您好,欢迎访问北京市农林科学院 机构知识库!

Field monitoring of wheat seedling stage with hyperspectral imaging

文献类型: 外文期刊

作者: Wu Qiong 1 ; Wang Cheng 2 ; Fang Jingjing 1 ; Ji Jianwei 1 ;

作者机构: 1.Shenyang Agr Univ, Coll Informat & Elect Engn, Shenyang 1008611, Peoples R China

2.Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

关键词: wheat seedling;monitoring;ASD;hyperspectral imaging;partial least squares

期刊名称:INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING ( 影响因子:2.032; 五年影响因子:2.137 )

ISSN: 1934-6344

年卷期: 2016 年 9 卷 5 期

页码:

收录情况: SCI

摘要: Nutrient elements such as chlorophyll, nitrogen and water at the seedling stage are important key factors that could influence growth, development and even the final yield of wheat. In this study, the spectral data of canopy and single wheat plant leaves at seedling stage were acquired in field by using ASD non-imaging hyperspectrometer and imaging spectrometer respectively to establish prediction models for monitoring the growth at the seedling stage of wheat. According to the comparative analysis of models results built through partial least square algorithm (PLS), it was found that the models built using spectral data of canopy based on ASD non-imaging hyperspectrometer and imaging spectrometer both had low precision, which was possibly caused by background such as soil; while the model established from single wheat plant leaves based on the imaging spectrometer had a better effect. At last, the PLS model was established for chlorophyll SPAD value of wheat seedling leaves based on imaging spectrometry and its correlation coefficient R reached 0.8836, and the correlation coefficient R of the relevant model for nitrogen content was 0.8520, suggesting that the superiority of location monitoring of growth at seedling stage of wheat based on hyperspectral imaging is significant.

  • 相关文献

[1]The Recognition of Biological Pesticide Adulteration by Attenuated Total Reflection Infrared Spectroscopy. Li Xiao-ting,Wand Dong,Ma Zhi-hong,Pan Li-gang,Wang Ji-hua,Li Xiao-ting,Wang Ji-hua,Zhu Da-Zhou.

[2]Hyperspectral Estimation of Leaf Water Content for Winter Wheat Based on Grey Relational Analysis(GRA). Jin Xiu-liang,Wang Yan,Tan Chang-wei,Zhu Xin-kai,Guo Wen-shan,Xu Xin-gang,Wang Ji-hua,Li Xin-chuan. 2012

[3]Research on Error Reduction of Path Change of Liquid Samples Based on Near Infrared Trans-Reflective Spectra Measurement. Wang Ya-hong,Dong Da-ming,Zheng Wen-gang,Wang Wen-zhong,Wang Ya-hong,Zhou Ping,Ye Song,Wang Wen-zhong. 2014

[4]Using hyperspectral measurements to estimate ratio of leaf carbon to nitrogen in winter wheat. Xu, Xin-gang,Yang, Xiao-dong,Yang, Hao,Feng, Hai-kuai,Yang, Gui-jun,Song, Xiao-yu. 2014

[5]A comparative study for the quantitative determination of soluble solids content, pH and firmness of pears by Vis/NIR spectroscopy. Li, Jiangbo,Huang, Wenqian,Zhao, Chunjiang,Zhang, Baohua.

[6]Research on Building Technology of Aquaculture Water Quality Real-Time Monitoring Software Platform. Ma, Yinchi,Ding, Wen,Li, Wentong,Ma, Yinchi,Ding, Wen,Li, Wentong. 2015

[7]The Study and Application of the IOT Technology in Agriculture. Zhao, Ji-chun,Zhang, Jun-feng,Feng, Yu,Guo, Jian-xin. 2010

[8]Wheat lodging monitoring using polarimetric index from RADARSAT-2 data. Yang, Hao,Chen, Erxue,Li, Zengyuan,Zhao, Lei,Yang, Hao,Zhao, Chunjiang,Yang, Guijun,Pignatti, Stefano,Casa, Raffaele. 2015

[9]REMOTE SENSING OF THE SEASONAL NAKED CROPLANDS USING SERIES OF NDVI IMAGES AND PHENOLOGICAL FEATURE. Shan, Zhengying,Xu, Qingyen. 2013

[10]Detection of Early Rottenness on Apples by Using Hyperspectral Imaging Combined with Spectral Analysis and Image Processing. Zhang, Baohua,Fan, Shuxiang,Li, Jiangbo,Huang, Wenqian,Zhao, Chunjiang,Qian, Man,Zheng, Ling,Zhang, Baohua,Zhao, Chunjiang.

[11]Prediction of soluble solids content of apple using the combination of spectra and textural features of hyperspectral reflectance imaging data. Fan, Shuxiang,Zhang, Baohua,Li, Jiangbo,Liu, Chen,Huang, Wenqian,Tian, Xi,Fan, Shuxiang,Zhang, Baohua,Li, Jiangbo,Liu, Chen,Huang, Wenqian,Tian, Xi,Fan, Shuxiang,Zhang, Baohua,Li, Jiangbo,Liu, Chen,Huang, Wenqian,Tian, Xi,Fan, Shuxiang,Zhang, Baohua,Li, Jiangbo,Liu, Chen,Huang, Wenqian,Tian, Xi.

[12]Multispectral detection of skin defects of bi-colored peaches based on vis-NIR hyperspectral imaging. Li, Jiangbo,Chen, Liping,Huang, Wenqian,Wang, Qingyan,Zhang, Baohua,Tian, Xi,Li, Bin,Li, Jiangbo,Chen, Liping,Huang, Wenqian,Wang, Qingyan,Tian, Xi,Fan, Shuxiang,Li, Bin,Li, Jiangbo,Chen, Liping,Huang, Wenqian,Li, Jiangbo,Chen, Liping,Huang, Wenqian.

[13]Development of a multispectral imaging system for online detection of bruises on apples. Huang, Wenqian,Li, Jiangbo,Wang, Qingyan,Chen, Liping.

[14]Prediction of Soluble Solids Content and Firmness of Pears Using Hyperspectral Reflectance Imaging. Fan, Shuxiang,Huang, Wenqian,Guo, Zhiming,Zhang, Baohua,Zhao, Chunjiang,Fan, Shuxiang,Zhao, Chunjiang.

[15]Hyperspectral classification for identifying decayed oranges infected by fungi. Yin, Shiyang,Gu, Xiaomin,Xiao, Yong,Bi, Xiaoqing,Niu, Yong. 2017

[16]Vertical features of yellow rust infestation on winter wheat using hyperspectral imaging measurements. Zhao, Jinling,Zhang, Dongyan,Huang, Linsheng,Zhang, Qing,Liu, Wenjing,Yang, Hao. 2016

[17]Detection of Wheat Powdery Mildew by Differentiating Background Factors using Hyperspectral Imaging. Zhang, Dongyan,Zhang, Lifu,Zhang, Dongyan,Wang, Xiu,Zhang, Dongyan,Wang, Xiu,Lin, Fenfang,Huang, Yanbo. 2016

[18]Geographical classification of apple based on hyperspectral imaging. Guo, Zhiming,Huang, Wenqian,Chen, Liping,Zhao, Chunjiang. 2013

[19]Recognition of wheat preharvest sprouting based on hyperspectral imaging. Wu, Qiong,Wang, Jihua,Wu, Qiong,Zhu, Dazhou,Wang, Cheng,Ma, Zhihong,Wang, Jihua. 2012

[20]Identification of seedling cabbages and weeds using hyperspectral imaging. Wei, Deng,Zhao Chunjiang,Xiu, Wang,Huang, Yanbo,Wei, Deng,Zhao Chunjiang,Xiu, Wang,Wei, Deng,Zhao Chunjiang,Xiu, Wang,Wei, Deng,Zhao Chunjiang,Xiu, Wang. 2015

作者其他论文 更多>>