Derivative FTIR spectroscopy for cluster analysis and classification of morocco olive oils

Authentication of the botanical and geographical origin of distillers dried grains and solubles (DDGS) by FT-IR spectroscopy

Distillers dried grains and solubles (DDGS) were investigated with attenuated total reflection FT-IR spectroscopy both directly in their solid state and as the isolated oils (fat fractions). The collected spectra were evaluated in a first step with principal component analysis (PCA) according to the botanical origin (corn, rice, wheat) and the geographical origin (Canada, China, European Union, India, United States) of the DDGS. In a second step, statistical models were constructed for the characterization of the botanical and geographical origin using linear discriminant analysis (LDA) and soft independent modeling of class analogy (SIMCA). For this purpose, the botanical origin was investigated more deeply for corn and wheat as the most important raw materials used for DDGS production. Also, the geographical origin was investigated exemplary for corn DDGS, derived from China and the United States. Models were validated by a randomized batchwise procedure and showed satisfactory classification rates, in most cases better than 80% correct classification.

Quantification and classification of corn and sunflower oils as adulterants in olive oil using chemometrics and FTIR spectra

Commercially, extra virgin olive oil (EVOO) is subjected to be adulterated with low-price oils having similar color to EVOO. Fourier transform infrared (FTIR) spectroscopy combined with chemometrics has been successfully used for classification and quantification of corn (CO) and sunflower oils (SFOs) in EVOO sets. The combined frequency regions of 3027–3000, 1076–860, and 790–698 cm⁻¹ were used for classification and quantification of CO in EVOO; meanwhile, SFO was analyzed using frequency regions of 3025–3000 and 1400–985 cm⁻¹. Discriminant analysis can make classification of pure EVOO and EVOO adulterated with CO and SFO with no misclassification reported. The presence of CO in EVOO was determined with the aid of partial least square calibration using FTIR normal spectra. The calibration and validation errors obtained in CO's quantification are 0.404 and 1.13%, respectively. Meanwhile, the first derivative FTIR spectra and PLS calibration model were preferred for quantification of SFO in EVOO with high coefficient of determination (R²) and low errors, either in calibration or in validation sample sets.