Quality Evaluation of Plant Products

Abstract

Hyperspectral imaging or imaging spectrometry combines the strengths of computer vision technology with optical spectroscopy. It is primarily suited for measurement of parameters that vary spatially both at the external surface of samples and internally within the samples. The parameters may be physical features such as incipient bruises or surface contamination, or chemical constituents such as sugar and acidity. While the acquisition of images generally follows the procedures of machine vision, adding a spectral dimension would require the rigor of multivariate statistics, also known as chemometrics, to find functional relationships between the measured values and target parameters. Its application to agriculture, particularly to post-harvest processing, has recently been explored by university research laboratories in order to develop new techniques for non-destructive measurement of quality.