Articles
NIR SPECTROSCOPY IS SUITABLE TO DETECT INSECT INFESTED CHESTNUTS
Article number
1043_20
Pages
153 – 160
Language
English
Abstract
In this study, the feasibility of using NIR spectroscopy to detect hidden insect damage is demonstrated.
Using a genetic algorithm for feature selection (from 2 to 6 wavelengths) in combination with a linear discriminant analysis routine, classification error rates as low as 16.81% false negative, 0.00% false positive, and 8.41% total error were achieved, with an AUC value of 0.952 and an Wilks λ of 0.403 (P<0.001). A Savitzky-Golay first derivative spectral pretreatment with 13 smoothing points was used.
The optimal features corresponded to Abs[1582 nm], Abs[1900 nm], and Abs[1964 nm]. These results represent an average of 55.3% improvement over a traditional floatation sorting system.
Using a genetic algorithm for feature selection (from 2 to 6 wavelengths) in combination with a linear discriminant analysis routine, classification error rates as low as 16.81% false negative, 0.00% false positive, and 8.41% total error were achieved, with an AUC value of 0.952 and an Wilks λ of 0.403 (P<0.001). A Savitzky-Golay first derivative spectral pretreatment with 13 smoothing points was used.
The optimal features corresponded to Abs[1582 nm], Abs[1900 nm], and Abs[1964 nm]. These results represent an average of 55.3% improvement over a traditional floatation sorting system.
Publication
Authors
R. Moscetti, D. Monarca , M. Cecchini, R. Massantini, R.P. Haff, S. Saranwong
Keywords
Castanea sativa, insect damage, Acousto-Optic Tunable Filter-Near Infrared spectroscopy, Linear Discriminant Analysis, wavelengths selection
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