DocumentCode :
1592621
Title :
Spatial structure of LAI of spring soybean based on sunscan canopy analysis system and geo-statistic
Author :
Zhao Conghui ; Zhang Shujuan ; Wang Fenghua ; Jie Dengfei ; Zhang Haihong
Author_Institution :
Coll. of Eng. & Technol., Shanxi Agric. Univ., Taigu, China
fYear :
2010
Firstpage :
91
Lastpage :
94
Abstract :
In order to analyze the spatial structure of the leaf area index (LAI) of the spring soybean which was planted in late April and was harvested in early October, it was the LAI of the soybean as the breed of Jinda 74 that was studied in this paper in detail on further guiding the fine cultivation for this kind of the soybean, which was grown in the most of the China. During this research, the 54 sampling points was sampled on a 7m×7m grid, which were oriented by the DGPS receipt machine, the LAI of the soybean in flowering period was taken by the SunScan Canopy Analysis System. By taking to use the theory of geostatistics, the spatial structure of the LAI was discussed and its model of the semi-variance function was established. The results showed that the discussed LAI had medium variability with the CV being as 30.92%, and its semi-variance function model was the spherical model with the R2 being as 0.924 in the researched situation. It also proved that the LAI had medium spatial self-relatively for the C0/(C+C0) as 34.4%, and the range of its correlation distance was 44.8 meters in the situation discussed here. The results in this paper may provide the more information in the basis and prerequisite for the further studying on the physiological characteristics of the growth of the soybean, the soil properties, the spatial variability of the yield of it and the relevance in them. Moreover, these results provide a possibility for the realization of the precision management of water and the fertilizer for growing this kind of spring soybean in coping with the more field factors. And these results could improve the yield of the crop in a certain region.
Keywords :
agriculture; crops; statistical analysis; DGPS receipt machine; LAI; SunScan canopy analysis system; geo-statistics; leaf area index; semivariance function model; spatial structure; spherical model; spring soybean; Accuracy; Agriculture; Correlation; Frequency measurement; Soil; Springs; Statistical analysis; LAI; SunScan Canopy Analysis System; geo-statistic; spatial structure; spring soybean;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
World Automation Congress (WAC), 2010
Conference_Location :
Kobe
ISSN :
2154-4824
Print_ISBN :
978-1-4244-9673-0
Electronic_ISBN :
2154-4824
Type :
conf
Filename :
5665540
Link To Document :
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