Breeding super black soldier flies at scale for sustainable food production. This project aims to address the current challenges impeding the industrial scale-up of Australian Black Soldier Fly (BSF) farming across diverse feed waste substrates by generating critical on-farm knowledge. This project expects to generate fundamental knowledge in commercial BSF breeding designs whilst also developing and testing new animal evaluation technologies (ie, genetic & spectroscopy) through interdisciplinar ....Breeding super black soldier flies at scale for sustainable food production. This project aims to address the current challenges impeding the industrial scale-up of Australian Black Soldier Fly (BSF) farming across diverse feed waste substrates by generating critical on-farm knowledge. This project expects to generate fundamental knowledge in commercial BSF breeding designs whilst also developing and testing new animal evaluation technologies (ie, genetic & spectroscopy) through interdisciplinary approaches that will accelerate industry productivity. Expected outcomes of this project include the long-term growth and competitive advantage of the Australian insect farming industry, as well as promoting the benefits of a circular economy through bioconversion of organic waste into commercially viable products.Read moreRead less
Prediction of phenotype for multiple traits from multi-omic data. This project aims to develop better methods for predicting traits in an individual based on their genome sequence. This method will be tested in agricultural animals and plants and in humans. The prediction formula is derived from a training dataset that has information on the traits and genome sequence of a sample of individuals. The prediction formula can then be applied to predict the trait in individuals where the trait is un ....Prediction of phenotype for multiple traits from multi-omic data. This project aims to develop better methods for predicting traits in an individual based on their genome sequence. This method will be tested in agricultural animals and plants and in humans. The prediction formula is derived from a training dataset that has information on the traits and genome sequence of a sample of individuals. The prediction formula can then be applied to predict the trait in individuals where the trait is unknown. This is useful for selecting the best parents for breeding in agriculture and for predicting the future phenotype of animals, crops and people. The proposed method uses data on very many traits to identify sequence variants that have a function and to predict the traits affected by each variant.Read moreRead less