Novel non-destructive quality assessment techniques of onion bulbs: a comparative study.

This study was designed to compare the performances of four different non-destructive methods of assessing onion quality, one of which was based on near-infrared spectroscopy, and three of which were based on spectral imaging. These methods involve a combination of wavelengths from visible to near-infrared with different acquisition systems that were applied to discriminate between pre-sorted onions by in situ measurements of the onion surface. Compared with the partial least squares discriminant analysis classification models associated with different methods, hyperspectral imaging (HSI) with both static horizontal and rotating orientation obtained a higher level of sensitivity and specificity with a lower classification error than did other methods. Moreover, models built with the reduced variables did not lower the model performances. Overall, these results demonstrate that HSI with selected wavelengths would be useful for further developing an improved real-time system for sorting onion bulbs.