title: Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice.
abstract: Leaf nitrogen content (LNC) is a significant factor which can be utilized to monitor the status of paddy rice and it requires a reliable approach for fast and precise quantification. This investigation aims to quantitatively analyze the correlation between fluorescence parameters and LNC based on laser-induced fluorescence (LIF) technology. The fluorescence parameters exhibited a consistent positive linear correlation with LNC in different growing years (2014 and 2015) and different rice cultivars. The R(2) of the models varied from 0.6978 to 0.9045. Support vector machine (SVM) was then utilized to verify the feasibility of the fluorescence parameters for monitoring LNC. Comparison of the fluorescence parameters indicated that F740 is the most sensitive (the R(2) of linear regression analysis of the between predicted and measured values changed from 0.8475 to 0.9226, and REs ranged from 3.52% to 4.83%) to the changes in LNC among all fluorescence parameters. Experimental results demonstrated that fluorescence parameters based on LIF technology combined with SVM is a potential method for realizing real-time, non-destructive monitoring of paddy rice LNC, which can provide guidance for the decision-making of farmers in their N fertilization strategies.
authors.affiliation: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei 430079, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Yang
authors.affiliation: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei 430079, China.|Collaborative Innovation Center of Geospatial Technology, Wuhan, Hubei 430079, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Gong
authors.affiliation: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei 430079, China.|Collaborative Innovation Center of Geospatial Technology, Wuhan, Hubei 430079, China.
authors.forename: Shuo
authors.initials: S
authors.lastname: Shi
authors.affiliation: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei 430079, China.|School of Physics and Technology, Wuhan University, Wuhan, Hubei 430072, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Du
authors.affiliation: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei 430079, China.
authors.forename: Jia
authors.initials: J
authors.lastname: Sun
authors.affiliation: Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, Hubei 430071, China.
authors.forename: Shalei
authors.initials: S
authors.lastname: Song
authors.affiliation: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei 430079, China.
authors.forename: Biwu
authors.initials: B
authors.lastname: Chen
authors.affiliation: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei 430079, China.
authors.forename: Zhenbing
authors.initials: Z
authors.lastname: Zhang
mesh_terms: D000383:Agriculture / Q000379:methods; D003657:Decision Making; D000067565:Farmers / Q000523:psychology; D005308:Fertilizers / Q000706:statistics & numerical data; D005453:Fluorescence; D007834:Lasers; D009584:Nitrogen / Q000378:metabolism*; D012275:Oryza / Q000378:metabolism*; D018515:Plant Leaves / Q000378:metabolism*; D013057:Spectrum Analysis / Q000379:methods; D060388:Support Vector Machine
chemical_list: D005308:Fertilizers; D009584:Nitrogen