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Prediction of oleic acid content of rapeseed using hyperspectral technique

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成果类型:
期刊论文
作者:
Liu, Fan;Wang, Fang;Liao, Guiping;Lu, Xin;Yang, Jiayi
通讯作者:
Liao, G.
作者机构:
[Yang, Jiayi; Liao, Guiping; Wang, Fang; Lu, Xin; Liu, Fan] Hunan Agr Univ, Southern Reg Collaborat Innovat Ctr Grain & Oil C, Changsha 410128, Peoples R China.
通讯机构:
[Liao, G.] S
Southern Regional Collaborative Innovation Center for Grain and Oil Crops, China
语种:
英文
关键词:
BP neural networks;Hurst exponent;Hyperspectral;Multifractal;Oleic acid content
期刊:
Applied Sciences-Basel
ISSN:
2076-3417
年:
2021
卷:
11
期:
12
基金类别:
Chinese National Natural Science FoundationNational Natural Science Foundation of China (NSFC) [61973111]; Natural Science Foundation of Hunan Province (CN)Natural Science Foundation of Hunan Province [2020JJ4377]
机构署名:
本校为第一机构
摘要:
In order to detect the oleic acid content of rapeseed quickly and accurately, we propose, in this paper, an artificial BP neural networks based model for predicting oleic acid content by using rapeseed’s hyperspectral information. Four types of spectral features are selected for our investigation, namely multifractal index, sensitive band, trilateral parameters, and spectral index. Both univariate variable and multiple variables are considered as our model input. The result shows that the combined feature has higher precision and better stabil...

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