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Predicting Apple Fruit Firmness and Sugar Content Using Near-Infrared Scattering Properties

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

Citation:  Paper number  036212,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.14161) @2003
Authors:   Renfu Lu
Keywords:   Fruit, Apple, Firmness, Soluble Solids, Near-Infrared, Scattering, Multispectral Imaging, Neural Networks

Firmness and soluble solids content (SSC or total sugar content) are important attributes for apples and many other fresh fruits. This research investigated the feasibility of using multispectral imaging to quantify light backscattering profiles from apple fruit for predicting firmness and SSC. Backscattering images, generated from a focused broadband beam (0.8 mm diameter), were obtained from Red Delicious apples for five selected spectral bands (10 nm bandpass) between 670 nm and 1060 nm. Ratios of scattering profiles for different spectral bands were used as inputs to a neural network to predict fruit firmness and SSC. Three ratio combinations with four spectral bands (680 nm, 880 nm, 905 nm, and 940 nm) gave the best predictions of fruit firmness, with r = 0.87 and the standard error of prediction (SEP) = 5.8 N. Two ratio combinations with three spectral bands (880 nm, 905 nm and 940 nm) were needed to predict the SSC with r =0.77 and SEP = 0.78 Brix. The multispectral imaging technique is promising for grading and sorting of fruit for firmness and sweetness.

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