Rapid nondestructive detection of peanut varieties and peanut mildew based on hyperspectral imaging and stacked machine learning models

Moldy peanut seeds are damaged by mold, which seriously affects the germination rate of peanut seeds. At the same time, the quality and variety purity of peanut seeds profoundly affect the final yield of peanuts and the economic benefits of farmers. In this study, hyperspectral imaging technology wa...

Full description

Saved in:

Bibliographic Details
Published in:	Frontiers in plant science Vol. 13; p. 1047479
Main Authors:	Wu, Qingsong, Xu, Lijia, Zou, Zhiyong, Wang, Jian, Zeng, Qifeng, Wang, Qianlong, Zhen, Jiangbo, Wang, Yuchao, Zhao, Yongpeng, Zhou, Man
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Media SA 10.11.2022 Frontiers Media S.A
Subjects:	Accuracy Airborne microorganisms Algorithms Cameras Chromatography Classification Crop yield Ensemble learning Food Food quality Germination Humidity Hyperspectral imaging Imaging techniques Legumes Machine learning Mildew mildew detection Mold nondestructive testing Nuts peanut seeds Peanuts Plant Science Real time Seeds Spectrum analysis stacked ensemble learning model variety classification Vision systems Wavelengths nondestructive testing variety classification peanut seeds stacked ensemble learning model mildew detection
ISSN:	1664-462X, 1664-462X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!