iMeatSense Work Packages
The iMeatSense project willl be conducted over a three-year period and consists of seven work packages (WP), which are further divided into tasks. Specifically:
WP1: System specification (Months: 1-2)
Task 1.1: Food Microbiological specification
Task 1.2: Sensors specification
WP2: Multi sensor platform / Microbiological Investigation of samples (Months: 3-24)
Task 2.1: Evaluation of microbial association and dynamics during production, storage (conventional and active packaging) and distribution of meats.
Task 2.2: Metabolic profiling of targeted foods stored at different storage temperature.
Task 2.3: Application of electronic nose and GC-MS for the simple and rapid detection of microbial metabolites (metabolomics) indicative of meat quality.
Task 2.4: Application of FT-IR spectroscopy.
Task 2.5: Application of image analysis for monitoring meat freshness.
WP3: Data Preprocessing / Sensor Fusion (Months: 13-18)
Task 3.1: Feature Extraction Scheme for the multi-spectral imaging system.
Task 3.2: Dimensionality Reduction schemes.
Task 3.3: Fuzzy Logic approach for input variables selection.
Task 3.4: Multiple Classifiers/ Fusion schemes.
Task 3.5: Reduced number of samples problem.
WP4: Development of “Diagnostic” / Classification Systems (Months: 19-27)
Task 4.1: Indices of quality identified by neural networks.
Task 4.2: Indices of quality identified by hybrid learning-based methodologies.
Task 4.3: Indices of quality identified by multivariate statistical analysis.
Task 4.4: Investigation of an incremental learning scheme for hybrid intelligent classifiers.
WP5: Development of Predictive Models and User Interface Platform (Months: 19-33)
Task 5.1: Kinetic modelling and prediction of metabolite formation in meat.
Task 5.2: Hybrid intelligent schemes/models for prediction of metabolite formation in meat.
Task 5.3: Online intelligent decision utilising multispectral image sensing device.
WP6: Validation studies (classification / prediction) (Months: 24-36)
Task 6.1: Validation studies including testing of new techniques.
Task 6.2: Validation of mathematical models
WP7: Dissemination of the project outcomes (Μonths: 6-36)
"This work has been supported by the iMeatSense project 550 of the ARISTEIA-I call co -funded by EC European Social Fund and the Greek General Secretariat of Research and Technology"
