Non-invasive prediction of mango quality using near-infrared spectroscopy: Assessment on spectral interferences of different packaging materials

Different packaging materials pose a challenging work for the non-invasive determination of contaminated food quality using near infrared (NIR) spectroscopy. This study investigated the effects of polyvinyl chloride (PVC), polyethylene (PE) and expandable polyethylene (EPE) packaging materials on the prediction of mango firmness (FI), dry matter (DMC), soluble solids (SSC), and titratable acidity (TA) using NIR. Obvious spectral interferences resulting from the three packaging materials were particularly located at 1150-1250 nm and 2320-2400 nm, and significantly reduced NIR prediction accuracy. Spectral filtering methods had the potential to reduce the NIR spectral interferences of packaging materials for contaminated mangoes' quality assessment. Besides, least squares support vector machine (LS-SVM) models with the combination of spectral filtering and variable selection method can further improve the FI, SSC, DMC and TA prediction of packaged mango, with RPD values from 2.31 to 3.05. Consequently, it is crucial to consider suitable spectral filtering and variable selection methods to improve NIR prediction of quality of packaged food.

Automated summary

Different packaging materials, such as PVC, PE, and EPE, have significant effects on the near infrared (NIR) prediction of mango quality. The spectral interferences resulting from these materials can be reduced using spectral filtering methods. Combining spectral filtering with variable selection methods can further improve the prediction accuracy of mango quality parameters.