Abstract

The presence of milk fat globule emulsion produces scattering phenomena on near infrared (NIR) radiation through the raw milk. Numerically, 80% of milk fat globules have a diameter of less than 3μm interfering with the radiation having a wavelength from 1 μm to 2.5 μm with a radiation dispersion in all directions. Consequently, the NIR transmitted radiation does not behave in accordance with Lambert–Beer's law: the NIR spectra of milk samples with high fat content have high offset values and lower specific absorptions than those of samples with lower fat levels. Usually, this problem is reduced by acting at the level of sample preparation (homogenisation), of optical geometry (transflectance mode coupled with the use of an integrating sphere to collect the widespread radiation) and using chemometric regression models able to optimise non-linear spectral responses. Transmittance measurements have already been exploited for the determination of macro-composition in the agro-food and in the dairy fields. In this work, a set of 150 individual milk samples, collected over three days from a single farm with 49 milking cows, was analysed with Fourier transform-NIR apparatus in order to study the effects of scattering on partial least squares predictors for casein. The spectra of non-homogenised raw whole milk and the respective skimmed samples were collected in transmission mode. Using the true scattering curves obtained by subtraction from the raw milk spectra of skimmed milk spectra the extended multiplicative scatter correction (EMSC) estimate of scattering effects was optimised. EMSC uses polynomial filters in modelling the aspecific absorptions due to the scattering effects. The correct scatter elimination can help in the individuation and interpretation of the true predictors in calibration procedures.

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