A near-infrared spectroscopic (NIRS) sensing system was developed on an experimental basis for the quality determination of three major milk constituents (fat, protein and lactose) and somatic cell count (SCC) of non-homogenized milk. The NIRS sensing system was used for acquiring NIR spectra of non-homogenized milk during milking in an automatic milking system (milking robot) over the wavelength range of 700 nm to 1050 nm. The three major milk constituents were analyzed for reference data using a MilkoScan instrument, while SCC was analyzed using a Fossomatic instrument.We developed calibration models using partial least square (PLS) regression analysis, and the precision and accuracy of the models was validated.The coefficients of determination (r2), standard errors of prediction (SEP) and bias were 0.98, 0.23% and 0.00% for fat, 0.72, 0.25% and 0.00% for protein, 0.54, 0.15% and 0.00% for lactose,and 0.63, 0.48 Log SCC/mL and 0.00 Log SCC/mL for SCC respectively. These results show that the NIRS sensing system developed in this study could be used for online real-time determination of milk quality in a milking robot. The system can provide dairy farmers with information on milk quality and physiological status of each cow and therefore, give them feedback control for improving dairy farm management. By using the NIRS system, dairy farmers will be able to produce high-quality milk and precision dairy farming will be realized.


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    Titel :

    NON-DESTRUCTIVE ONLINE REAL-TIME MILK QUALITY DETERMINATION IN A MILKING ROBOT USING NEAR-INFRARED SPECTROSCOPIC SENSING SYSTEM


    Beteiligte:
    Iweka, P. (Autor:in) / Kawamura, S. (Autor:in) / Mitani, T. (Autor:in) / Koseki, S. (Autor:in)

    Erscheinungsdatum :

    2018-12-31


    Anmerkungen:

    Arid Zone Journal of Engineering, Technology and Environment; Vol 14 No SPi4 (2018): AZOJETE - CIGR Section VI Special Issue: Innovation & Technologies for Sustainable Agricultural Production & Food Sufficiency; 121-128 ; 2545-5818 ; 1596-2490


    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    600 / 629



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