Optical Sensors for Complex Media

The work of the COMIC team is focused on the research and development of optical sensors based on spectral measurements (UV-VIS_NIR) and associated data analysis methods in order to characterize the complex biological environments that are at the heart of agro-bio-processes.

The measurement systems developed by the COMiC team are indirect optical sensors (indirect sensors don't directly measure the quantity Y required, but another quantity, influenced by Y) multivariate, based on Ultra-Violet, Visible, Near Infrared (UV-VIS-NIR) spectrometry and hyperspectral imaging.
The usual approach to extracting information about the medium under study (often concentrations) involves two complementary steps:

1. acquisition of an optical signal that has interacted with the medium,
2. the construction, by learning, of a statistical model linking this signal and the quantity of interest to be quantified.


General principle of a multivariate indirect optical measurement

The challenge is then to accurately predict this parameter of interest from an optical signal acquired on a new sample. These two steps therefore have an impact on the metrological quality of the measurement. The optical signal must be of good quality and contain useful information. The chemometric model must be robust, i.e. remain stable in the face of external disturbances.

The COMiC team's pioneering work combining "multi/hyperspectral measurements" and "calibration model" has proven itself and given excellent results for more than two decades. However, due to :

  1.    the complexity and diversity of the new environments studied by the laboratory (soil, microalgae, sewage plant sludge, genetically modified plants, etc.)
  2.    the increase in measurements in uncontrolled environments (outdoors, reactors, methanisers, etc.)

Optical measurements and calibration models don't always meet the required quality and robustness criteria. In order to overcome these two limitations, the research work of the COMiC team is centred around two following axes :

  1.     Development of specific optical methods and devices to improve signal quality.
  2.     Development of chemometric methods to improve the robustness of models.

Contact details of team leader :


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Modification date : 17 July 2023 | Publication date : 14 April 2021 | Redactor : AD