NDLI: Nondestructive inspection of melon's sugar content based on impedance characteristics

Content Provider	IEEE Xplore Digital Library
Author	Yongbo Yao Zhen-Hong Jia Mei Liu Xiao-Hui Huang
Copyright Year	2011
Description	Author affiliation: College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China (Yongbo Yao; Zhen-Hong Jia; Mei Liu; Xiao-Hui Huang)
Abstract	The objective of the study is to establish a model between the impedance characteristics and the sugar content of internal quality index of melons. The equivalent series resistor and equivalent series capacitor of melon are measured over the frequency from 1 KHz to 100 KHz by a LCR meter and an airtight shielding case. Then the impedance is calculated. Through principal component analysis (PCA), four principal components are selected to model for back propagation neural network (BPNN) optimized by genetic algorithm (GA). Comparing this method with BPNN and partial least squares (PLS), it is obviously showed that BPNN optimized by GA model is reliable and practicable. The inspecting results are assessed by correlation coefficient R=0.8413, and the root mean squares error of prediction RMSEP=0.762. A method is proposed to detect melon's sweetness.
Starting Page	37
Ending Page	40
File Size	115946
Page Count	4
File Format	PDF
ISBN	9781612843742
e-ISBN	9781612843759
DOI	10.1109/IWACI.2011.6159970
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Atmospheric modeling Educational institutions Calibration Impedance Sugar Biological neural networks Genetic algorithms
Content Type	Text
Resource Type	Article

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