DocumentCode
2899810
Title
Non-Destructive Estimation Oilseed Rape Nitrogen Status using Chlorophyll Meter
Author
Song, Hai-Yan ; Guo, Zong-lou ; He, Yong ; Fang, Hui ; Zhu, Zhe-yan
Author_Institution
Coll. of Biosyst. Eng. & Food Sci., Zhejiang Univ., Hangzhou
fYear
2006
fDate
13-16 Aug. 2006
Firstpage
4252
Lastpage
4256
Abstract
Chlorophyll meter, soil plant analysis development (SPAD) is a simple, portable diagnostic tool that measures the greenness or relative content of leaves. The objective of this study is to analyze the relationships between the chlorophyll meter readings of the functional leaves at different stages and the nitrogen content of the oilseed rape leaves, and analyze the variation laws of the SPAD values of the oilseed rape in different growth stage and different fertilizer levels by using the spatial distribution maps of the geographic information system (GIS) software. The experiment is conducted in the farm of Zhejiang University. Three nitrogen fertilizers and two repeated experiments are carried on in this research. The result shows that SPAD values can represent the nitrogen content of the oilseed rape leaves with the correlation coefficient of 0.863, and different growth stages and different fertilizer levels have different SPAD values, but the variation laws is regular, which is beneficial for the further nitrogen management, so interim stage from bud to anthesis was recommended as the optimal management stage for nitrogen fertilizer recommendations
Keywords
biological techniques; biology computing; botany; cellular biophysics; crops; fertilisers; geographic information systems; molecular biophysics; nitrogen; photosynthesis; GIS software; chlorophyll meter readings; geographic information system; leaf greenness measure; nitrogen fertilizer levels; nondestructive estimation; oilseed rape nitrogen status; soil plant analysis development; spatial distribution maps; Content management; Crops; Cybernetics; Fertilizers; Geographic Information Systems; Information analysis; Infrared detectors; Machine learning; Meter reading; Nitrogen; Software systems; Soil; Soil measurements; Chlorophyll meter; GIS; nitrogen; oilseed rape;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location
Dalian, China
Print_ISBN
1-4244-0061-9
Type
conf
DOI
10.1109/ICMLC.2006.259007
Filename
4028819
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