving avocado fruit quality and market potential by pre and post harvest factors.

Improving the quality of kikuyu by reducing the lignin content

Development of improved pasture grass via chemical mutagenesis and selection of mutations in lignin genes.

A tilling approach to develop high quality tropical and sub-tropical pasture gra

This project aims to develop high quality kikuyu pasture grass via chemical mutagenesis, followed by screening for mutations in lignin biosynthesis genes.

Variety quality management in strawberry, using DNA genotyping as a tool

Quality management strawberry, DNA genotyping.

Impact of Stem Defect Agent Defects on Hardwood Wood Quality

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.

Management of fruit quality and pest infestations of mango and mangosteen for Market access requirements

Management of fruit quality and pest infestations of mango and mangosteen for Market access requirements.

Improving fruit quality and profitability of 'Honey Gold' mango

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.

ACIAR Improving Postrainy Sorghum Varieties Grain and Fodder in India

Sorghum grown in India in the post-rainy season (Rabi) relies on residual soil moisture, and the crop is commonly exposed to terminal drought stress. But there is a ready market for its high-quality grain and stover (used as fodder on dairy farms). Steps to improve productivity while maintaining quality offer an attractive opportunity for sorghum farmers to improve their incomes. Genetically improving the efficiency of using stored soil moisture is a prime target to maximise grain/stover production and quality of Rabi sorghum. This project aims to achieve this through the application of DNA sequences known as quantitative trait loci (QTLs). The project scientists will introduce marker-assisted introgression of stay-green QTLs into sorghum lines, enhancing both the quality and the quantity of grain/stover of postrainy sorghum. They will also use modelling to identify the key physiological traits involved in a higher, more stable yield across water-limited environments of India and Australia, and the key stay-green QTLs contributing to these traits. The publicly available QTL isolines lines developed in this project will be the basis of new varieties to be bred in a subsequent phase.

Agronomic Packages for Improved Yield and Quality in the Australian Peanut Industry

Monitoring aflatoxin and developing improved peanut drying practices, cadmium management and web based irrigation decision support systems.

Developing agronomic solutions to improve barley yield and grain quality

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.

DAN00106 Developing agronomic solutions to improve barley yield and grain quality

Producing management packages for new northern barley varieties. Evaluating silage barley varieties.

Enhancing supplies of high quality barley to meet pork industry demands

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.

DAQ00104 Sponge and dough bread quality of Australian wheat germplasm

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.

A simple and fast two-locus quality control test to detect false positives due to batch effects in genome-wide association studies

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.