Kunstig intelligens og interaktiv læring vil forme arbeidslivet
Vil roboter i nær fremtid klare å utføre kompleks bearbeiding av råstoff som i dag kun utføres av mennesker? Hvordan kan dette bidra til en mer bærekraftig matproduksjon i Norge? Den 4. februar ble den
Program og påmelding til TechFood og sluttmøte i iProcess
TechFood Vil roboter i nær fremtid klare å utføre kompleks bearbeiding av råstoff som i dag kun utføres av mennesker? Hvordan kan dette bidra til en mer bærekraftig matproduksjon i Norge? Hva kan robotene gjøre for
Raman spectroscopy for quality differentiation of pork
Raman spectroscopy can be used for analysis of important quality indicators in meat, feasibly leading to on-line applications of the technique in the future. Overall meat eating quality is very important for consumer confidence, willingness to pay
5 points to consider before setting sails in data science projects in the food industry
In the slipstream of the digitalization of modern food industry, part of Industry 4.0, a paramount need to handle larger and larger amounts of data has called for new developments in both the analytical toolbox
Tracking non-rigid objects using depth camera
Surface of non-rigid objects, such as leafy vegetables, meats and fishes can be completely and accurately tracked using a depth camera with the approach proposed in this article. This is exceptionally useful while interacting with
Raman spectroscopy for estimation of residual bone minerals in mechanically deboned chicken meat
Residual bone, measured as %calcium or %ash, is a strictly controlled quality parameter of mechanically deboned chicken meat (MDCM). Raman spectroscopy was developed as a rapid tool for estimation of this important parameter. Mechanical deboning
Porosity maps give an ‘airy’ image of fruit and vegetables
See the internal structure of your product through 3D X-ray based porosity mapping. The porosity of a fruit or vegetable quantifies the amount of air spaces inside the product. The porosity strongly determines to what
Managing supply uncertainty in operational production planning – A whitefish case study
Managing supply uncertainty by a formal stochastic programming approach demonstrates how expected profit may be increased due to more robust production plans. Production planning Operational production planning deals with establishing optimal production plans. A production
Integrated planning in white fish supply chains
Through integrated supply chain planning by sharing information, uncertainty is mitigated
WP 7 Management
Project Leader: Ekrem Misimi, SINTEF Ocean (SO) Participating partners SO, Management team,
WP 6 Dissemination and Communication
Work Package leader / Responsible partner: SFA and Røe Kommunikasjon
WP 5 Value chain strategies and business models
Work Package Leader/Responsible partner Dr. Ragnar Tveterås, Centre for Innovation
WP 4 Information Management
Work Package Leader/Responsible partner: Dr. Maitri Thakur, SINTEF Fisheries and
WP 3 Flexible Processing Automation
Work Package Leader Dr. Ekrem Misimi, SINTEF Fisheries and Aquaculture
WP 2 Optimal process control and raw material differentiation
Work Package Leader: Dr. Jens Petter Wold, Nofima Participating partners: Nofima, SFA,
About us
iProcess’s main objective is to develop novel concepts and methods for flexible and sustainable food processing in Norway – that are to cope with small volume series and high biologicalvariation of the existing raw materials – to enable increased raw material utilization for food
products and to increase profitability.