Abstract
This chapter reports the results of evaluation of near-infrared (NIR) spectroscopy for measurements of fat content in the raw milk and the influences of spectral region, sample thickness and different spectral preprocessing techniques on the measurement accuracy. Transmittance (T) spectra of 260 milk samples were acquired in the wavelength range from 400 to 2,500 nm using quartz sample cells with different pathlengths (1 mm, 4 mm and 10 mm). The fat content was predicted by partial least squares (PLS) regression, and absorbance bands important for fat determination were found based on the highest PLS regression vector coefficients. The spectral region and the sample thickness were found to be significant factors influencing the accuracy of milk fat determination. The best prediction model was obtained for region of 1,100–2,400 nm in combination with 1 mm sample thickness and first-derivative spectral transformation with standard error of cross-validation of 0.113, and cross-validation correlation coefficient 0.9983. For the spectral region from 700 to 1,100 nm, the best result was found for 10 mm sample thickness and no transformation. The most influential absorbance bands for the determination of fat were related to CH bands of fat and OH bands of water.
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Tsenkova, R., Muncan, J. (2022). Milk Fat Measurement. In: Aquaphotomics for Bio-diagnostics in Dairy. Springer, Singapore. https://doi.org/10.1007/978-981-16-7114-2_4
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