Responses of photosynthetic apparatus in sunflower cultivars to combined drought and salt stress

Abstract

Response of photosynthetic apparatus in some sunflower cultivars, i.e., S.28111, Hysun-33, Hysun-39, and SF0049, to salt, drought, and combined stresses were studied. The combined stress caused severe damage to photosynthetic apparatus as compared to single stress. The maximum quantum yield of PSII, phenomenological fluxes, plastoquinone pool size, performance indexes, and driving force of absorption were greatly affected by the combined stress. Among the cultivars, the combined stress produced synergistic effect (greater damage) in Hysun-33 and cross-tolerance (lesser damage) in S.28111. Similarly, concerning the ion imbalance, S.28111 and SF0049 showed lower Na + and Clconcentrations with lesser electrolyte leakage as compared to Hysun-33 and Hysun-39 under salt and combined stress. Results revealed that the disturbance in photosynthetic performance could be easily determined using JIP test by measuring chlorophyll a fluorescence. This information can be useful for the screening of oil-seed crop plants having better photosynthetic performance under salinized and desertified conditions.Additional key words: electron transport rate; malondialdehyde; nonphotochemical quenching; OJIP transient. Abbreviations: ABS/RC -apparent antenna size of active PSII RC; Area -area over the fluorescence curve between F0 and Fm; DFABSdriving force on absorption basis; DI0/RC -effective dissipation of energy in active RC; ET0/RC -electron transport per active reaction center; F0 -minimum fluorescence; F0/Fv -efficiency of water-splitting complex; F0/Fm -quantum yield baseline; Fm -maximum fluorescence; Fm/F0 -electron transport rate through PSII; Fv/F0 -size and number of active reaction centers of photosynthetic apparatus; Fv/Fm -maximum quantum yield of PSII; J -linear electron transport rate; MDA -malondialdehyde; NPQ -nonphotochemical quenching; PIABS -performance index on absorption basis; PICS -performance index on cross-section basis; PItot -total performance index; qN -nonphotochemical quenching coefficient; qP -photochemical quenching; RC/ABS -density of reaction centers on chlorophyll basis; RC/CSm -amount of active reaction centers per excited cross section; TR0/DI0 -ratio of trapping and dissipation fluxes; TR0/RC -maximal trapping rate of absorbed photons in RC; δR0 or RE0/ET0 -probability that an electron is transported from reduced PQ to electron acceptor side of PSI; ΔVIP -amplitude of the relative variable fluorescence of the I-to-P-rise; ΦPSII -efficiency of PSII or quantum yield of PSII; ϕR0 -quantum yield for reduction of the end electron acceptors at the PSI acceptor side (RE); ψ0yield of electron transport per trapped excitation or probability with which a PSII trapped electron is transferred from reduced QA to QB.

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“…The positions along PC2 of the respective controls of every hybrid were mostly defined by higher values of biomass traits and higher PItotal. Contrarily, plants in NaCl treatment showed higher δRo representing higher tolerance of PSI to salt stress than PSII (Umar et al 2019).…”

“…Increase of δRo in the NaCl treatment is probably due to decrease in redox balance of PSII electron acceptors due to lower PSII activity. Furthermore, increased values of δRo might be associated with higher resilience of PSI to salt stress compared to PSII (Umar et al 2019).…”

“…The JIP-test was proven to be a very useful tool for the in vivo investigations of the adaptive behavior of the photosynthetic apparatus to a wide variety of stressors, as it translates the shape changes of the O-J-I-P transient curve to quantitative changes of the several parameters (Strasser et al 2004) and provides assessment of the cascade of chloroplast redox reactions at microsecond or millisecond scales (Kalaji et al 2016). Particularly, the JIP-test and ChlF transients have been used so far to assess the effects of salt stress in many species, such as barley (Kalaji et al 2011), wheat (Mehta et al 2010), sunflower (Umar et al 2019), maize (Kan et al 2017), Tilia cordata Mill. (Kalaji et al 2018), sorghum (Sayyad-Amin et al 2016, Zhang et al 2018, and rocket (Hniličková et al 2017).…”

“…The next step towards obtaining more accurate predictions would be the integration of the new phenotypes that are easy to measure, highly heritable, and correlated with traits of interest into the models. Subsequently, these relevant variables have to be integrated into the genotypeto-phenotype (G2P) models to improve the model prediction accuracy (van Eeuwijk et al 2018). Technow et al (2015) developed a crop growth model (CGM), which integrates the physiological variables into the genome-wide prediction models.…”

Special issue in honour of Prof. Reto J. Strasser - Analysis of drought response of sunflower inbred lines by chlorophyll a fluorescence induction kinetics

“…The damage to PSII was caused by the formation of reactive oxygen species, which can lead to membrane damage and deterioration of membrane integrity (Nishiyama et al 2006). Chl a fluorescence (ChlF) measurements have been widely used to detect response of photosynthetic apparatus under stress conditions in wide range of species due to its simple, reliable, nondestructive, and rapid testing technique (Boureima et al 2012(Boureima et al , Çiçek et al 2015(Boureima et al , 2018Kaya et al 2016, Umar et al 2019. ChlF measurements allow determining the physiological status of plants based on the detection of changes in PSII components, electron transport chain, and light-dependent photochemical reactions (Lotfi et al 2018).…”