Nondestructive quality evaluation of banana slices during microwave vacuum drying using spectral and imaging techniques

摘要

Microwave vacuum drying of banana slices was investigated in this study. Near-infrared hyperspectral imaging (NIR-HSI, 950-1650nm with 7nm increments) and chemometrics were used to predict moisture content, hardness, and fracturability of banana slices during the entire drying process. A computer vision system was also used to evaluate browning index (BI) of slices at different drying stages; dark brown spots observed in slices were subjected to over 21-min total microwave heating. In addition, thermal imaging results showed that higher temperature occurred in the central part of banana slices. Calibration models were developed based on partial least square regression and support vector machine regression (SVM-R) using mean spectra with standard normal variate pretreatment. The results showed that SVM-R models performed better in the prediction of the three quality attributes with of 0.996, 0.927, and 0.961, respectively. The moisture distribution maps were generated using NIR-HSI; uniformly distributed moisture patterns were observed in each drying batch with small variations observed within individual slices. This study demonstrated the potential of spectral and imaging techniques for nondestructive quality evaluation of food products during drying processes.