Nitrogen Status Diagnosis of Rice by Using a Digital Camera
Nitrogen Status Diagnosis of Rice by Using a Digital Camera
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利用数码相机诊断水稻氮素状态
DOI：
10.3964/j.issn.1000-0593(2009)08-2176-04
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发表时间：
2009-08-01
影响因子：
0.7
通讯作者：
Sun Yan-ming
中科院分区：
文献类型：
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作者：
Jia Liang-liang;Fan Ming-sheng;Sun Yan-ming
本研究通过不同施氮量的田间试验，探讨利用可见光波段颜色分析方法监测水稻冠层氮素状况的可行性。研究了数码相机获取的水稻冠层图像可见光波段颜色强度与叶片SPAD叶绿素计、全氮含量、陆地生物量和氮吸收等常规氮状态诊断参数的相关性。结果表明：红色强度(R)、绿色强度(G)和归一化红色强度（NRI）与SPAD常规氮诊断参数、全氮含量、陆地生物量和全氮吸收量呈显著的线性负相关；红色波段(r)的相关系数(r)为-0.561 ~ -0.714，绿色波段(G)的相关系数(r)为-0.452 ~ -0.505，归一化红度强度（NRI）的相关系数(r)为-0.541 ~ 0.817。归一化绿化强度（NGI）与常规氮素参数呈显著正相关，相关系数(r)在0.505 ~ 0.559之间。与SPAD数据相比，常规氮素参数下的归一化红度（NRI） r值较高，为0.541 ~ 0.780，能更好地表达水稻的氮素状况。该方法在水稻氮素状况诊断中具有广阔的应用前景。
In the present research, a field experiment with different N application rate was conducted to study the possibility of using visible band color analysis methods to monitor the N status of rice canopy. The Correlations of visible spectrum band color intensity between rice canopy image acquired from a digital camera and conventional nitrogen status diagnosis parameters of leaf SPAD chlorophyll meter readings, total N content, upland biomass and N uptake were studied. The results showed that the red color intensity (R), green color intensity (G) and normalized redness intensity (NRI) have significant inverse linear correlations with the conventional N diagnosis parameters of SPAD readings, total N content, upland biomass and total N uptake. The correlation coefficient values (r) were from -0.561 to -0.714 for red band (R), from -0.452 to -0.505 for green band (G), and from -0.541 to 0.817 for normalized redness intensity (NRI). But the normalized greenness intensity (NGI) showed a significant positive correlation with conventional N parameters and the correlation coefficient values (r) were from 0.505 to 0.559. Compared with SPAD readings, the normalized redness intensity (NRI), with a high r value of 0.541-0.780 with conventional N parameters, could better express the N status of rice. The digital image color analysis method showed the potential of being used in rice N status diagnosis in the future.