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ROI: region of interest. The solid horizontal line was set by the threshold value 1. VIP: Variable importance projection. SVR: support vector machine regression. Open Access Feature Paper Article. Abstract The objective of this study was to develop a nondestructive method to evaluate chemical components such as moisture content MC , pH, and soluble solid content SSC in intact tomatoes by using hyperspectral imaging in the range of — nm.

The mean spectra of [ The objective of this study was to develop a nondestructive method to evaluate chemical components such as moisture content MC , pH, and soluble solid content SSC in intact tomatoes by using hyperspectral imaging in the range of — nm. The mean spectra of the 95 matured tomato samples were extracted from the hyperspectral images, and multivariate calibration models were built by using partial least squares PLS regression with different preprocessing spectra.

The results showed that the regression model developed by PLS regression based on Savitzky—Golay S—G first-derivative preprocessed spectra resulted in better performance for MC, pH, and the smoothing preprocessed spectra-based model resulted in better performance for SSC in intact tomatoes compared to models developed by other preprocessing methods, with correlation coefficients r pred of 0. The full wavelengths were used to create chemical images by applying regression coefficients resulting from the best PLS regression model.

These results obtained from this study clearly revealed that hyperspectral imaging, together with suitable analysis model, is a promising technology for the nondestructive prediction of chemical components in intact tomatoes. Abstract Models for determining contents of soy products in ground beef were developed using near-infrared NIR spectroscopy. Models for determining contents of soy products in ground beef were developed using near-infrared NIR spectroscopy.

Partial least squares PLS regression with full leave-one-out cross-validation was used to build prediction models. The results based on dispersive NIR spectra revealed that the coefficient of determination for cross-validation R cv 2 ranged from 0.