首页 | 本学科首页   官方微博 | 高级检索  
     


Independent component analysis in information extraction from visible/near-infrared hyperspectral imaging data of cucumber leaves
Authors:Zou Xiaobo  Zhao Jiewen  Mao Hanpin  Yin Xiaopin
Affiliation:
  • a Agricultural Product Processing and Storage Lab, School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China
  • b School of Food Science and Nutrition, the University of Leeds, Leeds LS2 9JT, United Kingdom
  • c Agricultural Engineering Key Lab of China, Jiangsu University, Zhenjiang, Jiangsu 212013, China
  • Abstract:Hyperspectral imaging at visible and short near infrared (VIS/SNIR) region has been used to estimate the pigment content of leaves. A complicating feature of measurements with any hyperspectral imaging methodology is the large amount of information generated during the measurement process. In this paper we discuss the identification of the desirable information using independent component analysis (ICA). After hyperspectral image acquisition and pre-processing, the average spectra obtained from the region of interest (ROI) in cucumber leaves were used for model development. Additionally a multi-linear regression model was developed for the prediction of cucumber leaf chlorophyll content. When compared with normal principal component analysis (PCA), the ICA multi-linear regression model provided improved estimates. When the calibration models were applied to an independent validation set, chlorophyll content was reasonably well predicted with a high correlation (r2 = 0.774). Depending on the sample, the technique enabled the identification and characterization of the relative content of various chlorophyll types that were distributed within the cucumber leaves. Typically low levels of chlorophyll at leaf margins and higher levels along main vein regions were identified. Our results indicate that hyperspectral imaging exhibits considerable promise for predicting pigments within cucumber leaves and furthermore can be applied non-destructively and in situ to living plant samples.
    Keywords:Hyperspectral imaging  Cucumber leaves  Chlorophyll content  Principal component analysis  Independent component analysis  Multi-linear regression
    本文献已被 ScienceDirect 等数据库收录!
    设为首页 | 免责声明 | 关于勤云 | 加入收藏

    Copyright©北京勤云科技发展有限公司  京ICP备09084417号