The MUSE-Tech project will bridge the gap between state of the art sensing technologies and industrial Process Analytical Technology (PAT) applications by demonstrating fitness for purpose of the versatile Multi Sensor Device (MSD).

What is the MUSE-Tech Project?

The concept of MUSE-Tech project is the integration of three High-End sensing technologies (Photoacoustic Spectroscopy, Quasi Imaging UV-Vis Spectrometry and Distributed Temperature Sensing) in a versatile Multi Sensor Device (MSD), for real-time monitoring (on-line or in-line) of multiple parameters associated with the quality and the chemical safety of raw and in-process materials.

Development of three novel sensors

Three novel sensors will be developed, namely:

  • A miniaturised and affordable Photoacoustic Sensor (PAS), specifically designed for real-time and on-line detection of gases and volatile compounds in foods and beverages;
  • A rugged and miniaturised Quasi Imaging Vis-NIR (QIVN) sensor based on a piezo-actuated tuneable FPI, combined with multi-channel detector technology, for real-time and in-line acquisition of multiple wavelength channels and still get the highest possible measurement speed with affordable cost;
  • A multipoint Distributed Temperature Sensor (DTS), based on optical fibre technology, Bragg gratings and FPIs, protected from the environment with oleophobic and super-oleophobic surfaces, for real-time and in-line monitoring of the spatial temperature distribution in critical points of the food processes.

Integration of the three novel sensors

The three sensors will be integrated in an affordable and easy cleanable Multi Sensor Device (MSD), which can support on-line/in-line and real-time monitoring of a wide range of volatile and non-volatile food components, as well as the temperature distribution in crucial points of the process. The MSD will be based on a flexible plug-in architecture, allowing additional inputs from other sensors already installed in the process lines. Optical fibre and gas sampling systems, engineered following hygienic design guidelines, will be used for remote sensing under hash working conditions, and to simultaneously monitor critical parameters in raw and in-process materials during the process.

Assembling and calibration of the MSD

Three MSD prototypes will be assembled, calibrated and tested, in order to demonstrate the versatility and auto-adaptive capacity of the device in three food case studies, namely:

  • Bread production (dough mixing & prover fermentation)
  • Potato chips frying
  • Brewing (wort mashing and boiling)

These applications have a great relevance in the food industry, are representative of a wide range of demanding working conditions (high temperatures, high humidity, dust, continuous flow of foodstuff, etc.), and underline the potential range of applications of the MSD in different food and beverage processes. The list of CQAs & CPPs, which will be monitored by the MSD, includes a wide range of parameters, associated with both food quality (sugars, water content, DMS, Hexanal, colour, etc.) and chemical safety (acrylamide, furan, mineral oil contamination, etc.).

Demonstration at industrial level

Fitness for purpose and versatility of the MSD will be demonstrated under industrial and/or pilot plant conditions for the three case studies. In a first stage, the measurements obtained from the MSD will be merged and processed by the means of chemometric tools to develop empirical and multivariate predictive models for CQAs.  Suitable communication systems and dedicated software, integrating the chemometric tools, the predictive models and the operator interface, will be implemented to support the integration of the MSD with the programmable logic controllers (PLC) of the processing equipment. Once validated the models, CPPs will be automatically adjusted during food processing, in order to achieve targeted levels for Critical Quality Attributes (CQAs) in the final products, thus being a key element of the practical decision-making tools and early warning system for the three case studies.

Project Information



Coordinated by:


Project coordinator:



2013-10-01 till 2016-09-30


Funding programme:

EU 7th Framework Programme


Grant agreement no.:




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