Abstract

Paddy rice is one of the most significant food sources and an important part of the ecosystem. Thus, accurate monitoring of paddy rice growth is highly necessary. Leaf nitrogen content (LNC) serves as a crucial indicator of growth status of paddy rice and determines the dose of nitrogen (N) fertilizer to be used. This study aims to compare the predictive ability of the fluorescence spectra excited by different excitation wavelengths (EWs) combined with traditional multivariate analysis algorithms, such as principal component analysis (PCA), back-propagation neural network (BPNN), and support vector machine (SVM), for estimating paddy rice LNC from the leaf level with three different fluorescence characteristics as input variables. Then, six estimation models were proposed. Compared with the five other models, PCA-BPNN was the most suitable model for the estimation of LNC by improving R2 and reducing RMSE and RE. For 355, 460 and 556 nm EWs, R2 was 0.89, 0.80 and 0.88, respectively. Experimental results demonstrated that the fluorescence spectra excited by 355 and 556 nm EWs were superior to those excited by 460 nm for the estimation of LNC with different models. BPNN algorithm combined with PCA may provide a helpful exploratory and predictive tool for fluorescence spectra excited by appropriate EW based on practical application requirements for monitoring the N status of crops.

© 2017 Optical Society of America

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References

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    [Crossref]
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    [Crossref]
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    [Crossref]
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    [Crossref] [PubMed]
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    [Crossref]
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    [Crossref]
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    [Crossref] [PubMed]
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    [Crossref] [PubMed]
  36. C. Buschmann, “Variability and application of the chlorophyll fluorescence emission ratio red/far-red of leaves,” Photosynth. Res. 92(2), 261–271 (2007).
    [Crossref] [PubMed]
  37. F. Heisel, M. Sowinska, J. A. Miehé, M. Lang, and H. K. Lichtenthaler, “Detection of nutrient deficiencies of maize by laser induced fluorescence imaging,” J. Plant Physiol. 148(5), 622–631 (1996).
    [Crossref]
  38. H. Shahabi, B. B. Ahmad, M. H. Mokhtari, and M. A. Zadeh, “Detection of urban irregular development and green space destruction using normalized difference vegetation index (NDVI), principal component analysis (PCA) and post classification methods: a case study of Saqqez City,” Int. J. Phys. Sci. 7, 2587–2595 (2012).
  39. R. Cavalli, G. Licciardi, and J. Chanussot, “Archaeological structures using nonlinear principal component analysis applied to airborne hyperspectral image,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 6(2), 659–669 (2013).
    [Crossref]
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    [Crossref]
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    [Crossref]
  42. J. Yang, S. Shi, W. Gong, L. Du, Y. Y. Ma, B. Zhu, and S. L. Song, “Application of fluorescence spectrum to precisely inverse paddy rice nitrogen content,” Plant Soil Environ. 61(4), 182–188 (2015).
    [Crossref]

2016 (5)

H. M. Kalaji, A. Jajoo, A. Oukarroum, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, I. Łukasik, V. Goltsev, and R. J. Ladle, “Chlorophyll a fluorescence as a tool to monitor physiological status of plants under abiotic stress conditions,” Acta Physiol. Plant. 38(4), 1–11 (2016).
[Crossref]

J. Yang, W. Gong, S. Shi, L. Du, B. Zhu, J. Sun, and S. Song, “Excitation Wavelength Analysis of Laser-Induced Fluorescence LiDAR for Identifying Plant Species,” IEEE Geosci. Remote Sens. Lett. 13(7), 977–981 (2016).
[Crossref]

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, and S. Song, “Laser-Induced Fluorescence Characteristics of Vegetation by a New Excitation Wavelength,” Spectrosc. Lett. 49(4), 263–267 (2016).
[Crossref]

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
[PubMed]

M. P. Cendrero-Mateo, M. S. Moran, S. A. Papuga, K. R. Thorp, L. Alonso, J. Moreno, G. Ponce-Campos, U. Rascher, and G. Wang, “Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments,” J. Exp. Bot. 67(1), 275–286 (2016).
[Crossref] [PubMed]

2015 (3)

P. Nugroho, M. Shimizu, H. Nakamato, A. Nagatake, S. Suwardi, U. Sudadi, and R. Hatano, “Nitrous oxide fluxes from soil under different crops and fertilizer management,” Plant Soil Environ. 61, 385–392 (2015).

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, Y. Y. Ma, and S. L. Song, “Accurate identification of nitrogen fertilizer application of paddy rice using laser-induced fluorescence combined with support vector machine,” Plant Soil Environ. 61(11), 501–506 (2015).
[Crossref]

J. Yang, S. Shi, W. Gong, L. Du, Y. Y. Ma, B. Zhu, and S. L. Song, “Application of fluorescence spectrum to precisely inverse paddy rice nitrogen content,” Plant Soil Environ. 61(4), 182–188 (2015).
[Crossref]

2014 (4)

N. Neeti and J. R. Eastman, “Novel approaches in Extended Principal Component Analysis to compare spatio-temporal patterns among multiple image time series,” Remote Sens. Environ. 148, 84–96 (2014).
[Crossref]

M. Živcak, K. Olsovska, P. Slamka, J. Galambošová, V. Rataj, H. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60, 210–215 (2014).

R. Zong, Y. Zhi, B. Yao, J. Gao, and A. A. Stec, “Classification and identification of soot source with principal component analysis and back-propagation neural network,” Aust. J. Forensic Sci. 46(2), 224–233 (2014).
[Crossref]

A. I. Samborska, V. Alexandrov, L. Sieczko, B. Kornatowska, V. Goltsev, D. C. Magdalena, and H. M. Kalaji, “Artificial neural networks and their application in biological and agricultural research,” J. Nano PhotoBioSciences 2, 14–30 (2014).

2013 (2)

X. Liang, H. Li, S. Wang, Y. Ye, Y. Ji, G. Tian, C. van Kessel, and B. Linquist, “Nitrogen management to reduce yield-scaled global warming potential in rice,” Field Crops Res. 146, 66–74 (2013).
[Crossref]

R. Cavalli, G. Licciardi, and J. Chanussot, “Archaeological structures using nonlinear principal component analysis applied to airborne hyperspectral image,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 6(2), 659–669 (2013).
[Crossref]

2012 (5)

H. Shahabi, B. B. Ahmad, M. H. Mokhtari, and M. A. Zadeh, “Detection of urban irregular development and green space destruction using normalized difference vegetation index (NDVI), principal component analysis (PCA) and post classification methods: a case study of Saqqez City,” Int. J. Phys. Sci. 7, 2587–2595 (2012).

M. Brestic, M. Zivcak, H. M. Kalaji, R. Carpentier, and S. I. Allakhverdiev, “Photosystem II thermostability in situ: environmentally induced acclimation and genotype-specific reactions in Triticum aestivum L,” Plant Physiol. Biochem. 57, 93–105 (2012).
[Crossref] [PubMed]

Y. Ma and W. Gong, “Evaluating the performance of SVM in dust aerosol discrimination and testing its ability in an extended area,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 5(6), 1849–1858 (2012).
[Crossref]

V. Goltsev, I. Zaharieva, P. Chernev, M. Kouzmanova, H. M. Kalaji, I. Yordanov, V. Krasteva, V. Alexandrov, D. Stefanov, S. I. Allakhverdiev, and R. J. Strasser, “Drought-induced modifications of photosynthetic electron transport in intact leaves: analysis and use of neural networks as a tool for a rapid non-invasive estimation,” Biochim. Biophys. Acta 1817(8), 1490–1498 (2012).
[Crossref] [PubMed]

N. Tremblay, Z. Wang, and Z. G. Cerovic, “Sensing crop nitrogen status with fluorescence indicators. A review,” Agron. Sustain. Dev. 32(2), 451–464 (2012).
[Crossref]

2011 (1)

Y. C. Tian, X. Yao, J. Yang, W. X. Cao, D. B. Hannaway, and Y. Zhu, “Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance,” Field Crops Res. 120(2), 299–310 (2011).
[Crossref]

2010 (3)

D. L. Farkas, A. S. Gouveia-Neto, J. E. A. Silva, E. B. Costa, L. A. Bueno, L. M. H. Silva, M. M. C. Granja, M. J. L. Medeiros, T. J. R. Câmara, L. G. Willadino, D. V. Nicolau, and R. C. Leif, “Plant abiotic stress diagnostic by laser induced chlorophyll fluorescence spectral analysis of in vivo leaf tissue of biofuel species,” Int. Soc. Opt. Photonics 7568, 75680G (2010).

Z. Tuba, D. K. Saxena, K. Srivastava, S. Singh, S. Czobel, and H. M. Kalaji, “Chlorophyll a fluorescence measurements for validating the tolerant bryophytes for heavy metal (Pb) biomapping,” Curr. Sci. 98, 1505–1508 (2010).

H. Abdi and L. J. Williams, “Principal component analysis,” Wiley Interdiscip. Rev. Comput. Stat. 2(4), 433–459 (2010).
[Crossref]

2009 (1)

Z. Malenovský, K. B. Mishra, F. Zemek, U. Rascher, and L. Nedbal, “Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence,” J. Exp. Bot. 60(11), 2987–3004 (2009).
[Crossref] [PubMed]

2008 (1)

W. Feng, X. Yao, Y. Zhu, Y. Tian, and W. Cao, “Monitoring leaf nitrogen status with hyperspectral reflectance in wheat,” Eur. J. Agron. 28(3), 394–404 (2008).
[Crossref]

2007 (3)

C. Buschmann, “Variability and application of the chlorophyll fluorescence emission ratio red/far-red of leaves,” Photosynth. Res. 92(2), 261–271 (2007).
[Crossref] [PubMed]

Q.-X. Yi, J.-F. Huang, F.-M. Wang, X.-Z. Wang, and Z.-Y. Liu, “Monitoring rice nitrogen status using hyperspectral reflectance and artificial neural network,” Environ. Sci. Technol. 41(19), 6770–6775 (2007).
[Crossref] [PubMed]

S. Apostol, A. A. Viau, and N. Tremblay, “A comparison of multiwavelength laser-induced fluorescence parameters for the remote sensing of nitrogen stress in field-cultivated corn,” Can. J. Rem. Sens. 33(3), 150–161 (2007).
[Crossref]

2006 (2)

S. S. Malhi, R. Lemke, Z. Wang, and B. S. Chhabra, “Tillage, nitrogen and crop residue effects on crop yield, nutrient uptake, soil quality, and greenhouse gas emissions,” Soil Tillage Res. 90(1-2), 171–183 (2006).
[Crossref]

M. K. Gill, T. Asefa, M. W. Kemblowski, and M. McKee, “Soil moisture prediction using support vector machines,” J. Am. Water Resour. Assoc. 42(4), 1033–1046 (2006).
[Crossref]

2005 (1)

Z. Kolber, D. Klimov, G. Ananyev, U. Rascher, J. Berry, and B. Osmond, “Measuring photosynthetic parameters at a distance: laser induced fluorescence transient (LIFT) method for remote measurements of photosynthesis in terrestrial vegetation,” Photosynth. Res. 84(1-3), 121–129 (2005).
[Crossref] [PubMed]

2004 (1)

M. E. Ramos and M. G. Lagorio, “True fluorescence spectra of leaves,” Photochem. Photobiol. Sci. 3(11-12), 1063–1066 (2004).
[Crossref] [PubMed]

2003 (1)

N. Agarwal, S. Gupta, A. Pradhan, K. Vishwanathan, and P. K. Panigrahi, “Wavelet transform of breast tissue fluorescence spectra: a technique for diagnosis of tumors,” IEEE J. Sel. Top. Quantum Electron. 9(2), 154–161 (2003).
[Crossref]

1999 (1)

A. A. Gitelson, C. Buschmann, and H. K. Lichtenthaler, “The chlorophyll fluorescence ratio F 735/F 700 as an accurate measure of the chlorophyll content in plants,” Remote Sens. Environ. 69(3), 296–302 (1999).
[Crossref]

1998 (4)

L. E. Keiner and X.-H. Yan, “A neural network model for estimating sea surface chlorophyll and sediments from thematic mapper imagery,” Remote Sens. Environ. 66(2), 153–165 (1998).
[Crossref]

G. Agati, “Response of the in vivo chlorophyll fluorescence spectrum to environmental factors and laser excitation wavelength,” Pure Appl. Opt.: J. Euro. Opt. Soc. A 7(4), 797–807 (1998).
[Crossref]

M. Buscema, “Back propagation neural networks,” Subst. Use Misuse 33(2), 233–270 (1998).
[Crossref] [PubMed]

M. A. Hearst, S. T. Dumais, E. Osman, J. Platt, and B. Scholkopf, “Support vector machines,” Intelligent Syst. Appl. 13(4), 18–28 (1998).
[Crossref]

1996 (2)

J. Schweiger, M. Lang, and H. K. Lichtenthaler, “Differences in Fluorescence Excitation Spectra of Leaves between Stressed and Non-Stressed Plants,” J. Plant Physiol. 148(5), 536–547 (1996).
[Crossref]

F. Heisel, M. Sowinska, J. A. Miehé, M. Lang, and H. K. Lichtenthaler, “Detection of nutrient deficiencies of maize by laser induced fluorescence imaging,” J. Plant Physiol. 148(5), 622–631 (1996).
[Crossref]

1995 (1)

S. Svanberg, “Fluorescence lidar monitoring of vegetation status,” Phys. Scr. T58, 79–85 (1995).
[Crossref]

1984 (1)

Abdi, H.

H. Abdi and L. J. Williams, “Principal component analysis,” Wiley Interdiscip. Rev. Comput. Stat. 2(4), 433–459 (2010).
[Crossref]

Agarwal, N.

N. Agarwal, S. Gupta, A. Pradhan, K. Vishwanathan, and P. K. Panigrahi, “Wavelet transform of breast tissue fluorescence spectra: a technique for diagnosis of tumors,” IEEE J. Sel. Top. Quantum Electron. 9(2), 154–161 (2003).
[Crossref]

Agati, G.

G. Agati, “Response of the in vivo chlorophyll fluorescence spectrum to environmental factors and laser excitation wavelength,” Pure Appl. Opt.: J. Euro. Opt. Soc. A 7(4), 797–807 (1998).
[Crossref]

Ahmad, B. B.

H. Shahabi, B. B. Ahmad, M. H. Mokhtari, and M. A. Zadeh, “Detection of urban irregular development and green space destruction using normalized difference vegetation index (NDVI), principal component analysis (PCA) and post classification methods: a case study of Saqqez City,” Int. J. Phys. Sci. 7, 2587–2595 (2012).

Alexandrov, V.

A. I. Samborska, V. Alexandrov, L. Sieczko, B. Kornatowska, V. Goltsev, D. C. Magdalena, and H. M. Kalaji, “Artificial neural networks and their application in biological and agricultural research,” J. Nano PhotoBioSciences 2, 14–30 (2014).

V. Goltsev, I. Zaharieva, P. Chernev, M. Kouzmanova, H. M. Kalaji, I. Yordanov, V. Krasteva, V. Alexandrov, D. Stefanov, S. I. Allakhverdiev, and R. J. Strasser, “Drought-induced modifications of photosynthetic electron transport in intact leaves: analysis and use of neural networks as a tool for a rapid non-invasive estimation,” Biochim. Biophys. Acta 1817(8), 1490–1498 (2012).
[Crossref] [PubMed]

Allakhverdiev, S. I.

V. Goltsev, I. Zaharieva, P. Chernev, M. Kouzmanova, H. M. Kalaji, I. Yordanov, V. Krasteva, V. Alexandrov, D. Stefanov, S. I. Allakhverdiev, and R. J. Strasser, “Drought-induced modifications of photosynthetic electron transport in intact leaves: analysis and use of neural networks as a tool for a rapid non-invasive estimation,” Biochim. Biophys. Acta 1817(8), 1490–1498 (2012).
[Crossref] [PubMed]

M. Brestic, M. Zivcak, H. M. Kalaji, R. Carpentier, and S. I. Allakhverdiev, “Photosystem II thermostability in situ: environmentally induced acclimation and genotype-specific reactions in Triticum aestivum L,” Plant Physiol. Biochem. 57, 93–105 (2012).
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Alonso, L.

M. P. Cendrero-Mateo, M. S. Moran, S. A. Papuga, K. R. Thorp, L. Alonso, J. Moreno, G. Ponce-Campos, U. Rascher, and G. Wang, “Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments,” J. Exp. Bot. 67(1), 275–286 (2016).
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Ananyev, G.

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M. K. Gill, T. Asefa, M. W. Kemblowski, and M. McKee, “Soil moisture prediction using support vector machines,” J. Am. Water Resour. Assoc. 42(4), 1033–1046 (2006).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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H. M. Kalaji, A. Jajoo, A. Oukarroum, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, I. Łukasik, V. Goltsev, and R. J. Ladle, “Chlorophyll a fluorescence as a tool to monitor physiological status of plants under abiotic stress conditions,” Acta Physiol. Plant. 38(4), 1–11 (2016).
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M. Živcak, K. Olsovska, P. Slamka, J. Galambošová, V. Rataj, H. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60, 210–215 (2014).

M. Brestic, M. Zivcak, H. M. Kalaji, R. Carpentier, and S. I. Allakhverdiev, “Photosystem II thermostability in situ: environmentally induced acclimation and genotype-specific reactions in Triticum aestivum L,” Plant Physiol. Biochem. 57, 93–105 (2012).
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D. L. Farkas, A. S. Gouveia-Neto, J. E. A. Silva, E. B. Costa, L. A. Bueno, L. M. H. Silva, M. M. C. Granja, M. J. L. Medeiros, T. J. R. Câmara, L. G. Willadino, D. V. Nicolau, and R. C. Leif, “Plant abiotic stress diagnostic by laser induced chlorophyll fluorescence spectral analysis of in vivo leaf tissue of biofuel species,” Int. Soc. Opt. Photonics 7568, 75680G (2010).

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A. A. Gitelson, C. Buschmann, and H. K. Lichtenthaler, “The chlorophyll fluorescence ratio F 735/F 700 as an accurate measure of the chlorophyll content in plants,” Remote Sens. Environ. 69(3), 296–302 (1999).
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Bussotti, F.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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D. L. Farkas, A. S. Gouveia-Neto, J. E. A. Silva, E. B. Costa, L. A. Bueno, L. M. H. Silva, M. M. C. Granja, M. J. L. Medeiros, T. J. R. Câmara, L. G. Willadino, D. V. Nicolau, and R. C. Leif, “Plant abiotic stress diagnostic by laser induced chlorophyll fluorescence spectral analysis of in vivo leaf tissue of biofuel species,” Int. Soc. Opt. Photonics 7568, 75680G (2010).

Cao, W.

W. Feng, X. Yao, Y. Zhu, Y. Tian, and W. Cao, “Monitoring leaf nitrogen status with hyperspectral reflectance in wheat,” Eur. J. Agron. 28(3), 394–404 (2008).
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Y. C. Tian, X. Yao, J. Yang, W. X. Cao, D. B. Hannaway, and Y. Zhu, “Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance,” Field Crops Res. 120(2), 299–310 (2011).
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Carpentier, R.

M. Brestic, M. Zivcak, H. M. Kalaji, R. Carpentier, and S. I. Allakhverdiev, “Photosystem II thermostability in situ: environmentally induced acclimation and genotype-specific reactions in Triticum aestivum L,” Plant Physiol. Biochem. 57, 93–105 (2012).
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M. P. Cendrero-Mateo, M. S. Moran, S. A. Papuga, K. R. Thorp, L. Alonso, J. Moreno, G. Ponce-Campos, U. Rascher, and G. Wang, “Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments,” J. Exp. Bot. 67(1), 275–286 (2016).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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Chernev, P.

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Czobel, S.

Z. Tuba, D. K. Saxena, K. Srivastava, S. Singh, S. Czobel, and H. M. Kalaji, “Chlorophyll a fluorescence measurements for validating the tolerant bryophytes for heavy metal (Pb) biomapping,” Curr. Sci. 98, 1505–1508 (2010).

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J. Yang, W. Gong, S. Shi, L. Du, B. Zhu, J. Sun, and S. Song, “Excitation Wavelength Analysis of Laser-Induced Fluorescence LiDAR for Identifying Plant Species,” IEEE Geosci. Remote Sens. Lett. 13(7), 977–981 (2016).
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J. Yang, W. Gong, S. Shi, L. Du, J. Sun, and S. Song, “Laser-Induced Fluorescence Characteristics of Vegetation by a New Excitation Wavelength,” Spectrosc. Lett. 49(4), 263–267 (2016).
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J. Yang, W. Gong, S. Shi, L. Du, J. Sun, Y. Y. Ma, and S. L. Song, “Accurate identification of nitrogen fertilizer application of paddy rice using laser-induced fluorescence combined with support vector machine,” Plant Soil Environ. 61(11), 501–506 (2015).
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J. Yang, S. Shi, W. Gong, L. Du, Y. Y. Ma, B. Zhu, and S. L. Song, “Application of fluorescence spectrum to precisely inverse paddy rice nitrogen content,” Plant Soil Environ. 61(4), 182–188 (2015).
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M. A. Hearst, S. T. Dumais, E. Osman, J. Platt, and B. Scholkopf, “Support vector machines,” Intelligent Syst. Appl. 13(4), 18–28 (1998).
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D. L. Farkas, A. S. Gouveia-Neto, J. E. A. Silva, E. B. Costa, L. A. Bueno, L. M. H. Silva, M. M. C. Granja, M. J. L. Medeiros, T. J. R. Câmara, L. G. Willadino, D. V. Nicolau, and R. C. Leif, “Plant abiotic stress diagnostic by laser induced chlorophyll fluorescence spectral analysis of in vivo leaf tissue of biofuel species,” Int. Soc. Opt. Photonics 7568, 75680G (2010).

Feng, W.

W. Feng, X. Yao, Y. Zhu, Y. Tian, and W. Cao, “Monitoring leaf nitrogen status with hyperspectral reflectance in wheat,” Eur. J. Agron. 28(3), 394–404 (2008).
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Ferroni, L.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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M. Živcak, K. Olsovska, P. Slamka, J. Galambošová, V. Rataj, H. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60, 210–215 (2014).

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R. Zong, Y. Zhi, B. Yao, J. Gao, and A. A. Stec, “Classification and identification of soot source with principal component analysis and back-propagation neural network,” Aust. J. Forensic Sci. 46(2), 224–233 (2014).
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M. K. Gill, T. Asefa, M. W. Kemblowski, and M. McKee, “Soil moisture prediction using support vector machines,” J. Am. Water Resour. Assoc. 42(4), 1033–1046 (2006).
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A. A. Gitelson, C. Buschmann, and H. K. Lichtenthaler, “The chlorophyll fluorescence ratio F 735/F 700 as an accurate measure of the chlorophyll content in plants,” Remote Sens. Environ. 69(3), 296–302 (1999).
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Goltsev, V.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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H. M. Kalaji, A. Jajoo, A. Oukarroum, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, I. Łukasik, V. Goltsev, and R. J. Ladle, “Chlorophyll a fluorescence as a tool to monitor physiological status of plants under abiotic stress conditions,” Acta Physiol. Plant. 38(4), 1–11 (2016).
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A. I. Samborska, V. Alexandrov, L. Sieczko, B. Kornatowska, V. Goltsev, D. C. Magdalena, and H. M. Kalaji, “Artificial neural networks and their application in biological and agricultural research,” J. Nano PhotoBioSciences 2, 14–30 (2014).

V. Goltsev, I. Zaharieva, P. Chernev, M. Kouzmanova, H. M. Kalaji, I. Yordanov, V. Krasteva, V. Alexandrov, D. Stefanov, S. I. Allakhverdiev, and R. J. Strasser, “Drought-induced modifications of photosynthetic electron transport in intact leaves: analysis and use of neural networks as a tool for a rapid non-invasive estimation,” Biochim. Biophys. Acta 1817(8), 1490–1498 (2012).
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Gong, W.

J. Yang, W. Gong, S. Shi, L. Du, B. Zhu, J. Sun, and S. Song, “Excitation Wavelength Analysis of Laser-Induced Fluorescence LiDAR for Identifying Plant Species,” IEEE Geosci. Remote Sens. Lett. 13(7), 977–981 (2016).
[Crossref]

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, and S. Song, “Laser-Induced Fluorescence Characteristics of Vegetation by a New Excitation Wavelength,” Spectrosc. Lett. 49(4), 263–267 (2016).
[Crossref]

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, Y. Y. Ma, and S. L. Song, “Accurate identification of nitrogen fertilizer application of paddy rice using laser-induced fluorescence combined with support vector machine,” Plant Soil Environ. 61(11), 501–506 (2015).
[Crossref]

J. Yang, S. Shi, W. Gong, L. Du, Y. Y. Ma, B. Zhu, and S. L. Song, “Application of fluorescence spectrum to precisely inverse paddy rice nitrogen content,” Plant Soil Environ. 61(4), 182–188 (2015).
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D. L. Farkas, A. S. Gouveia-Neto, J. E. A. Silva, E. B. Costa, L. A. Bueno, L. M. H. Silva, M. M. C. Granja, M. J. L. Medeiros, T. J. R. Câmara, L. G. Willadino, D. V. Nicolau, and R. C. Leif, “Plant abiotic stress diagnostic by laser induced chlorophyll fluorescence spectral analysis of in vivo leaf tissue of biofuel species,” Int. Soc. Opt. Photonics 7568, 75680G (2010).

Granja, M. M. C.

D. L. Farkas, A. S. Gouveia-Neto, J. E. A. Silva, E. B. Costa, L. A. Bueno, L. M. H. Silva, M. M. C. Granja, M. J. L. Medeiros, T. J. R. Câmara, L. G. Willadino, D. V. Nicolau, and R. C. Leif, “Plant abiotic stress diagnostic by laser induced chlorophyll fluorescence spectral analysis of in vivo leaf tissue of biofuel species,” Int. Soc. Opt. Photonics 7568, 75680G (2010).

Guidi, L.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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Hannaway, D. B.

Y. C. Tian, X. Yao, J. Yang, W. X. Cao, D. B. Hannaway, and Y. Zhu, “Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance,” Field Crops Res. 120(2), 299–310 (2011).
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Hearst, M. A.

M. A. Hearst, S. T. Dumais, E. Osman, J. Platt, and B. Scholkopf, “Support vector machines,” Intelligent Syst. Appl. 13(4), 18–28 (1998).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
[PubMed]

H. M. Kalaji, A. Jajoo, A. Oukarroum, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, I. Łukasik, V. Goltsev, and R. J. Ladle, “Chlorophyll a fluorescence as a tool to monitor physiological status of plants under abiotic stress conditions,” Acta Physiol. Plant. 38(4), 1–11 (2016).
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Kalaji, H. M.

H. M. Kalaji, A. Jajoo, A. Oukarroum, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, I. Łukasik, V. Goltsev, and R. J. Ladle, “Chlorophyll a fluorescence as a tool to monitor physiological status of plants under abiotic stress conditions,” Acta Physiol. Plant. 38(4), 1–11 (2016).
[Crossref]

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
[PubMed]

A. I. Samborska, V. Alexandrov, L. Sieczko, B. Kornatowska, V. Goltsev, D. C. Magdalena, and H. M. Kalaji, “Artificial neural networks and their application in biological and agricultural research,” J. Nano PhotoBioSciences 2, 14–30 (2014).

M. Brestic, M. Zivcak, H. M. Kalaji, R. Carpentier, and S. I. Allakhverdiev, “Photosystem II thermostability in situ: environmentally induced acclimation and genotype-specific reactions in Triticum aestivum L,” Plant Physiol. Biochem. 57, 93–105 (2012).
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V. Goltsev, I. Zaharieva, P. Chernev, M. Kouzmanova, H. M. Kalaji, I. Yordanov, V. Krasteva, V. Alexandrov, D. Stefanov, S. I. Allakhverdiev, and R. J. Strasser, “Drought-induced modifications of photosynthetic electron transport in intact leaves: analysis and use of neural networks as a tool for a rapid non-invasive estimation,” Biochim. Biophys. Acta 1817(8), 1490–1498 (2012).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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H. M. Kalaji, A. Jajoo, A. Oukarroum, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, I. Łukasik, V. Goltsev, and R. J. Ladle, “Chlorophyll a fluorescence as a tool to monitor physiological status of plants under abiotic stress conditions,” Acta Physiol. Plant. 38(4), 1–11 (2016).
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F. Heisel, M. Sowinska, J. A. Miehé, M. Lang, and H. K. Lichtenthaler, “Detection of nutrient deficiencies of maize by laser induced fluorescence imaging,” J. Plant Physiol. 148(5), 622–631 (1996).
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D. L. Farkas, A. S. Gouveia-Neto, J. E. A. Silva, E. B. Costa, L. A. Bueno, L. M. H. Silva, M. M. C. Granja, M. J. L. Medeiros, T. J. R. Câmara, L. G. Willadino, D. V. Nicolau, and R. C. Leif, “Plant abiotic stress diagnostic by laser induced chlorophyll fluorescence spectral analysis of in vivo leaf tissue of biofuel species,” Int. Soc. Opt. Photonics 7568, 75680G (2010).

Lemke, R.

S. S. Malhi, R. Lemke, Z. Wang, and B. S. Chhabra, “Tillage, nitrogen and crop residue effects on crop yield, nutrient uptake, soil quality, and greenhouse gas emissions,” Soil Tillage Res. 90(1-2), 171–183 (2006).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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X. Liang, H. Li, S. Wang, Y. Ye, Y. Ji, G. Tian, C. van Kessel, and B. Linquist, “Nitrogen management to reduce yield-scaled global warming potential in rice,” Field Crops Res. 146, 66–74 (2013).
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A. A. Gitelson, C. Buschmann, and H. K. Lichtenthaler, “The chlorophyll fluorescence ratio F 735/F 700 as an accurate measure of the chlorophyll content in plants,” Remote Sens. Environ. 69(3), 296–302 (1999).
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J. Schweiger, M. Lang, and H. K. Lichtenthaler, “Differences in Fluorescence Excitation Spectra of Leaves between Stressed and Non-Stressed Plants,” J. Plant Physiol. 148(5), 536–547 (1996).
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F. Heisel, M. Sowinska, J. A. Miehé, M. Lang, and H. K. Lichtenthaler, “Detection of nutrient deficiencies of maize by laser induced fluorescence imaging,” J. Plant Physiol. 148(5), 622–631 (1996).
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Linquist, B.

X. Liang, H. Li, S. Wang, Y. Ye, Y. Ji, G. Tian, C. van Kessel, and B. Linquist, “Nitrogen management to reduce yield-scaled global warming potential in rice,” Field Crops Res. 146, 66–74 (2013).
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Liu, Z.-Y.

Q.-X. Yi, J.-F. Huang, F.-M. Wang, X.-Z. Wang, and Z.-Y. Liu, “Monitoring rice nitrogen status using hyperspectral reflectance and artificial neural network,” Environ. Sci. Technol. 41(19), 6770–6775 (2007).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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Lukasik, I.

H. M. Kalaji, A. Jajoo, A. Oukarroum, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, I. Łukasik, V. Goltsev, and R. J. Ladle, “Chlorophyll a fluorescence as a tool to monitor physiological status of plants under abiotic stress conditions,” Acta Physiol. Plant. 38(4), 1–11 (2016).
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Y. Ma and W. Gong, “Evaluating the performance of SVM in dust aerosol discrimination and testing its ability in an extended area,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 5(6), 1849–1858 (2012).
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Magdalena, D. C.

A. I. Samborska, V. Alexandrov, L. Sieczko, B. Kornatowska, V. Goltsev, D. C. Magdalena, and H. M. Kalaji, “Artificial neural networks and their application in biological and agricultural research,” J. Nano PhotoBioSciences 2, 14–30 (2014).

Malenovský, Z.

Z. Malenovský, K. B. Mishra, F. Zemek, U. Rascher, and L. Nedbal, “Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence,” J. Exp. Bot. 60(11), 2987–3004 (2009).
[Crossref] [PubMed]

Malhi, S. S.

S. S. Malhi, R. Lemke, Z. Wang, and B. S. Chhabra, “Tillage, nitrogen and crop residue effects on crop yield, nutrient uptake, soil quality, and greenhouse gas emissions,” Soil Tillage Res. 90(1-2), 171–183 (2006).
[Crossref]

McKee, M.

M. K. Gill, T. Asefa, M. W. Kemblowski, and M. McKee, “Soil moisture prediction using support vector machines,” J. Am. Water Resour. Assoc. 42(4), 1033–1046 (2006).
[Crossref]

McMurtrey, J. E.

Medeiros, M. J. L.

D. L. Farkas, A. S. Gouveia-Neto, J. E. A. Silva, E. B. Costa, L. A. Bueno, L. M. H. Silva, M. M. C. Granja, M. J. L. Medeiros, T. J. R. Câmara, L. G. Willadino, D. V. Nicolau, and R. C. Leif, “Plant abiotic stress diagnostic by laser induced chlorophyll fluorescence spectral analysis of in vivo leaf tissue of biofuel species,” Int. Soc. Opt. Photonics 7568, 75680G (2010).

Miehé, J. A.

F. Heisel, M. Sowinska, J. A. Miehé, M. Lang, and H. K. Lichtenthaler, “Detection of nutrient deficiencies of maize by laser induced fluorescence imaging,” J. Plant Physiol. 148(5), 622–631 (1996).
[Crossref]

Mishra, K. B.

Z. Malenovský, K. B. Mishra, F. Zemek, U. Rascher, and L. Nedbal, “Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence,” J. Exp. Bot. 60(11), 2987–3004 (2009).
[Crossref] [PubMed]

Mishra, V. K.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
[PubMed]

Misra, A. N.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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Moran, M. S.

M. P. Cendrero-Mateo, M. S. Moran, S. A. Papuga, K. R. Thorp, L. Alonso, J. Moreno, G. Ponce-Campos, U. Rascher, and G. Wang, “Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments,” J. Exp. Bot. 67(1), 275–286 (2016).
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M. P. Cendrero-Mateo, M. S. Moran, S. A. Papuga, K. R. Thorp, L. Alonso, J. Moreno, G. Ponce-Campos, U. Rascher, and G. Wang, “Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments,” J. Exp. Bot. 67(1), 275–286 (2016).
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Nagatake, A.

P. Nugroho, M. Shimizu, H. Nakamato, A. Nagatake, S. Suwardi, U. Sudadi, and R. Hatano, “Nitrous oxide fluxes from soil under different crops and fertilizer management,” Plant Soil Environ. 61, 385–392 (2015).

Nakamato, H.

P. Nugroho, M. Shimizu, H. Nakamato, A. Nagatake, S. Suwardi, U. Sudadi, and R. Hatano, “Nitrous oxide fluxes from soil under different crops and fertilizer management,” Plant Soil Environ. 61, 385–392 (2015).

Nebauer, S. G.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
[PubMed]

Nedbal, L.

Z. Malenovský, K. B. Mishra, F. Zemek, U. Rascher, and L. Nedbal, “Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence,” J. Exp. Bot. 60(11), 2987–3004 (2009).
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D. L. Farkas, A. S. Gouveia-Neto, J. E. A. Silva, E. B. Costa, L. A. Bueno, L. M. H. Silva, M. M. C. Granja, M. J. L. Medeiros, T. J. R. Câmara, L. G. Willadino, D. V. Nicolau, and R. C. Leif, “Plant abiotic stress diagnostic by laser induced chlorophyll fluorescence spectral analysis of in vivo leaf tissue of biofuel species,” Int. Soc. Opt. Photonics 7568, 75680G (2010).

Nugroho, P.

P. Nugroho, M. Shimizu, H. Nakamato, A. Nagatake, S. Suwardi, U. Sudadi, and R. Hatano, “Nitrous oxide fluxes from soil under different crops and fertilizer management,” Plant Soil Environ. 61, 385–392 (2015).

Olsovska, K.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
[PubMed]

M. Živcak, K. Olsovska, P. Slamka, J. Galambošová, V. Rataj, H. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60, 210–215 (2014).

Osman, E.

M. A. Hearst, S. T. Dumais, E. Osman, J. Platt, and B. Scholkopf, “Support vector machines,” Intelligent Syst. Appl. 13(4), 18–28 (1998).
[Crossref]

Osmond, B.

Z. Kolber, D. Klimov, G. Ananyev, U. Rascher, J. Berry, and B. Osmond, “Measuring photosynthetic parameters at a distance: laser induced fluorescence transient (LIFT) method for remote measurements of photosynthesis in terrestrial vegetation,” Photosynth. Res. 84(1-3), 121–129 (2005).
[Crossref] [PubMed]

Oukarroum, A.

H. M. Kalaji, A. Jajoo, A. Oukarroum, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, I. Łukasik, V. Goltsev, and R. J. Ladle, “Chlorophyll a fluorescence as a tool to monitor physiological status of plants under abiotic stress conditions,” Acta Physiol. Plant. 38(4), 1–11 (2016).
[Crossref]

Pancaldi, S.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
[PubMed]

Panigrahi, P. K.

N. Agarwal, S. Gupta, A. Pradhan, K. Vishwanathan, and P. K. Panigrahi, “Wavelet transform of breast tissue fluorescence spectra: a technique for diagnosis of tumors,” IEEE J. Sel. Top. Quantum Electron. 9(2), 154–161 (2003).
[Crossref]

Papuga, S. A.

M. P. Cendrero-Mateo, M. S. Moran, S. A. Papuga, K. R. Thorp, L. Alonso, J. Moreno, G. Ponce-Campos, U. Rascher, and G. Wang, “Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments,” J. Exp. Bot. 67(1), 275–286 (2016).
[Crossref] [PubMed]

Penella, C.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
[PubMed]

Platt, J.

M. A. Hearst, S. T. Dumais, E. Osman, J. Platt, and B. Scholkopf, “Support vector machines,” Intelligent Syst. Appl. 13(4), 18–28 (1998).
[Crossref]

Pollastrini, M.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
[PubMed]

Ponce-Campos, G.

M. P. Cendrero-Mateo, M. S. Moran, S. A. Papuga, K. R. Thorp, L. Alonso, J. Moreno, G. Ponce-Campos, U. Rascher, and G. Wang, “Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments,” J. Exp. Bot. 67(1), 275–286 (2016).
[Crossref] [PubMed]

Pradhan, A.

N. Agarwal, S. Gupta, A. Pradhan, K. Vishwanathan, and P. K. Panigrahi, “Wavelet transform of breast tissue fluorescence spectra: a technique for diagnosis of tumors,” IEEE J. Sel. Top. Quantum Electron. 9(2), 154–161 (2003).
[Crossref]

Ramos, M. E.

M. E. Ramos and M. G. Lagorio, “True fluorescence spectra of leaves,” Photochem. Photobiol. Sci. 3(11-12), 1063–1066 (2004).
[Crossref] [PubMed]

Rascher, U.

M. P. Cendrero-Mateo, M. S. Moran, S. A. Papuga, K. R. Thorp, L. Alonso, J. Moreno, G. Ponce-Campos, U. Rascher, and G. Wang, “Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments,” J. Exp. Bot. 67(1), 275–286 (2016).
[Crossref] [PubMed]

Z. Malenovský, K. B. Mishra, F. Zemek, U. Rascher, and L. Nedbal, “Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence,” J. Exp. Bot. 60(11), 2987–3004 (2009).
[Crossref] [PubMed]

Z. Kolber, D. Klimov, G. Ananyev, U. Rascher, J. Berry, and B. Osmond, “Measuring photosynthetic parameters at a distance: laser induced fluorescence transient (LIFT) method for remote measurements of photosynthesis in terrestrial vegetation,” Photosynth. Res. 84(1-3), 121–129 (2005).
[Crossref] [PubMed]

Rataj, V.

M. Živcak, K. Olsovska, P. Slamka, J. Galambošová, V. Rataj, H. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60, 210–215 (2014).

Rusinowski, S.

H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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Samborska, A. I.

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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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J. Yang, S. Shi, W. Gong, L. Du, Y. Y. Ma, B. Zhu, and S. L. Song, “Application of fluorescence spectrum to precisely inverse paddy rice nitrogen content,” Plant Soil Environ. 61(4), 182–188 (2015).
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A. I. Samborska, V. Alexandrov, L. Sieczko, B. Kornatowska, V. Goltsev, D. C. Magdalena, and H. M. Kalaji, “Artificial neural networks and their application in biological and agricultural research,” J. Nano PhotoBioSciences 2, 14–30 (2014).

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D. L. Farkas, A. S. Gouveia-Neto, J. E. A. Silva, E. B. Costa, L. A. Bueno, L. M. H. Silva, M. M. C. Granja, M. J. L. Medeiros, T. J. R. Câmara, L. G. Willadino, D. V. Nicolau, and R. C. Leif, “Plant abiotic stress diagnostic by laser induced chlorophyll fluorescence spectral analysis of in vivo leaf tissue of biofuel species,” Int. Soc. Opt. Photonics 7568, 75680G (2010).

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M. Živcak, K. Olsovska, P. Slamka, J. Galambošová, V. Rataj, H. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60, 210–215 (2014).

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J. Yang, W. Gong, S. Shi, L. Du, J. Sun, and S. Song, “Laser-Induced Fluorescence Characteristics of Vegetation by a New Excitation Wavelength,” Spectrosc. Lett. 49(4), 263–267 (2016).
[Crossref]

J. Yang, W. Gong, S. Shi, L. Du, B. Zhu, J. Sun, and S. Song, “Excitation Wavelength Analysis of Laser-Induced Fluorescence LiDAR for Identifying Plant Species,” IEEE Geosci. Remote Sens. Lett. 13(7), 977–981 (2016).
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Song, S. L.

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, Y. Y. Ma, and S. L. Song, “Accurate identification of nitrogen fertilizer application of paddy rice using laser-induced fluorescence combined with support vector machine,” Plant Soil Environ. 61(11), 501–506 (2015).
[Crossref]

J. Yang, S. Shi, W. Gong, L. Du, Y. Y. Ma, B. Zhu, and S. L. Song, “Application of fluorescence spectrum to precisely inverse paddy rice nitrogen content,” Plant Soil Environ. 61(4), 182–188 (2015).
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Sun, J.

J. Yang, W. Gong, S. Shi, L. Du, B. Zhu, J. Sun, and S. Song, “Excitation Wavelength Analysis of Laser-Induced Fluorescence LiDAR for Identifying Plant Species,” IEEE Geosci. Remote Sens. Lett. 13(7), 977–981 (2016).
[Crossref]

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, and S. Song, “Laser-Induced Fluorescence Characteristics of Vegetation by a New Excitation Wavelength,” Spectrosc. Lett. 49(4), 263–267 (2016).
[Crossref]

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, Y. Y. Ma, and S. L. Song, “Accurate identification of nitrogen fertilizer application of paddy rice using laser-induced fluorescence combined with support vector machine,” Plant Soil Environ. 61(11), 501–506 (2015).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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W. Feng, X. Yao, Y. Zhu, Y. Tian, and W. Cao, “Monitoring leaf nitrogen status with hyperspectral reflectance in wheat,” Eur. J. Agron. 28(3), 394–404 (2008).
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Tian, Y. C.

Y. C. Tian, X. Yao, J. Yang, W. X. Cao, D. B. Hannaway, and Y. Zhu, “Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance,” Field Crops Res. 120(2), 299–310 (2011).
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X. Liang, H. Li, S. Wang, Y. Ye, Y. Ji, G. Tian, C. van Kessel, and B. Linquist, “Nitrogen management to reduce yield-scaled global warming potential in rice,” Field Crops Res. 146, 66–74 (2013).
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S. Apostol, A. A. Viau, and N. Tremblay, “A comparison of multiwavelength laser-induced fluorescence parameters for the remote sensing of nitrogen stress in field-cultivated corn,” Can. J. Rem. Sens. 33(3), 150–161 (2007).
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M. P. Cendrero-Mateo, M. S. Moran, S. A. Papuga, K. R. Thorp, L. Alonso, J. Moreno, G. Ponce-Campos, U. Rascher, and G. Wang, “Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments,” J. Exp. Bot. 67(1), 275–286 (2016).
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X. Liang, H. Li, S. Wang, Y. Ye, Y. Ji, G. Tian, C. van Kessel, and B. Linquist, “Nitrogen management to reduce yield-scaled global warming potential in rice,” Field Crops Res. 146, 66–74 (2013).
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Q.-X. Yi, J.-F. Huang, F.-M. Wang, X.-Z. Wang, and Z.-Y. Liu, “Monitoring rice nitrogen status using hyperspectral reflectance and artificial neural network,” Environ. Sci. Technol. 41(19), 6770–6775 (2007).
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J. Yang, W. Gong, S. Shi, L. Du, J. Sun, and S. Song, “Laser-Induced Fluorescence Characteristics of Vegetation by a New Excitation Wavelength,” Spectrosc. Lett. 49(4), 263–267 (2016).
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J. Yang, S. Shi, W. Gong, L. Du, Y. Y. Ma, B. Zhu, and S. L. Song, “Application of fluorescence spectrum to precisely inverse paddy rice nitrogen content,” Plant Soil Environ. 61(4), 182–188 (2015).
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H. M. Kalaji, G. Schansker, M. Brestic, F. Bussotti, A. Calatayud, L. Ferroni, V. Goltsev, L. Guidi, A. Jajoo, P. Li, P. Losciale, V. K. Mishra, A. N. Misra, S. G. Nebauer, S. Pancaldi, C. Penella, M. Pollastrini, K. Suresh, E. Tambussi, M. Yanniccari, M. Zivcak, M. D. Cetner, I. A. Samborska, A. Stirbet, K. Olsovska, K. Kunderlikova, H. Shelonzek, S. Rusinowski, and W. Bąba, “Frequently asked questions about chlorophyll fluorescence, the sequel,” Photosynth. Res. 318, 1–54 (2016).
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Y. C. Tian, X. Yao, J. Yang, W. X. Cao, D. B. Hannaway, and Y. Zhu, “Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance,” Field Crops Res. 120(2), 299–310 (2011).
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W. Feng, X. Yao, Y. Zhu, Y. Tian, and W. Cao, “Monitoring leaf nitrogen status with hyperspectral reflectance in wheat,” Eur. J. Agron. 28(3), 394–404 (2008).
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Yi, Q.-X.

Q.-X. Yi, J.-F. Huang, F.-M. Wang, X.-Z. Wang, and Z.-Y. Liu, “Monitoring rice nitrogen status using hyperspectral reflectance and artificial neural network,” Environ. Sci. Technol. 41(19), 6770–6775 (2007).
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H. Shahabi, B. B. Ahmad, M. H. Mokhtari, and M. A. Zadeh, “Detection of urban irregular development and green space destruction using normalized difference vegetation index (NDVI), principal component analysis (PCA) and post classification methods: a case study of Saqqez City,” Int. J. Phys. Sci. 7, 2587–2595 (2012).

Zaharieva, I.

V. Goltsev, I. Zaharieva, P. Chernev, M. Kouzmanova, H. M. Kalaji, I. Yordanov, V. Krasteva, V. Alexandrov, D. Stefanov, S. I. Allakhverdiev, and R. J. Strasser, “Drought-induced modifications of photosynthetic electron transport in intact leaves: analysis and use of neural networks as a tool for a rapid non-invasive estimation,” Biochim. Biophys. Acta 1817(8), 1490–1498 (2012).
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R. Zong, Y. Zhi, B. Yao, J. Gao, and A. A. Stec, “Classification and identification of soot source with principal component analysis and back-propagation neural network,” Aust. J. Forensic Sci. 46(2), 224–233 (2014).
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Zhu, B.

J. Yang, W. Gong, S. Shi, L. Du, B. Zhu, J. Sun, and S. Song, “Excitation Wavelength Analysis of Laser-Induced Fluorescence LiDAR for Identifying Plant Species,” IEEE Geosci. Remote Sens. Lett. 13(7), 977–981 (2016).
[Crossref]

J. Yang, S. Shi, W. Gong, L. Du, Y. Y. Ma, B. Zhu, and S. L. Song, “Application of fluorescence spectrum to precisely inverse paddy rice nitrogen content,” Plant Soil Environ. 61(4), 182–188 (2015).
[Crossref]

Zhu, Y.

Y. C. Tian, X. Yao, J. Yang, W. X. Cao, D. B. Hannaway, and Y. Zhu, “Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance,” Field Crops Res. 120(2), 299–310 (2011).
[Crossref]

W. Feng, X. Yao, Y. Zhu, Y. Tian, and W. Cao, “Monitoring leaf nitrogen status with hyperspectral reflectance in wheat,” Eur. J. Agron. 28(3), 394–404 (2008).
[Crossref]

Zivcak, M.

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Figures (5)

Fig. 1
Fig. 1 The normalized leaf fluorescence spectra of paddy rice excited by three different EWs with the changes in LNCs: (a) 355 nm; (b) 460 nm; (c) 556 nm.
Fig. 2
Fig. 2 The relationship between LNC and fluorescence parameters excited by different EWs. (n = 432). The red solid line represents linear regression.
Fig. 3
Fig. 3 The loading weights of the first three principal components with different EWs: (a) 355 nm; (b) 460 nm; (c) 556 nm.
Fig. 4
Fig. 4 The relationship between the predicted LNC using different fluorescence characteristics based on BPNN algorithm and observed LNC (n = 130) for different EWs. (a), (b), (c): 355 nm laser; (d), (e), (f): 460 nm laser; (g), (h), (i): 556 nm laser. (a), (d), (g): using fluorescence characteristic peaks as the input variables; (b), (e), (h): using fluorescence spectra as the input variables; (c), (f), (i): using the factor scores calculated from the first three PCs as the input variables. The dotted line denotes the 1:1 line and the red solid line represents linear regression.
Fig. 5
Fig. 5 The relationship between the predicted LNC using different fluorescence characteristics based on SVM algorithm and the observed LNC (n = 130) for different EWs. (a), (b), (c): 355 nm laser; (d), (e), (f): 460 nm laser; (g), (h), (i): 556 nm laser. (a), (d), (g): using fluorescence peaks as the input variables; (b), (e), (h): using fluorescence spectra as the input variables; (c), (f), (i): using the factor scores calculated from the first three PCs as the input variables. The dotted line denotes the 1:1 line and the red solid line represents linear regression.

Tables (2)

Tables Icon

Table 1 The percentage of explained variance for the first three PCs. EV: Explained variance; CV: Cumulative variance.

Tables Icon

Table 2 The performance analysis of different models for leaf nitrogen content (n = 130) based on coefficient of determination (R2), root mean square error (RMSE), and relative error (RE) in the prediction with different excitation wavelengths (EWs).

Equations (3)

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K ( x i , x j ) = exp ( γ x j x i 2 )
R M S E = 1 n i = 1 n ( P i M i ) 2
R E = 100 M ¯ R M S E

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