Non-destructive measurement of soluble solid content in Gannan navel oranges by visible/near-infrared spectroscopy

被引:0
|
作者
Engineering College, Jiangxi Agriculture University, Nanchang 330045, China [1 ]
不详 [2 ]
机构
[1] Engineering College, Jiangxi Agriculture University
[2] Department of Automobile, Jiangxi Blue Sky College
来源
Guangxue Xuebao | 2008年 / 3卷 / 478-481期
关键词
Artificial neural network; Medical optics and biotechnology; Non-destructive measurement; Principal component analysis; Soluble solid contents Gannan navel oranges; Visible/near-infrared spectroscopy;
D O I
10.3788/AOS20082803.0478
中图分类号
学科分类号
摘要
Non-destructive measurement of soluble solid content in Gannan navel oranges was carried out by visible/near-infrared spectroscopy detection method. Effective information of spectra was obtained by principal component analysis, and was used as the input variables of artificial neural network for building the nonlinear model. The results, based on calibration for 90 samples, are 0.9147 and 0.5203 for calibration correlation coefficient and root mean square error of calibration. The results, based on prediction for 38 unknown samples, are 0.9033, 0.6964 and 4.5709% for prediction correlation coefficient, root mean square error of prediction, and relative standard deviation (RSD), respectively. Experimental results show that visible/near-infrared spectroscopy detection method, based on artificial neural network, for non-destructive measurement of soluble solid content in Gannan navel oranges is feasible.
引用
收藏
页码:478 / 481
页数:3
相关论文
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