• Spectroscopy and Spectral Analysis
  • Vol. 29, Issue 8, 2176 (2009)
JIA Liang-liang1、2, FAN Ming-sheng1, ZHANG Fu-suo1, CHEN Xin-ping1, LU Shi-hua3, and SUN Yan-ming2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: Cite this Article
    JIA Liang-liang, FAN Ming-sheng, ZHANG Fu-suo, CHEN Xin-ping, LU Shi-hua, SUN Yan-ming. Nitrogen Status Diagnosis of Rice by Using a Digital Camera[J]. Spectroscopy and Spectral Analysis, 2009, 29(8): 2176 Copy Citation Text show less

    Abstract

    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.
    JIA Liang-liang, FAN Ming-sheng, ZHANG Fu-suo, CHEN Xin-ping, LU Shi-hua, SUN Yan-ming. Nitrogen Status Diagnosis of Rice by Using a Digital Camera[J]. Spectroscopy and Spectral Analysis, 2009, 29(8): 2176
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