Application of hyperspectral imaging to discriminate waxy corn seed vigour after aging

Yuan P., . and Pang L., . and Wang L. M., . and Yan L., . Application of hyperspectral imaging to discriminate waxy corn seed vigour after aging. pp. 397-405. ISSN 22317546

A hyperspectral imaging system covering 400 - 1000 nm spectral range was applied for vigour detection of waxy maize seeds after artificial aging. After spectral pre-processing the characteristic wavelength was selected by uninformative variable elimination (UVE) competitive adaptive reweighted sampling (CARS) and random frog (RF) methods. The moisture starch protein and fat contents were measured for each grade of seed and these values were correlated with the spectrum. Finally the vitality detection model was established by least squares support vector machine (LS-SVM) extreme learning machine (ELM) and random forest (RF). The prediction sets exhibited high classification accuracy ( 99) for 115 features. The model constructed from the bands significantly correlated with chemical composition (CC) and was better than the classic feature selection methods. The overall results indicated that hyperspectral imaging could be a potential technique to assess seed vigour.

Full text available from: Official URL: http://www.ifrj.upm.edu.my/29%20(02)%202022/17%20-...

Abstract

A hyperspectral imaging system covering 400 - 1000 nm spectral range was applied for vigour detection of waxy maize seeds after artificial aging. After spectral pre-processing the characteristic wavelength was selected by uninformative variable elimination (UVE) competitive adaptive reweighted sampling (CARS) and random frog (RF) methods. The moisture starch protein and fat contents were measured for each grade of seed and these values were correlated with the spectrum. Finally the vitality detection model was established by least squares support vector machine (LS-SVM) extreme learning machine (ELM) and random forest (RF). The prediction sets exhibited high classification accuracy ( 99) for 115 features. The model constructed from the bands significantly correlated with chemical composition (CC) and was better than the classic feature selection methods. The overall results indicated that hyperspectral imaging could be a potential technique to assess seed vigour.

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Item Type:	Article
AGROVOC Term:	Waxy corn
AGROVOC Term:	Zea mays
AGROVOC Term:	hyperspectral imaging
AGROVOC Term:	Seed vigour
AGROVOC Term:	Aging
AGROVOC Term:	Detectors
AGROVOC Term:	Varieties
AGROVOC Term:	Seed vigour
Depositing User:	Mr. AFANDI ABDUL MALEK
Last Modified:	24 Apr 2025 00:55
URI:	http://webagris.upm.edu.my/id/eprint/10644

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