Hyperspectral imaging of intact bell peppers

Abstract

Agricultural engineering technologies have successfully addressed certain challenges by the use of advanced sensors and machine vision technologies. The objective of this study was to develop a non-destructive method to evaluate and to map quality indices in bell pepper. Three cultivars of bell pepper (‘Ever Green’, ‘No. 117’ and ‘Celica’) were studied during maturation by using hyperspectral imaging in the visible and near-infrared (550–850 nm) region. Peppers were marked in the flowering stage and 20 samples from each variety were collected weekly, along a growing period of seven weeks, until full growth. Quality parameters like total soluble solids, total chlorophyll, carotenoid and ascorbic acid content were determined and correlated with the spectral data. Images of intact peppers were collected by an acousto-optic-tuneable-filter (AOTF) hyperspectral charged-coupled-device (CCD) camera, in spectral resolution of 5 nm. Spectral information of the hyper cubes was analysed by chemometric procedures. Partial least squares regression was used for model development. Comparisons were made between the PLS regression analysis of the reflectance spectra (R), and the pre-processed spectra such as the first derivative (D1R), log(1/R), D1(log(1/R)) and D2(log(1/R)). Models were established to predict the quality attributes creating the basis for multiple sampling of a particular fruit or individual peppers from many fruits in the same time. High correlations were obtained by the established models with coefficients of determination of 0.95, 0.95, 0.97, and 0.72 for total soluble solids, total chlorophyll, carotenoid and ascorbic acid content, respectively.