The laser-induced fluorescence spectrum, Renner–Teller effect, and molecular quantum beats in the Ã 2Πi-X̃ 2Πi transition of the jet-cooled HCCSe free radical

2004 ◽  
Vol 121 (12) ◽  
pp. 5801-5811 ◽  
Author(s):  
David A. Hostutler ◽  
Sheng-Gui He ◽  
Dennis J. Clouthier
Keyword(s):  
Free Radical ◽  
Fluorescence Spectrum ◽  
Laser Induced Fluorescence ◽  
Teller Effect ◽  
Quantum Beats

scholarly journals Performance Characteristics of Compact Mobile LIFS (Laser-Induced Fluorescence Spectrum) Lidar

2016 ◽  
Vol 119 ◽  
pp. 17009 ◽  
Author(s):  
Takayuki Tomida ◽  
Naoto Nishizawa ◽  
Kosuke Sakurai ◽  
Hikaru Suganumata ◽  
Shodai Tsukada ◽  
...  
Keyword(s):  
Fluorescence Spectrum ◽  
Laser Induced Fluorescence ◽  
Performance Characteristics

The Laser Induced Fluorescence Spectrum of Te2Studied by Fourier Transform Spectrometry

1982 ◽  
Vol 25 (2) ◽  
pp. 338-350 ◽  
Author(s):  
J Vergès ◽  
C Effantin ◽  
O Babaky ◽  
J d'Incan ◽  
S J Prosser ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Fluorescence Spectrum ◽  
Laser Induced Fluorescence ◽  
Fourier Transform Spectrometry

scholarly journals Estimating leaf nitrogen concentration based on the combination with fluorescence spectrum and first-derivative

2020 ◽  
Vol 7 (2) ◽  
pp. 191941
Author(s):  
Jian Yang ◽  
Lin Du ◽  
Wei Gong ◽  
Shuo Shi ◽  
Jia Sun
Keyword(s):  
Fluorescence Spectrum ◽  
Nitrogen Concentration ◽  
Principal Component ◽  
Laser Induced Fluorescence ◽  
Leaf Nitrogen ◽  
Leaf Nitrogen Concentration ◽  
Growth Status ◽  
First Derivative ◽  
Fluorescence Characteristics ◽  
The Difference

Leaf nitrogen concentration (LNC) is a major indicator in the estimation of the crop growth status which has been diffusely applied in remote sensing. Thus, it is important to accurately obtain LNC by using passive or active technology. Laser-induced fluorescence can be applied to monitor LNC in crops through analysing the changing of fluorescence spectral information. Thus, the performance of fluorescence spectrum (FS) and first-derivative fluorescence spectrum (FDFS) for paddy rice (Yangliangyou 6 and Manly Indica) LNC estimation was discussed, and then the proposed FS + FDFS was used to monitor LNC by multivariate analysis. The results showed that the difference between FS ( R 2 = 0.781, s.d. = 0.078) and FDFS ( R 2 = 0.779, s.d. = 0.097) for LNC estimation by using the artificial neural network is not obvious. The proposed FS + FDFS can improved the accuracy of LNC estimation to some extent ( R 2 = 0.813, s.d. = 0.051). Then, principal component analysis was used in FS and FDFS, and extracted the main fluorescence characteristics. The results indicated that the proposed FS + FDFS exhibited higher robustness and stability for LNC estimation ( R 2 = 0.851, s.d. = 0.032) than that only using FS ( R 2 = 0.815, s.d. = 0.059) or FDFS ( R 2 = 0.801, s.d. = 0.065).

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