Bruises in Strawberries - Spectral Cameras

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Results and Discussion Bruise Development with Force Level 0 N 1.5 N 3.0 N 70-80% Ripe Full- Ripe Masateru Nagata, Jasper Tallada, Taiichi Kobayashi, University of Miyazaki
Results and Discussion Classification efficiency (success in %) for bruised and non-bruised pixels using stepwise linear discriminant analysis Discriminant function wavelengths, nm Model development Nonbruised Bruised Bruised Nonbruised Nonbruised Model validation Bruised 980 96.0 88.4 98.8 84.6 980, 825 99.4 90.7 99.7 86.5 980, 825, 925 99.4 90.9 99.8 86.5 980, 825, 925, 680 99.6 91.3 99.8 86.7 980, 825, 925, 680, 650 99.5 91.8 99.9 86.1 ? O ? × Masateru Nagata, Jasper Tallada, Taiichi Kobayashi, University of Miyazaki
Page 1 and 2: Bruise Detection Using NIR Hyperspe
Page 3 and 4: Introduction External Quality Size
Page 5 and 6: Materials and Methods Strawberry Sa
Page 7 and 8: Materials and Methods Application o
Page 9 and 10: Results and Discussion VIS-NIR Spec
Page 11: Results and Discussion Visual Obser
Page 15 and 16: Results and Discussion Detected Bru
Page 17: Bruise Detection Using NIR Hyperspe

Bruises in Strawberries - Spectral Cameras

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