DocumentCode
1931371
Title
Structural and Fractal Dimensions are Reliable Determinants of Grain Yield in Soybean
Author
Jaradat, A.A. ; Surek, D. ; Archer, D.W.
Author_Institution
United States Dept. of Agric., Agric. Res. Service, Morris, IL
fYear
2006
fDate
13-17 Nov. 2006
Firstpage
153
Lastpage
158
Abstract
Soybean [Glycin max (L.) Merr.] plants grown under five management strategies differed significantly in their geometric structures, and were classified with 75 to 100% correct classification, based on differences in their fractal dimension (Do), midday differential canopy temperature (dT), and canopy light penetration [Log(UIo)]. Single soybean plants grown under a conventional system using moldboard tillage developed complex geometric structures, with significantly larger Do (1.477) values and grain yield (11.2 g per plant) as compared to plants grown under an organic system with strip tillage (Do =1.358, and grain yield = 2.32 g per plant). Across management strategies, Do of single plants was a function of stem perimeter, circularity, and volume, and plant dry weight; whereas grain yield m was a function of Do, plant dry weight and volume, and stem circularity. Knowledge of how plants respond to single and multiple management strategies will help agronomists develop better predictive models and will help farmers refine management practices to optimize yield.
Keywords
agricultural products; farming; fractals; Glycin max (L.) Merr; canopy light penetration; differential canopy temperature; fractal dimensions; grain yield; management strategy; moldboard tillage; soybean plants; strip tillage; Artificial neural networks; Crops; Fractals; Image analysis; Knowledge management; Predictive models; Soil; Strips; Temperature; US Department of Agriculture;
fLanguage
English
Publisher
ieee
Conference_Titel
Plant Growth Modeling and Applications, 2006. PMA '06. Second International Symposium on
Conference_Location
Beijing
Print_ISBN
978-0-7695-2851-9
Type
conf
DOI
10.1109/PMA.2006.19
Filename
4548362
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