Next Article in Journal
Recent Developments in Tandem White Organic Light-Emitting Diodes
Next Article in Special Issue
Wavelength Selection for NIR Spectroscopy Based on the Binary Dragonfly Algorithm
Previous Article in Journal
Aflatoxin B1–Formamidopyrimidine DNA Adducts: Relationships between Structures, Free Energies, and Melting Temperatures
Previous Article in Special Issue
Quantification of Total Phenolic and Carotenoid Content in Blackberries (Rubus Fructicosus L.) Using Near Infrared Spectroscopy (NIRS) and Multivariate Analysis
Open AccessArticle

Classification of Frozen Corn Seeds Using Hyperspectral VIS/NIR Reflectance Imaging

College of Biosystems Enginaeering and Food Science, Zhejiang University, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
Molecules 2019, 24(1), 149; https://doi.org/10.3390/molecules24010149
Received: 3 December 2018 / Revised: 26 December 2018 / Accepted: 27 December 2018 / Published: 2 January 2019
A VIS/NIR hyperspectral imaging system was used to classify three different degrees of freeze-damage in corn seeds. Using image processing methods, the hyperspectral image of the corn seed embryo was obtained first. To find a relatively better method for later imaging visualization, four different pretreatment methods (no pretreatment, multiplicative scatter correction (MSC), standard normal variation (SNV) and 5 points and 3 times smoothing (5-3 smoothing)), four wavelength selection algorithms (successive projection algorithm (SPA), principal component analysis (PCA), X-loading and full-band method) and three different classification modeling methods (partial least squares-discriminant analysis (PLS-DA), K-nearest neighbor (KNN) and support vector machine (SVM)) were applied to make a comparison. Next, the visualization images according to a mean spectrum to mean spectrum (M2M) and a mean spectrum to pixel spectrum (M2P) were compared in order to better represent the freeze damage to the seed embryos. It was concluded that the 5-3 smoothing method and SPA wavelength selection method applied to the modeling can improve the signal-to-noise ratio, classification accuracy of the model (more than 90%). The final classification results of the method M2P were better than the method M2M, which had fewer numbers of misclassified corn seed samples and the samples could be visualized well. View Full-Text
Keywords: VIS/NIR hyperspectral imaging; corn seed; classification; freeze-damaged; image processing; imaging visualization VIS/NIR hyperspectral imaging; corn seed; classification; freeze-damaged; image processing; imaging visualization
Show Figures

Figure 1

MDPI and ACS Style

Zhang, J.; Dai, L.; Cheng, F. Classification of Frozen Corn Seeds Using Hyperspectral VIS/NIR Reflectance Imaging. Molecules 2019, 24, 149.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop