Design and Experiment of Chlorophyll Content Detection Device for Active Light Source Based on RED-NIR
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    Abstract:

    In order to monitor the chlorophyll content of crop leaves quickly and without damage, a portable chlorophyll content monitoring device was designed with active light. Dual wavelengths were involved with the deep absorption of crop at 660nm and strong reflection at 850nm. After the conversion, modulation and amplification of the signal, the signal indicated the reflected light intensity of crop was obtained. The calculated models of spectral reflectance at dual wavelengths were fitted by using the calibration with four gray board, and the R2 were 0.993, 0.979 at 660nm and 850nm, respectively. The stability and the antiinterference tests of the light source were carried out. The results showed that the mean square errors of the stability test data at 660nm and 850nm were 0.0079 and 0.0044, and the 〖JP2〗error rates were 2378% and 1223%, respectively. The mean variances of antiinterference were 0.0099 and 0.0187, the error rates were 2.000% and 4.360%, respectively. The correlation test of chlorophyll gradient and dualwavelength reflectance was designed. The results showed that the correlation coefficients of dualwavelength and chlorophyll concentration based on 660nm and 850nm were -0.919 and 0.272, which reflected the strong absorption characteristics of chlorophyll in the vicinity of 660nm. Meanwhile, 850nm was selected as reference band witha low correlation coefficient between reflected light and chlorophyll. Furthermore, the field experiment was conducted to detect the chlorophyll content of maize canopy. The vegetation indices were calculated, including NDVI, DVI, RVI, SAVI dualwavelength spectral vegetation index. The correlative coefficients r of NDVI, DVI, RVI, SAVI and SPAD were 0.892, 0.846, 0.867 and 0.883, respectively. The linear models of NDVI, DVI, RVI and SAVI with SPAD were established, and the model determination coefficient R2 was 0.831. Subsequently, the model embedding function provided by the device can be used to further improve its field application ability in crop chlorophyll content detection.

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History
  • Received:April 08,2019
  • Revised:
  • Adopted:
  • Online: July 10,2019
  • Published: July 10,2019
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