Estimating rice chlorophyll content and leaf nitrogen concentration with a digital still color camera under natural light.
Estimating rice chlorophyll content and leaf nitrogen concentration with a digital still color camera under natural light.
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DOI：
10.1186/1746-4811-10-36
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发表时间：
2014
期刊：
影响因子：
5.1
通讯作者：
Omasa K
中科院分区：
文献类型：
--
作者：
Wang Y;Wang D;Shi P;Omasa K
作物叶片的颜色与氮素状况密切相关，可以通过数码相机和图像处理软件进行定量。建立自然光下图像颜色指数与氮素营养状况的关系，对田间作物监测和氮素诊断具有重要意义。本研究利用数码相机对6个水稻品种的冠层进行了拍摄。在2010年和2011年分别在晴天和阴天条件下，在田间施用0 - 315 kg N ha-1的N处理。SPAD读数，叶氮浓度（LNC）和13个图像颜色指数之间的显着相关性进行了观察，从数码相机图像计算使用三种颜色模型：RGB，广泛使用的添加剂颜色模型; HSV，一个圆柱坐标类似于人类感知的颜色;和L*a*B* 系统的国际照明委员会。在这些颜色指数中，表征黄蓝色度的视觉感知指数B* 与SPAD阅读和LNC的线性关系最密切。然而，LNC和颜色指数之间的关系受发育阶段的影响。线性回归模型被用来预测LNC和SPAD的颜色指数和相位发展。在此基础上，用独立数据对模型进行了验证。总体而言，在不同自然光照条件下，不同品种和不同采样期的颜色指数B*、SPAD阅读和LNC之间表现出可接受的性能和预测性。本研究表明，数字彩色图像分析可以作为一种简单的方法来评估自然光照条件下不同品种和不同发育阶段的水稻氮素营养状况。本文的在线版本（doi：10.1186/1746-4811-10-36）包含补充材料，可供授权用户使用。
The color of crop leaves is closely correlated with nitrogen (N) status and can be quantified easily with a digital still color camera and image processing software. The establishment of the relationship between image color indices and N status under natural light is important for crop monitoring and N diagnosis in the field. In our study, a digital still color camera was used to take pictures of the canopies of 6 rice (Oryza sativa L.) cultivars with N treatments ranging from 0 to 315 kg N ha-1 in the field under sunny and overcast conditions in 2010 and 2011, respectively. Significant correlations were observed between SPAD readings, leaf N concentration (LNC) and 13 image color indices calculated from digital camera images using three color models: RGB, widely used additive color model; HSV, a cylindrical-coordinate similar to the human perception of colors; and the L*a*b* system of the International Commission on Illumination. Among these color indices, the index b*, which represents the visual perception of yellow-blue chroma, has the closest linear relationship with SPAD reading and LNC. However, the relationships between LNC and color indices were affected by the developmental phase. Linear regression models were used to predict LNC and SPAD from color indices and phasic development. After that, the models were validated with independent data. Generally, acceptable performance and prediction were found between the color index b*, SPAD reading and LNC with different cultivars and sampling dates under different natural light conditions. Our study showed that digital color image analysis could be a simple method of assessing rice N status under natural light conditions for different cultivars and different developmental stages. The online version of this article (doi:10.1186/1746-4811-10-36) contains supplementary material, which is available to authorized users.
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影响因子：
2.1
作者：
PENG, SB;GARCIA, FV;CASSMAN, KG
通讯作者：
CASSMAN, KG
影响因子：
6.2
作者：
Antunes, MAH;Walter-Shea, EA;Mesarch, MA
通讯作者：
Mesarch, MA
DOI：
10.1051/agro:19970903
发表时间：
1997-11-01
期刊：
AGRONOMIE
影响因子：
--
作者：
Baret, F;Fourty, T
通讯作者：
Fourty, T
影响因子：
6.2
作者：
Liu, Jiangui;Pattey, Elizabeth
通讯作者：
Pattey, Elizabeth
影响因子：
5.2
作者：
Li, Fei;Mistele, Bodo;Schmidhalter, Urs
通讯作者：
Schmidhalter, Urs