All data analysis was done on MATLAB R2014a (The MathWorks, MA, USA), Unscrambler Version 9.7 (CAMO Software A/S, Trondheim, Norway), and IBM SPSS Statistics Version 20 (IBM Corporation, NY, USA). GA-PLS was run on Leardi's GA-PLS Toolbox in Matlab [41 ].
Unscrambler version 9
Manufactured by CAMO Software
Sourced in United States, Norway
Unscrambler Version 9.7 is a comprehensive software package designed for multivariate data analysis. It provides tools for processing, visualizing, and interpreting complex datasets. The software is suitable for a wide range of applications, including chemometrics, spectroscopy, and process control.
Automatically generated - may contain errors
Lab products found in correlation
2 protocols using unscrambler version 9
1
Multivariate Analysis of Experimental Data
2
Milk Sample Classification via PCA and PLS-DA
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Data processing consisted in the sample recognition and classification. Sample recognition was done using Principal Component Analysis (PCA). Classification models were calculated using Partial Least-Squares regression-Discriminant Analysis (PLS-DA), which is a variant of PLS regression with dummy-dependent variables coding class membership. Two classes were modelled: samples prepared from raw milk and samples prepared from pasteurized milk. Validation was done using cross-validation with 4 segments due to the small number of samples. Unscrambler (version 9.7, CAMO Software AS, Oslo, Norway) was used for PCA and PLS-DA.
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