2021 Volume 83 Issue 4 Pages 282-289
Near-infrared (900-1700 nm) hyperspectral imaging was used to visualize the sugar content distribution in cross-sections of the Japanese pear “Nikkori.” The average absorbance spectrum (approximately 11×11 mm) and sugar content for each block of the fruit cross section were measured using a grid gauge. A sugar content estimation model with high prediction accuracy was successfully developed using partial-least-squares (PLS) regression analysis. The prediction coefficient of determination (R2 p) between the predicted and measured sugar content was 0.73, with a root mean square error of prediction (RMSEP) of 0.68. The coefficient of determination between the mean value of the sugar-content distribution mapped by this model and the mean value of the measured sugar-content distribution was 0.91.
