Authenticity of almond flour using handheld near infrared instruments and one class classifiers

Abstract:

Almonds (Prunus dulcis) are highly nutritious fruit seeds and are widely consumed, mainly in powder form (flour). With considerable economic value, this product has become a candidate for adulterations to increase profit by lowering the product cost. In the present work, methods were developed for identification of almond flour adulteration, using near infrared spectroscopy (NIR). Three different portable NIR instruments were evaluated to verify the authenticity of almond flours and the results were compared with a benchtop FT-NIR. Fifty-four almond flours of different varieties were adulterated with low-cost flours widely consumed in Brazil. Soft independent modeling of class analogies (SIMCA), Data driven SIMCA (DD-SIMCA), and One-class partial least squares (OCPLS) were used as classification methods. PLSR was employed to predict the purity of the sample. The classification results achieved 100% sensitivity and more than 95% specificity for samples with adulterant concentration of 5% (w/w) or above. The PLS models showed coefficients of determination (R²) greater than 0.90 for all models and RMSEP values between 3.2% and 4.8% for purity. The results of the multivariate models indicate that the portable NIR instruments are efficient for the identification and quantification of adulterated almond flour.