Non‐destructive estimation peach SSC and firmness by mutispectral reflectance imaging

Abstract

Mutispectral reflectance imaging combined with multi‐linear analysis appears as a new, efficient and cheap method for detecting soluble solids content (SSC) and firmness of peach. Six hundred spectral images from a combination of filter 632, 650, 670, 780, 850, and 900 nm were acquired for each peach sample. The Lorentzian distribution (LD), Gaussian distribution (GD) and Exponential distribution (ED) with three parameters were used to fit scattering profiles of each spectral imaging. LD was found to be the best function for fitting gray distribution of imaging. The multi‐linear regression model was developed relating Lorentzian parameters to fruit firmness and SSC using a single wavelength, double wavelengths, three wavelengths and four wavelengths respectively. The best model with four wavelengths was able to predict peach flesh firmness with r = 0.949, standard error of prediction (SEP) = 1.56 N, and predict peach SSC with r = 0.970, SEP = 0.69° Bnx. Results show that the multispectral scattering imaging is anon‐destructive, fast and cheap method for estimating fruit SSC and firmness.