DocumentCode
2125231
Title
Rapid Shelf-Life Identification Model of Citrus Based on Near Infrared Spectroscopy
Author
Huijun, Liu ; Xiangfeng, Wu
Author_Institution
Coll. of Metrol. Technol. & Eng., China Jiliang Univ., Hangzhou
fYear
2008
fDate
21-22 Dec. 2008
Firstpage
298
Lastpage
301
Abstract
The near-infrared spectroscopy (NIR) was used in modeling of rapid shelf-life identification in citrus in this paper. The spectra of 54 citrus yielded in Huangyan were collected at three different times, and were set of class I, II and III (interval of 10 days), respectively. The principal component analysis was applied in characteristic selection, and ten variables were used as the input of the neural network. The shelf-life identification model of citrus based on principal component analysis and neural network by near-infrared spectroscopy was built. 40 examples were predicated, and the prediction precision was 80%.The result shows that the near-infrared spectroscopy technology can be applied in fast identification of shelf-life of citrus fruits perfectly.
Keywords
agricultural products; infrared spectroscopy; neural nets; principal component analysis; characteristic selection; citrus; near infrared spectroscopy; neural network; principal component analysis; rapid shelf-life identification model; Algorithm design and analysis; Delta modulation; Food technology; Infrared spectra; Life testing; Neural networks; Predictive models; Principal component analysis; Solids; Spectroscopy;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3488-6
Type
conf
DOI
10.1109/KAM.2008.50
Filename
4732833
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