Industrial validation of fourier transform infrared trans and lodine value analyses of fats and oils

A Fourier transform infrared (FTIR) edible oil analysis package designed to simultaneously analyze for trans content, cis content, iodine value (IV), and saponification number (SN) of neat fats and oils by using calibrations based on pure triglycerides and derived by application of partial-least-squares (PLS) regression was assessed and validated. More than 100 hydrogenated rapeseed and soybean samples were analyzed by using the edible oil analysis package as well as the newly proposed modification of the AOCS IR trans method with trielaidin in a trans-free oil as a basis for calibration. In addition, ∼1/3 of the samples were subsequently reanalyzed by gas chromatography (GC) for IV and trans content. The PLS approach predicted somewhat higher trans values than the modified AOCS IR method, which was traced to a combination of the inclusion of trilinolelaidin in the calibration set and the effects of baseline fluctuations. Eliminating trilinolelaidin from the triglyceride standards and the use of second-derivative spectra to remove baseline fluctuations produced excellent concurrence between the PLS and modified AOCS IR methods (mean difference of 0.61% trans). Excellent internal consistency was obtained between the IV and cis and trans data provided by the edible oil analysis package, and the relationship was close to that theoretically expected IV=0.86 (cis + trans)]. The IV data calculated for the GC-analyzed samples matched the PLS IV predictions within 1 IV unit. The trans results obtained by both IR methods were linearly related to the GC data; however, as is commonly observed, the GC values were significantly lower than the IR values, the GC and IR data being related by a slope factor of ∼0.88, with an SD of ∼0.80. The concurrence between the trans data obtained by the two FTIR methods, and between the FTIR and GC-IV data, as well as the internal consistency of the IV, cis and trans FTIR predictions, provides strong experimental evidence that the edible oil analytical package measures all three variables accurately. Co-Director, McGill IR Group.