[Nondestructive discrimination of waxed apples based on hyperspectral imaging technology].
The potential of hyperspectral imaging technology was evaluated for discriminating three types of waxed apples. Three types of apples smeared with fruit wax, with industrial wax, and not waxed respectively were imaged by a hyperspectral imaging system with a spectral range of 308-1 024 nm. ENVI software processing platform was used for extracting hyperspectral image object of diffuse reflection spectral response characteristics. Eighty four of 126 apple samples were selected randomly as calibration set and the rest were prediction set. After different preprocess, the related mathematical models were established by using the partial least squares (PLS), the least squares support vector machine (LS-SVM) and BP neural network methods and so on. The results showed that the model of MSC-SPA-LSSVM was the best to discriminate three kinds of waxed apples with 100%, 100% and 92.86% correct prediction respectively.
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. gaojunfeng@163.com
Jun-Feng
JF
Gao
Hai-Liang
HL
Zhang
Wen-Wen
WW
Kong
Yong
Y
He
D000465:Algorithms; D005513:Food Inspection / Q000379:methods*; D016018:Least-Squares Analysis; D027845:Malus / Q000737:chemistry*; D008962:Models, Theoretical; D055095:Optics and Photonics; D011786:Quality Control; D013057:Spectrum Analysis / Q000379:methods*; D060388:Support Vector Machine