DocumentCode
2962440
Title
Research on Optimized Fertilization for Filling Type Flue-cured Tobacco Based on Partial Least -squares Regression
Author
Pengda, Yin ; Wenxu, Zhu ; Huihui, Zhang ; Guangyu, Sun ; Yusheng, Jiao ; Guangwei, Zhao ; Deyu, Liu
Author_Institution
Coll. of Life Sci., Northeast Forestry Univ., Harbin, China
Volume
2
fYear
2011
fDate
28-29 March 2011
Firstpage
149
Lastpage
153
Abstract
This study constructed a quantitative fertilization model for high-quality filling flue-cured tobacco leaves and the reduce of environmental pollution and the leaf quality decline caused by over-fertilization. A mathematic model of flue-cured tobacco production and principal chemical components was established by the Partial Least-squares Regression (PLSR) fertilization function model through massive field experiment. The results showed that there was significant regression relationship between NPK fertilizers and flue-cured tobacco production and chemical components. First order term modulus showed the primary and secondary relationship between NPK fertilizers affecting flue-cured tobacco, reciprocation term and quadratic term modulus indicated the occurrence of the threshold value of NPK fertilizer proration. The application of NPK fertilizers showed the synergistic effects below the threshold value, whereas NPK fertilizer application produced the antagonistic effects beyond the threshold. For obtaining the max economic returns, the optimum fertilization was N:P:K=1:1.6:2.1. For improving flue-cured tobacco aroma, inflammability and safely smoking, the optimum fertilization was N:P:K=1:1.3:2.9.
Keywords
air pollution; curing; fertilisers; regression analysis; tobacco products; NPK fertilizers; environmental pollution; filling type flue-cured tobacco leaves; flue-cured tobacco aroma; inflammability; leaf quality; optimized fertilization; partial least-squares regression; principal chemical components; quadratic term modulus; synergistic effects; Automation; fertilizer; flue-cured tobacco; partial least-squares regression model (PLSR model);
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
Conference_Location
Shenzhen, Guangdong
Print_ISBN
978-1-61284-289-9
Type
conf
DOI
10.1109/ICICTA.2011.328
Filename
5750853
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