Comparison of milk analysis performance between NIR laboratory analyser and miniaturised NIR MEMS sensors

Sanna Uusitalo, Ben Aernouts, Juha Sumen, Eero Hietala, Mikko Utriainen, Matti Pastell

    Research output: Contribution to conferenceConference AbstractScientificpeer-review


    The capacity of milk production of dairy farms is not only dependent on farm animal counts, but is also affected by the ability of single milking cows
    to convert the energy uptake into milk secretion. The ability of a farmer to predict the effect of farm animal diet to the milking capacity requires
    information on the animal behaviour as well as on the near instant feedback of the milk composition in regards to the fed diet. The
    conventional method for information on milk composition at farms is sending samples to central laboratories for comprehensive analysis.
    However, many farms would consider alternative on-site analysis if cost-effective and reliable options would be available. In this study, we
    have evaluated the ability of affordable Micro Electro Mechanical System (MEMS) based NIR sensors on the analysis of milk ingredients such as
    fat and protein. These NIR MEMS sensors use Fabry-Perot Interferometers for wavelength scanning, which enables compact sensor packaging
    and fast signal collection. The spectral information content of milk was recorded using automated sampling device with integrated four NIR
    MEMS sensors. The results were compared from three different wavelength areas 1.1 - 1.4 µm, 1.7 – 2.0 µm and 2.2 – 2.5 µm in transmission and
    one wavelength area 1.7 – 2.0 µm in reflection method. The achieved MEMS NIR results were compared to the golden standard NIR spectrometer
    (Si-PDA) results
    Original languageEnglish
    Publication statusPublished - 17 Jun 2019
    MoE publication typeNot Eligible
    EventICAR conference 2019 - Prague, Czech Republic
    Duration: 17 Jun 201921 Jun 2019


    ConferenceICAR conference 2019
    Country/TerritoryCzech Republic
    Internet address


    • OtaNano


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