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Application of Hyperspectral Technique for Color Classification Avocados Subjected to Different Treatments
Authors:Yousef Karimi  Neda Maftoonazad  Hosahalli S. Ramaswamy  Shiv O. Prasher  Michele Marcotte
Affiliation:(1) Food Science Department, McGill University, 21111 Lakeshore, Ste Anne de Bellevue, QC, H9X 3V9, Canada;(2) Biosystems Engineering Department, McGill University, 21111 Lakeshore, Ste Anne de Bellevue, QC, H9X 3V9, Canada;(3) Food Research and Development Centre, Agriculture and Agri-Food Canada, 3600 Casavant Boulevard West, St. Hyacinthe, QC, J2S 8E3, Canada;(4) Present address: Agricultural Engineering Research Institute, Zarghan, Fars, Iran;
Abstract:In this study, the applicability of hyperspectral technique, a fast and non-destructive, novel method was investigated for the color discrimination of avocados subjected to different treatments. Fruits like avocados are coated with edible films to extend their shelf life. Using different formulations of coating with varying pectin, beeswax, and sorbitol contents, nine different coating preparations with potential to influence the ripening behavior of avocados were developed. Avocados were coated with these formulations, air-dried, and stored at room temperature. Concurrently, the reflectance responses of the avocado fruits were measured in 2,151 wavebands (350 to 2500 nm) with a field spectroradiometer. To tackle the co-linearity that exists between the spectral observations, aggregated 10- and 20-nm data sets were used. Using a stepwise procedure, the most effective wavebands capable of discriminating treatment effects were selected. By applying a discrimination procedure with a well-chosen subset of the selected wavebands, treatments were correctly classified with more than 92% accuracy.
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