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| Online detection of soluble solids content for Gannan navel by visible-near infrared diffuse transmission spectroscopy |
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| DOI：10.16968/j.issn.1004-894X.2016.09.016 |
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| Abstract: |
| The feasibility was investigated for online detection of soluble solids content（SSC） of Gannan navel
orange by visible-near infrared（visible-NIR） diffuse transmission spectroscopy coupled with least square support
vector machine（LS-SVM） algorithm. 139 samples were divided into the calibration and prediction sets（103∶
36）for developing calibration models and assessing their performance. The partial least square（PLS） regression
and LS-SVM model were developed with the pretreatment by the combination of first derivative（1D），Smoothing
and multiplicative scattering correction（MSC）. The new samples of prediction set were applied to evaluate the
performance of the model. Compared with PLS model，the performance of LS-SVM model was better with the root
mean square error of prediction（RMSEP） of 0.6423% and the correlation coefficient of prediction of 0.9059. And
the spectral dimension reduction method of principal component analysis（PCA） and the kernel function of radial
basis function（RBF） were suitable to improve the predictive ability of LS-SVM model. The results suggested that
it was feasible for online detection of SSC of Gannan navel orange by visible-NIR diffuse transmission spectroscopy
combined with LS-SVM algorithm. |
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