Visible And Shortwave Near Infrared Research Articles

Comparison of different modes of visible and near-infrared spectroscopy for detecting internal insect infestation in jujubes

This study compared the abilities of the interactance, reflectance, and transmission modes of visible and near-infrared (Vis/NIR) spectroscopy in detecting internal insect-infested jujubes. Statistical analysis was performed to identify the effective wavelengths that best discriminated the insect-infested jujubes from intact jujubes and to derive a discriminant function in classifying the jujubes showing internal insect infestation and those that were free of infestation. The highest correct classification rates obtained from the above modes were 100%, 90.0%, and 97.0%, respectively. The interactance mode in the long-wave NIR (LWNIR) range is preferable to the transmission mode in the visible and short-wave near-infrared (VSWNIR) ranges. Furthermore, the transmission mode in the VSWNIR range displayed an obvious advantage over the reflectance mode in every range. The results indicate that it is possible to use both the interactance and transmission modes to develop a system in detecting the internal qualities of jujubes.

Nondestructive Differentiation of Panax Species Using Visible and Shortwave Near-Infrared Spectroscopy

Visible and short-wave near-infrared (Vis-SWNIR) spectroscopy was investigated to differentiate species of panax, including American Panax quinquefoliumI, Chinese Panax quinquefolium, and Chinese Panax ginseng. Principal component analysis (PCA) was applied before least-square support vector machine (LS-SVM) modeling, and the vast points of the spectral data (376–1,025 nm) were effectively reduced. PCA-LS-SVM differentiated species with 100% correct classification rate for the tested samples. In addition, effective wavelengths were selected according to modeling power, discrimination power, regression coefficients, loading weights, and genetic algorithms, respectively. The optimal and simplified LS-SVM model with 100% correct classification rate was achieved using the effective wavelengths selected by genetic algorithms. The results showed that Vis-SWNIR spectroscopy technique can be applied as a high accuracy and fast way for the qualitative discrimination of herb species.

Comparison of calibrations for the determination of soluble solids content and pH of rice vinegars using visible and short-wave near infrared spectroscopy

Visible and short-wave near infrared (Vis/SWNIR) spectroscopy combined with chemometrics was investigated for the fast determination of soluble solids content (SSC) and pH values of rice vinegars. Two hundred and twenty-five samples (45 for each variety) were selected randomly for the calibration set, whereas, 75 samples (15 for each variety) for the validation set, and the remaining 25 samples for the independent set. After some preprocessing, partial least squares (PLS) analysis was implemented for calibration models with different wavelength bands including visible, SWNIR and Vis/SWNIR regions. The best PLS models were achieved with Vis/SWNIR (550–1000 nm) region. Furthermore, different latent variables (5, 6, 7, 8 LVs) were used as inputs of least squares-support vector machine (LS-SVM) to develop the LV-LS-SVM models with grid search technique and RBF kernel. The optimal models were obtained with 6 LVs and they outperformed PLS models. Moreover, effective wavelengths (EWs) were selected according to regression coefficients. The EW-LS-SVM models were developed and an excellent prediction precision was achieved, and the effectiveness of the EWs was also validated. The correlation coefficient ( r), root mean square error of prediction (RMSEP) and bias for the best prediction by EW-LS-SVM were 0.999, 0.189 and 0.051 for SSC, whereas 0.999, 0.008 and −1.7 × 10 −3 for pH, respectively. The overall results indicated that Vis/SWNIR spectroscopy combined with LS-SVM could be applied as a high precision and fast way for the determination of SSC and pH values of rice vinegars.