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

Vasilij Goltsev, Ivelina Zaharieva, Petko Chernev, Margarita Kouzmanova, Hazem M. Kalaji, Ivan Yordanov, Vassilena Krasteva, Vladimir Alexandrov, Detelin Stefanov, Suleyman Allakhverdiev, Reto J. Strasser

Research output: Contribution to journalArticle

96 Citations (Scopus)

Abstract

Water deficit is one of the most important environmental factors limiting sustainable crop yields and it requires a reliable tool for fast and precise quantification. In this work we use simultaneously recorded signals of photoinduced prompt fluorescence (PF) and delayed fluorescence (DF) as well as modulated reflection (MR) of light at 820 nm for analysis of the changes in the photosynthetic activity in detached bean leaves during drying. Depending on the severity of the water deficit we identify different changes in the primary photosynthetic processes. When the relative water content (RWC) is decreased to 60% there is a parallel decrease in the ratio between the rate of excitation trapping in the Photosystem (PS) II reaction center and the rate of reoxidation of reduced PSII acceptors. A further decrease of RWC to 20% suppresses the electron transfer from the reduced plastoquinone pool to the PSI reaction center. At RWC below values 15%, the reoxidation of the photoreduced primary quinone acceptor of PSII, QA -, is inhibited and at less than 5%, the primary photochemical reactions in PSI and II are inactivated. Using the collected sets of PF, DF and MR signals, we construct and train an artificial neural network, capable of recognizing the RWC in a series of unknown samples with a correlation between calculated and gravimetrically determined RWC values of about R2 ≈ 0.98. Our results demonstrate that this is a reliable method for determination of RWC in detached leaves and after further development it could be used for quantifying of drought stress of crop plants in situ. This article is part of a Special Issue entitled: Photosynthesis Research for Sustainability: from Natural to Artificial.

Original languageEnglish
Pages (from-to)1490-1498
Number of pages9
JournalBiochimica et Biophysica Acta - Bioenergetics
Volume1817
Issue number8
DOIs
Publication statusPublished - Aug 1 2012
Externally publishedYes

Fingerprint

Drought
Droughts
Electron Transport
Water content
Neural networks
Water
Fluorescence
Crops
Plastoquinone
Photosystem II Protein Complex
Photosynthesis
Photochemical reactions
Sustainable development
Drying
Electrons
Light
Research

Keywords

  • Artificial neural network
  • Delayed fluorescence
  • Drought stress
  • JIP-test
  • Prompt fluorescence
  • Reflection change at 820 nm

ASJC Scopus subject areas

  • Biophysics
  • Biochemistry
  • Cell Biology

Cite this

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. / Goltsev, Vasilij; Zaharieva, Ivelina; Chernev, Petko; Kouzmanova, Margarita; Kalaji, Hazem M.; Yordanov, Ivan; Krasteva, Vassilena; Alexandrov, Vladimir; Stefanov, Detelin; Allakhverdiev, Suleyman; Strasser, Reto J.

In: Biochimica et Biophysica Acta - Bioenergetics, Vol. 1817, No. 8, 01.08.2012, p. 1490-1498.

Research output: Contribution to journalArticle

Goltsev, V, Zaharieva, I, Chernev, P, Kouzmanova, M, Kalaji, HM, Yordanov, I, Krasteva, V, Alexandrov, V, Stefanov, D, Allakhverdiev, S & Strasser, RJ 2012, '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', Biochimica et Biophysica Acta - Bioenergetics, vol. 1817, no. 8, pp. 1490-1498. https://doi.org/10.1016/j.bbabio.2012.04.018
Goltsev, Vasilij ; Zaharieva, Ivelina ; Chernev, Petko ; Kouzmanova, Margarita ; Kalaji, Hazem M. ; Yordanov, Ivan ; Krasteva, Vassilena ; Alexandrov, Vladimir ; Stefanov, Detelin ; Allakhverdiev, Suleyman ; Strasser, Reto J. / 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. In: Biochimica et Biophysica Acta - Bioenergetics. 2012 ; Vol. 1817, No. 8. pp. 1490-1498.
@article{a5c7e043df5c4ffd94244cb84c421e8b,
title = "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",
abstract = "Water deficit is one of the most important environmental factors limiting sustainable crop yields and it requires a reliable tool for fast and precise quantification. In this work we use simultaneously recorded signals of photoinduced prompt fluorescence (PF) and delayed fluorescence (DF) as well as modulated reflection (MR) of light at 820 nm for analysis of the changes in the photosynthetic activity in detached bean leaves during drying. Depending on the severity of the water deficit we identify different changes in the primary photosynthetic processes. When the relative water content (RWC) is decreased to 60{\%} there is a parallel decrease in the ratio between the rate of excitation trapping in the Photosystem (PS) II reaction center and the rate of reoxidation of reduced PSII acceptors. A further decrease of RWC to 20{\%} suppresses the electron transfer from the reduced plastoquinone pool to the PSI reaction center. At RWC below values 15{\%}, the reoxidation of the photoreduced primary quinone acceptor of PSII, QA -, is inhibited and at less than 5{\%}, the primary photochemical reactions in PSI and II are inactivated. Using the collected sets of PF, DF and MR signals, we construct and train an artificial neural network, capable of recognizing the RWC in a series of unknown samples with a correlation between calculated and gravimetrically determined RWC values of about R2 ≈ 0.98. Our results demonstrate that this is a reliable method for determination of RWC in detached leaves and after further development it could be used for quantifying of drought stress of crop plants in situ. This article is part of a Special Issue entitled: Photosynthesis Research for Sustainability: from Natural to Artificial.",
keywords = "Artificial neural network, Delayed fluorescence, Drought stress, JIP-test, Prompt fluorescence, Reflection change at 820 nm",
author = "Vasilij Goltsev and Ivelina Zaharieva and Petko Chernev and Margarita Kouzmanova and Kalaji, {Hazem M.} and Ivan Yordanov and Vassilena Krasteva and Vladimir Alexandrov and Detelin Stefanov and Suleyman Allakhverdiev and Strasser, {Reto J.}",
year = "2012",
month = "8",
day = "1",
doi = "10.1016/j.bbabio.2012.04.018",
language = "English",
volume = "1817",
pages = "1490--1498",
journal = "Biochimica et Biophysica Acta - Bioenergetics",
issn = "0005-2728",
publisher = "Elsevier",
number = "8",

}

TY - JOUR

T1 - Drought-induced modifications of photosynthetic electron transport in intact leaves

T2 - Analysis and use of neural networks as a tool for a rapid non-invasive estimation

AU - Goltsev, Vasilij

AU - Zaharieva, Ivelina

AU - Chernev, Petko

AU - Kouzmanova, Margarita

AU - Kalaji, Hazem M.

AU - Yordanov, Ivan

AU - Krasteva, Vassilena

AU - Alexandrov, Vladimir

AU - Stefanov, Detelin

AU - Allakhverdiev, Suleyman

AU - Strasser, Reto J.

PY - 2012/8/1

Y1 - 2012/8/1

N2 - Water deficit is one of the most important environmental factors limiting sustainable crop yields and it requires a reliable tool for fast and precise quantification. In this work we use simultaneously recorded signals of photoinduced prompt fluorescence (PF) and delayed fluorescence (DF) as well as modulated reflection (MR) of light at 820 nm for analysis of the changes in the photosynthetic activity in detached bean leaves during drying. Depending on the severity of the water deficit we identify different changes in the primary photosynthetic processes. When the relative water content (RWC) is decreased to 60% there is a parallel decrease in the ratio between the rate of excitation trapping in the Photosystem (PS) II reaction center and the rate of reoxidation of reduced PSII acceptors. A further decrease of RWC to 20% suppresses the electron transfer from the reduced plastoquinone pool to the PSI reaction center. At RWC below values 15%, the reoxidation of the photoreduced primary quinone acceptor of PSII, QA -, is inhibited and at less than 5%, the primary photochemical reactions in PSI and II are inactivated. Using the collected sets of PF, DF and MR signals, we construct and train an artificial neural network, capable of recognizing the RWC in a series of unknown samples with a correlation between calculated and gravimetrically determined RWC values of about R2 ≈ 0.98. Our results demonstrate that this is a reliable method for determination of RWC in detached leaves and after further development it could be used for quantifying of drought stress of crop plants in situ. This article is part of a Special Issue entitled: Photosynthesis Research for Sustainability: from Natural to Artificial.

AB - Water deficit is one of the most important environmental factors limiting sustainable crop yields and it requires a reliable tool for fast and precise quantification. In this work we use simultaneously recorded signals of photoinduced prompt fluorescence (PF) and delayed fluorescence (DF) as well as modulated reflection (MR) of light at 820 nm for analysis of the changes in the photosynthetic activity in detached bean leaves during drying. Depending on the severity of the water deficit we identify different changes in the primary photosynthetic processes. When the relative water content (RWC) is decreased to 60% there is a parallel decrease in the ratio between the rate of excitation trapping in the Photosystem (PS) II reaction center and the rate of reoxidation of reduced PSII acceptors. A further decrease of RWC to 20% suppresses the electron transfer from the reduced plastoquinone pool to the PSI reaction center. At RWC below values 15%, the reoxidation of the photoreduced primary quinone acceptor of PSII, QA -, is inhibited and at less than 5%, the primary photochemical reactions in PSI and II are inactivated. Using the collected sets of PF, DF and MR signals, we construct and train an artificial neural network, capable of recognizing the RWC in a series of unknown samples with a correlation between calculated and gravimetrically determined RWC values of about R2 ≈ 0.98. Our results demonstrate that this is a reliable method for determination of RWC in detached leaves and after further development it could be used for quantifying of drought stress of crop plants in situ. This article is part of a Special Issue entitled: Photosynthesis Research for Sustainability: from Natural to Artificial.

KW - Artificial neural network

KW - Delayed fluorescence

KW - Drought stress

KW - JIP-test

KW - Prompt fluorescence

KW - Reflection change at 820 nm

UR - http://www.scopus.com/inward/record.url?scp=84862216527&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84862216527&partnerID=8YFLogxK

U2 - 10.1016/j.bbabio.2012.04.018

DO - 10.1016/j.bbabio.2012.04.018

M3 - Article

C2 - 22609146

AN - SCOPUS:84862216527

VL - 1817

SP - 1490

EP - 1498

JO - Biochimica et Biophysica Acta - Bioenergetics

JF - Biochimica et Biophysica Acta - Bioenergetics

SN - 0005-2728

IS - 8

ER -