[Diagnoses of rice nitrogen status based on characteristics of scanning leaf].
In the present research, the scanner was adopted as the digital image sensor, and a new method to diagnose the status of rice based on image processing technology was established. The main results are as follows: (1) According to the analysis of relations between leaf percentage nitrogen contents and color parameter, the sensitive color parameters were abstracted as B, b, b/(r+g), b/r and b/g. The leaf position (vertical spatial variation) effects on leaf chlorophyll contents were investigated, and the third fully expanded leaf was selected as the diagnosis leaf. (2) Field ground data such as ASD were collected simultaneously. Then study on the relationships between scanned leaf color characteristics and hyperspectral was carried out. The results indicated that the diagnosis of nitrogen status based on the scanned color characteristic is able to partly reflect the hyperspectral properties. (3) The leaf color and shape features were intergrated and the model of diagnosing the status of rice was established with calculated at YIQ color system. The distinct accuracy of nitrogen status was as follows: N0: 74.9%; N1 : 52%; N2 : 84.7%; N3 : 75%. The preliminary study showed that the methodology has been proved successful in this study and provides the potential to monitor nitrogen status in a cost-effective and accurate way based on the scanned digital image. Although, some confusion exists, with rapidly increasing resolution of digital platform and development of digital image technology, it will be more convenient for larger farms that can afford to use mechanized systems for site-specific nutrient management. Moreover, deeper theory research and practice experiment should be needed in the future.
Zhu
Jin-Xia
JX
Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou 310029, China. ko-ko998@163.com
Deng
Jin-Song
JS
Shi
Yuan-Yuan
YY
Chen
Zhu-Lu
ZL
Han
Ning
N
Wang
Ke
K
D002734:Chlorophyll / Q000737:chemistry; D003116:Color; D008962:Models, Theoretical; D009584:Nitrogen / Q000737:chemistry*; D012275:Oryza / Q000737:chemistry*; D018515:Plant Leaves / Q000737:chemistry*
D002734:Chlorophyll; D009584:Nitrogen