Non-destructive prediction of quality parameters of sweet lemon (Citrus limetta) by Vis/SWNIR spectroscopy

Document Type : Research Paper

Authors

1 M.Sc. student, Isfahan University of Technology

2 Faculty member

3 Faculty member, Isfahan University of Technology

4 Faculty member, University of Kashan

Abstract

In this study, the potential of visible and short-wavelength near infrared spectroscopy for nondestructive predicting the SSC, MC and TA of sweet lemon was evaluated. The spectra of 120 sweet lemon samples were acquired in the interactance and transmission modes and the wavelength region of 400 to 1100 nm. Different preprocessing methods, including Savitzky-Golay, multiplicative scatter correction, baseline correction, standard normal variate, 1st derivative, and the combination of these methods were applied to the raw spectra. The most appropriate preprocessing methods were then selected for building the predictive models using partial least squares method. The results showed that the best SSC and MC predictive models were achieved in the interactance mode, while the best TA predictive model was obtained in the transmission mode. Among three quality parameters, the best models were resulted in the prediction of SSC, MC, and TA, respectively. The SSC with a correlation coefficient (rp) of 0.87 and a root mean squares error of prediction (RMSEP) of 0.5 °Brix, MC with a rp of 0.88 and an RMSEP of 0.57%, and TA with a rp of 0.74 and an RMSEP of 0.0076% could be predicted.

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Main Subjects


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