2002
DOI: 10.1255/jnirs.346
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Effect of Multiplicative Scatter Correction on Wavelength Selection for near Infrared Calibration to Determine Fat Content in Raw Milk

Abstract: The effect of multiplicative scatter correction (MSC) on wavelength selection for near infrared (NIR) calibration to determine fat content in raw milk was investigated. Short-wave NIR spectra (700-1100 nm) of raw milk samples were measured. The calibration equations for fat content were performed by multiple linear regression (MLR) using original, second derivative and MSC-treated spectra. It was found that first wavelength selection from the fat absorption band for a calibration equation was generally effecti… Show more

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Cited by 54 publications
(28 citation statements)
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“…[26] The optimum spectral regions were determined by creating a section using the X-loading weights and correlation coefficients and performing a comparison with the modeling effect of full wavelength. [27][28][29] …”
Section: Ew Selectionmentioning
confidence: 99%
“…[26] The optimum spectral regions were determined by creating a section using the X-loading weights and correlation coefficients and performing a comparison with the modeling effect of full wavelength. [27][28][29] …”
Section: Ew Selectionmentioning
confidence: 99%
“…Moreover, the possible convergence of the different models on the same regions brings to the identification of relevant wavelengths for the prediction of fat quality related properties. The wavelength selection has been regarded as an important subject by many authors before (Panford and deMan 1990;Wu et al 2009;Balabin and Smirnov 2011;Chen et al 2002), because it constitutes a critical step in the perspective of the development of hand-held devices. In fact, the selection of limited spectral regions for the calculation of multivariate calibration models could allow the development of simple, fast and cheap systems that are required for effective industrial applications.…”
Section: Introductionmentioning
confidence: 99%
“…The short-wave NIR region (780-1100 nm) has been previously used to monitor several parameters of milk (Chen, Iyo, Terada, & Kawano, 2002;Sasic & Ozaki, 2001;Tsenkova et al, 1999). Indeed, several on-line sensors have been developed, for instance, an online sensor to measure the fat content in milk in the range of 800-1100 nm (Brennan, Alderman, Sattler, O'Connor, & O'Mathuana, 2003) or an on-line sensor to analyse the fat, lactose and protein content, somatic cell count and urea nitrogen in the range of 600-1050 nm (Kawamura et al, 2008).…”
Section: Introductionmentioning
confidence: 99%