A mathematical procedure based on Canonical Correlation Analysis (CCA)
was used in order to assign the wavelengths of the near-infrared spec
tra through knowledge of the mid-infrared spectra. The relevance of th
e treatment was tested on commercial oils that mainly differ in their
level of unsaturation. Initially, two separated Principal Component An
alyses (PCAs) were performed on the near- and mid-infrared data to ove
rcome the high intercorrelations across the wavelengths. CCA was then
applied to the resulting principal components. Near- and mid-infrared
canonical variates were assessed so that they achieved maximum correla
tion. The procedure makes it possible to draw CCA spectral patterns th
at exhibit significant positive and negative peaks. The first near-inf
rared canonical variate was highly correlated with the first mid-infra
red canonical variate (r2 = 0.97). The corresponding near- and mid-inf
rared CCA spectral patterns were therefore given the same interpretati
on. The mid-infrared pattern opposed negative peaks characteristic of
CH2 groups to the positive peaks of CH3 and =CH groups. Consequently,
in the near-infrared pattern, the positive peaks at 1708, 2140, 2170,
and 2480 nm were assigned to CH3 or =CH groups, and the negative peaks
at 2304, 2344, and 2445 nm were assigned to CH2 groups. A more precis
e interpretation was obtained by comparing the wavelengths observed to
theoretical values and to previous assignments.