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
Link To Document