Comparison of PLS, PCR and MLR for the quantitative determination of foreign oils and fats in butter fat of several European countries by its triglyceride composition
Three methods for evaluation of gas chromatographic data have been compared. Multiple linear regression as developed by Precht, principal component regression, and partial least square regression methods have been applied for the detection of foreign fat added to pure butter fat samples from several European countries. A calibration model was built for the detection of various vegetable oils and lard. The MLR as developed for German butter fat is found to be appropriate for the detection of the addition of about 3-5 % foreign fat depending on the formula used. PCR calibration leads to a model with 11 factors indicating a detection limit of about 3 % foreign fat added. PLS seems to offer the lowest detection limits (of about 2 %) of the methods compared.
Bibliographic Reference: Article: Lebensmittel Untersuchung und Forschung (1995)
Record Number: 199511215 / Last updated on: 1995-10-10
Original language: en
Available languages: en