Database providing access to the High Technology Network's industrial research offering: research competences, type of analyses and tests available at the Laboratories. Companies can consult the Catalogue to find Laboratories and researchers that match their needs.
Competence
Acquisition and pre-processing of signals for model identification
Analysis of chemical compositions and qualitative characteristics of lipid fractions of pig carcasses and thighs
Analysis of grape, fruits and food processing left-overs
Analysis of standards and regulations: laws and guidelines for protected, typical and biological raw material
Chemical and chemo-physical analysis on meat and vegetal products
Continuous-time and discrete-time mathematical modeling of systems and processes
Design of new molecular markers for assisted selection (MAS) for vegetal products
Determination of the protein variation during product processing (i.e. dairy and meat products)
Discrete events mathematical modeling of systems and processes
DNA samples: preparations and conservation from vegetal materials and plants
Finite element simulation (FEM)
Formal languages for systems modeling (Unified Modeling Language-UML and SysML-System Modeling Language)
Identification of models and parameters estimation
In silico evaluation of potentially xenoestrogenic compounds
Infinite-dimensional mathematical modeling of systems
Intruments and services for precision agriculture
Kits for the determination of contaminants, pesticides and pathogens in raw materials
Modeling of the collision of bodies in mechanical systems
Molecular DNA analysis of vegetal materials
Non-parametric modeling (neural networks, etc.)
On-farm rapid methods for quality assessment of dairy and meat products
On-line bank "Cerealab" as informatics instrument to support assisted selection (MAS) for vegetal production
Production of new vegetal products (populations, lines, new varieties) with peculiar characteristics by marker assisted selection (MAS)
Quality assesment of milk and meat
Rapid non-destructive methods for the optimization , characterization, and monitoring of raw material and finished products
Simulation for discrete events models
Simulation for dynamic continuous-time and discrete-time models
Technological strategies for the imporvement of organoleptic and nutritional properties of raw materials strategies
Transformation potential of oenological raw materials (grape, musts, etc.)
Validation of models and X-In-The-Loop (software in the loop and hardware in the loop)
Varietal comparison of wheat and rice collections