From Event: SPIE Defense + Commercial Sensing, 2020
The objective of this study was to evaluate the effect of the cutting method on the quality of the dried ginger (Zingiber officinale Rosc.) by NIR hyperspectral imaging and computer vision systems. The cutting method of ginger was done vertically (slices) and horizontally (splits). The mean spectra were extracted from the collected NIR hyperspectral images (950-1,655 nm) for individual ginger samples and the partial least squares regression (PLSR) was employed to establish the prediction models. Determination coefficient (R2) of PLSR models based on non-pretreatment spectra for predicting moisture contents and rehydration rates of ginger samples were 0.960 and 0.957, respectively. The prediction maps of ginger slices and splits showed the same dehydration and rehydration patterns, which the moisture contents and rehydration rates in center parts were higher than edges. However, the shrinkage rates of ginger slices were higher than splits, while rehydration rates of ginger splits were higher than slices.
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Xiaohui Lin and Da-Wen Sun, "Investigation of moisture distribution of ginger slices and splits during hot-air drying and rehydration procedures by NIR hyperspectral imaging," Proc. SPIE 11421, Sensing for Agriculture and Food Quality and Safety XII, 114210D (Presented at SPIE Defense + Commercial Sensing: April 28, 2020; Published: 22 April 2020); https://doi.org/10.1117/12.2558213.