Pitiporn RitthiruangdejRonnarit RitthironHideyuki ShinzawaYukihiro OzakiMahidol UniversityKasetsart UniversityNational Institute of Advanced Industrial Science and TechnologyKwansei Gakuin University2018-05-032018-05-032011-11-15Food Chemistry. Vol.129, No.2 (2011), 684-69218737072030881462-s2.0-79959979261https://repository.li.mahidol.ac.th/handle/20.500.14594/11237The objective of the present study was to evaluate the ability of near-infrared (NIR) spectroscopy to predict chemical compositions of Thai steamed pork sausages in relation to different types of sample presentation forms of NIR measurements (with and without plastic casing). NIR spectra of sausages were scanned to predict the chemical compositions, protein, fat, ash and carbohydrate non-destructively. NIR spectrum features of the sausage samples were strongly influenced by physical properties of the samples, such as the presence of plastic casing and inhomogeneous physical structure inside the samples, yielding significant baseline fluctuations. Thus, regression models were developed using partial least squares (PLS) regressions with two pretreatment methods, namely multiplicative scatter correction (MSC) and second derivative, which overcame the baseline problems. The prediction results suggest that the contents for the protein, fat and moisture can be estimated well with the proper selection of the pretreatment method. © 2011 Elsevier Ltd. All rights reserved.Mahidol UniversityAgricultural and Biological SciencesChemistryArticleSCOPUS10.1016/j.foodchem.2011.04.110