TabMenu

Poverty and InequalitySexual and Reproductive HealthFamily, Maternal & Child HealthMethodology

Rapid and visual detection of the main chemical compositions in maize seeds based on Raman hyperspectral imaging

TitleRapid and visual detection of the main chemical compositions in maize seeds based on Raman hyperspectral imaging
Publication TypeJournal Article
Year of Publication2018
AuthorsYang, G, Wang, Q, Liu, C, Wang, X, Fan, S, Huang, W
JournalSpectrochim Acta A Mol Biomol Spectrosc
Volume200
Pagination186-194
Date PublishedJul 5
ISBN Number1386-1425
Accession Number29680497
Keywords*Image Processing, Computer-Assisted, Algorithms, Chemical compositions, Maize seeds, Raman hyperspectral imaging, Seeds/*chemistry, spatial distribution, Spectrum Analysis, Raman/*methods, Vibration, Vibrational assignment, Zea mays/*chemistry/embryology
Abstract

Rapid and visual detection of the chemical compositions of plant seeds is important but difficult for a traditional seed quality analysis system. In this study, a custom-designed line-scan Raman hyperspectral imaging system was applied for detecting and displaying the main chemical compositions in a heterogeneous maize seed. Raman hyperspectral images collected from the endosperm and embryo of maize seed were acquired and preprocessed by Savitzky-Golay (SG) filter and adaptive iteratively reweighted Penalized Least Squares (airPLS). Three varieties of maize seeds were analyzed, and the characteristics of the spectral and spatial information were extracted from each hyperspectral image. The Raman characteristic peaks, identified at 477, 1443, 1522, 1596 and 1654cm(-1) from 380 to 1800cm(-1) Raman spectra, were related to corn starch, mixture of oil and starch, zeaxanthin, lignin and oil in maize seeds, respectively. Each single-band image corresponding to the characteristic band characterized the spatial distribution of the chemical composition in a seed successfully. The embryo was distinguished from the endosperm by band operation of the single-band images at 477, 1443, and 1596cm(-1) for each variety. Results showed that Raman hyperspectral imaging system could be used for on-line quality control of maize seeds based on the rapid and visual detection of the chemical compositions in maize seeds.