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Discriminant analysis of vegetable oils by near‐infrared reflectance spectroscopy
Author(s) -
Bewig Karen M.,
Clarke Andrew D.,
Roberts Craig,
Unklesbay Nan
Publication year - 1994
Publication title -
journal of the american oil chemists' society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.512
H-Index - 117
eISSN - 1558-9331
pISSN - 0003-021X
DOI - 10.1007/bf02541556
Subject(s) - mahalanobis distance , linear discriminant analysis , iodine value , soybean oil , canola , vegetable oil , mathematics , infrared spectroscopy , chemistry , food science , statistics , organic chemistry
Discriminant analysis of four vegetable oil types (cotton‐seed, peanut, soybean and canola) was performed by near‐infrared reflectance spectroscopy. The objective of this study was to provide an alternate method to differentiate vegetable oil types and to classify unknown oil samples. Second derivative spectra of the vegetable oils were subjected to discriminate analysis with Mahalanobis distances principles. A four‐wavelength (1704, 1802, 1816 and 2110 nm) equation was derived, which produced a sum of inverse squared distance of 0.0548. Although all four groups were successfully separated with a chi square of 18.9, the soybean oil group is more dispersed in space than the other three groups. Iodine values of the soybean oil samples suggest that this group may have a wide range of hydrogenation states. Discriminant analysis can be successfully used to differentiate vegetable oil types and possibly could also be used to differentiate degree of hydrogenation and oxidative states of oils.