Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6664674 | Journal of Food Engineering | 2018 | 9 Pages |
Abstract
Near-infrared (NIR) hyperspectral imaging was used to evaluate soluble solids content (SSC) in 'Fuji' apples [Malus sylvestris (L.) Mill. var. domestica (Borkh. Mansf.)]. Eighty 'Fuji' apples were analyzed by collecting four small block samples from each one (approximately 2.0â¯cmâ¯Ãâ¯2.0â¯cmâ¯Ãâ¯1.5â¯cm). Partial least squares (PLS) regression analysis was performed to determine the relation between SSC reference data and NIR spectral data measured from each sample. The cross-validation coefficient of determination (r2) between predicted and measured SSC values is 0.89 with a root mean squared error of cross-validation (RMSECV) of 0.55%. Then, we successfully mapped SSC at a high spatial resolution (375â¯Î¼m per pixel). In addition, the absorption and reduced scattering coefficients of the measured samples were determined based on a diffusion theory model. The absorption coefficients are positively correlated to the SSC values (chemical information), whereas water cored tissue content (physical information) causes a characteristic change in light scattering coefficients. The fitting results were validated by Monte Carlo simulation, and the light penetration depth in 'Fuji' apples was estimated to be around 0.33â¯cmâ¯at 1198â¯nm and 0.17â¯cmâ¯at 1450â¯nm, respectively.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Chemical Engineering (General)
Authors
Te Ma, Xinze Li, Tetsuya Inagaki, Haoyu Yang, Satoru Tsuchikawa,