All days




The most advanced applications of re-sequencing, genotyping and phenotype characterisation will be applied in order to identify codifying sequences and their most common allelic variants in apple or in related species (in the specific case of resistance genes). Finely-tuned molecular characterisation of phenotypically distant varieties may allow association studies by means of linkage disequilibrium analyses, to identify genes and genomic regions determining variations in terms of product quality and/or disease resistance (studies in part ongoing at FEM-IASMA). Two main lines of action will be followed: i) the re-sequencing of different varieties which cannot be traced back to a common lineage, and ii) the development of DNA-microarrays with the entire apple transcriptome deduced from the genomic sequence available at FEM-IASMA. This information can be used by WPs 2, 3, 4 and 5, in order to identify subsets of genes characterising the phenotypical events of interest to the project, such as abscission, self-thinning, fruit ripening, storage effects, etc.


The project will have access to the FEM equipment platform of metabolic profiling includes an array of 6 mass spectrometers interfaced with UPLC and HRGC chromatographs. The project will exploit ongoing systematic studies carried on at FEM-IASMA, aimed to build state-of-the-art libraries for the characterization of the organic compounds constituting the apple metabolome. With a set of three complementary analyses running in parallel under optimized conditions, which will be validated within the project,  it will be possible to accurately analyse hundreds of low-molecular-weight organic compounds, thus covering all the major metabolic pathways of interest for fruit quality. In addition, in order to highlight possible complex metabolite patterns and include unknown and/or uncharacterised compounds, advanced metabolomic methods will be adopted along with a “discovery-based research”. These approaches will be integrated with and complete the conventional “hypothesis-driven research” method. WPs 2, 3 and 5 will identify the main compounds of interest for fruit quality.

Non-invasive analyses.

The project will use the innovative DA-Meter and NIRs non-invasive analytical tools, currently being developed at the University of Bologna. These tools will be validated using data either already available or produced within the project to allow the development of an apple-specific system. In addition, a GPS will be integrated into both the classic DA-Meter and the apple-specific version to allow georeferencing of data obtained with portable tools. All these techniques will provide support for WPs 3 and 4, in particular. Finally, new storage technologies with low environmental impact are to be developed in collaboration with WP4, using the 1-MCP along with an increase in the thermal regime, which may be suitable in reducing costs and improving environmental sustainability.