Abstract

Nitrogen (N) is an essential nutrient for crop growth. The rapid and non-destructive monitoring of N nutrition in crops through remote sensing is important for the accurate diagnosis and quality evaluation of crop growth status. Leaf nitrogen concentration (LNC), which has been widely utilized in remote sensing, serves as a crucial indicator for the monitoring of crops growth status. In this study, the first-derivative fluorescence spectrum (FDFS) based on laser-induced fluorescence (LIF) was proposed for LNC estimation in paddy rice. First, the correlation between the LNC and FDFS at each wavelength was analyzed in detail using different excitation light wavelengths (ELWs; 355, 420, and 556 nm). Then, FDFS was used as an input parameter to train a back-propagation neural networks (BPNN) model for LNC estimation. The coefficients of determination (R2) of the linear regression analysis between the measured and predicted LNC were 0.823, 0.743, and 0.837, corresponding to 355, 420, and 556 nm ELWs, respectively. Second, the principal components analysis was performed for the extraction of the main characteristics of FDFS, and the calculated variables were used for LNC inversion. The R2 values were 0.891, 0.815, and 0.907 for 355, 420, and 556 nm ELWs, respectively. In addition, the correlation between the ratio of FDFS and LNC was also analyzed, which can provide a reference for the selection of optimal wavelengths for LNC monitoring. The experimental results exhibited the promising potential of FDFS combined with multivariate analysis for LNC monitoring, which can allow additional fluorescence characteristics to improve the accuracy of LNC monitoring.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2018 (3)

W. Huang, Y. J. Yang, S. B. Zhang, and T. Liu, “Cyclic Electron Flow around Photosystem I Promotes ATP Synthesis Possibly Helping the Rapid Repair of Photodamaged Photosystem II at Low Light,” Front. Plant Sci. 9, 239 (2018).
[Crossref] [PubMed]

J. Yang, L. Du, W. Gong, S. Shi, J. Sun, and B. Chen, “Potential of vegetation indices combined with laser-induced fluorescence parameters for monitoring leaf nitrogen content in paddy rice,” PLoS One 13(1), e0191068 (2018).
[Crossref] [PubMed]

X. Zhou, C. Sun, P. Zhu, and F. Liu, “Effects of Antimony Stress on Photosynthesis and Growth of Acorus calamus,” Front. Plant Sci. 9, 579 (2018).
[Crossref] [PubMed]

2017 (2)

J. Yang, J. Sun, L. Du, B. Chen, Z. Zhang, S. Shi, and W. Gong, “Effect of fluorescence characteristics and different algorithms on the estimation of leaf nitrogen content based on laser-induced fluorescence lidar in paddy rice,” Opt. Express 25(4), 3743–3755 (2017).
[Crossref] [PubMed]

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. 132(1), 13–66 (2017).
[PubMed]

2016 (5)

L. He, X. Song, W. Feng, B.-B. Guo, Y.-S. Zhang, Y.-H. Wang, C.-Y. Wang, and T.-C. Guo, “Improved remote sensing of leaf nitrogen concentration in winter wheat using multi-angular hyperspectral data,” Remote Sens. Environ. 174, 122–133 (2016).
[Crossref]

C. Gameiro, A. Utkin, P. Cartaxana, J. M. da Silva, and A R.. Matos, “The use of laser induced chlorophyll fluorescence (LIF) as a fast and non‑destructive method to investigate water deficit in Arabidopsi,” Agr. Water Manage. 164, 127–136 (2016).
[Crossref]

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]

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, S. Song, B. Chen, and Z. Zhang, “Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice,” Sci. Rep. 6, 28787 (2016).
[Crossref] [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), 102 (2016).
[Crossref]

2015 (4)

J. Wang, T. Wang, A. K. Skidmore, T. Shi, and G. Wu, “Evaluating Different Methods for Grass Nutrient Estimation from Canopy Hyperspectral Reflectance,” Remote Sens. 7(5), 5901–5917 (2015).
[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]

M. Zivcak, M. Brestic, K. Kunderlikova, K. Olsovska, and S. I. Allakhverdiev, “Effect of photosystem I inactivation on chlorophyll a fluorescence induction in wheat leaves: Does activity of photosystem I play any role in OJIP rise?” J. Photochem. Photobiol. B 152(Pt B), 318–324 (2015).
[Crossref] [PubMed]

M. Zivcak, M. Brestic, K. Kunderlikova, O. Sytar, and S. I. Allakhverdiev, “Repetitive light pulse-induced photoinhibition of photosystem I severely affects CO2 assimilation and photoprotection in wheat leaves,” Photosynth. Res. 126(2-3), 449–463 (2015).
[Crossref] [PubMed]

2014 (6)

A. Raesch, O. Muller, R. Pieruschka, and U. Rascher, “Field Observations with Laser-Induced Fluorescence Transient (LIFT) Method in Barley and Sugar Beet,” Agriculture 4(2), 159–169 (2014).
[Crossref]

R. Bro and A. K. Smilde, “Principal component analysis,” Anal. Methods 6(9), 2812–2831 (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. NanoPhotoBioSciences 2, 14–30 (2014).

F. Li, B. Mistele, Y. Hu, X. Chen, and U. Schmidhalter, “Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression,” Eur. J. Agron. 52, 198–209 (2014).
[Crossref]

H. M. Kalaji, A. Oukarroum, V. Alexandrov, M. Kouzmanova, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, S. I. Allakhverdiev, and V. Goltsev, “Identification of nutrient deficiency in maize and tomato plants by in vivo chlorophyll a fluorescence measurements,” Plant Physiol. Biochem. 81, 16–25 (2014).
[Crossref] [PubMed]

M. Živčák, K. Olšovská, P. Slamka, J. Galambošová, V. Rataj, H. B. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60(5), 210–215 (2014).
[Crossref]

2013 (1)

M. Diacono, P. Rubino, and F. Montemurro, “Precision nitrogen management of wheat. A review,” Agron. Sustain. Dev. 33(1), 219–241 (2013).
[Crossref]

2012 (2)

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]

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]

2011 (2)

S. Song, W. Gong, B. Zhu, and X. Huang, “Wavelength selection and spectral discrimination for paddy rice, with laboratory measurements of hyperspectral leaf reflectance,” ISPRS J. Photogramm. 66(5), 672–682 (2011).
[Crossref]

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 (1)

R. Pieruschka, D. Klimov, Z. S. Kolber, and J. A. Berry, “Monitoring of cold and light stress impact on photosynthesis by using the laser induced fluorescence transient (LIFT) approach,” Funct. Plant Biol. 37(5), 395–402 (2010).
[Crossref]

2009 (1)

D. Stroppiana, M. Boschetti, P. A. Brivio, and S. Bocchi, “Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry,” Field Crops Res. 111(1-2), 119–129 (2009).
[Crossref]

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 (2)

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]

2005 (2)

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]

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 (2)

B. Anderson, P. K. Buah-Bassuah, and J. P. Tetteh, “Using violet laser-induced chlorophyll fluorescence emission spectra for crop yield assessment of cowpea (Vigna unguiculata (L) Walp) varieties,” Meas. Sci. Technol. 15(7), 1255–1265 (2004).
[Crossref]

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)

P. J. Zarco-Tejada, C. A. Rueda, and S. L. Ustin, “Water content estimation in vegetation with MODIS reflectance data and model inversion methods,” Remote Sens. Environ. 85(1), 109–124 (2003).
[Crossref]

2002 (1)

S. L. Osborne, J. S. Schepers, D. D. Francis, and M. R. Schlemmer, “Detection of Phosphorus and Nitrogen Deficiencies in Corn Using Spectral Radiance Measurements,” Agron. J. 94(6), 1215–1221 (2002).
[Crossref]

2001 (1)

L. S. Galvão, M. A. Pizarro, and J. C. N. Epiphanio, “Variations in reflectance of tropical soils: spectral-chemical composition relationships from AVIRIS data,” Remote Sens. Environ. 75(2), 245–255 (2001).
[Crossref]

1999 (1)

N. Subhash, O. Wenzel, and H. K. Lichtenthaler, “Changes in blue-green and chlorophyll fluorescence emission and fluorescence ratios during senescence of tobacco plants,” Remote Sens. Environ. 69(3), 215–223 (1999).
[Crossref]

1998 (2)

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

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]

1996 (1)

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]

1995 (1)

B. J. Yoder and R. E. Pettigrew-Crosby, “Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400–2500 nm) at leaf and canopy scales,” Remote Sens. Environ. 53(3), 199–211 (1995).
[Crossref]

1994 (4)

K. Günther, H.-G. Dahn, and W. Lüdeker, “Remote sensing vegetation status by laser-induced fluorescence,” Remote Sens. Environ. 47(1), 10–17 (1994).
[Crossref]

N. Subhash and C. N. Mohanan, “Laser-induced red chlorophyll fluorescence signatures as nutrient stress indicator in rice plants,” Remote Sens. Environ. 47(1), 45–50 (1994).
[Crossref]

J. McMurtrey, E. Chappelle, M. Kim, J. Meisinger, and L. Corp, “Distinguishing nitrogen fertilization levels in field corn (Zea mays L.) with actively induced fluorescence and passive reflectance measurements,” Remote Sens. Environ. 47(1), 36–44 (1994).
[Crossref]

G. Cecchi, P. Mazzinghi, L. Pantani, R. Valentini, D. Tirelli, and P. De Angelis, “Remote sensing of chlorophyll a fluorescence of vegetation canopies: 1. Near and far field measurement techniques,” Remote Sens. Environ. 47(1), 18–28 (1994).
[Crossref]

1984 (1)

1983 (1)

Agati, G.

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

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. NanoPhotoBioSciences 2, 14–30 (2014).

H. M. Kalaji, A. Oukarroum, V. Alexandrov, M. Kouzmanova, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, S. I. Allakhverdiev, and V. Goltsev, “Identification of nutrient deficiency in maize and tomato plants by in vivo chlorophyll a fluorescence measurements,” Plant Physiol. Biochem. 81, 16–25 (2014).
[Crossref] [PubMed]

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.

M. Zivcak, M. Brestic, K. Kunderlikova, K. Olsovska, and S. I. Allakhverdiev, “Effect of photosystem I inactivation on chlorophyll a fluorescence induction in wheat leaves: Does activity of photosystem I play any role in OJIP rise?” J. Photochem. Photobiol. B 152(Pt B), 318–324 (2015).
[Crossref] [PubMed]

M. Zivcak, M. Brestic, K. Kunderlikova, O. Sytar, and S. I. Allakhverdiev, “Repetitive light pulse-induced photoinhibition of photosystem I severely affects CO2 assimilation and photoprotection in wheat leaves,” Photosynth. Res. 126(2-3), 449–463 (2015).
[Crossref] [PubMed]

H. M. Kalaji, A. Oukarroum, V. Alexandrov, M. Kouzmanova, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, S. I. Allakhverdiev, and V. Goltsev, “Identification of nutrient deficiency in maize and tomato plants by in vivo chlorophyll a fluorescence measurements,” Plant Physiol. Biochem. 81, 16–25 (2014).
[Crossref] [PubMed]

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]

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).
[Crossref] [PubMed]

Ananyev, G.

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]

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]

Anderson, B.

B. Anderson, P. K. Buah-Bassuah, and J. P. Tetteh, “Using violet laser-induced chlorophyll fluorescence emission spectra for crop yield assessment of cowpea (Vigna unguiculata (L) Walp) varieties,” Meas. Sci. Technol. 15(7), 1255–1265 (2004).
[Crossref]

Apostol, S.

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]

Baba, W.

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. 132(1), 13–66 (2017).
[PubMed]

Berry, J.

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]

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]

Berry, J. A.

R. Pieruschka, D. Klimov, Z. S. Kolber, and J. A. Berry, “Monitoring of cold and light stress impact on photosynthesis by using the laser induced fluorescence transient (LIFT) approach,” Funct. Plant Biol. 37(5), 395–402 (2010).
[Crossref]

Bocchi, S.

D. Stroppiana, M. Boschetti, P. A. Brivio, and S. Bocchi, “Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry,” Field Crops Res. 111(1-2), 119–129 (2009).
[Crossref]

Boschetti, M.

D. Stroppiana, M. Boschetti, P. A. Brivio, and S. Bocchi, “Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry,” Field Crops Res. 111(1-2), 119–129 (2009).
[Crossref]

Brestic, 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. 132(1), 13–66 (2017).
[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), 102 (2016).
[Crossref]

M. Zivcak, M. Brestic, K. Kunderlikova, O. Sytar, and S. I. Allakhverdiev, “Repetitive light pulse-induced photoinhibition of photosystem I severely affects CO2 assimilation and photoprotection in wheat leaves,” Photosynth. Res. 126(2-3), 449–463 (2015).
[Crossref] [PubMed]

M. Zivcak, M. Brestic, K. Kunderlikova, K. Olsovska, and S. I. Allakhverdiev, “Effect of photosystem I inactivation on chlorophyll a fluorescence induction in wheat leaves: Does activity of photosystem I play any role in OJIP rise?” J. Photochem. Photobiol. B 152(Pt B), 318–324 (2015).
[Crossref] [PubMed]

M. Živčák, K. Olšovská, P. Slamka, J. Galambošová, V. Rataj, H. B. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60(5), 210–215 (2014).
[Crossref]

H. M. Kalaji, A. Oukarroum, V. Alexandrov, M. Kouzmanova, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, S. I. Allakhverdiev, and V. Goltsev, “Identification of nutrient deficiency in maize and tomato plants by in vivo chlorophyll a fluorescence measurements,” Plant Physiol. Biochem. 81, 16–25 (2014).
[Crossref] [PubMed]

Brivio, P. A.

D. Stroppiana, M. Boschetti, P. A. Brivio, and S. Bocchi, “Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry,” Field Crops Res. 111(1-2), 119–129 (2009).
[Crossref]

Bro, R.

R. Bro and A. K. Smilde, “Principal component analysis,” Anal. Methods 6(9), 2812–2831 (2014).
[Crossref]

Buah-Bassuah, P. K.

B. Anderson, P. K. Buah-Bassuah, and J. P. Tetteh, “Using violet laser-induced chlorophyll fluorescence emission spectra for crop yield assessment of cowpea (Vigna unguiculata (L) Walp) varieties,” Meas. Sci. Technol. 15(7), 1255–1265 (2004).
[Crossref]

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. 132(1), 13–66 (2017).
[PubMed]

Calatayud, A.

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. 132(1), 13–66 (2017).
[PubMed]

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).
[Crossref]

Cao, W. X.

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]

Cartaxana, P.

C. Gameiro, A. Utkin, P. Cartaxana, J. M. da Silva, and A R.. Matos, “The use of laser induced chlorophyll fluorescence (LIF) as a fast and non‑destructive method to investigate water deficit in Arabidopsi,” Agr. Water Manage. 164, 127–136 (2016).
[Crossref]

Cecchi, G.

G. Cecchi, P. Mazzinghi, L. Pantani, R. Valentini, D. Tirelli, and P. De Angelis, “Remote sensing of chlorophyll a fluorescence of vegetation canopies: 1. Near and far field measurement techniques,” Remote Sens. Environ. 47(1), 18–28 (1994).
[Crossref]

Cendrero-Mateo, M. P.

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]

Cerovic, Z. G.

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]

Cetner, M. D.

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. 132(1), 13–66 (2017).
[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), 102 (2016).
[Crossref]

H. M. Kalaji, A. Oukarroum, V. Alexandrov, M. Kouzmanova, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, S. I. Allakhverdiev, and V. Goltsev, “Identification of nutrient deficiency in maize and tomato plants by in vivo chlorophyll a fluorescence measurements,” Plant Physiol. Biochem. 81, 16–25 (2014).
[Crossref] [PubMed]

Chappelle, E.

J. McMurtrey, E. Chappelle, M. Kim, J. Meisinger, and L. Corp, “Distinguishing nitrogen fertilization levels in field corn (Zea mays L.) with actively induced fluorescence and passive reflectance measurements,” Remote Sens. Environ. 47(1), 36–44 (1994).
[Crossref]

Chappelle, E. W.

Chen, B.

J. Yang, L. Du, W. Gong, S. Shi, J. Sun, and B. Chen, “Potential of vegetation indices combined with laser-induced fluorescence parameters for monitoring leaf nitrogen content in paddy rice,” PLoS One 13(1), e0191068 (2018).
[Crossref] [PubMed]

J. Yang, J. Sun, L. Du, B. Chen, Z. Zhang, S. Shi, and W. Gong, “Effect of fluorescence characteristics and different algorithms on the estimation of leaf nitrogen content based on laser-induced fluorescence lidar in paddy rice,” Opt. Express 25(4), 3743–3755 (2017).
[Crossref] [PubMed]

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, S. Song, B. Chen, and Z. Zhang, “Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice,” Sci. Rep. 6, 28787 (2016).
[Crossref] [PubMed]

Chen, X.

F. Li, B. Mistele, Y. Hu, X. Chen, and U. Schmidhalter, “Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression,” Eur. J. Agron. 52, 198–209 (2014).
[Crossref]

Chernev, P.

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]

Corp, L.

J. McMurtrey, E. Chappelle, M. Kim, J. Meisinger, and L. Corp, “Distinguishing nitrogen fertilization levels in field corn (Zea mays L.) with actively induced fluorescence and passive reflectance measurements,” Remote Sens. Environ. 47(1), 36–44 (1994).
[Crossref]

da Silva, J. M.

C. Gameiro, A. Utkin, P. Cartaxana, J. M. da Silva, and A R.. Matos, “The use of laser induced chlorophyll fluorescence (LIF) as a fast and non‑destructive method to investigate water deficit in Arabidopsi,” Agr. Water Manage. 164, 127–136 (2016).
[Crossref]

Dahn, H.-G.

K. Günther, H.-G. Dahn, and W. Lüdeker, “Remote sensing vegetation status by laser-induced fluorescence,” Remote Sens. Environ. 47(1), 10–17 (1994).
[Crossref]

De Angelis, P.

G. Cecchi, P. Mazzinghi, L. Pantani, R. Valentini, D. Tirelli, and P. De Angelis, “Remote sensing of chlorophyll a fluorescence of vegetation canopies: 1. Near and far field measurement techniques,” Remote Sens. Environ. 47(1), 18–28 (1994).
[Crossref]

Diacono, M.

M. Diacono, P. Rubino, and F. Montemurro, “Precision nitrogen management of wheat. A review,” Agron. Sustain. Dev. 33(1), 219–241 (2013).
[Crossref]

Du, L.

J. Yang, L. Du, W. Gong, S. Shi, J. Sun, and B. Chen, “Potential of vegetation indices combined with laser-induced fluorescence parameters for monitoring leaf nitrogen content in paddy rice,” PLoS One 13(1), e0191068 (2018).
[Crossref] [PubMed]

J. Yang, J. Sun, L. Du, B. Chen, Z. Zhang, S. Shi, and W. Gong, “Effect of fluorescence characteristics and different algorithms on the estimation of leaf nitrogen content based on laser-induced fluorescence lidar in paddy rice,” Opt. Express 25(4), 3743–3755 (2017).
[Crossref] [PubMed]

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, S. Song, B. Chen, and Z. Zhang, “Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice,” Sci. Rep. 6, 28787 (2016).
[Crossref] [PubMed]

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]

Epiphanio, J. C. N.

L. S. Galvão, M. A. Pizarro, and J. C. N. Epiphanio, “Variations in reflectance of tropical soils: spectral-chemical composition relationships from AVIRIS data,” Remote Sens. Environ. 75(2), 245–255 (2001).
[Crossref]

Feng, H.

X. Gu, P. Xu, H. Qiu, and H. Feng, “Monitoring the chlorophyll fluorescence parameters in rice under flooding and waterlogging stress based on remote sensing,” in World Automation Congress, 848–854 (2014).

Feng, W.

L. He, X. Song, W. Feng, B.-B. Guo, Y.-S. Zhang, Y.-H. Wang, C.-Y. Wang, and T.-C. Guo, “Improved remote sensing of leaf nitrogen concentration in winter wheat using multi-angular hyperspectral data,” Remote Sens. Environ. 174, 122–133 (2016).
[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]

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. 132(1), 13–66 (2017).
[PubMed]

Francis, D. D.

S. L. Osborne, J. S. Schepers, D. D. Francis, and M. R. Schlemmer, “Detection of Phosphorus and Nitrogen Deficiencies in Corn Using Spectral Radiance Measurements,” Agron. J. 94(6), 1215–1221 (2002).
[Crossref]

Galambošová, J.

M. Živčák, K. Olšovská, P. Slamka, J. Galambošová, V. Rataj, H. B. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60(5), 210–215 (2014).
[Crossref]

Galvão, L. S.

L. S. Galvão, M. A. Pizarro, and J. C. N. Epiphanio, “Variations in reflectance of tropical soils: spectral-chemical composition relationships from AVIRIS data,” Remote Sens. Environ. 75(2), 245–255 (2001).
[Crossref]

Gameiro, C.

C. Gameiro, A. Utkin, P. Cartaxana, J. M. da Silva, and A R.. Matos, “The use of laser induced chlorophyll fluorescence (LIF) as a fast and non‑destructive method to investigate water deficit in Arabidopsi,” Agr. Water Manage. 164, 127–136 (2016).
[Crossref]

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. 132(1), 13–66 (2017).
[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), 102 (2016).
[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. NanoPhotoBioSciences 2, 14–30 (2014).

H. M. Kalaji, A. Oukarroum, V. Alexandrov, M. Kouzmanova, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, S. I. Allakhverdiev, and V. Goltsev, “Identification of nutrient deficiency in maize and tomato plants by in vivo chlorophyll a fluorescence measurements,” Plant Physiol. Biochem. 81, 16–25 (2014).
[Crossref] [PubMed]

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]

Gong, W.

J. Yang, L. Du, W. Gong, S. Shi, J. Sun, and B. Chen, “Potential of vegetation indices combined with laser-induced fluorescence parameters for monitoring leaf nitrogen content in paddy rice,” PLoS One 13(1), e0191068 (2018).
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Meisinger, J.

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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).
[Crossref] [PubMed]

Wang, J.

J. Wang, T. Wang, A. K. Skidmore, T. Shi, and G. Wu, “Evaluating Different Methods for Grass Nutrient Estimation from Canopy Hyperspectral Reflectance,” Remote Sens. 7(5), 5901–5917 (2015).
[Crossref]

Wang, T.

J. Wang, T. Wang, A. K. Skidmore, T. Shi, and G. Wu, “Evaluating Different Methods for Grass Nutrient Estimation from Canopy Hyperspectral Reflectance,” Remote Sens. 7(5), 5901–5917 (2015).
[Crossref]

Wang, X.-Z.

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]

Wang, Y.-H.

L. He, X. Song, W. Feng, B.-B. Guo, Y.-S. Zhang, Y.-H. Wang, C.-Y. Wang, and T.-C. Guo, “Improved remote sensing of leaf nitrogen concentration in winter wheat using multi-angular hyperspectral data,” Remote Sens. Environ. 174, 122–133 (2016).
[Crossref]

Wang, Z.

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]

Wenzel, O.

N. Subhash, O. Wenzel, and H. K. Lichtenthaler, “Changes in blue-green and chlorophyll fluorescence emission and fluorescence ratios during senescence of tobacco plants,” Remote Sens. Environ. 69(3), 215–223 (1999).
[Crossref]

Wood, F. M.

Wu, G.

J. Wang, T. Wang, A. K. Skidmore, T. Shi, and G. Wu, “Evaluating Different Methods for Grass Nutrient Estimation from Canopy Hyperspectral Reflectance,” Remote Sens. 7(5), 5901–5917 (2015).
[Crossref]

Xu, P.

X. Gu, P. Xu, H. Qiu, and H. Feng, “Monitoring the chlorophyll fluorescence parameters in rice under flooding and waterlogging stress based on remote sensing,” in World Automation Congress, 848–854 (2014).

Yan, X.-H.

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]

Yang, J.

J. Yang, L. Du, W. Gong, S. Shi, J. Sun, and B. Chen, “Potential of vegetation indices combined with laser-induced fluorescence parameters for monitoring leaf nitrogen content in paddy rice,” PLoS One 13(1), e0191068 (2018).
[Crossref] [PubMed]

J. Yang, J. Sun, L. Du, B. Chen, Z. Zhang, S. Shi, and W. Gong, “Effect of fluorescence characteristics and different algorithms on the estimation of leaf nitrogen content based on laser-induced fluorescence lidar in paddy rice,” Opt. Express 25(4), 3743–3755 (2017).
[Crossref] [PubMed]

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, S. Song, B. Chen, and Z. Zhang, “Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice,” Sci. Rep. 6, 28787 (2016).
[Crossref] [PubMed]

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]

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]

Yang, Y. J.

W. Huang, Y. J. Yang, S. B. Zhang, and T. Liu, “Cyclic Electron Flow around Photosystem I Promotes ATP Synthesis Possibly Helping the Rapid Repair of Photodamaged Photosystem II at Low Light,” Front. Plant Sci. 9, 239 (2018).
[Crossref] [PubMed]

Yanniccari, 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. 132(1), 13–66 (2017).
[PubMed]

Yao, X.

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]

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).
[Crossref] [PubMed]

Yoder, B. J.

B. J. Yoder and R. E. Pettigrew-Crosby, “Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400–2500 nm) at leaf and canopy scales,” Remote Sens. Environ. 53(3), 199–211 (1995).
[Crossref]

Yordanov, 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]

Yungel, J. K.

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).
[Crossref] [PubMed]

Zarco-Tejada, P. J.

P. J. Zarco-Tejada, C. A. Rueda, and S. L. Ustin, “Water content estimation in vegetation with MODIS reflectance data and model inversion methods,” Remote Sens. Environ. 85(1), 109–124 (2003).
[Crossref]

Zhang, S. B.

W. Huang, Y. J. Yang, S. B. Zhang, and T. Liu, “Cyclic Electron Flow around Photosystem I Promotes ATP Synthesis Possibly Helping the Rapid Repair of Photodamaged Photosystem II at Low Light,” Front. Plant Sci. 9, 239 (2018).
[Crossref] [PubMed]

Zhang, Y.-S.

L. He, X. Song, W. Feng, B.-B. Guo, Y.-S. Zhang, Y.-H. Wang, C.-Y. Wang, and T.-C. Guo, “Improved remote sensing of leaf nitrogen concentration in winter wheat using multi-angular hyperspectral data,” Remote Sens. Environ. 174, 122–133 (2016).
[Crossref]

Zhang, Z.

J. Yang, J. Sun, L. Du, B. Chen, Z. Zhang, S. Shi, and W. Gong, “Effect of fluorescence characteristics and different algorithms on the estimation of leaf nitrogen content based on laser-induced fluorescence lidar in paddy rice,” Opt. Express 25(4), 3743–3755 (2017).
[Crossref] [PubMed]

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, S. Song, B. Chen, and Z. Zhang, “Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice,” Sci. Rep. 6, 28787 (2016).
[Crossref] [PubMed]

Zhou, X.

X. Zhou, C. Sun, P. Zhu, and F. Liu, “Effects of Antimony Stress on Photosynthesis and Growth of Acorus calamus,” Front. Plant Sci. 9, 579 (2018).
[Crossref] [PubMed]

Zhu, B.

S. Song, W. Gong, B. Zhu, and X. Huang, “Wavelength selection and spectral discrimination for paddy rice, with laboratory measurements of hyperspectral leaf reflectance,” ISPRS J. Photogramm. 66(5), 672–682 (2011).
[Crossref]

Zhu, P.

X. Zhou, C. Sun, P. Zhu, and F. Liu, “Effects of Antimony Stress on Photosynthesis and Growth of Acorus calamus,” Front. Plant Sci. 9, 579 (2018).
[Crossref] [PubMed]

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.

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. 132(1), 13–66 (2017).
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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), 102 (2016).
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M. Zivcak, M. Brestic, K. Kunderlikova, O. Sytar, and S. I. Allakhverdiev, “Repetitive light pulse-induced photoinhibition of photosystem I severely affects CO2 assimilation and photoprotection in wheat leaves,” Photosynth. Res. 126(2-3), 449–463 (2015).
[Crossref] [PubMed]

M. Zivcak, M. Brestic, K. Kunderlikova, K. Olsovska, and S. I. Allakhverdiev, “Effect of photosystem I inactivation on chlorophyll a fluorescence induction in wheat leaves: Does activity of photosystem I play any role in OJIP rise?” J. Photochem. Photobiol. B 152(Pt B), 318–324 (2015).
[Crossref] [PubMed]

H. M. Kalaji, A. Oukarroum, V. Alexandrov, M. Kouzmanova, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, S. I. Allakhverdiev, and V. Goltsev, “Identification of nutrient deficiency in maize and tomato plants by in vivo chlorophyll a fluorescence measurements,” Plant Physiol. Biochem. 81, 16–25 (2014).
[Crossref] [PubMed]

Živcák, M.

M. Živčák, K. Olšovská, P. Slamka, J. Galambošová, V. Rataj, H. B. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60(5), 210–215 (2014).
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Acta Physiol. Plant. (1)

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), 102 (2016).
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Agr. Water Manage. (1)

C. Gameiro, A. Utkin, P. Cartaxana, J. M. da Silva, and A R.. Matos, “The use of laser induced chlorophyll fluorescence (LIF) as a fast and non‑destructive method to investigate water deficit in Arabidopsi,” Agr. Water Manage. 164, 127–136 (2016).
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Agriculture (1)

A. Raesch, O. Muller, R. Pieruschka, and U. Rascher, “Field Observations with Laser-Induced Fluorescence Transient (LIFT) Method in Barley and Sugar Beet,” Agriculture 4(2), 159–169 (2014).
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Agron. J. (1)

S. L. Osborne, J. S. Schepers, D. D. Francis, and M. R. Schlemmer, “Detection of Phosphorus and Nitrogen Deficiencies in Corn Using Spectral Radiance Measurements,” Agron. J. 94(6), 1215–1221 (2002).
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M. Diacono, P. Rubino, and F. Montemurro, “Precision nitrogen management of wheat. A review,” Agron. Sustain. Dev. 33(1), 219–241 (2013).
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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).
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R. Bro and A. K. Smilde, “Principal component analysis,” Anal. Methods 6(9), 2812–2831 (2014).
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Biochim. Biophys. Acta (1)

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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Can. J. Rem. Sens. (1)

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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Environ. Sci. Technol. (1)

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]

Eur. J. Agron. (2)

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]

F. Li, B. Mistele, Y. Hu, X. Chen, and U. Schmidhalter, “Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression,” Eur. J. Agron. 52, 198–209 (2014).
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Field Crops Res. (2)

D. Stroppiana, M. Boschetti, P. A. Brivio, and S. Bocchi, “Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry,” Field Crops Res. 111(1-2), 119–129 (2009).
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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).
[Crossref]

Front. Plant Sci. (2)

W. Huang, Y. J. Yang, S. B. Zhang, and T. Liu, “Cyclic Electron Flow around Photosystem I Promotes ATP Synthesis Possibly Helping the Rapid Repair of Photodamaged Photosystem II at Low Light,” Front. Plant Sci. 9, 239 (2018).
[Crossref] [PubMed]

X. Zhou, C. Sun, P. Zhu, and F. Liu, “Effects of Antimony Stress on Photosynthesis and Growth of Acorus calamus,” Front. Plant Sci. 9, 579 (2018).
[Crossref] [PubMed]

Funct. Plant Biol. (1)

R. Pieruschka, D. Klimov, Z. S. Kolber, and J. A. Berry, “Monitoring of cold and light stress impact on photosynthesis by using the laser induced fluorescence transient (LIFT) approach,” Funct. Plant Biol. 37(5), 395–402 (2010).
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ISPRS J. Photogramm. (1)

S. Song, W. Gong, B. Zhu, and X. Huang, “Wavelength selection and spectral discrimination for paddy rice, with laboratory measurements of hyperspectral leaf reflectance,” ISPRS J. Photogramm. 66(5), 672–682 (2011).
[Crossref]

J. Exp. Bot. (1)

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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J. NanoPhotoBioSciences (1)

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. NanoPhotoBioSciences 2, 14–30 (2014).

J. Photochem. Photobiol. B (1)

M. Zivcak, M. Brestic, K. Kunderlikova, K. Olsovska, and S. I. Allakhverdiev, “Effect of photosystem I inactivation on chlorophyll a fluorescence induction in wheat leaves: Does activity of photosystem I play any role in OJIP rise?” J. Photochem. Photobiol. B 152(Pt B), 318–324 (2015).
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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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B. Anderson, P. K. Buah-Bassuah, and J. P. Tetteh, “Using violet laser-induced chlorophyll fluorescence emission spectra for crop yield assessment of cowpea (Vigna unguiculata (L) Walp) varieties,” Meas. Sci. Technol. 15(7), 1255–1265 (2004).
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Opt. Express (1)

Photochem. Photobiol. Sci. (1)

M. E. Ramos and M. G. Lagorio, “True fluorescence spectra of leaves,” Photochem. Photobiol. Sci. 3(11-12), 1063–1066 (2004).
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Photosynth. Res. (4)

M. Zivcak, M. Brestic, K. Kunderlikova, O. Sytar, and S. I. Allakhverdiev, “Repetitive light pulse-induced photoinhibition of photosystem I severely affects CO2 assimilation and photoprotection in wheat leaves,” Photosynth. Res. 126(2-3), 449–463 (2015).
[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]

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. 132(1), 13–66 (2017).
[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).
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Plant Physiol. Biochem. (1)

H. M. Kalaji, A. Oukarroum, V. Alexandrov, M. Kouzmanova, M. Brestic, M. Zivcak, I. A. Samborska, M. D. Cetner, S. I. Allakhverdiev, and V. Goltsev, “Identification of nutrient deficiency in maize and tomato plants by in vivo chlorophyll a fluorescence measurements,” Plant Physiol. Biochem. 81, 16–25 (2014).
[Crossref] [PubMed]

Plant Soil Environ. (2)

M. Živčák, K. Olšovská, P. Slamka, J. Galambošová, V. Rataj, H. B. Shao, and M. Brestič, “Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency,” Plant Soil Environ. 60(5), 210–215 (2014).
[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]

PLoS One (1)

J. Yang, L. Du, W. Gong, S. Shi, J. Sun, and B. Chen, “Potential of vegetation indices combined with laser-induced fluorescence parameters for monitoring leaf nitrogen content in paddy rice,” PLoS One 13(1), e0191068 (2018).
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G. Agati, “Response of the in vivo chlorophyll fluorescence spectrum to environmental factors and laser excitation wavelength,” Pure Appl. Opt. 7(4), 797–807 (1998).
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Remote Sens. (1)

J. Wang, T. Wang, A. K. Skidmore, T. Shi, and G. Wu, “Evaluating Different Methods for Grass Nutrient Estimation from Canopy Hyperspectral Reflectance,” Remote Sens. 7(5), 5901–5917 (2015).
[Crossref]

Remote Sens. Environ. (10)

N. Subhash, O. Wenzel, and H. K. Lichtenthaler, “Changes in blue-green and chlorophyll fluorescence emission and fluorescence ratios during senescence of tobacco plants,” Remote Sens. Environ. 69(3), 215–223 (1999).
[Crossref]

B. J. Yoder and R. E. Pettigrew-Crosby, “Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400–2500 nm) at leaf and canopy scales,” Remote Sens. Environ. 53(3), 199–211 (1995).
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L. S. Galvão, M. A. Pizarro, and J. C. N. Epiphanio, “Variations in reflectance of tropical soils: spectral-chemical composition relationships from AVIRIS data,” Remote Sens. Environ. 75(2), 245–255 (2001).
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N. Subhash and C. N. Mohanan, “Laser-induced red chlorophyll fluorescence signatures as nutrient stress indicator in rice plants,” Remote Sens. Environ. 47(1), 45–50 (1994).
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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).
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J. McMurtrey, E. Chappelle, M. Kim, J. Meisinger, and L. Corp, “Distinguishing nitrogen fertilization levels in field corn (Zea mays L.) with actively induced fluorescence and passive reflectance measurements,” Remote Sens. Environ. 47(1), 36–44 (1994).
[Crossref]

L. He, X. Song, W. Feng, B.-B. Guo, Y.-S. Zhang, Y.-H. Wang, C.-Y. Wang, and T.-C. Guo, “Improved remote sensing of leaf nitrogen concentration in winter wheat using multi-angular hyperspectral data,” Remote Sens. Environ. 174, 122–133 (2016).
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G. Cecchi, P. Mazzinghi, L. Pantani, R. Valentini, D. Tirelli, and P. De Angelis, “Remote sensing of chlorophyll a fluorescence of vegetation canopies: 1. Near and far field measurement techniques,” Remote Sens. Environ. 47(1), 18–28 (1994).
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P. J. Zarco-Tejada, C. A. Rueda, and S. L. Ustin, “Water content estimation in vegetation with MODIS reflectance data and model inversion methods,” Remote Sens. Environ. 85(1), 109–124 (2003).
[Crossref]

Sci. Rep. (1)

J. Yang, W. Gong, S. Shi, L. Du, J. Sun, S. Song, B. Chen, and Z. Zhang, “Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice,” Sci. Rep. 6, 28787 (2016).
[Crossref] [PubMed]

Other (1)

X. Gu, P. Xu, H. Qiu, and H. Feng, “Monitoring the chlorophyll fluorescence parameters in rice under flooding and waterlogging stress based on remote sensing,” in World Automation Congress, 848–854 (2014).

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Figures (5)

Fig. 1
Fig. 1 First-derivative fluorescence spectrum of paddy rice leaf with different excitation light wavelengths (355, 460, and 556 nm).
Fig. 2
Fig. 2 Correlation coefficients between the leaf nitrogen concentration and first-derivative fluorescence spectrum with different excitation light wavelengths. (A): 355 nm, (B): 460 nm, (C): 556 nm.
Fig. 3
Fig. 3 Equipotential graphs of coefficient of determination between leaf nitrogen concentration and the ratio of the first-derivative fluorescence spectrum with different excitation light wavelengths. (A): 355 nm; (B): 460 nm; (C): 556 nm.
Fig. 4
Fig. 4 Relationship between the predicted LNC using BPNN based on FDFS and the measured LNC for different excitation light wavelengths. (A): 355 nm, (B): 460 nm, (C): 556 nm. The red solid line represents the linear regression.
Fig. 5
Fig. 5 Relationship between the predicted LNC using PCA combined with BPNN and the measured LNC for different excitation light wavelengths. (A): 355 nm, (B): 460 nm, (C): 556 nm. The red solid line represents the linear regression.

Equations (4)

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F ( λ i , λ ex )= F( λ i+1 , λ ex )F( λ i1 , λ ex ) λ i+1 λ i1
w i = j=1 k P 2 ( X j , Y i )
RMSE= 1 n i=1 n ( P i M i ) 2
RE= 100 M ¯ RMSE

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