• DocumentCode
    2088631
  • Title

    Application partial least squares regression in the analysis of maize regulated deficit irrigation

  • Author

    Bai, Wang ; Fanghua, Li ; Yan, Huang ; Yun, Teng

  • Author_Institution
    Heilongjiang Water Conservancy Inst., Harbin, China
  • fYear
    2011
  • fDate
    27-29 May 2011
  • Firstpage
    437
  • Lastpage
    440
  • Abstract
    In this paper, using the test-pit experiments, experimental research of the maize regulated deficit irrigation was made in black soil in cold area. The partial least-square regression was applied to set up the yield model of the maize regulated deficit irrigation, which dealed with serious multicollinearity and a small with numerous predictor variables, eliminated the bad impact of serious multicollinearity among factors, explained the dependent variables very well. The research analysis indicated that its achievement was reasonable and close to actual situation very well, providing a new idea and research method of deficit irrigation.
  • Keywords
    crops; irrigation; least squares approximations; regression analysis; soil; black soil; dependent variables; experimental research; maize regulated deficit irrigation; multicollinearity among factors; numerous predictor variables; partial least squares regression; research analysis; test-pit experiments; yield model; Analytical models; Ear; Equations; Irrigation; Mathematical model; Predictive models; Production; maize; partial least-square regression; regulated deficit irrigation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    New Technology of Agricultural Engineering (ICAE), 2011 International Conference on
  • Conference_Location
    Zibo
  • Print_ISBN
    978-1-4244-9574-0
  • Type

    conf

  • DOI
    10.1109/ICAE.2011.5943835
  • Filename
    5943835