Presentation of a new system to monitor and stabilize mid infrared spectral data

  • Fernández Pierna, J.A. , Grelet, C. , Baeten, V. , Dardenne, P. , Abbas, O. & Dehareng, F. (2018). Presentation of a new system to monitor and stabilize mid infrared spectral data. Proceedings in: ICAR annual conference, Auckland, New Zealand, 7-11/02/2018,
Type Conference Proceedings
Year of conference 2018
Title Presentation of a new system to monitor and stabilize mid infrared spectral data
Conference name ICAR annual conference
Conference location Auckland, New Zealand
conference Date 7-11/02/2018
Endnote Keywords FT-MIR, milk, network, standardization, daily monitoring
Abstract The recent developments of indirect models (e.g. bhb, methane emissions,…) based on mid infrared spectroscopy of milk have obliged the implementation of a standardization procedure. It permits their transfer between instruments of the same or/and different brands. Moreover, it stabilizes and corrects the deviations resulting from hardware modifications over time. In the approach proposed within the frame of the Optimir project, each spectrometer is monthly standardized. A common set of raw milk samples is measured on all instruments. This method is applied in several countries and on different instruments. Through this network, the standardization allowed a successful development of common prediction equations of new parameters. Furthermore, it permitted the transfer of these models on all instruments across brands and models. However, between two monthly standardizations, there is currently a lack of knowledge regarding the stability of the individual spectrometer. So far there is no quality insurance system to monitor daily the stability of the predictions for the new indirect parameters. Consequently, a complementary system is needed to insure daily accuracy and validity of predictions. The aim of this presentation is to evaluate the potential of a new approach developed to monitor and stabilize daily the spectral data. The daily monitoring system gives a visual representation of the spectral stability. The proposed method is to correct the raw spectral data when perturbations or drifts are detected. The first results obtained show that this method can help lab manager to have a precise monitoring of the raw spectral data, being complementary to the other quality insurance systems focusing on final predictions. In addition, the results show that the approach has an interesting potential to be used in routine for stabilizing all the new MIR equations predicting direct and indirect parameters.
Author address
Authors Fernández Pierna, J.A., Grelet, C., Baeten, V., Dardenne, P., Abbas, O., Dehareng, F.