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Imaging Spectroscopy for Assessing Internal Quality of Apple Fruit

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  036012,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.14120) @2003
Authors:   Renfu Lu
Keywords:   Fruit, Apples, Firmness, Soluble Solids, Near-Infrared, Imaging Spectroscopy, Neural Networks

Nondestructive sensing of internal quality would allow the fruit industry to deliver better quality, more consistent fruit to the consumer. The objective of this research was to study the feasibility of using an imaging spectroscopy technique to predict the firmness and soluble solid content (SSC) of apple fruit. An imaging spectroscopy system was assembled to acquire scattering images from apple fruit over the spectral region between 500 nm and 1000 nm. Computer algorithms were developed using the neural network method to relate the mean and standard deviation spectra to the firmness and SSC of apple fruit. Preliminary analysis showed that the imaging spectroscopy system was able to predict fruit firmness with r=0.83 and the standard error of prediction (SEP) of 7.3 N for Golden Delicious, and r=0.71 and SEP=6.1 N for Red Delicious. Better SSC predictions were obtained with r = 0.88 and 0.80,and the SEP of 0.72 and 0.81 for Golden Delicious and Red Delicious apples, respectively.

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