In-depth chemometric strategy to detect up to four adulterants in cashew nuts by IR spectroscopic techniques

An untargeted strategy was developed to determine cashew nuts adulteration with Brazilian nuts, pecan nuts, macadamia nuts and peanuts. A one-class SIMCA model was developed for the cashew non-adulterated samples by means of two spectroscopic techniques: Near-Infrared (NIR) and Attenuated Total Reflection-Fourier Trans-form Infrared (ATR-FTIR). Receiver operating characteristic (ROC) curves have been proved to be useful to optimize class limits, both for the NIR and ATR-FTIR models, allowing to balance the values of the performance parameters. An increase in the sensitivity of the training and test set has been obtained from 79% with NIR and 85% with ATR-FTIR to 93% in both cases. As a result, the specificity has slightly decreased from 100% with NIR and a range of 90-98% with ATR-FTIR to a range of 82-98% and 84-96%, respectively. The implementation of high-level data fusion to the classification results obtained from NIR and ATR-FTIR, considering the limit value optimized by ROC curves, allowed the improvement of the performance parameters of the untargeted strategy. Obtaining sensitivity values for the training and test set of 100% and 93%, respectively. Specificity values of 100% were obtained for the detection of Brazilian nuts, macadamia nuts and peanuts, while for pecans it was 98%.

Automated summary

An untargeted strategy was developed to detect the adulteration of cashew nuts with other nuts. A one-class SIMCA model was established using spectroscopic techniques and the class limits were optimized using ROC curves. The implementation of high-level data fusion improved the performance of the strategy.