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  • Title: [Nondestructive measurement of sugar content of Hami melon based on diffuse reflectance hyperspectral imaging technique].
    Author: Ma BX, Xiao WD, Qi XX, He QH, Li FX.
    Journal: Guang Pu Xue Yu Guang Pu Fen Xi; 2012 Nov; 32(11):3093-7. PubMed ID: 23387186.
    Abstract:
    The research on nondestructive test for detecting the sugar content of Hami melon by the technology of hyperspectral imaging was put forward. The research used the hyperspectral imaging system to get the diffuse reflective spectrum information (400 - 1 000 nm) of anilox class Hami melon sugar content, chose effective whole wavelength (500 - 820 nm)to do the modeling regression analysis the sugar content of Hami melon. The research compared the correction method of MSC and SNV, and also compared the influence of accuracy of modeling in terms of the spectrum pretreatment methods of original spectrum, first order differential, second order differential; Using the methods of PLS, SMLR and PCR, the comparative analysis of sugar content detection model effect with skin Hami melon and peel Hami melon was conducted. The results showed that after the original spectrum being processed by MSC and first order differential spectrum, modeling effect could be very good using the method of PLS and SMLR. Synthesizing correction set correlation coefficient and forecast modeling effect, it's feasible to detect the sugar content of skin Hami melon by the PLS method, with a correction sample correlation coefficient (R(c)) of 0.861 and the lower root mean square errors of correction (RMSEC) of 0.627, and a prediction sample correlation coefficient (R(p)) of 0.706 and root mean square errors of prediction (RMSEP) of 0.873. The best effect to detecti the sugar content of peel Hami melon was obtained by the SMLR method with a correction sample correlation coefficient (R(c)) of 0.928 and the lower root mean square errors of correction (RMSEC) of 0.458, with a Prediction sample correlation coefficient (R(p)) of 0.818 and root mean square errors of prediction (RMSEP) of 0.727. The results of this study indicate that the technology of hyperspectral imaging can be used to predict the sugar content of Hami melon.
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