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Peer-reviewed

Research Article

The effect of light quality on plant physiology, photosynthetic, and stress response in Arabidopsis thaliana leaves

Roles Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing – original draft

* E-mail: [email protected] (ML); [email protected] (NY)

Affiliation Department of Bioresource Engineering, McGill University–Macdonald Campus, Sainte-Anne-de-Bellevue, Quebec, Canada

Roles Methodology

Affiliation Department of Plant Science, McGill University–Macdonald Campus, Sainte-Anne-de-Bellevue, Quebec, Canada

Roles Writing – review & editing

Roles Resources

Roles Conceptualization, Funding acquisition, Investigation, Project administration, Resources, Supervision, Writing – original draft

Nafiseh Yavari,
Rajiv Tripathi,
Bo-Sen Wu,
Sarah MacPherson,
Jaswinder Singh,
Mark Lefsrud

Published: March 4, 2021
https://doi.org/10.1371/journal.pone.0247380
Reader Comments

The impacts of wavelengths in 500–600 nm on plant response and their underlying mechanisms remain elusive and required further investigation. Here, we investigated the effect of light quality on leaf area growth, biomass, pigments content, and net photosynthetic rate (Pn) across three Arabidopsis thaliana accessions, along with changes in transcription, photosynthates content, and antioxidative enzyme activity. Eleven-leaves plants were treated with BL; 450 nm, AL; 595 nm, RL; 650 nm, and FL; 400–700 nm as control. RL significantly increased leaf area growth, biomass, and promoted Pn. BL increased leaf area growth, carotenoid and anthocyanin content. AL significantly reduced leaf area growth and biomass, while Pn remained unaffected. Petiole elongation was further observed across accessions under AL. To explore the underlying mechanisms under AL, expression of key marker genes involved in light-responsive photosynthetic reaction, enzymatic activity of antioxidants, and content of photosynthates were monitored in Col-0 under AL, RL (as contrast), and FL (as control). AL induced transcription of GSH2 and PSBA , while downregulated NPQ1 and FNR2 . Photosynthates, including proteins and starches, showed lower content under AL. SOD and APX showed enhanced enzymatic activity under AL. These results provide insight into physiological and photosynthetic responses to light quality, in addition to identifying putative protective-mechanisms that may be induced to cope with lighting-stress in order to enhance plant stress tolerance.

Citation: Yavari N, Tripathi R, Wu B-S, MacPherson S, Singh J, Lefsrud M (2021) The effect of light quality on plant physiology, photosynthetic, and stress response in Arabidopsis thaliana leaves. PLoS ONE 16(3): e0247380. https://doi.org/10.1371/journal.pone.0247380

Editor: Keqiang Wu, National Taiwan University, TAIWAN

Received: August 31, 2020; Accepted: December 13, 2020; Published: March 4, 2021

Copyright: © 2021 Yavari et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: This work was supported by the “Natural Sciences and Engineering Research Council of Canada (NSERC)”. The specific grant number is RGPIN 355743-13, CRDPJ418919-11. It is “all” the funding and/or financial sources of support (whether external and/or internal to our organization) that were received during this study. And there was no additional external and/or internal funding received for this study. ML is the author, who received this award. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Introduction

Among various environmental factors, light is one of the most important variables affecting photosynthesis as well as plant growth and development [ 1 ]. Plants require light not only as an energy source but also as a clue to adjust their development to environmental conditions. During photosynthesis, absorbed energy is transferred to the photosynthetic apparatus, which is comprised of Photosystem I (PSI), Photosystem II (PSII), electron transport ‬carriers (cytochrome b6f (cytb6f), plastoquinone (PQ), plastocyanin (PC)), and ATP synthase. The light-responsive photosynthetic process is driven by the released electrons through the water-splitting reaction on the PSII side, followed by NADP + reduction to NADPH, and proton flow into the lumen in order to generate ATP. Generated NADPH and ATP serve as an energy source for the carbon fixation process [ 2 ].‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

‬‬‬‬‬‬‬‬‬‬‬‬ Both quality and quantity of incident light can have drastic impacts on photosynthetic activity and photosystem adaption to changing light quality [ 3 , 4 ]. Earlier studies on photosynthetic activity reported that photosynthesis is a wavelength-dependent response, in which amber light (AL; 595 nm) induces higher photosynthetic rates than blue light (BL; 450 nm) or red light (RL; 650 nm) [ 3 , 5 , 6 ]. These studies have become the foundation for our plant lighting research as light emitting diodes (LEDs) are proven to be ‬an ‬optimal and effective ‬tool to study the effect of ‬‬‬‬wavelength on plant physiological and biochemical responses [ 7 – 10 ]. Prior research has demonstrated that the wavelength range from 430–500 nm is effective at simulating pigmentation, metabolism of secondary metabolites, photosynthetic function, and development of chloroplasts [ 11 – 14 ]. The wavelength range of 640–670 nm was found effective in promoting photosynthetic activity, plant biomass and leaf area growth [ 3 , 15 ] while playing critically important roles in the development of photosynthetic apparatus, net photosynthetic rate (Pn) and primary metabolism [ 12 , 16 ]. Growing research on the wavelength range 500–600 nm have highlighted its important physiological and morphological impact on growth, chlorophyll content, and photosynthetic function [ 8 , 17 – 19 ]. However, conflicting results on the impact of AL were reported [ 3 , 20 ]. Although AL results in high photosynthetic activity, poor plant growth responses such as elongation and growth suppression have been reported [ 20 , 21 ], and this underlying mechanism remains unknown. In addition to this, AL is weakly absorbed by the photosynthetic pigments [ 22 ]. At the current state, further investigation of AL impact is required to better understand the photoactivity of the photosystems.‬ ‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

Recent studies reported that light quality and quantity can have drastic impacts on imbalanced excitation of either PSII or PSI, resulting in energy imbalance between photosystems and triggering stoichiometric adjustments of photosynthetic complexes [ 23 , 24 ]. This imbalance between the two photosystems can result in generation of harmful reactive intermediates, mainly reactive oxygen species (ROS) [ 25 , 26 ]. Generation of ROS can result in oxidative damage to the chloroplasts, leading to photosystem photo-inhibition that strongly limits plant growth [ 27 ].‬‬‬‬ To maintain steady state photosynthetic efficiency and prevent ROS accumulation, plants activate the buffering mechanisms, including cyclic photosynthetic electron flow (CEF) and non-photochemical quenching (NPQ) [ 28 , 29 ]. To scavenge ROS, plants further stimulate antioxidative mechanisms via enhanced activity of associated enzymes such as glutathione synthetase (GSH), ascorbate peroxidase (APX), and superoxide dismutase (SOD) [ 30 ]. These studies and their findings allow us to understand the impact of light within photosystems; however, the wavelength that can induce such stress responses and their physiological consequence on plants remain poorly studied.

Therefore, to better understand the effect of light quality on plant growth and photosynthetic performance, we studied three narrow-wavelength LEDs of blue light (BL; 450 nm), amber light (AL; 595 nm), and red light (RL; 650 nm), and compared them with fluorescent light (FL; 400–700) as the control. We chose light quality of BL and RL as leaf pigments have absorption peaks at these wavelengths [ 31 ]. AL was chosen due to the conflicting results between high photosynthetic activity and poor plant growth responses [ 3 , 5 ]. Furthermore, to assess whether light quality-induced changes in plant growth and photosynthesis are mediated by the genotype, we investigated the light quality response in three A . thaliana accessions Col-0, Est-1, and C24. These accessions show different geographical distributions and hence are adopted to different environments [ 32 – 34 ]. Congruently, they show a high degree of divergence in their photosynthetic response to the light environment [ 35 , 36 ]‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬. Two experiments were designed to‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬ ‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬assess the impact of light quality on the plant. First, we investigated the physiological and photosynthetic response of A . thaliana to BL, AL, and RL lights compared it to FL by measuring leaf area growth, biomass content, Pn, and pigments content. Second, we tested whether changes in plant response to light quality is genotype specific by conducting the experiments across three A . thaliana accessions. Third, we investigated the potential induction of stress responses under AL by testing whether there are light quality-specific changes in the expression of marker genes involved in light-responsive photosynthetic process and enzymatic activity of antioxidants, as well as photosynthates content. Our findings expand the current understanding on physiological and photosynthetic responses of plants to light quality, in addition to identifying putative protective-mechanisms that may be induced to cope with lighting-stress in order to enhance plant stress tolerance.

Materials and methods

Plant materials and growth condition.

Seeds of A . thaliana accessions Col-0, Est-1, and C24 were obtained from the Arabidopsis Biological Resource Center (ABRC; Columbus, OH, US). Seeds were placed in rockwool cubes (Grodan A/S, DK-2640, Hedehusene, Denmark) and incubated at 4°C for 2 days. White broad-spectrum light (FL; 4200 K, F72T8CW, Osram Sylvania, MA, US) were used as light sources for seed germination. Seedlings were hydroponically grown under FL for 21 days with the environmental condition of 24 h photoperiod, 23°C, 50% relative humidity, and ambient CO 2 in a growth chamber (TC30, Conviron, Winnipeg, MB, Canada). Seed density was adjusted to limit treated plants from shadowing each other. FL was placed over the plant-growing surface area (49 cm × 95 cm) at a low photosynthetic photon flux density (PPFD) of 69 to 71 μmol·m -2 ·sec -1 . PPFD was measured at the conjunction of a grid (square area 3 cm 2 ) placed over the growing area. After 21 days, plants formed rosettes with nine (C24) and eleven (Col-0 and Est-1) leaves. To reach the same growth stage as Col-0 and Est-1 plants, C24 plants were allowed to grow for 23 days [ 37 ]. Fresh half-strength Hoagland nutrient solution [ 38 ] was provided every other day.

Light treatment

After day 21 (Col-0 and Est-1) or 23 (C24), plants were transferred to their respective light treatment for 5 days, each with the same environmental conditions: 24 h photoperiod, 23°C, 50% relative humidity, and ambient CO 2 . 21-day old plants were randomly divided into four experimental groups and received treatments using light emitting diodes (LED) (VanqLED, Shenzhen, China) of BL (peak wavelength: 450 nm), AL (peak wavelength: 595 nm), and RL (peak wavelength: 650 nm). The fourth group was treated with FL (400–700 nm), as the control. The light spectra and PPFD were monitored daily by using a PS-300 spectroradiometer (Apogee, Logan, UT, US). PPFD was maintained at 69 to 71 μmol·m -2 ·sec -1 throughout the whole plant growth period. Fresh half-strength Hoagland nutrient solution [ 38 ] was provided every other day. Biological replicates were grown at different time points under the same environmental settings.

Physical and biochemical analyses

Leaf area growth determination..

Three plants per biological replicate were randomly selected for each measurement. Leaves from the selected plants were collected for the determination after treatment (5 days). Digital images of leaves were taken with a window size of 640 x 480 pixels and a camera-object distance of approximately 80 cm. The digital images were next used to determine leaf area growth using Image J software with default settings (Bethesda, MD, US), as described previously [ 39 ].

Biomass content determination.

Three plants per biological replicate were randomly selected for each determination. Leaf samples from the selected plants were collected for the dry mass determination before (0 h) and after treatment (5 days). Leaves were dried at 80°C for 2 days until a constant mass was achieved (less than < 5% mass difference over a 2 h period).

Pigment content determination.

Five plants per biological replicate were randomly selected for each assay. Leaf samples from the selected plants were collected for the determination after treatment (5 days). Methods and equations described by [ 40 – 42 ] were used to estimate the content of chlorophyll (Chl a and Chl b), carotenoids, and anthocyanin, respectively. Briefly, chlorophylls and carotenoids were extracted with 5 ml of 80% acetone at 4°C overnight, before centrifugation at 13,000 g for 5 min. Total anthocyanins were determined by extracting with 5 ml 80% methanol containing 1% HCl solvent at 4°C overnight, before centrifugation at 13,000 g for 5 min. The absorbance of the extraction solution was determined for Chl a (664 nm), Chl b (647 nm), carotenoids (440 nm), and anthocyanins (530 nm and 657 nm) using a UV–VIS spectrophotometer (UV-180, Shimadzu, Japan).

Net photosynthetic rate determination

Net photosynthetic rate was monitored before (0 h) and after treatment (5 days) using the LI-6400XT Portable Photosynthesis System (LI-COR Biosciences, Lincoln, NE, US) equipped with a 6400–17 Whole Plant Arabidopsis Chamber (LI-COR Biosciences). To reduce potential measurement errors, three plants were grouped as a single sample for determinations [ 43 ]. To avoid mismatch between the light quality used by the LI-6400XT Portable Photosynthetic System, and the LED lights used for the treatments [ 44 ], measurements were taken inside the controlled-chamber, in which whole plants (still embedded in rockwool) were placed and illuminated with LEDs. As a precaution, parafilm was placed on top of the rockwool cube to maintain moisture within the root zone while measurements were recorded. The environmental conditions of the chamber were set as: 400 ppm CO 2 , 50% relative humidity, 23°C, and 400 μl min -1 flow rate. Each measurement was taken over 20 min, including 5 min in the dark and 10–15 min under a light treatment at 69–71 μmol·m -2 ·sec -1 . A stable Pn reading was reached 10 min after illumination. Leaf area growth was determined to normalize Pn per unit leaf area growth. Measurements for three replicates (three plants per replicate, three replicates per treatment) were performed.

Photosynthate content determination

Previous studies have reported that the diurnal cycle and developmental stage of plants, along with the stress response can affect the plant metabolism [ 45 , 46 ]. Thus, we performed a time course assessment of 0, 1, 3, 5, and 7 days to determine the content of leaf photosynthates (proteins, starches, and lipids). Five plants per biological replicate were randomly selected for each measurement. Leaf samples from selected plants were collected for the determination prior (0 h) and after light treatments (1, 3, 5, and 7 days). Samples were immediately frozen in liquid nitrogen and stored at -80 ∘ C, before they were used for determination. Protein : Total protein content was measured using the Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific, Rockford, IL, USA). As a standard, the absorbance of the bovine serum albumin was determined at UV/Vis: λ max 562 nm. Starch : A previously described method [ 47 ] was used to estimate total starch content. Lipids : Previously described methods [ 48 , 49 ] were used (with minor modifications) to estimate the total lipid content. Briefly, each sample was homogenized with (CHCl 3 /MeOH, 70:30 v/v), before centrifuged at 1000 rpm for 5 min. The collected supernatant was incubated for 30 min at 70°C in a boiling water bath. Next, (H 2 SO 4 : 1 ml) was added and heated for 20 min. Following 2 min cooling on ice, (H 3 PO 4 : 1.5 ml) was added and incubated for 10 min until a pink color developed.

Antioxidative enzyme activity estimation

Five plants per biological replicate were randomly selected for each measurement. Leaf samples from selected plants were collected for the determination after treatment (5 days). Samples were immediately frozen in liquid nitrogen and stored at -80 ∘ C, before they were used for determination. Methods described by [ 50 , 51 ] were used to monitor the activity of SOD and APX antioxidative enzymes, respectively. Enzymatic activity was measured for 5 min at room temperature. The protein content in the supernatant was determined by the Pierce™ BCA Protein Assay Kit. The activity of SOD and APX was expressed as unit min −1 mg −1 protein.

Gene expression analysis

Cdna synthesis..

Changes in transcription of the interested genes were analyzed in A . thaliana Col-0 treated for 24 h under AL, RL, and FL. Leaf samples from selected plants were collected for the determination prior to treatment (0 h) and after treatment (2 h, 4 h, and 24 h). Samples were immediately frozen in liquid nitrogen and stored at -80 ∘ C, before they were used for determination. Four biological replicates were examined. For each biological replicate, five A . thaliana plants were selected, and their leaves were pooled together to represent a biological replicate. Plants in each biological replicate were grown independently, and at different times. Total RNA was extracted from (100 mg) leaves using the Sigma Spectrum Plant Total RNA Kit (STRN50; Sigma, Seelze, Germany) according to the manufacturer’s protocol. A total of (2 μg) RNA per sample was treated with amplification grade DNase I (Invitrogen, Carlsbad, CA, USA) to remove any traces of genomic DNA contamination. RNA concentrations were measured before and after DNase I digestion with a NanoDrop ND-1000 UV-Vis spectrophotometer (NanoDrop Technologies, Wilmington, Delware, USA). The cDNA was synthesized using AffinityScript QPCR cDNA Synthesis Kit (Agilent, Tech., Santa Clara, USA).

Primer design.

Primers for genes of interest ( S1 Table ) were designed using IDT software ( https://www.idtdna.com/calc/analyzer ) with the following criteria: Tm of 58–60°C and PCR amplicon lengths of 70 to 120 bp, yielding primer sequences 20 to 25 nucleotides in length with G-C contents of 40% to 50%. Specificity of the resulting primer pair sequences was examined using Arabidopsis transcript database with TAIR BLAST ( http://www.arabidopsis.org/Blast/ ). Specificity of the primer amplicons was further confirmed by melting-curve analysis (30 amplification cycles by PCR and subsequent gel-electrophoretic analysis). Primer amplicons were resolved on (agarose gels, 2% w/v) run at 110 V in Tris-borate/EDTA buffer, along with a 1Kb + DNA-standard ladder (Invitrogen, Carlsbad, CA, USA).

Quantitative real time-PCR (qRT-PCR) analysis.

Real-time qRT-PCR was performed with a MX3000P qPCR System (Agilent, Tech., Santa Clara, CA, USA) using three biological and two technical replicates, as described previously [ 52 ]. Relative expression was conducted following the manufacturer’s recommendations with two reference genes gamma tonoplast intrinsic protein 2 ( TIP2 ; AT3g26520) and actin 2 ( ACT2 ; AT3g18780) and the Brilliant III SYBR Green QPCR master mix (Agilent, Tech., Santa Clara, CA, USA). Amplification was performed in a (20 μL) reaction mixture containing (160 nmol) for each primer, 1x Brilliant III SYBR Green QPCR master mix, (15μM) ROX reference dye, and (0.3 μL) of cDNA template. Amplification conditions were 95°C for 10 min (hot start), followed by 40 cycles at 94°C for 30 s, 60°C for 30 s, and 72°C for 30 s. Fluorescence readings were taken at 72°C, at the end of the elongation cycle.

Data analysis.

Ct values were calculated with CFX-Manager and MX-3000P software. Relative expression changes (delta-delta Ct) were calculated according to [ 53 ] using A . thaliana TIP2 (AT3g26520) and ACT2 (AT3g18780) as reference genes. To avoid multiple testing, the p-values were only considered for 0 h with 24 h (a total of 12 genes and two light conditions). A gene was considered differentially expressed if p < 0.05 and the fold change pattern at 24 h was consistent with those observed at 2 and 4 h.

Statistical analysis

Differences between light treatments were tested using the two-tailed Student’s t-test. A two-way ANOVA was used to assess the effects of accession and different light treatments on leaf area growth, biomass content, Pn value, and pigments content. We observed similar patterns using the non-parametric tests of Wilcoxon-Mann-Whitney and Kruskal-Wallis tests (data not shown). ‬

Effect of light quality and natural genotype variation on leaf area growth, biomass content, net photosynthetic rate, and pigment content in A . thaliana

To assess the effect of light quality, 21-days-old plants (11 leave plants) of three A . thaliana accessions Col-0, Est-1, and C24 were randomly divided into groups and treated under narrow-spectrum light (BL, AL, and RL), along with FL as control (baseline), for 5 days at approximately 70 μmol m -2 sec -1 ( Fig 1A and 1B ). Summary of light quantity compositions emitted from FL and LEDs light sources are shown in Table 1 . After 5 days of narrow-spectrum light treatments, leaf area growth, leaf biomass (dry mass), net photosynthetic rate, and pigment contents were measured across three A . thaliana accessions and compared with the baseline FL treatment ( Fig 1C–1E and Table 2 ).

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(A) Light emission spectra of LED light sources and FL. (B) Eleven-leaves stage A . thaliana accessions Col-0, Est-1, and C24 were grown hydroponically and treated for 5 days under narrow-spectrum BL, AL, and RL lights, as well as FL as control. (C) Leaf area growth. (D) Leaf biomass (dry mass). (E) Net photosynthetic rate (Pn) measured at 69–71 μmol m -2 sec -1 . Data are expressed as mean values ± standard deviation (n = 3). Statistical analysis was performed against FL using a two-tailed Student’s t-test (n.s.: not statistically significant; *: P < 0.05; **: P < 0.01).

https://doi.org/10.1371/journal.pone.0247380.g001

https://doi.org/10.1371/journal.pone.0247380.t001

https://doi.org/10.1371/journal.pone.0247380.t002

Under RL, the leaf area growth was significantly increased across accessions ( P < 0.05; Fig 1C ). Under BL, leaf area growth was significantly increased in C24 and Col-0 ( P < 0.05; Fig 2C ), but the increase in the leaf area growth was not significant in Est-1. Under AL, leaf area growth showed a severe reduction in Col-0 and C24 ( P < 0.05; Fig 1C ), while Al showed no change in Est-1. Petioles were noticeably elongated under AL ( Fig 1B ).

https://doi.org/10.1371/journal.pone.0247380.g002

The leaf biomass significantly increased under RL across the three accessions ( P < 0.05; Fig 1D ). Under BL, the leaf biomass was significantly decreased in Est-1 and C24 but increased in Col-0 ( P < 0.01; Fig 1D ). Under AL, the leaf biomass was significantly lower in Col-0 and C24 ( P < 0.01), while it showed no change in Est-1 ( Fig 1D ).

As for the net photosynthetic rates (Pn), it significantly increased under RL across the accessions ( P < 0.05; Fig 1E ). In contrast, there was no significant difference in Pn under AL ( Fig 1E ). Under BL, Pn significantly increased in Col-0 and Est-1 ( P < 0.05; Fig 1E ) but remained unchanged in C24.

There was no significant difference in contents of chlorophyll a (Chl a) and chlorophyll b (Chl b) in Col-0 and C24 under the light quality of BL, AL, and RL ( Table 2 ). In contrast, Chl a content significantly increased in Est-1 under RL ( P < 0.05; Table 2 ). Across accessions, Chl a: b content significantly increased, remained unchanged, and decreased under RL, BL, and AL, respectively ( Table 2 ). Moreover, there was no significant difference in carotenoid and anthocyanin contents across the accessions under AL and RL. However, BL significantly stimulated carotenoids content in Est-1 and Col-0 ( P < 0.05; Table 2 ). Additionally, anthocyanins content significantly increased under BL in Est-1 and C24 ( P < 0.01; Table 2 ).

The two-way ANOVA analysis indicated significant effects of the light treatments for the determined parameters, except Chl b. Also, the interaction between light treatments and genotype was significant for leaf area growth and leaf biomass ( P < 0.01; Table 3 ).

https://doi.org/10.1371/journal.pone.0247380.t003

Changes in transcription of photosynthetic marker genes, content of photosynthates, and activity of antioxidant in A . thaliana Col-0 under AL and RL

The severe reduction in leaf area growth and biomass, along with unchanged levels of Pn in Col-0 and C24 under AL suggested that amber light has mismatched effects on photosynthetic activity and photomorphology. Further to this, although chlorophyll contents under AL were 10–20% lower than the FL, both light treatments triggered similar photosynthetic activity, which implies that amber light has unidentified mechanisms in the photosynthetic process. To identify the mechanisms that amber light triggers within plants, we next explored transcriptional changes in marker genes associated with the photosynthetic light reaction and photo-protective mechanisms, photosynthates content and antioxidant enzymatic activity in Col-0 under AL ( Fig 2 ). Among three accession, Accession Col-0 was chosen for the transcription analysis, as it is the most common A . thaliana accession in conducting biological analysis. In addition to AL and FL (as control), changes were investigated under RL, as RL-treated plants showed opposing changes in leaf physiological phenotypes compared to AL.

Gene expression analysis indicated a significant increase in transcription level of ATP synthase gamma chain 1 ( ATPC1 ;member of ATP synthase complex) and proton gradient regulation Like 1 ( PGRL1B ;member of CET complex), after 24 h treatment under AL ( P < 0.05; Fig 3B ). ATPC1 transcription significantly increased after 24 h treatment under RL ( P < 0.05; Fig 3B ). No significant difference, after 24 h treatment, was observed in the transcription level of the selected marker genes associated with linear photosynthetic electron transfer (i.e., ferredoxin-2 ( Fd2) , plastocyanin (PETE1) , and cytochrome b6f complex ( PETC ) under both AL and RL ( Fig 3B ). After the 24 h treatment, transcription of ferredoxin-NADP+-oxidoreductase (FNR2) was significantly decreased under AL ( P < 0.05; Fig 3B ), while it remained unchanged under RL ( Fig 3B ). The transcription level of ribulose bisphosphate carboxylase small chain (RBCS1A) was significantly reduced at 2 h and 4 h treatment under both AL and RL ( P < 0.05; Fig 3B ). The RBCS1A transcription level significantly was downregulated under AL ( P < 0.05; Fig 3B ). However, RBCS1A transcription level recovered after the 24 h treatment under RL ( Fig 3B ).

(A) Genes of interest are highlighted in green. (B) Transcription of genes implicated in the light-responsive photosynthetic process that is located within the thylakoid membrane. A time course assessment prior to treatment (0 h), and after treatment (2, 4, and 24 h) of AL and RL was performed, compared to FL. Four biological replicates were examined. For each biological replicate, five A . thaliana plants were selected, and their leaves were pooled together to represent a biological replicate. Plants in each biological replicate were grown independently, and at different time.

https://doi.org/10.1371/journal.pone.0247380.g003

All data were normalized to the housekeeping genes; gamma tonoplast intrinsic protein 2 ( TIP2 ; AT3g26520) and actin 2 ( ACT2 ; AT3g18780). Red borders represent significant changes in expression ( P < 0.05). Studied genes include: ATP synthase gamma chain 1, ATPC1 (AT4g04640); fatty acid desaturase 6, FAD6 (AT4g30950); ferredoxin-2, Fd2 (AT1g60950); ferredoxin-NADP+-oxidoreductase, FNR2 (AT1g20020); (Fdx)-thioredoxin (Trx)-reductase, FTRB (AT2g04700); glutathione synthetase, GSH2 (AT5g27380); PSII nonphotochemical quenching, NPQ1 (AT1g08550); cytochrome b6f complex (Cyt b6f), PETC (AT4g03280); plastocyanin, PETE1 (AT1g76100); proton gradient regulation Like 1, PGRL1B (AT4g11960); photosystem II protein D1, PSBA (ATCG00020) and ribulose bisphosphate carboxylase small chain, RBCS1A (AT1g67090).

To confirm changes in the ATP synthase and CET complex under AL, we leveraged available proteomics data where eleven-leaves plants of A . thaliana Col-0 were grown under AL and RL for 5 days. Consistent with the observed transcriptomic data, a significant increase in the level of protein abundance was observed for both CET complex ( P < 1.3 x 10 −12 ; S1A Fig ) and ATP synthase ( P < 2 x 10 −4 ; S1B Fig ) under AL compared to RL.

Regulation patterns of PSBA , NPQ1 , GSH2 and FAD6 transcripts in A . thaliana Col-0 under AL and RL

The transcription level of photosystem II protein D1 ( PSBA) was significantly upregulated at 4 h and 24 h treatment under RL ( P < 0.05; Fig 3B ). Under AL, the transcription level of PBSA showed a similar increase after the 4 h treatment ( P < 0.05; Fig 3B ); However, its transcription level was reduced to a comparable level with FL after the 24 h treatment under AL. After the 24 h treatment, the transcription level of PSII nonphotochemical quenching (NPQ1) was significantly downregulated under AL ( P < 0.05; Fig 3B ), while it remained steady under RL. Between the 2 h and 4 h treatment, the transcription level of GSH2 gradually increased under both AL and RL ( P < 0.05; Fig 3B ) but reduced to a comparable level with FL after the 24 h treatment under RL. No significant difference was observed in the transcription level of fatty acid desaturase 6 ( FAD6) after the 24 h treatment under either AL or RL ( Fig 3B ).

Photosynthates content in A . thaliana Col-0 under AL and RL

Photosynthates accumulation was probed in Col-0 treated under AL, RL, and FL. Total lipid, protein and starch were measured at days 0, 1, 3, 5, and 7 ( Fig 4 ). The lipid content gradually increased under AL and RL ( P < 0.05; Fig 4A ). The content level of proteins and starches increased under RL but decreased under AL ( P < 0.05; Fig 4B and 4C ).

(A) Lipid; (B) Protein; (C) Starch. Data are expressed as mean values ± standard deviation (n = 5). Statistical analysis was performed against FL using a two-tailed Student’s t-test.

https://doi.org/10.1371/journal.pone.0247380.g004

Antioxidative enzyme activity in A . thaliana Col-0 under AL and RL

We examined the antioxidative activity of superoxide dismutase (SOD) and ascorbate peroxidase (APX) enzymes in Col-0 treated under AL, RL, and FL ( Fig 5 ). After the 24 h treatments, activity of both antioxidants was significantly increased under AL ( P < 0.05; Fig 5 ), while no significant changes were observed for either of these enzymes when plants were treated under RL.

(A) Superoxide dismutase (SOD) activity. One unit of SOD activity was defined as the amount of enzyme required to result in a 50% inhibition of the rate of reduction at 550 nm in 1 min. (B) Ascorbate peroxidase (APX) activity. One unit of APX activity was defined as the amount of enzyme required to oxidize 1 μmol of ascorbate at 290 nm in 1 min. Enzymatic activity was measured for 5 min at room temperature and data are expressed as mean values ± standard deviation (n = 5). Statistical analysis was performed against FL using a two-tailed Student’s t-test (n.s., not statistically significant; *, P < 0.05; **, P < 0.01).

https://doi.org/10.1371/journal.pone.0247380.g005

In this work, we investigated the impact of light quality BL, AL, and RL on leaf growth and photosynthetic response across three A . thaliana accessions Col-0, Est-1, and C24. The analyses clearly demonstrate the significant impact of light quality on leaf area growth, biomass content, and pigments accumulation (chlorophylls, carotenoid, and anthocyanin). The results indicate that light quality significantly influences Pn across accessions, consistent with the reported results that leaf photosynthetic reaction is wavelength-dependent in higher plants [ 54 ].

Importance of geographic habitats on light quality response of leaf growth and biomass

The selected accessions Col-0, Est-1, and C24 have different geographic habitats; C24 originated from a part of Europe (Portugal), Est-1 from Northern Asia (Russia), and Col-0 from United States (Columbia). Therefore, we took into account differences in geographical range for these accessions resulted in a high degree of divergence in photosynthetic characteristics to light [ 35 ]. The most extreme responder in leaf area growth and leaf biomass analyses was Est-1 from Russia. It is worth pointing out that the two Col-0 and C24 accessions highlighted here as weak responders, they elongated very quickly under AL and thus may not be true candidates for weak responders. Previous studies have found negative correlations between hypocotyl height and latitude of accession origin in European Arabidopsis accessions [ 55 , 56 ], suggesting that this natural variation in light sensitivity could be a result of adaptation to the north-south gradient in ambient light intensity.

The results of the study described here emphasize the strength of explicitly incorporating LxG interactions into the leaf area growth and leaf biomass content across the accessions. Importantly, as further elaborated below, the genotype-specific responses in leaf area growth and biomass content were observed exclusively under AL and BL, while the three accessions exhibited similar patterns of changes under RL. Our findings are consistent with previous reports on different accessions and light quality treatments, and underscores the importance of considering the natural habitat effect in characterizing the impact of light quality on leaves [ 57 ].

Leaf development varied between accessions such that the overall dynamic of growth and biomass were different. For example, we took efforts in synchronizing leaf growth stage in the accessions, resulting in the C24 plants being grow for 23 days to reach the same leaf stages of the plant. Some of the observed variation in leaf growth response could be simply a manifestation of the different time-course between accessions. These differences between accession can be significant and have the potential to enhance our understanding of the ecological role of specific adaptations.

Findings on BL supports its role on activation of protective pigments

BL induced higher leaf area growth across three accessions. However, its impact on biomass production is accession-dependent, and may be caused by accessory pigment accumulation (anthocyanins). Under BL, only Col-0 showed an increase in biomass, as opposed to Est-1 and C24, which showed a decrease in biomass. It was observed that BL induced a significantly higher concentration of anthocyanins in Est-1 and C24 than Col-0. These results imply that the impact of wavelength on accessory pigment accumulation is accession-dependent, and that this difference in accessory pigment accumulation consequently leads to differences in biomass production across accessions. Anthocyanin is a photo-protective pigment, which protects plant and its chloroplast membrane by absorbing blue light and against photo-oxidation [ 58 , 59 ]. Higher concentration of anthocyanin accumulating in a plant results in lower BL interception, which consequently lead to lower biomass production over the long term. Further to this, in this study, we found the ratio of Chl a:b is similar under BL and FL across accessions. This consistency in Chl a:b, suggests a lack of photosystems reconfiguration under BL [ 60 , 61 ]. Our results confirm the role of BL in stimulating anthocyanin content in plants and protecting them from light stress [ 62 ]. Plants activate photo-protective mechanisms under BL to cope with a potential induced-light stress, resulting in an increased accumulation of photo-protective pigments [ 58 , 59 ]. Notably, we found different patterns in content of anthocyanin accumulation in the accessions. Results showed that anthocyanin accumulation can be triggered at low BL (~70 μmol m -2 sec -1 ), which suggests that this protective mechanism against BL can vary based on the accession (i.e. natural adaptations) and can be triggered under low light. Further investigation on these two accessions on BL with a wide range of BL intensity is required. Our results thus encourage future studies analyzing this trait using BL with a wide range of BL intensity to further advance our understanding of the underlying mechanisms.

Plants showed high antioxidative and photo-protective under AL

AL had no impact on the photosynthetic activity across the three accessions compared to FL; yet it induced the poorest morphological traits. Col-0 and C24 showed a severe reduction ‬‬in leaf area growth and biomass, while Est-1 was unaffected. These two accessions (Col-0 and C24) showed a clear elongation of petioles under AL, which suggests that leaf resources are redirected from leaves to petioles as insufficient lighting conditions under AL were performed in this study [ 63 ]. However, the results on transcriptional changes and photosynthates content showed the opposite responses to the morphological traits.

The photosynthates, including proteins and starches, showed lower content in leaves of plants treated under AL. A downregulation of RBCS1A (small subunit of Rubisco) transcription was also observed in the leaves treated under AL. A lower accumulation of proteins was previously observed under AL [ 64 ], suggesting a positive contribution of downregulated Rubisco genes, as it is the main protein in leaves. A lower content of carbohydrates under stress conditions has been observed before in A . thaliana [ 65 ]. Future work is needed to explore if a reduced conversion of light energy into chemical energy has occurred in the photosynthesis process under AL.

High capacity for lipids accumulation was observed for plants treated under AL. Lipid accumulation had been previously linked to oxidative stress [ 66 ]. suggesting an increase in lipophilic antioxidants content such as tocopherols, which play an important role in the scavenging of singlet oxygen [ 67 ]. Moreover, we found a significant increase in both expression and enzymatic activity of antioxidants under AL. Plants stimulate antioxidative mechanisms to protect the photosynthetic apparatus from incurring damage via ROS detoxification [ 30 , 68 ]. Our results on photosynthates thus suggest that plants tried to cope with a potential ROS stress condition under AL.

A significant upregulation in glutathione biosynthesis, transcription level of PGRL1B , ATPC1 , and marker genes associated with ATP synthase and CET complex was observed. In agreement with this result, a significant increase in the expression of ATPC1 at the protein level was recently reported in A . thaliana Col-0 treated with 595 nm light [ 69 ]. CET plays an important role to protect plants under high light and other stress environments [ 70 ]. During CET, electrons are cycled around PSI and protons are translocated to generate a proton gradient across the thylakoid membranes [ 71 ]. In addition to contributing ATP synthesis, another function of a generated proton gradient is to dissipate excess energy as heat from the PSII antennae [ 72 ]. Further to this, an upregulation of CET and ATP synthase suggests of an accelerated rate of PSII repair through elevated ATP synthesis [ 73 , 74 ]. As such, the results on photosynthates and at the transcription level under AL both suggest that AL, even at low light, induces protective mechanisms of photosystems related to light stress, which consequently triggers low protein and starch accumulation and result in poor morphological traits.

One possible hypothesis for the conflicting AL responses can be explained by the detour effect [ 75 , 76 ], where a major part of AL transmitted into the leaf is reflected within leaf tissues and re-absorbed by unsaturated chlorophylls multiple times, which leads to an observed light stress response. Due to the nature of the high absorbing efficiency of the chloroplast, nearly 90% of BL and RL are absorbed at the leaf surface and their detour effect is small [ 76 , 77 ]. While for the wavelength within 500–600 nm [i.e. green light (GL) and AL] that are less absorbed by chloroplast, its light path can increase by several folds and this results in its increased/overexpressed photosynthetic activity through light absorption by unsaturated chloroplast. Although there is no study reporting the underlying mechanisms triggered by AL, several studies have observed the impact of supplemented GL and AL on photosynthetic activity and plant productivity in horticultural plants, which reinforces our hypothesis on the increased photosynthetic activity under AL. Further to this, the aggressive suppression responses on morphological traits in A . thaliana under AL, opposed to the positive impact on plant development, is expected as A . thaliana is a low light plant. They are more sensitive to the change in light properties. Overall, our results suggest AL as a potential light source in activating the potential of increased plant productivity efficiently, but it requires high control on its intensity. This study clarifies why AL alone induces overexpressed high photosynthetic activity yet results in poor plant development.

RL modulated plant adaptation and energy assimilation

The leaf area growth was significantly increased under RL across all accessions, which in turn enabled a greater light interception by the leaves [ 78 ]. This agrees with the increased Pn that was observed across accessions. These observations along with a significant increase of leaf biomass suggests proper plant adaptation under RL across accessions. We found a significant increase in the Chl a: b under RL across accession. Chl a is mainly concentrated around PSI and PSII, whereas Chl b is most abundant in light-harvesting complexes [ 79 ]. An increase in Chl a: b can increase the likelihood of an efficient electron transfer system within the chloroplast membrane [ 80 ]. This, in turn, could positively influence the photosynthetic performance in plants under RL. Considering that timely synthesis of D1 protein is key to maintain the PSII function and consequently, photosynthetic performance in leaves [ 25 ]. An increasing trend of PSBA expression was observed in plants under RL. The PSBA gene is critical for the de novo synthesis of the D1 protein during PSII repairs [ 81 , 82 ]. Therefore, upregulated transcription of PSBA gene could play an important role in accelerating the process of D1 protein turnover under RL. Plants showed that leaf photosynthates (starches, lipids, proteins) increased under RL. Overall, our results present RL as an efficient light source in helping the leaf energy assimilation process, resulting in an increased leaf growth, photosynthetic performance, and photosynthates content in plants.

Supporting information

https://doi.org/10.1371/journal.pone.0247380.s001

S1 Table. List of primers sequences used in qPCR experiments.

https://doi.org/10.1371/journal.pone.0247380.s002

S1 Fig. Proteins involved in ATP synthase and CET complex of A . thaliana Col-0 are upregulated under AL (595 nm) compared to RL (650 nm).

In this experiment, eleven-leaves plants were grown under AL and RL for 5 days (three biological replicates per light condition). A) The expression pattern of protein members involved in Cyclic electron transfer (CET) complex. B) The expression pattern of protein members involved in ATP synthase complex. Expression levels for each protein is normalized to have mean of zero and standard deviation of one. Yellow or blue color indicates upregulation or downregulation, respectively.

https://doi.org/10.1371/journal.pone.0247380.s003

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How light reactions of photosynthesis in c4 plants are optimized and protected under high light conditions.

1. Diversity of C4 Photosynthesis

2. ways of light energy utilization: balanced distribution between photosystems and emission of excess energy as a heat, 2.1. elevation of cyclic electron transport components.

Click here to enlarge figure

2.2. Function of PTOX Protein and Chlororespiration

2.3. changes in the amount of thylakoid complexes and rearrangement of super- and megacomplexes, 2.4. photoinhibition and role of d1 protein phosphorylation, 2.5. state transitions and phosphorylation of lhcii, 2.6. xanthophyll cycle and heat dissipation, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest, abbreviations.

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Process Taking Place in Chloroplasts	C3 Plants	C4 Plants
Xanthophyll cycle and heat dissipation	Typical, occurring with the zeaxanthin and PsbS protein [ ].
State transitions and LHCII phosphorylation	Function of state 1 and state 2, depending on phosphorylation of the LHCII antenna [ ].	Permanent state 2 in agranal BS maize (NADP-ME) chloroplasts. LHCII in phosphorylated form, regardless of the condition [ ].
Photoinhibition and phosphorylation of D1 protein	Damaged D1 is directed to the thylakoid stroma, dephosphorylated, and then degraded.	D1 degradation is faster in the BS chloroplast of maize [ ]. Photodamage of some PSII pools for protection against PSI excess [ ].
Cyclic electron transport components	Lower ATP demand resulting from metabolism.	Elevation of the CET ad alternative CET pathway with NDH complex for higher efficiency of ATP production [ , , ].
PTOX functioning and chlororespiration	Minor importance, activity mainly under stressful conditions.	High amount and activity in maize BS chloroplasts for better protection against ROS formation during elevated cyclic electron transport [ ].
Changes in antenna and reaction centers amount	Higher content of LHCII antenna in low light intensities. Higher content of reaction centers at high light intensities [ ].
Additional mechanism(s)	No data available.	Formation of megacomplexes in maize mesophyll chloroplasts [ ].

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Wasilewska-Dębowska, W.; Zienkiewicz, M.; Drozak, A. How Light Reactions of Photosynthesis in C4 Plants Are Optimized and Protected under High Light Conditions. Int. J. Mol. Sci. 2022 , 23 , 3626. https://doi.org/10.3390/ijms23073626

Wasilewska-Dębowska W, Zienkiewicz M, Drozak A. How Light Reactions of Photosynthesis in C4 Plants Are Optimized and Protected under High Light Conditions. International Journal of Molecular Sciences . 2022; 23(7):3626. https://doi.org/10.3390/ijms23073626

Wasilewska-Dębowska, Wioleta, Maksymilian Zienkiewicz, and Anna Drozak. 2022. "How Light Reactions of Photosynthesis in C4 Plants Are Optimized and Protected under High Light Conditions" International Journal of Molecular Sciences 23, no. 7: 3626. https://doi.org/10.3390/ijms23073626

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The effect of light quality on plant physiology, photosynthetic, and stress response in Arabidopsis thaliana leaves

Affiliations.

1 Department of Bioresource Engineering, McGill University-Macdonald Campus, Sainte-Anne-de-Bellevue, Quebec, Canada.
2 Department of Plant Science, McGill University-Macdonald Campus, Sainte-Anne-de-Bellevue, Quebec, Canada.
PMID: 33661984
PMCID: PMC7932170
DOI: 10.1371/journal.pone.0247380

The impacts of wavelengths in 500-600 nm on plant response and their underlying mechanisms remain elusive and required further investigation. Here, we investigated the effect of light quality on leaf area growth, biomass, pigments content, and net photosynthetic rate (Pn) across three Arabidopsis thaliana accessions, along with changes in transcription, photosynthates content, and antioxidative enzyme activity. Eleven-leaves plants were treated with BL; 450 nm, AL; 595 nm, RL; 650 nm, and FL; 400-700 nm as control. RL significantly increased leaf area growth, biomass, and promoted Pn. BL increased leaf area growth, carotenoid and anthocyanin content. AL significantly reduced leaf area growth and biomass, while Pn remained unaffected. Petiole elongation was further observed across accessions under AL. To explore the underlying mechanisms under AL, expression of key marker genes involved in light-responsive photosynthetic reaction, enzymatic activity of antioxidants, and content of photosynthates were monitored in Col-0 under AL, RL (as contrast), and FL (as control). AL induced transcription of GSH2 and PSBA, while downregulated NPQ1 and FNR2. Photosynthates, including proteins and starches, showed lower content under AL. SOD and APX showed enhanced enzymatic activity under AL. These results provide insight into physiological and photosynthetic responses to light quality, in addition to identifying putative protective-mechanisms that may be induced to cope with lighting-stress in order to enhance plant stress tolerance.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Fig 1. Effect of BL, AL, RL…

Fig 1. Effect of BL, AL, RL and FL on morphology, leaf area growth, biomass,…

Fig 2. Flow diagram of study design…

Fig 2. Flow diagram of study design to investigate the potential induction of stress response…

Fig 3. A schematic model of light-responsive…

Fig 3. A schematic model of light-responsive photosynthetic process and effect of AL and RL…

Fig 4. Effect of AL and RL…

Fig 4. Effect of AL and RL on photosynthates content in A . thaliana Col-0.

Fig 5. Effect of AL and RL…

Fig 5. Effect of AL and RL on SOD and APX activity in A .…

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Effects of growth under different light spectra on the subsequent high light tolerance in rose plants

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Leyla Bayat, Mostafa Arab, Sasan Aliniaeifard, Mehdi Seif, Oksana Lastochkina, Tao Li, Effects of growth under different light spectra on the subsequent high light tolerance in rose plants, AoB PLANTS , Volume 10, Issue 5, October 2018, ply052, https://doi.org/10.1093/aobpla/ply052

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Photosynthesis is defined as a light-dependent process; however, it is negatively influenced by high light (HL) intensities. To investigate whether the memory of growth under monochromatic or combinational lights can influence plant responses to HL, rose plants were grown under different light spectra [including red (R), blue (B), 70:30 % red:blue (RB) and white (W)] and were exposed to HL (1500 μmol m −2 s −1 ) for 12 h. Polyphasic chlorophyll a fluorescence (OJIP) transients revealed that although monochromatic R- and B-grown plants performed well under control conditions, the functionality of their electron transport system was more sensitive to HL than that of the RB- and W-grown plants. Before exposure to HL, the highest anthocyanin concentration was observed in R- and B-grown plants, while exposure to HL reduced anthocyanin concentration in both R- and B-grown plants. Ascorbate peroxidase and catalase activities decreased, while superoxide dismutase activity was increased after exposure to HL. This caused an increase in H 2 O 2 concentration and malondialdehyde content following HL exposure. Soluble carbohydrates were decreased by exposure to HL, and this decrease was more emphasized in R- and B-grown plants. In conclusion, growing plants under monochromatic light reduced the plants ability to cope with HL stress.

Light is the original source of energy for plant photosynthesis and growth. A wide range of signals and information for morphogenesis and many other physiological processes is triggered by light ( Chen et al. 2004 ). Different characteristics of light such as spectral composition (wavelengths), intensity, duration and direction can influence plant growth and development. The photosynthesis process is also sensitive to all aspects of lighting environments.

The rapid development of lighting technologies using light-emitting diodes (LEDs) has caused an increase in the application of this technology for lighting in closed horticultural systems ( Kozai et al. 2015 ). Light-emitting diodes are also attractive because of their high radiant efficiency, long lifetimes, small size, low temperature, narrow spectrum and physical robustness ( Tennessen et al. 1994 ; Kim et al. 2004 ; Breive et al. 2005 ; Morrow 2008 ). The application of LEDs in horticulture makes it possible to use certain wavelengths to study particular plant responses. For instance, intercrop lighting using LEDs is nowadays used to promote photosynthesis of the middle and lower leaves. However, research on the effect of spectral wavelengths on plant growth and development is still in progress.

Plant responses to light differ based on the lighting environment, season, genotype, cultivation practices and many others ( Kozai 2016 ). Although light is the energy source for photosynthesis, it can simultaneously function as a stress factor. Under high light (HL) intensity conditions or when plants are exposed to other abiotic stresses (e.g. drought), the energy supply (ATP) and reducing power (NADPH) through photosystems (and by involvement of electron transport chain) exceed the demand for metabolic processes in carbon-fixing reactions ( Miyake et al. 2009 ; Gu et al. 2017 ). The accumulation of reactive oxygen species (ROS) is the result of a disturbance between supply and demand for electron transport end products. Depending on the rate of accumulation, ROS can have dual effects on plant responses. At low concentrations, ROS act as a signal to induce defence responses, while at high concentrations ROS are toxic and induce lipid peroxidation in the cell membranes and cause oxidative damage to cellular components ( Dat et al. 2000 ; Vranová et al. 2002 ). Consequently, the functionality of photosynthesis decreases under stressful conditions. Photosynthesis suppression due to exposure to HL intensities is known as photoinhibition. Damage caused by the photoinhibition process can take place in all components of the photosynthetic machinery. Among them, the photosystem II (PSII) complex of the electron transport chain is considered the primary target of photoinhibition ( Vass 2012 ; Roach and Krieger-Liszkay 2014 ). However, photosynthesis as a fine-tuned process employs multiple mechanisms to cope with photoinhibition. Dissipation of excess energy in the form of heat is the main protective strategy to get rid of the damage induced by HL intensities ( Müller et al. 2001 ). Thermal dissipation is known as non-photochemical quenching (NPQ) of Chl fluorescence. Non-photochemical quenching encompasses several strategies including: energy-dependent quenching by involvement of the xanthophyll cycle, conformational changes in light harvesting complex II (LHCII), which are known as state transitions, and photoinhibition resulting in reduction of quantum yield as a consequence of light-induced damage ( Müller et al. 2001 ; Zhao et al. 2017 ).

Light is absorbed by plant pigments. Chl a and b are the main photosynthetic pigments in plants. They mainly absorb blue and red wavelengths of the light spectrum. Carotenoids with an absorption spectrum between 350 and 500 nm are also found in all chlorophyll-based photosynthesis systems. They contribute to light absorption in the antenna system. Furthermore, carotenoids help the plant to dissipate excess energy as heat to protect the photosynthesis apparatus from HL intensities ( Sharma and Hall 1993 ). Anthocyanins are also involved in the protection of photosynthetic apparatus from damage due to HL intensity ( Petrella et al. 2016 ).

Roses are the most famous ornamental plants worldwide. The growth and development as well as post-harvest quality of rose plants are affected by pre-harvest environmental factors such as relative humidity (RH) and light ( Fanourakis et al. 2013 ). Issues related to light have attracted much attention for rose cultivation during the last few decades. In some places (especially at high latitudes), supplementary lighting is used to compensate sun light limitations. In other places exposure to HL intensities during the summer negatively influences rose production. In those places shading the rose plants is a common practice during summer time. Furthermore, in many places plants are only exposed to HL conditions for a short duration. However, both shading and HL can negatively influence photosynthesis ( García Victoria et al. 2011 ).

Each spectral band of light can induce certain responses in plants. For instance, red and blue lights mainly contain the range of wavelengths necessary for electron excitation in the photosynthetic apparatus ( Taiz and Zeiger 2002 ). Wavelengths in the range of blue and UV cause the accumulation of carotenoids and anthocyanins in the leaves ( Li and Kubota 2009 ; Carvalho et al. 2016 ), and red light induces accumulation of carbohydrates in the leaf ( Sæbø et al. 1995 ). Since each band of light wavelengths can induce certain mechanisms and responses in plants, which can affect subsequent plant responses to environmental stresses, in the current study, we hypothesize that protective mechanisms against HL stress would be up-regulated/down-regulated through growing plants under certain light spectra which can influence plant responses to HL intensity afterwards. Furthermore, since limited wavelengths can induce certain protective mechanisms against HL, plants grown under combined wavelengths have more capabilities to tolerate HL intensities.

Cryptochromes and phototropins are the B light acceptors, whereas phytochromes are more sensitive acceptors for R light ( Whitelam and Halliday 2008 ). These photoreceptors acquire information from the light environment and use that information to modulate cellular processes ( Smith 1982 ). Therefore, different signal transduction pathways are involved in the up- or down-regulation of certain metabolic pathways by the information gained from specific photoreceptor of certain wavelength. The aims of the current study were to investigate (i) the structure and function of photosynthetic apparatus in plants (grown under different light spectra) exposed to HL intensity, and (ii) the mechanisms involved in HL tolerance in rose plants grown under different light spectra.

It has been shown that the energy flow and information related to the structure and function of the photosynthetic apparatus can be analysed through Chl fluorescence data. Although chlorophyll fluorescence parameters obtained by the saturation pulse method in light-adapted leaves give valuable information regarding the energy flow across thylakoid membranes, these types of measurement are time-consuming and are not fully ideal for assessing fluorescence parameters in practical conditions ( Brestic and Zivcak 2013 ). The non-destructive analysis of polyphasic fast chlorophyll transient by the so-called OJIP test was developed for quick evaluation of biophysical aspects of photosynthesis especially under stress conditions ( Strasser 1995 ; Mathur et al. 2013 ). This test relies on energy flow in thylakoid membranes, which provides detailed information about the biophysics of the photosynthetic system through measurement of fluorescence signals ( Kalaji et al. 2017 ). The OJIP test has been successfully used for studying the photosynthetic apparatus of different plant species under abiotic stress conditions ( Panda et al. 2008 ; Martinazzo et al. 2012 ; Kalaji et al. 2014 ; Rapacz et al. 2015 ; Kalaji et al. 2016 ). Therefore, this test was used in the current study to detect the negative effects of HL stress on the photosynthetic apparatus of the rose plants.

Plant material and growth conditions

Rose plants ( Rosa hybrida cv. ‘Avalanche’) were propagated from cuttings in March 2017 in a perlite medium. Rooting was achieved following 4–5 weeks of planting. The rooted cuttings (10–15 cm long with two emerging leaves) were transplanted into 15 cm diameter plastic pots containing a mixture of cocopite and perlite (70/30 % by volume). The plants were watered daily for 3 days after transplantation, and thereafter, they were irrigated with half-strength Hoagland solution. Homogeneous plants were divided into four growth chambers (four plant per each growth chamber) with the same climatic conditions (temperature: 27 ± 3 °C; RH: 50 ± 5 %; photoperiod: 12-h light/12-h dark between 0800 and 2000 h). Plants were subjected to four different light spectra: white (W), blue (B), red (R) and 70 % red + 30 % blue (RB) provided by LED production modules (24-W, Iran Grow Light Co., Iran) at a photosynthetic photon flux density (PPFD) of 250 ± 10 μmol m −2 s −1 . The W spectrum consisted of 41 % in the range of B and 18 % in the range of R. Photosynthetic photon flux density intensities and light spectra were monitored using a light meter (Sekonic C-7000, Japan). The relative spectra of the light treatments are shown in Fig. 1 . Four weeks after growth at different light spectra, all plants were exposed to a HL intensity (1500 μmol m −2 s −1 ) for 12 h (between 0800 and 2000 h) ( Fig. 2 ). To provide the same temperature during plant exposure to HL intensity as the growth chamber temperature, plants were illuminated with LED production modules (Iran Grow Light Co., Iran) in the range of 400–700 nm in a temperature-controlled room at 21 °C and 50 % RH. Under this condition, the temperature was fixed to 27 °C under HL intensity (same as the temperature in the growth chambers). Since such a HL intensity caused an increase in the temperature of growth chamber (27 °C), to maintain the same temperature before and after HL intensity same temperature was also kept inside the growth chambers during the growth of plants. The module consisted of 320 LEDs equipped with three fan ventilators to reduce the heat produced in the module. Measurement of the parameters was performed at two time points: first, at the end of plant growth under different light spectra with PPFD of 250 μmol m −2 s −1 , and second, at the end of plant exposure to HL intensity (1500 μmol m −2 s −1 ).

Light spectra of the blue (B), red (R), red and blue (RB) and white (W) lighting environments measured at plant level in the growth chambers.

Representative images showing plants (A) that were grown for 3 weeks under different light spectra [blue (B), red (R), white (W) and red and blue (RB)], growth chambers that were used for growing plants under 250 (B) and 1500 (C) µmol m −2 s −1 PPFD.

Chl fluorescence and OJIP test measurements

The youngest fully developed leaves were used for measuring the maximum quantum efficiency of PSII ( F v / F m ) with the Handy Fluorcam FC 1000-H (Photon Systems Instruments, PSI, Czech Republic). Intact leaves attached to the plants were dark-adapted for 20 min. After dark adaptation, intact plants were immediately used to measure F v / F m . The Fluorcam consisting of a CCD camera and four fixed LED panels, one pair supplying the measuring pulses and the second pair providing actinic illumination and saturating flash, were used. F v / F m was calculated using a custom-made protocol ( Genty et al. 1989 ; Aliniaeifard et al. 2014 ; Aliniaeifard and van Meeteren 2014 ). Images were recorded during short measuring flashes in darkness. At the end of the short flashes, the samples were exposed to a saturating light pulse (3900 µmol m −2 s −1 ) that resulted in a transitory saturation of photochemistry and reduction of the primary quinone acceptor of PSII ( Genty et al. 1989 ). After reaching steady-state fluorescence, two successive series of fluorescence data were digitized and averaged, one during the short measuring flashes in darkness ( F 0 ), and the other during the saturating light flash ( F m ). From these two images, F v was calculated by the expression F v = F m − F 0 . The F v / F m was calculated using the ratio ( F m − F 0 )/ F m . Maximum fluorescence ( F m ′) was determined in light-adapted steady state and was used for calculation of NPQ according to the following equation:

The average values and standard deviation per image were calculated using Fluorcam software version 7.0.

The polyphasic Chl a fluorescence (OJIP) transients were measured using a Fluorpen FP 100-MAX (Photon Systems Instruments, Drasov, Czech Republic) on young fully expanded rose leaves after 20 min dark adaptation. OJIP was used to study different biophysical and phenomenological parameters related to PSII status ( Strasser 1995 ). The transient fluorescence measurement was induced by a saturating light of ~3000 μmol m −2 s −1 . All the measurements were performed on 20 min dark-adapted plants. The OJIP transients were done according to the JIP test ( Strasser et al. 2000b ). The following data from the original measurements were used after extraction by Fluorpen software: fluorescence intensities at 50 μs (F50μs, considered as the minimum fluorescence F 0 ), 2 ms (J-step, F J ), 60 ms (I-step, F I ) and maximum fluorescence ( F m ).

The performance index was calculated on the absorption basis (PI ABS ) and densities of QA − reducing PSII reaction centres at time 0 and time to reach maximum fluorescence. The yield ratios, including the probability that a trapped exciton moves an electron in the electron transport chain beyond QA − (ψ o ), the quantum yield of electron transport (φ Eo ), the quantum yield of energy dissipation (φ Do ) and the maximum quantum yield of primary photochemistry (φ Po ), were also calculated based on the following equations:

From these data the following parameters were calculated: the specific energy fluxes per reaction centre (RC) for energy absorption (ABS/RC = M 0 ·(1/V J )·(1/φ Po )), (M 0 = TR 0 /RC-ET 0 /RC), trapped energy flux (TR 0 /RC = M 0 · (1/V J )), electron transport flux (ET 0 /RC = M 0 ·(1/V J )·ψ o ) and dissipated energy flux (DI 0 /RC = (ABS/RC) – (TR 0 /RC)).

Pigment measurements

The Chl and carotenoid contents of the leaves were measured according to the method described by Arnon (1949) . For measuring the anthocyanin content of the leaves, 1 g of leaf tissue was homogenized in 10 mL methanol and the extract was incubated at 4 °C in the dark overnight. The slurry was centrifuged (SIGMA-3K30) at 4000 g for 10 min. The anthocyanin in the supernatant was spectrophotometrically (Lambda 25 UV/VIS spectrometer) determined at 520 nm according to the method described by Wagner (1979) .

Determination of hydrogen peroxide content and lipid peroxidation

The level of lipid peroxidation in the leaf tissue was measured based on the malondialdehyde (MDA, a product of lipid peroxidation) content of the leaves. Malondialdehyde was determined by the thiobarbituric acid (TBA) reaction by minor modification of the method described by Heath and Packer (1968) . A 0.25 g leaf sample was homogenized in 5 mL of 0.1 % trichloroacetic acid (TCA). The homogenate was centrifuged at 10000 g for 5 min. Four millilitres of 20 % TCA containing 0.5 % TBA was added to a 1-mL aliquot of the supernatant. The mixture was heated at 95 °C for 30 min and then quickly cooled in an ice bath. After centrifuging at 10000 g for 10 min the absorbance of the supernatant at 532 nm was read and the value for the non-specific absorption at 600 nm was subtracted. The concentration of MDA was calculated using its extinction coefficient of 155 mM −1 cm −1 ( Heath and Packer 1968 ).

Hydrogen peroxide (H 2 O 2 ) content was spectrophotometrically measured after reaction with potassium iodide (KI). The reaction mixture contained 0.5 mL of 0.1 % TCA, leaf extract supernatant, 0.5 mL of 100 mm K-phosphate buffer and 2 mL reagent (1 M KI w/v in fresh double-distilled H 2 O). The blank contained 0.1 % TCA in the absence of leaf extract. The reaction was developed for 1 h in darkness and absorbance was measured at 390 nm. The amount of H 2 O 2 was calculated using a standard curve prepared with known concentrations of H 2 O 2 according to the method described by Patterson et al. (1984) .

Determination of carbohydrates

Young fully developed leaves (300 mg fresh weight [FW]) were collected from each replicate per treatment and were ground in liquid nitrogen, mixed with 7 mL of 70 % ethanol (w/v) for 5 min on ice and centrifuged at 6700 g for 10 min at 4 °C. After adding 200 mL of the supernatant to 1 mL of an anthrone solution (0.5 g anthrone, 250 mL 95 % H 2 SO 4 and 12.5 mL distilled water), the absorbance was spectrophotometrically recorded at 625 nm ( van Doorn 2012 ).

For starch quantification, 0.1 g of a fresh fully developed leaf was ground and sugars were extracted with 80 % ethanol and starch was solubilized using 52 % perchloric acid. Starch was colorimetrically determined at 630 nm using the sugar-anthrone-sulfuric acid reaction based on the method described by McCready et al. (1950) .

Determination of activities of antioxidant enzymes

Ascorbate peroxidase (APX) activity was determined by oxidation of ascorbic acid (AA) at 265 nm (ε = 13.7 mM −1 cm −1 ) by slight modification of the method described by Nakano and Asada (1981) . The reaction mixture contained 50 mM potassium phosphate buffer (pH 7.0), 5 mM AA, 0.5 mM H 2 O 2 and the enzyme extract. The reaction was started by adding H 2 O 2 . The rates were corrected for the non-enzymatic oxidation of AA by the inclusion of a reaction mixture without the enzyme extract (blind sample). The enzyme activity was expressed in μmol AA min −1 per g of fresh weight ( Nakano and Asada 1981 ).

For determination of catalase (CAT) activity, the decomposition of H 2 O 2 was recorded by the decrease in absorbance at 240 nm. Reaction mixture consisted of 1.5 mL 50 mM sodium phosphate buffer (pH 7.8), 0.3 mL 100 mM H 2 O 2 and 0.2 mL enzyme extract. One CAT unit was defined as the amount of enzyme necessary to decompose 1 mM min −1 H 2 O 2 . Therefore, the CAT activity was expressed as U g −1 FW min −1 ( Díaz-Vivancos et al. 2008 ).

Superoxide dismutase (SOD) activity was measured according to the method described by Dhindsa et al. (1981) . The method is based on the ability of SOD to inhibit the photochemical reduction of nitro blue tetrazolium (NBT). The reaction mixture contained 50 mM phosphate buffer (pH 7–8), 13 mM methionine, 75 µM NBT, 0.15 mM riboflavin, 0.1 mM EDTA and 0.50 mL enzyme extract. Riboflavin was the last item that was added. The reaction mixture was shaken and placed under two 15-W fluorescent lamps. The reaction was started by switching on the light and was allowed to run for 10 min. The reaction was stopped by turning off the light and the tubes were covered using a black cloth. The absorbance by the reaction mixture was spectrophotometrically recorded at 560 nm. A reaction mixture without exposure to the light was used as the control. No colour was observed in the control. Under assay conditions, one unit of SOD activity is expressed as the amount of enzyme that led to 50 % inhibition of NBT reduction ( Dhindsa et al. 1981 ).

Statistical analysis

Four plants were used as four replicates in each light treatment. Individual plants were taken as independent replicates. The measurements were done on two timescales: before and after exposure to HL. To make the environmental conditions of the two timescales similar, environmental conditions inside the chambers and between the chambers were kept as similar as possible before and after exposure to HL. To do this, the same temperature, RH and light intensity and duration were maintained during these two timescales in a climate-controlled room. Sampling was done on the same plants before and after exposure to HL. The data were subjected to two-way analysis of variance (ANOVA) and the Tukey test was used as a post-test. P > 0.05 was considered not significant. GraphPad Prism 7.01 for Windows (GraphPad Software, Inc., San Diego, CA) was used for the statistical analysis.

Polyphasic Chl a fluorescence (OJIP) transients

In the current study, the PSII activity was studied by calculation of different Chl fluorescence parameters in a leaf in the dark-adapted state. Investigating the fast chlorophyll fluorescence induction curve showed that all plants produced typical polyphasic curves with the basic OJIP steps ( Fig. 3 ). For all plants, the intensity of the fluorescence signal was increased from the initial fluorescence level ( F 0 ) to the intermediate steps (J and I) and then reached the maximum level ( F m ). Except for R light, exposure to HL caused a decline in fluorescence intensity in all steps of OJIP.

Fast chlorophyll fluorescence induction curve exhibited by leaves of rose plants exposed to different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (C) and 1500 (HL) µmol m −2 s −1 PPFD.

Under control (C) conditions, the highest F 0 and F J were observed for W-grown plants and the lowest values were detected in R-grown plants ( Fig. 4A and B ). Under HL conditions, the highest F 0 , F J , F I and F P were observed for R-grown plants and their lowest values were detected in RB-grown plants ( Fig. 4A–D ). In all plants, exposure to HL resulted in a decrease in F v values; however, among the light treatments, the change in F v following exposure to HL was the lowest for W-grown plants ( Fig. 4E ). F v / F m also decreased following exposure to HL and this decrease was greatest for monochromatic R- and B-grown plants ( Fig. 4D ). The calculated parameters of the OJIP test were changed significantly due to exposure to different light spectra and HL, and the interactions were also significant for the calculated parameters [see Supporting Information—Table S1 ] . The calculated parameters for specific energy fluxes per reaction centre such as ABS/RC, TR 0 /RC and DI 0 /RC were increased following exposure to HL for all plants grown under different light spectra, except for the RB-grown plants ( Fig. 5A , B and D ). In the case of ABS/RC and DI 0 /RC, the highest difference between C and HL was observed in monochromatic R- and B-grown plants. There was no significant difference between C and HL for the RB-grown plants. ET 0 /RC was similar in the C and HL treatments for R- and B-grown plants, while it was increased in W- and RB-grown plants after exposure to HL ( Fig. 5C ).

Intensity of chlorophyll a fluorescence in the OJIP test including F 0 (A), F J (B), F I (C), F P (D), F v [E; ( F m − F 0 )] and F v / F m (F) from the fluorescence transient exhibited by leaves of rose plants grown under different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (black bars) and 1500 (grey bars) µmol m −2 s −1 PPFD. Bars represent means ± SD.

Specific energy fluxes per reaction centre (RC) for energy absorption [A; (ABS/RC)], trapped energy flux [B; (TR 0 /RC)], electron transport flux [C; (ET 0 /RC)] and dissipated energy flux [D; (DI 0 /RC)] from the fluorescence transient exhibited by leaves of rose plants grown under different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (black bars) and 1500 (grey bars) µmol m −2 s −1 PPFD. Bars represent means ± SD.

Analysis of the parameters that estimate the yields and efficiency of the electron transport chain showed that although the highest values for PI ABS , φ Po and φ Eo were observed in monochromatic R- and B-grown plants under control conditions, their values were decreased more in the HL condition in comparison with their values in W- and RB-grown plants ( Fig. 6A–C ). Exposure to HL led to an increase in φ Do and NPQ [see Supporting Information—Fig. S1 ] in all plants; however, the highest φ Do was observed in RB-grown plants under both control and HL conditions ( Fig. 6D ). An increase in φ RAV was observed in R- and RB-grown plants following exposure to HL ( Fig. 6E ). R- and RB-grown plants had the highest ψ o values under control conditions, while their ψ o values decreased following exposure to HL. Conversely, in W- and RB-grown plants ψ o values were low under control conditions and were increased after exposure to HL ( Fig. 6F ).

Performance index on the absorption basis [A; (PI ABS )], maximum quantum yield of primary photochemistry [B; (φ Po )], quantum yield of electron transport [C; (φ Eo )], quantum yield of energy dissipation [D; (φ Do )], average (from time 0 to t FM ) quantum yield for primary photochemistry [E; (φ PAV )] and the probability that a trapped exciton moves an electron in the electron transport chain beyond QA − [F; (ψ o )] from the fluorescence transient exhibited by leaves of rose plants grown under different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (black bars) and 1500 (grey bars) µmol m −2 s −1 PPFD. Bars represent means ± SD.

All photosynthetic pigments were significantly influenced by the light spectra ( Fig. 7 ). Chl a [see Supporting Information—Fig. S2A ] , b [see Supporting Information—Fig. S2B ] and total Chl [see Supporting Information—Fig. S2C ] as well as carotenoids ( Fig. 7A ) were significantly decreased by growing rose plants under blue light. In the case of anthocyanin, the interaction between light spectra and light intensity was significant ( P ≤ 0.01). Before exposure to HL, the highest anthocyanin concentration was observed in R- and B-grown plants, while exposure to HL led to an ~50 % reduction in anthocyanin concentration in both R- and B-grown plants; significant differences were not found for anthocyanin concentration before and after HL in the leaves of W- and RB-grown plants ( Fig. 7B ).

Carotenoid (A) and anthocyanin (B) concentrations and MDA (C) content in the leaves of rose plants grown under different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (black bars) and 1500 (grey bars) µmol m −2 s −1 PPFD. Bars represent means ± SD.

Antioxidant enzymes and oxidative damage

Ascorbate peroxidase and SOD were significantly influenced by light intensity in contrasting ways ( Fig. 8A and B ). Irrespective of the light spectra, APX activity was reduced following exposure to HL, while SOD activity was induced by HL exposure. Catalase activity was reduced by exposure to HL ( Fig. 8C ). The highest CAT activity was observed in RB-grown plants in both control and HL conditions. The H 2 O 2 level was considerably influenced by light intensity ( Fig. 8D ). In comparison with control conditions, the H 2 O 2 level was increased by 10 times following exposure to HL. Malondialdehyde content was also influenced by light intensity ( Fig. 7C ). In comparison with control conditions, the MDA content was doubled after exposure to HL. The highest MDA content was observed in RB-grown plants in both control and HL conditions.

Activity of APX (A), SOD (B) and CAT (C) and H 2 O 2 concentration in the leaves of rose plants grown under different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (black bars) and 1500 (grey bars) µmol m −2 s −1 PPFD. Bars represent means ± SD.

Carbohydrate concentrations

Soluble carbohydrates were considerably decreased by exposure to HL conditions ( Fig. 9A ). This decrease was greater in R- and B-grown plants (65 % and 79 % decrease, respectively) than in W- and RB-grown plants (60 % and 49 % decrease, respectively). The highest and lowest concentrations of soluble carbohydrates were detected in R- and B-grown plants under control and HL conditions, respectively.

Concentration of soluble carbohydrate (A) and starch (B) in the leaves of rose plants grown under different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (black bars) and 1500 (grey bars) µmol m −2 s −1 PPFD. Bars represent means ± SD.

Similarly to soluble carbohydrates, HL conditions led to a decrease in starch concentration ( Fig. 9B ). This decrease was, respectively, 28 % and 31 % for R- and B-grown plants and 46 % and 35 % for W- and RB-grown plants. The highest and lowest concentrations of starch were, respectively, detected in R- and W-grown plants under both control and HL conditions.

The reactions involved in photosynthesis in plants are dependent on environmental conditions. Different light attributes including spectrum and intensity are considered to have the most direct effects on photosynthetic reactions ( Chen et al. 2004 ). In our study, Chl fluorescence data were analysed using the OJIP test. Using this test we showed that the PSII system appropriately operated in plants grown under monochromatic R and B spectra. However, when R- and B-grown plants were exposed to HL conditions, their PI ABS and ϕ Eo decreased and DI 0 /RC increased in comparison with their values under control conditions ( Figs 5–7 ). On the other hand, in W- and RB-grown plants ψ o and ET 0 /RC increased following exposure to HL ( Figs 5 and 7 ). These results revealed that growing plants under combination of light spectra enabled the plants to develop a photosynthesis apparatus with lower vulnerability than the photosynthesis apparatus in monochromatically grown plants in response to HL stress. The PI ABS amalgamates the energy fluxes from the early step of the absorption process until the plastoquinone reduction ( Strasser et al. 2000a ). According to previous reports this parameter is very sensitive to different environmental stresses and has been successfully used to measure photosynthetic and plant performance in response to different abiotic stresses including high temperatures ( Martinazzo et al. 2012 ), salinity ( Mathur et al. 2013 ), nutrient deficiency ( Kalaji et al. 2014 ), submergence ( Sarkar and Ray 2016 ), cold ( Rabara et al. 2017 ) and low pH ( Long et al. 2017 ).

In the current experiment, to ensure the same temperature before and after HL, same temperature (27 °C) was also kept inside the growth chambers, which negatively influenced the Chl a fluorescence parameters, resulting in values slightly lower than 0.8 for F v / F m ( Fig. 4 ). The lower PSII photochemical performance (lower PI ABS and φ Eo ) in monochromatic R- and B-grown plants following exposure to HL was due to the higher light energy absorption (ABS/RC), trapping (TR 0 /RC) and dissipated energy flux (DI 0 /RC) and lower ET 0 /ABS per reaction centre ( Fig. 5 ), which consequently resulted in a decreased quantum yield of electron transport (φ Eo ) and maximum quantum yield of primary photochemistry (φ Po ) ( Fig. 6 ). The increase in ABS/RC could attribute to the inactivation of reaction centres and a decrease in active QA reducing centres ( Strasser and Stirbet 1998 ). Under HL conditions, defective QA reducing centres function as a heat sink and protect the plant from HL damage ( Zivcak et al. 2014 ). The higher value of TR 0 /RC resulted in higher inhibition of reoxidation of QA – to QA ( Strasser et al. 2000a ). Higher TR 0 /RC would result in lower electron transport per reaction centre (ET 0 /RC) ( Fig. 5 ), in turn resulting in reduced electron transport per trapping. In fact, a low proportion of absorbed energy is conveyed on the electron transport chain ( Sarkar and Ray 2016 ). Limitation of electron transport beyond PSII will result in QA over-reduction. High light restricts electron transport towards the cytb6f complex and causes QA over-reduction ( Foyer et al. 2012 ). In W- and RB-grown plants, electron transport flux per reaction centre and the probability that a trapped exciton would move an electron in the electron transport chain beyond QA − (ψ o ) increased following HL stress ( Figs 6 and 7 ). This showed that W- and RB-grown plants were more capable of transporting electrons from absorbed photons into the electron transport chain and beyond QA −1 . This confirmed that W- and RB-grown plants were positively regulating the energy level in reaction centres ( Strasser et al. 2004 ) following exposure to HL.

Plants’ adaptation to the prevailing light environment is reflected by a change in anatomy and morphology of leaves, which is known as developmental acclimation ( Vialet-Chabrand et al. 2017 ). Rapid and short-term exposure to HL intensities (as happened in the current study) results in the dynamic acclimation of plants to the light environment ( Lawson et al. 2012 ). Dynamic responses to HL intensities involve metabolic modifications, the down-regulation of the electron transport chain, and changes in stomatal responses and the activation rate of the a ( Tinoco-Ojanguren and Pearcy 1995 ; Lawson et al. 2012 ). In the current study, the focus was on dynamic responses to HL intensities. Therefore, metabolic modifications and changes in performance of the electron transport system were studied in details. Down-regulation of the electron transport system was an obvious response of the photosynthesis system to HL conditions. The antenna in association with PSII is a highly dynamic complex; it collects and transfers the light energy to the PSII reaction centre; however, depending on the physiological needs of the plant, it has the ability to decrease the amount of deliverable light energy to tune the excitation of the reaction centre ( Horton et al. 1996 ). To cope with HL stress, plants dissipate excess energy in the form of heat by a process known as NPQ of chlorophyll fluorescence. Using NPQ, the excitation energy of chlorophyll molecules in the antennae is not passed to the reaction centre and will be dissipated as heat ( Krause and Weis 1991 ). Consistent with this, in the current study, exposure to HL conditions resulted in an increase in NPQ [see Supporting Information—Fig. S1 ] .

Metabolic modifications due to HL were studied by analysing carbohydrate and pigment concentrations at the same time as analysing components of oxidative stress. Soluble carbohydrates and starch concentrations were dramatically decreased after exposure to HL conditions ( Fig. 9 ). Although light is the driving force of photosynthesis for the production of carbohydrates, our result showed that in plants grown under illumination of 250 μmol m −2 s −1 subsequent exposure to HL conditions (1500 μmol m −2 s −1 ) dramatically reduced both soluble and storage carbohydrates ( Fig. 9 ). Positive relationships were found between both soluble carbohydrates and starch with PI ABS ( Fig. 10 ). This indicates that the performance of the PSII operating system plays an important role in soluble carbohydrate and starch production in the rose plant. The greater decrease in soluble carbohydrates in R- and B-grown plants following HL stress is indicative of the higher sensitivity of their PSII operating system to HL stress.

Relationship between performance index on the absorption basis (PI ABS ) and concentration of carbohydrates (soluble carbohydrates and starch) in the leaves of rose plants grown under different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (C) and 1500 (HL) µmol m −2 s −1 PPFD.

In our study, H 2 O 2 accumulation was detected following HL stress ( Fig. 8 ). The production of ROS following exposure to various environmental stress conditions has previously been reported ( Steffens 2014 ; Pospíšil 2016 ). In photosynthetic electron transport systems, excess light energy beyond photosynthetic capacity induces the production of ROS ( Pospíšil 2016 ). Non-enzymatic and enzymatic scavenging systems are involved in the removal of ROS formed in the electron transport system during exposure to stress conditions ( Ahmad et al. 2010 ). During HL stress, the balance between the scavenging system and ROS formation can be disturbed, leading to oxidative damage to the PSII operating system and its components ( Aro et al. 1993 ). Moreover, in such circumstances, the excess energy absorbed by the PSII complex is not coupled with electron transport, which results in full reduction of the PQ pool and blockage of the electron ( Pospíšil 2016 ). To decrease the reduction of the PQ pool, an electron from Q A •− is transported to an O 2 molecule and generates a superoxide anion. A superoxide anion radical is also generated during the Mehler reaction at the acceptor side of photosystem I. This radical is converted by SOD to H 2 O 2 and subsequently to H 2 O by CAT and APX ( Caverzan et al. 2012 ). We showed that in contrast with a positive correlation between SOD activity and H 2 O 2 production ( Fig. 11 ), CAT and APX negatively regulate H 2 O 2 production. The accumulation of H 2 O 2 following HL stress could be attributed to an increase in SOD activity and decrease in CAT and APX activities ( Fig. 8 ). Photoinactivation of CAT by HL intensities has previously been reported. In accordance with our results, Feierabend and colleagues (1996) showed that CAT is photoinactivated when exposed to B or R lights.

Relationship between H 2 O 2 concentration and activity of antioxidant enzymes (CAT, APX and SOD) in the leaves of rose plants grown under different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (C) and 1500 (HL) µmol m −2 s −1 PPFD.

In our study, negative relationships were discovered between carbohydrates (soluble carbohydrates and starch) and H 2 O 2 concentration ( Fig. 12 ). In previous studies, it has been reported that sugar accumulation occurs when plants are grown under high illuminations. The relationship between sugars and ROS accumulation is not just a simple positive relationship. Both acceleration of certain ROS-production pathways and deceleration of other ROS-production pathways have been reported due to high levels of soluble carbohydrates ( Couée et al. 2006 ).

Relationship between H 2 O 2 concentration and concentration of carbohydrates (soluble carbohydrates and starch) in the leaves of rose plants grown under different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (C) and 1500 (HL) µmol m −2 s −1 PPFD.

We found a positive relationship between anthocyanin concentrations and PI ABS under our experimental set-up ( Fig. 13 ). Our data revealed that although plants grown under monochromatic R and B lights had higher anthocyanin concentrations which resulted in better performance of their PSII operating system, their anthocyanin concentrations were dramatically decreased following exposure to HL stress and as a result their PI ABS were also decreased accordingly. In contrast, anthocyanin concentrations in W- and RB-grown plants were not changed before or after HL stress. Therefore, anthocyanin protects the photosynthetic apparatus against HL stress. Apparently, the negative relationship between soluble carbohydrates and ROS accumulation is dependent on the type and duration of the stress condition. For instance, exposure to low temperatures under normal to high irradiances would result in photo-oxidative damage ( Harvaux and Kloppstech 2001 ) and accumulation of soluble carbohydrates. Under such conditions, sugar accumulation can help plants to cope with HL damage ( Ciereszko et al. 2001 ). Carbohydrate accumulation can induce the production of anthocyanin. Chalcone synthase as the key enzyme in anthocyanin biosynthesis can be activated by the signal from soluble carbohydrates ( Koch 1996 ; Deng et al. 2014 ). Therefore, HL stress can induce the accumulation of both anthocyanins and ROS ( Steyn et al. 2002 ; Hatier and Gould 2008 ). In our study, the level of soluble carbohydrates and anthocyanins decreased following exposure to HL to both monochromatic lights, while the levels of these reductions were lower in W- and RB-grown plants. As a consequence, there was lower damage to their PSII operating system ( Figs 10 and 13 ). Anthocyanins can act as light filters and protect the photosynthetic components against photoinhibition induced by HL stress ( Landi et al. 2015 ).

Relationship between performance index on the absorption basis (PI ABS ) and pigments (anthocyanin and carotenoid) in the leaves of rose plants grown under different light spectra [blue (B), red (R), white (W) and red and blue (RB)] under 250 (C) and 1500 (HL) µmol m −2 s −1 PPFD.

The management of a favourable lighting environment for rose production has attracted much attention in the last decade. Currently, many research teams all over the world are focusing on issues related to the best light intensity and spectra for rose plants. To prevent HL intensities shading screens are used for rose production. However, both shading and HL can negatively influence plant growth and photosynthesis. Using polyphasic chlorophyll a fluorescence transients (OJIP test), we showed that growing plants under monochromatic R and B lights resulted in higher sensitivity of their PSII operating system to HL compared to the PSII performance of RB- and W-grown plants. Superoxide dismutase activity increased while CAT and APX activity decreased after exposure to HL. This resulted in the accumulation of H 2 O 2 following HL exposure. Negative relationships were discovered between carbohydrates (soluble carbohydrates and starch) and H 2 O 2 concentration, while carbohydrate concentration positively influenced the performance index of the plants. Our study revealed the protective role of anthocyanin for the PSII operating system. The performance capacity of the photosynthetic systems in monochromatic R- and B-grown plants declined due to a dramatic reduction in anthocyanin concentration following HL exposure, whereas W- and RB-grown plants had similar anthocyanin levels before and after HL exposure. This suggests that anthocyanin protected their photosynthetic apparatus against HL stress.

We would like to thank Iran National Science Foundation (INSF) (grant number 96006991) and University of Tehran for their supports.

S.A. made substantial contributions to conception and design, also performed statistical analysis, drafted the manuscript and critically revised the final version. L.B. carried out the experiments, collected and critically analysed the scientific literatures and help in the writing of the manuscript. M.A. took part in designing and planning the experiments, preparation of material for the experiment and contributed to scientific discussion of the obtained results. M.S. helped in preparation of material for the experiment and took part in designing, planning and performing of experiments. T.L. contributed to conception and design of experiment, preparation of materials, scientific discussion and critical revision of the final manuscript. O.L. contributed to design of experiment and critical revision of the final manuscript.

None declared.

The following additional information is available in the online version of this article—

Table S1. Analysis of variance ( F -values) for assessed parameters for rose plants grown under different light spectrums and then exposed to high light intensity (1500 μmol m −2 s −1 ).

Figure S1. Non-photochemical quenching (NPQ) derived from chlorophyll fluorescence parameters in the leaves of rose plants grown at different light spectrums [blue (B), red (R), white (W) and red and blue (RB)] under 250 (black bars) and 1500 (grey bars) µmol m −2 s −1 photosynthetic photon flux density (PPFD). Bars represent means ± SD.

Figure S2. Chlorophyll a (A), chlorophyll b (B) and total chlorophyll (C) concentrations in the leaves of rose plants grown at different light spectrums [blue (B), red (R), white (W) and red and blue (RB)] under 250 (black bars) and 1500 (grey bars) µmol m −2 s −1 photosynthetic photon flux density (PPFD). Bars represent means ± SD.

We thank Z. Soltani, K. Pirasteh and S. Moemeni for their assistance in performing the experiments and measurements, Dr S. Kalhor for critical revision of the manuscript and Iran Grow Light Company for providing LEDs and projectors.

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Supplementary data

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The role of photosynthesis related pigments in light harvesting, photoprotection and enhancement of photosynthetic yield in planta

Published: 22 January 2022
Volume 152 , pages 23–42, ( 2022 )

Cite this article

Andrew J. Simkin 1 na1 ,
Leepica Kapoor 2 na1 ,
C. George Priya Doss 2 ,
Tanja A. Hofmann 4 ,
Tracy Lawson 3 &
Siva Ramamoorthy 2

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Photosynthetic pigments are an integral and vital part of all photosynthetic machinery and are present in different types and abundances throughout the photosynthetic apparatus. Chlorophyll, carotenoids and phycobilins are the prime photosynthetic pigments which facilitate efficient light absorption in plants, algae, and cyanobacteria. The chlorophyll family plays a vital role in light harvesting by absorbing light at different wavelengths and allowing photosynthetic organisms to adapt to different environments, either in the long-term or during transient changes in light. Carotenoids play diverse roles in photosynthesis, including light capture and as crucial antioxidants to reduce photodamage and photoinhibition. In the marine habitat, phycobilins capture a wide spectrum of light and have allowed cyanobacteria and red algae to colonise deep waters where other frequencies of light are attenuated by the water column. In this review, we discuss the potential strategies that photosynthetic pigments provide, coupled with development of molecular biological techniques, to improve crop yields through enhanced light harvesting, increased photoprotection and improved photosynthetic efficiency.

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Molecular Mechanism of Photosynthesis Driven by Red-Shifted Chlorophylls

Far-red light photoadaptations in aquatic cyanobacteria.

Recent Advances in the Photosynthesis of Cyanobacteria and Eukaryotic Algae

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Acknowledgements

The authors take this opportunity to thank the management of VIT for providing facilities to carry out this research work.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. AJS is supported by the Growing Kent and Medway Programme, UK; Ref 107139.

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Andrew J. Simkin and Leepica Kapoor have contributed equally to this work.

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School of Biosciences, University of Kent, Canterbury, CT2 7NJ, United Kingdom

Andrew J. Simkin

School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India

Leepica Kapoor, C. George Priya Doss & Siva Ramamoorthy

School of Life Sciences, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom

Tracy Lawson

OSFC, Scrivener Drive, Pinewood, Ipswich, IP8 3SU, United Kingdom

Tanja A. Hofmann

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Simkin, A.J., Kapoor, L., Doss, C.G.P. et al. The role of photosynthesis related pigments in light harvesting, photoprotection and enhancement of photosynthetic yield in planta. Photosynth Res 152 , 23–42 (2022). https://doi.org/10.1007/s11120-021-00892-6

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ORIGINAL RESEARCH article

Photosynthetic physiology of blue, green, and red light: light intensity effects and underlying mechanisms.

$\r\nJun Liu*$

Horticultural Physiology Laboratory, Department of Horticulture, University of Georgia, Athens, GA, United States

Red and blue light are traditionally believed to have a higher quantum yield of CO 2 assimilation ( QY , moles of CO 2 assimilated per mole of photons) than green light, because green light is absorbed less efficiently. However, because of its lower absorptance, green light can penetrate deeper and excite chlorophyll deeper in leaves. We hypothesized that, at high photosynthetic photon flux density ( PPFD ), green light may achieve higher QY and net CO 2 assimilation rate ( A n ) than red or blue light, because of its more uniform absorption throughtout leaves. To test the interactive effects of PPFD and light spectrum on photosynthesis, we measured leaf A n of “Green Tower” lettuce ( Lactuca sativa ) under red, blue, and green light, and combinations of those at PPFD s from 30 to 1,300 μmol⋅m –2 ⋅s –1 . The electron transport rates ( J ) and the maximum Rubisco carboxylation rate ( V c,max ) at low (200 μmol⋅m –2 ⋅s –1 ) and high PPFD (1,000 μmol⋅m –2 ⋅s –1 ) were estimated from photosynthetic CO 2 response curves. Both QY m,inc (maximum QY on incident PPFD basis) and J at low PPFD were higher under red light than under blue and green light. Factoring in light absorption, QY m,abs (the maximum QY on absorbed PPFD basis) under green and red light were both higher than under blue light, indicating that the low QY m,inc under green light was due to lower absorptance, while absorbed blue photons were used inherently least efficiently. At high PPFD , the QY inc [gross CO 2 assimilation ( A g )/incident PPFD ] and J under red and green light were similar, and higher than under blue light, confirming our hypothesis. V c,max may not limit photosynthesis at a PPFD of 200 μmol m –2 s –1 and was largely unaffected by light spectrum at 1,000 μmol⋅m –2 ⋅s –1 . A g and J under different spectra were positively correlated, suggesting that the interactive effect between light spectrum and PPFD on photosynthesis was due to effects on J . No interaction between the three colors of light was detected. In summary, at low PPFD , green light had the lowest photosynthetic efficiency because of its low absorptance. Contrary, at high PPFD , QY inc under green light was among the highest, likely resulting from more uniform distribution of green light in leaves.

Introduction

The photosynthetic activity of light is wavelength dependent. Based on McCree’s work ( McCree, 1971 , 1972 ), photosynthetically active radiation is typically defined as light with a wavelength range from 400 to 700 nm. Light with a wavelength shorter than 400 nm or longer than 700 nm was considered as unimportant for photosynthesis, due to its low quantum yield of CO 2 assimilation, when applied as a single waveband ( Figure 1 ). Within the 400–700 nm range, McCree (1971) showed that light in the red region (600–700 nm) resulted in the highest quantum yield of CO 2 assimilation of plants. Light in the green region (500–600 nm) generally resulted in a slightly higher quantum yield than light in the blue region (400–500 nm) ( Figure 1 ; McCree, 1971 ). The low absorptance of green light is partly responsible for its low quantum yield of CO 2 assimilation. Within the visible spectrum, green leaves have the highest absorptance in the blue region, followed by red. Green light is least absorbed by green leaves, which gives leaves their green appearance ( McCree, 1971 ; Zhen et al., 2019 ).

Figure 1. The normalized action spectrum of the maximum quantum yield of CO 2 assimilation for narrow wavebands of light from ultra-violet to far-red wavelengths ( McCree, 1971 ). Redrawn using data from Sager et al. (1988).

Since red and blue light are absorbed more strongly by photosynthetic pigments than green light, they are predominantly absorbed by the top few cell layers, while green light can penetrate deeper into leaf tissues ( Nishio, 2000 ; Vogelmann and Evans, 2002 ; Terashima et al., 2009 ; Brodersen and Vogelmann, 2010 ), thus giving it the potential to excite photosystems in deeper cell layers. Leaf photosynthesis may benefit from the more uniform light distribution throughout a leaf under green light. Absorption of photons by chloroplasts near the adaxial surface may induce heat dissipation of excess excitation energy in those chloroplasts, while chloroplasts deeper into the leaf receive little excitation energy ( Sun et al., 1998 ; Nishio, 2000 ). Blue and red photons, therefore, may be used less efficiently and are more likely to be dissipated as heat than green photons.

The misconception that red and blue light are used more efficiently by plants than green light still occasionally appears ( Singh et al., 2015 ), often citing McCree’s action spectrum or the poor absorption of green light by chlorophyll extracts. The limitations of McCree’s action spectrum were explained in his original paper: the quantum yield was measured under low photosynthetic photon flux density ( PPFD ), using narrow waveband light, and expressed on an incident light basis ( McCree, 1971 ), but these limitations are sometimes ignored. The importance of green light for photosynthesis has been well established in more recent studies ( Sun et al., 1998 ; Nishio, 2000 ; Terashima et al., 2009 ; Hogewoning et al., 2012 ; Smith et al., 2017 ).

From those studies, one trend has emerged that has not received much attention: there is an interactive effect of light quality and intensity on photosynthesis ( Sun et al., 1998 ; Evans and Vogelmann, 2003 ; Terashima et al., 2009 ). At low PPFD , green light has the lowest QY inc (quantum yield of CO 2 assimilation on incident light basis) because of its low absorptance; at high PPFD , on the other hand, red and blue light have a lower QY inc than green light, because of their high absorptance by photosynthetic pigments, which shifts much of the light absorption closer to the upper leaf surface. This reduces both the quantum yield of CO 2 assimilation in cells in the upper part of a leaf and light availability in the bottom part of a leaf.

The interactive effect between light quality and intensity was illustrated in an elegant study that quantified the differential quantum yield, or the increase in leaf CO 2 assimilation per unit of additional light ( Terashima et al., 2009 ). The differential quantum yield was measured by adding red or green light to a background illumination of white light of different intensities. At low background white light levels, the differential quantum yield of red light was higher than that of green light, due to the low absorptance of green light. But as the background light level increased, the differential quantum yield of green light decreased more slowly than that of red light, and was eventually higher than that of red light ( Terashima et al., 2009 ). The red light was absorbed efficiently by the chloroplasts in the upper part of leaves. With a high background level of white light, those chloroplasts already received a large amount of excitation energy from white light and up-regulated non-photochemical quenching (NPQ) to dissipate excess excitation energy as heat, causing the additional red light to be used inefficiently. Green light, on the other hand, was able to reach the chloroplasts deeper in the mesophyll and excited those chloroplasts that received relatively little excitation energy from white light. Therefore, with high background white light intensity, additional green light increased leaf photosynthesis more efficiently than red light ( Terashima et al., 2009 ).

In this paper, we present a comprehensive study to explore potential interactive effect of light intensity and light quality on C 3 photosynthesis and underlying processes. We quantified the photosynthetic response of plants to blue, green, and red light over a wide PPFD range to better describe how light intensity and waveband interact. In addition, we examined potential interactions among blue, green, and red light, using light with different ratios and intensities of the three narrow waveband lights. To get a better understanding of the biochemical reasons for the effects of light spectrum and intensity on CO 2 assimilation, we constructed assimilation – internal leaf CO 2 ( C i ) response curves ( A/C i curves) under blue, green, and red light, as well as combinations of the three narrow waveband lights at both high and low PPFD . We hypothesized that effects of different light spectra would be reflected in the electron transport rate ( J ) required to regenerate consumed ribulose 1,5-bisphosphate (RuBP), rather than the maximum carboxylation rate of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) ( V c,max ).

Materials and Methods

Plant material.

Lettuce “Green Towers” plants were grown from seed in 1.7 L round pots filled with soilless substrate (Fafard 4P Mix, Sun Gro Horticulture, Agawam, MA, United States). The plants were grown in a growth chamber (E15, Conviron, Winnipeg, Manitoba, Canada) at 23.2 ± 0.8°C (mean ± SD), under white fluorescent light with a 14-hr photoperiod, vapor pressure deficit (VPD) of 1.20 ± 0.43 kPa and a PPFD of 200–230 μmol⋅m –2 ⋅s –1 at the floor level, and ambient CO 2 concentration. Plants were sub-irrigated when necessary with a nutrient solution containing 100 mg⋅L –1 N, made with a complete, water-soluble fertilizer (Peter’s Excel 15-5-15 Cal-Mag fertilizer, Everris, Marysville, OH, United States).

Leaf Absorptance, Transmittance, and Reflectance

Leaf absorptance was determined using a method similar to that of Zhen et al. (2019) . Three plants were randomly selected. A newly expanded leaf from each plant was illuminated with a broad-spectrum halogen bulb (70W; Sylvania, Wilmington, MA, United States) for leaf transmittance measurement. Transmittance was measured with a spectroradiometer (SS-110, Apogee, Logan, UT, United States). The halogen light spectrum was taken as reference measurement with the spectroradiometer placed directly under the halogen bulb in a dark room. Then, a lettuce leaf was placed between the halogen bulb and spectroradiometer, with its adaxial side facing the halogen bulb and transmitted light was measured. Leaf transmittance was then calculated on 1 nm resolution. Light reflectance of the leaves was measured using a spectrometer with a leaf clip (UniSpec, PP systems, Amesbury, MA, United States). Light absorptance was calculated as 1− r e f l e c t a n c e − t r a n s m i t t a n c e . We verified that this method results in similar absorptance spectra as the use of an integrating sphere. Absorptance of each of the nine light spectra used in this study were calculated from the overall leaf absorptance spectrum and the spectra of the red, green, and blue LEDs.

Leaf Photosynthesis Measurements

All gas exchange measurements were made with a leaf gas exchange system (CIRAS-3, PP Systems). Light was provided by the LEDs built into the chlorophyll fluorescence module (CFM-3, PP Systems). This module has dimmable LED arrays of different colors, with peaks at 653 nm [red, full width at half maximum (FWHM) of 17 nm], 523 nm (green, FWHM of 36 nm), and 446 nm (blue, FWHM of 16 nm). Nine different combinations of red, green, and blue light were used in this study ( Table 1 ). Throughout the measurements, the environmental conditions inside the cuvette were controlled by the leaf gas exchange system. Leaf temperature was 23.0 ± 0.1°C, CO 2 concentration was 400.5 ± 4.1 μmol⋅mol –1 , and the VPD of air in the leaf cuvette was 1.8 ± 0.3 kPa (mean ± SD).

Table 1. List of light spectrum abbreviations and their spectral composition.

Photosynthesis – Light Response Curves

To explore photosynthetic efficiency of light with different spectra, we constructed light response curves for lettuce plants using each light spectrum. Lettuce plants were exposed to 10 PPFD levels ranging from 30 to 1,300 μmol⋅m –2 ⋅s –1 (30, 60, 90, 120, 200, 350, 500, 700, 1,000, and 1,300 μmol⋅m –2 ⋅s –1 ) in ascending orders for light response curves. Photosynthetic measurements were taken on 40–66 days old lettuce plants. Lettuce plants were taken out of the growth chamber and dark-adapted for 30 min. Starting from the lowest PPFD , one newly expanded leaf was exposed to all nine spectra. Net CO 2 assimilation rate ( A n ) of the leaf was measured using the leaf gas exchange system. Under each light spectrum, three A n readings were recorded at 10 s intervals after readings were stable (about 4–20 min depending on PPFD after changing PPFD and spectrum). The three A n readings were averaged for analysis. After A n measurements under all nine light spectra were taken, the leaf was exposed to the next PPFD level and A n measurements were taken with the light spectra in the same order, until measurements were completed at all PPFD levels. Throughout the light response curves, C i decreased with increasing PPFD , from 396 ± 10 μmol⋅mol –1 at a PPFD of 30 μmol⋅m –2 ⋅s –1 to 242 ± 44 μmol⋅mol –1 at a PPFD of 1,300 μmol⋅m –2 ⋅s –1 . To account for the potential effect of plants and the order of the spectra on assimilation rates, the order of the different spectra was re-randomized for each light response curve, using a Latin square design with plant and spectrum as the blocking factors. Data were collected on nine different plants.

Regression curves (exponential rise to maximum) were fitted to the data for each light spectrum and replication (plant):

where R d is the dark respiration rate, QY m,inc is the maximum quantum yield of CO 2 assimilation (initial slope of light response curve, mol of CO 2 fixed per mol of incident photons) and A g,max is the light-saturated gross assimilation rate. The A n,max is the light-saturated net assimilation rate and was calculated as A n , m a x = A g , m a x - R d . The maximum quantum yield of CO 2 assimilation was also calculated on absorbed light basis as Q ⁢ Y m , a ⁢ b ⁢ s = Q ⁢ Y m , i ⁢ n ⁢ c l ⁢ i ⁢ g ⁢ h ⁢ t ⁢ a ⁢ b ⁢ s ⁢ o ⁢ r ⁢ p ⁢ t ⁢ a ⁢ n ⁢ c ⁢ e .

The instantaneous quantum yield of CO 2 assimilation based on incident PPFD ( QY inc ) was calculated as A g P ⁢ P ⁢ F ⁢ D for each PPFD at which A n was measured, where the gross CO 2 assimilation rate ( A g ) was calculated as A g = A n + R d . To account for differences in absorptance among the different light spectra, the quantum yield of CO 2 assimilation was also calculated based on absorbed light base, as Q ⁢ Y a ⁢ b ⁢ s = A g P ⁢ P ⁢ F ⁢ D × l ⁢ i ⁢ g ⁢ h ⁢ t ⁢ a ⁢ b ⁢ s ⁢ o ⁢ r ⁢ p ⁢ t ⁢ a ⁢ n ⁢ c ⁢ e , where light absorptance is the absorptance of lettuce leaves for each specific light spectrum. The differential QY , the increase in assimilation rate per unit of additional incident PPFD , was calculated as the derivative of Eq. 1:

Photosynthesis – Internal CO 2 Response ( A/C i ) Curves

To explore the underlying physiological mechanisms of assimilation responses to different light spectra, we constructed A/C i curves. Typically, A/C i curves are collected under saturating PPFD . We collected A/C i curves at two PPFD s (200 and 1,000 μmol⋅m –2 ⋅s –1 ) to explore interactive effects of light spectrum and PPFD on the assimilation rate. At a PPFD of 200 μmol⋅m –2 ⋅s –1 , red light has the highest A n and green light the lowest A n , while at PPFD of 1,000 μmol⋅m –2 ⋅s –1 , red and green light resulted in the highest A n and blue light in the lowest A n .

We used the rapid A/C i response (RACiR) technique that greatly accelerates the process of constructing A/C i curves ( Stinziano et al., 2017 ). We used a Latin square design, similar to the light response curves. A/C i curves were measured under the same nine spectra used for the light response curves. Nine lettuce plants were used as replicates. For each A/C i curve, CO 2 concentration in the leaf cuvette started from 0 μmol⋅mol –1 , steadily ramping to 1,200 μmol⋅mol –1 over 6 min. A reference measurement was also taken at the beginning of each replication with an empty cuvette to correct for the reaction time of the leaf gas exchange system. Post-ramp data processing was used to calculate the real A and C i with the spreadsheet provided by PP systems, which yielded the actual A/C i curves with C i range of about 100–950 μmol mol –1 . Throughout the data collection, leaf temperature was 24.4 ± 1.3°C and VPD in the cuvette was 1.4 ± 0.2 kPa.

Curve fitting for A/C i curves was done by minimizing the residual sum of squares, following the protocol developed by Sharkey et al. (2007) . Among our nine replicates, four plants did not show clear Rubisco limitations at low PPFD and for those plants Rubisco limitation ( V c,ma x ) was not included in the model ( Sharkey et al., 2007 ). We therefore report V c,max values for high PPFD only. The J was determined for all light spectra at both PPFD s. We therefore report V c,max was determined for all light spectra only at high PPFD . The quantum yield of electron transport [ QY(J) ] was calculated on both incident and absorbed PPFD basis as Q ⁢ Y ⁢ ( J ) i ⁢ n ⁢ c = J P ⁢ P ⁢ F ⁢ D and Q ⁢ Y ⁢ ( J ) a ⁢ b ⁢ s = Q ⁢ Y ⁢ ( J ) i ⁢ n ⁢ c l ⁢ i ⁢ g ⁢ h ⁢ t ⁢ a ⁢ b ⁢ s ⁢ o ⁢ r ⁢ p ⁢ t ⁢ a ⁢ n ⁢ c ⁢ e , respectively. We did not estimate triose phosphate utilization, because the A/C i curves often did not show a clear plateau.

Data Analysis

The QY m,inc , QY m,abs , and A g,max were analyzed with ANOVA to determine the effects of light spectrum using SAS (SAS University Edition; SAS Institute, Cary, NC, United States). A n , QY inc , and QY abs at each PPFD level and V c,max and J estimated from A/C i curves were similarly analyzed with ANOVA using SAS. A n at different PPFD levels were analyzed with regression analysis to detect interactive effect of blue, green, and red light on leaf assimilation rates using the fractions of red, blue, and green light as explanatory variables (JMP Pro 15, SAS Institute).

Leaf Absorptance

A representative spectrum of light absorptance, reflectance and transmittance of a newly fully expanded lettuce leaf is shown in Figure 2 . In the blue region, 400–500 nm, the absorptance by “Green Towers” lettuce leaves was high and fairly constant, averaging 91.6%. The leaf absorptance decreased as the wavelength increased from 500 to 551 nm where the absorptance minimum was 69.8%. Absorptance increased again at longer wavelengths, with a second peak at 666 nm (92.6%). Above 675 nm, the absorptance decreased steadily to <5% at 747 nm ( Figure 2 ). The absorptance spectrum of our lettuce leaves is similar to what McCree (1971) obtained for growth chamber-grown lettuce, with the exception of slightly higher absorptance in the green part of the spectrum in our lettuce plants. Using this spectrum, the absorptance of the blue, green, and red LED lights were calculated to be 93.2 ± 1.0%, 81.1 ± 1.9% and 91.6 ± 1.1%, respectively. Absorptance of all nine spectra was calculated based on their ratios of red, green, and blue light ( Table 2 ).

Figure 2. Light absorptance, reflectance, and transmittance spectrum of a newly fully expanded “Green Towers” lettuce leaf.

Table 2. Light absorptance and transmittance of new fully expanded “Green towers” lettuce leaves under nine light spectra.

Light Quality and Intensity Effects on Photosynthetic Parameters

Light response curves of lettuce under all nine spectra are shown in Figure 3 , with regression coefficients in Supplementary Table 1 . It is worth noting that a few plants showed photoinhibition under 100B (decrease in A n with PPFD > 1,000 μmol⋅m –2 ⋅s –1 ). Those data were excluded in curve fitting for light response curves to better estimate asymptotes. Photoinhibition was not observed under other spectra.

Figure 3. Net assimilation ( A n ) – light response curves of “Green Towers” lettuce under nine light spectra. Error bars represent the standard deviation ( n = 9). Inserts show A n against PPFD of 30-90 μmol⋅m –2 ⋅s –1 s to better show the initial slopes of curves. The composition of the nine light spectra is shown in Table 1 . The light spectra in the graphs are (A) 100B, 100G, and 100R; (B) 100B, 80B20G, 20B80G, and 100G; (C) 100G, 80G20R, 20G80R, and 100R; and (D) 20B80R, 16B20G64R, and 100G.

The QY m,inc of lettuce plants was 22 and 27% higher under red light (74.3 mmol⋅mol –1 ) than under either 100G (60.8 mmol⋅mol –1 ) or 100B (58.4 mmol⋅mol –1 ), respectively ( Figure 4A and Supplementary Table 1 ). Spectra with a high fraction of red light (64% or more) resulted in a high QY m,inc ( Figure 4A ), while 80G20R resulted in an intermediate QY m,inc ( Figure 4A ). To determine whether differences in QY m,inc were due to differences in absorptance or in the ability of plants to use the absorbed photons for CO 2 assimilation, we also calculated QY m,abs . On an absorbed light basis, 100B light still resulted in the lowest QY m,abs (62.7 mmol⋅mol –1 ) and red light resulted in the highest QY m,abs (81.1 mmol⋅mol –1 ) among narrow waveband lights ( Figure 4B ). Green light resulted in a QY m,abs (74.9 mmol⋅mol –1 ) similar to that under red light, but significantly higher than that of blue light ( Figure 4B ). We did not find any interactions (synergism or antagonism) between lights of different colors, with all physiological responses under mixed spectra being similar to the weighted average of responses under single colors. Thus, for the rest of the results we focus on the three narrow waveband spectra.

Figure 4. Maximum quantum yield of CO 2 assimilation of “Green Towers” lettuce based on incident ( QY m,inc ) (A) and absorbed light ( QY m,abs ) (B) under nine different light spectra. Values are calculated as the initial slope of the light response curves of corresponding light spectra (see Figure 3 ). Bars with the same letter are not statistically different ( p ≤ 0.05). Error bars represent the standard deviation ( n = 9). The composition of the nine light spectra is shown in Table 1 .

Among the three narrow waveband lights, 100G resulted in the highest A g,max (20.0 μmol⋅m –2 ⋅s –1 ), followed by red (18.9 μmol⋅m –2 ⋅s –1 ), and blue light (17.0 μmol⋅m –2 ⋅s –1 ) ( Figure 5 and Supplementary Table 1 ). As with QY m ,inc and QY m,abs , combining two or three colors of light resulted in an A g,max similar to the weighted averages of individual light colors.

Figure 5. Maximum gross assimilation rate ( A g,max ) of “Green Towers” lettuce under different light spectra, calculated from the light response curves. Bars with the same letter are not statistically different ( p ≤ 0.05). Error bars represent standard deviation ( n = 9). The composition of the nine light spectra is shown in Table 1 .

QY inc initially increased with increasing PPFD and peaked at 90–200 μmol⋅m –2 ⋅s –1 , then decreased at higher PPFDs ( Figure 6A ). The QY inc under 100R was higher than under either green or blue light at low PPFD (≤300 μmol⋅m –2 ⋅s –1 ). Although 100G resulted in lower QY inc than 100B at low PPFD (≤300 μmol⋅m –2 ⋅s –1 ), the decrease in QY inc under 100G with increasing PPFD was slower than that with 100B or 100R. Above 500 μmol m –2 s –1 , the QY inc with 100G was comparable to the QY inc with 100R, and higher than with 100B ( Figure 6A ). The QY abs with 100R was higher than that with either 100G or 100B at PPFDs from 60 to 120 μmol⋅m –2 ⋅s –1 ( p < 0.05). The QY abs with 100G was similar to 100B at low PPFD , but decreased slower than that with either 100R or 100B as PPFD increased. At PPFD ≥ 500 μmol⋅m –2 ⋅s –1 , QY abs was lowest under 100B among the three monochromatic lights ( p < 0.05) ( Figure 6B ).

Figure 6. The quantum yield of CO 2 assimilation of “Green Towers” lettuce as a function of incident ( QY inc ) (A) and absorbed PPFD ( QY abs ) (B) under blue, green, and red LED light. Error bars represent the standard deviation ( n = 9).

The differential QY , which quantifies the increase in CO 2 assimilation per unit of additional PPFD , decreased with increasing PPFD . The differential QY with 100R was higher than those with 100B and 100G at low PPFD . At a PPFD of 30 μmol⋅m –2 ⋅s –1 , the differential QY was 70.5 mmol⋅mol –1 for 100R, 59.4 mmol⋅mol –1 for 100G, and 55.8 mmol⋅mol –1 for 100B ( Figure 7 ). However, the differential QY with 100R decreased rapidly with increasing PPFD and was lower than the differential QY with 100G at high PPFD ( Figure 7 ). At high PPFD , the differential QY with 100G was highest among three monochromatic light ( Figure 7 ). For instance, at a PPFD of 1,300 μmol⋅m –2 ⋅s –1 , the differential QY with 100G was 1.09 mmol⋅mol –1 , while those with 100B and 100R were 0.64 mmol⋅mol –1 and 0.46 mmol⋅mol –1 , respectively ( Figure 7 ).

Figure 7. The differential quantum yield of CO 2 assimilation ( differential QY ) of “Green Towers” lettuce under blue, green, and red LED light as a function of the PPFD . The differential QY is the increase in net assimilation per unit additional PPFD and was calculated as the first derivate of the light response curves ( Figure 3 ). The insert shows the differential quantum yield plotted at PPFDs of 1,000–1,300 μmol m –2 s –1 s to better show differences at high PPFD (note the different y -axis scale).

Effect of Light Spectrum and Intensity on J and V c,max

J of lettuce leaves at low PPFD was lowest under 100G (47.4 μmol⋅m –2 ⋅s –1 ), followed by 100B (56.1 μmol⋅m –2 ⋅s –1 ), and highest under 100R (64.1 μmol⋅m –2 ⋅s –1 ) ( Figure 8A ). At high PPFD , on the other hand, J of leaves exposed to 100G (115.3 μmol⋅m –2 ⋅s –1 ) and 100R (112.1 μmol⋅m –2 ⋅s –1 ) were among the highest, while J of leaves under 100B was the lowest (97.0 μmol⋅m –2 ⋅s –1 ) ( Figure 8A ). At high PPFD , V c,max of leaves under blue light (59.3 μmol⋅m –2 ⋅s –1 ) was lower than V c,max of leaves under 16B20G64R light (72.1 μmol⋅m –2 ⋅s –1 ), but none of the other treatments differed significantly ( Figure 8 ). When PPFD increased from 200 to 1,000 μmol⋅m –2 ⋅s –1 , J under green light increased by 143%, while J under blue and red light increased by 73% and 75%, respectively ( Figure 8A ). J and V c,max at high PPFD were strongly correlated ( R 2 = 0.82) ( Supplementary Figure 3 ).

Figure 8. Electron transport rate ( J ) at PPFD s of 200 (left bars) and 1,000 μmol m –2 s –1 (right bars) (A) and maximum Rubisco carboxylation rate ( V c,max ) at a PPFD of 1,000 μmol m –2 s –1 (B) of “Green Towers” lettuce, as estimated from A/C i curves under different light spectra. Bars with the same letter are not statistically different ( p ≤ 0.05). Error bars represent the standard deviation ( n = 9). The light composition of the nine light spectra is shown in Table 1 .

Interactive Effect of Light Spectrum and PPFD on Photosynthesis

There was an interactive effect of light spectrum and PPFD on photosynthetic properties of lettuce. Under low light conditions (≤200 μmol⋅m –2 ⋅s –1 ), the QY inc of lettuce leaves under green light was lowest among blue, green, and red light ( Figure 6A ), due to its lower absorptance by lettuce leaves. After accounting for absorptance, green photons were used at similar efficiency as blue photons, while red photons were used most efficiently ( Figure 6B ). The QY m,abs under green and red light were higher than under blue light ( Figure 4B ). At high PPFD , green and red light had similar quantum yield, higher than that of blue light, both on an absorbed and incident light basis ( Figure 6A ). Multiple factors contributed to the interactive effect of light spectrum and PPFD on quantum yield and photosynthesis.

Light Absorptance and Non-Photosynthetic Pigments Determine Assimilation at Low PPFD

QY m,inc with blue and green light was lower than with red light ( Figure 4A ), consistent with McCree’s action spectrum ( McCree, 1971 ). But when taking leaf absorptance into account, QY m,abs was similar under green and red light and lower under blue light ( Figure 4B ). Similarly, at low PPFD (≤200 μmol⋅m –2 ⋅s –1 ), QY inc of lettuce leaves was highest under red, intermediate under blue, and lowest under green light. When accounting for leaf absorptance, QY abs under red light remained highest and QY abs under both green and blue light were similar at low PPFD ( Figure 6A ). Consistent with our data, previous studies also documented that, once absorbed, green light can drive photosynthesis efficiently at low PPFD ( Balegh and Biddulph, 1970 ; McCree, 1971 ; Evans, 1987 ; Sun et al., 1998 ; Nishio, 2000 ; Terashima et al., 2009 ; Hogewoning et al., 2012 ; Vogelmann and Gorton, 2014 ). For example, the QY m,abs of spinach ( Spinacia oleracea ) and cabbage ( Brassica oleracea L. ) was highest under red light, followed by that under green light and lowest with blue light. But on incident light basis, QY m,inc of under green light was lower than under red or blue light ( Sun et al., 1998 ).

Both our data ( Figure 4B ) and those of Sun et al. (1998) show that QY m,abs with blue light is lower than that with red and green light, indicating that blue light is used intrinsically less efficiently by lettuce. Blue light, and, to a lesser extent, green light is absorbed not just by chlorophyll, but also by flavonoids and carotenoids ( Sun et al., 1998 ). Those pigments can divert energy away from photochemistry and thus reduce the QY abs under blue light. Flavonoids (e.g., anthocyanins) are primarily located in the vacuole and cannot transfer absorbed light energy to photosynthetic pigments ( Sun et al., 1998 ). Likewise, free carotenoids do not contribute to photochemistry ( Hogewoning et al., 2012 ). Carotenoids in light-harvesting antennae and reaction centers channel light energy to photochemistry, but with lower transfer efficiency than chlorophylls ( Croce et al., 2001 ; de Weerd et al., 2003a , b ; Wientjes et al., 2011 ; Hogewoning et al., 2012 ). Therefore, absorption of blue light by flavonoids and carotenoids reduces the quantum yield of CO 2 assimilation. Thus, even with the high absorptance of blue light by green leaves, QY m,abs of leaves under blue light was the lowest among the three monochromatic lights ( Figure 4B ). It is likely that the lower QY abs under green light than that under red light was also due to absorption of green light by carotenoids and flavonoids ( Hogewoning et al., 2012 ). At high PPFD , absorption of blue light by flavonoids and carotenoids still occurs, but this is less of a limiting factor for photosynthesis, since light availability is not limiting under high PPFD .

Light Dependence of Respiration and Rubisco Activity May Reduce the Quantum Yield at Low PPFD

At PPFD s below 200 μmol⋅m –2 ⋅s –1 , the QY inc and QY abs of lettuce showed an unexpected pattern in response to PPFD ( Figure 6 ). Unlike the quantum yield of PSII, which decreases exponentially with increasing PPFD ( Weaver and van Iersel, 2019 ), QY inc and QY abs increased initially with increasing PPFD ( Figure 6 ). A similar pattern was previously observed by Craver et al. (2020) in petunia ( Petunia × hybrida ) seedlings. This pattern could result from light-dependent regulation of respiration ( Croce et al., 2001 ), alternative electron sinks such as nitrate reduction ( Skillman, 2008 ; Nunes-Nesi et al., 2010 ), or Rubisco activity ( Campbell and Ogren, 1992 ; Zhang and Portis, 1999 ). In our calculations, we assumed that the leaf respiration in the light was the same as R d . However, leaf respiration in the light is lower than in the dark, in a PPFD -dependent manner ( Brooks and Farquhar, 1985 ; Atkin et al., 1997 ), which can lead to overestimation of A g with increasing PPFD . When we accounted for this down-regulation of respiration, using the model by Müller et al. (2005) to correct A g , QY inc , and QY abs , we found that depression of respiration by light did not explain the initial increase in QY inc and QY abs we observed ( Supplementary Figure 4 ). Alternative electron sinks in the chloroplasts that are upregulated in response to light can explain the low QY inc , and QY abs at low PPFD , because they compete with the Calvin cycle for reducing power (ferredoxin/NADPH). Such processes include photorespiration ( Krall and Edwards, 1992 ), nitrate assimilation ( Nunes-Nesi et al., 2010 ), sulfate assimilation ( Takahashi et al., 2011 ) and the Mehler reaction ( Badger et al., 2000 ) and their effect on QY inc , and QY abs would be especially notable under low PPFD ( Supplementary Figure 5 ).

Upregulation of Rubisco activity by Rubisco activase in the light may also have contributed to the increase in QY inc and QY abs at low PPFD ( Campbell and Ogren, 1992 ; Zhang and Portis, 1999 ). In the dark, 2-carboxy-D-arabinitol-1-phosphate (CA1P) or RuBP binds strongly to the active sites of Rubisco, preventing carboxylation activity. In the light, Rubisco activase releases the inhibitory CA1P or RuBP from the catalytic site of Rubisco, in a light-dependent manner ( Campbell and Ogren, 1992 ; Zhang and Portis, 1999 ; Parry et al., 2008 ). At PPFD < 120 μmol⋅m –2 ⋅s –1 , low Rubisco activity may have limited photosynthesis.

Light Distribution Within Leaves Affects QY at High PPFD

Except for the initial increase at low PPFD , both QY inc and QY abs decreased with increasing PPFD . QY inc decreased slower under green than under red or blue light ( Figure 6A ). At a PPFD ≥ 500 μmol⋅m –2 ⋅s –1 , QY inc under green light was higher than that under blue light ( Figure 6A ). Accordingly, A n under blue light was lower than under green and red light at PPFD s above 500 μmol⋅m –2 ⋅s –1 ( Figure 3A ). The lower QY inc under blue light than under green and red light at high PPFD can be explained by disparities in the light distribution within leaves.

Blue and red light were strongly absorbed by lettuce leaves (93.2 and 91.6%, respectively), while green light was absorbed less (81.1%) ( Table 2 ). Similar low green absorptance was found in sunflower ( Helianthus annuus L.), snapdragon ( Antirrhínum majus L.) ( Brodersen and Vogelmann, 2010 ), and spinach ( Vogelmann and Han, 2000 ). In leaves of those species, absorption of red and blue light peaked in the upper 20% of leaves, and declined sharply further into the leaf. Absorption of red light decreased slower with increasing depth than that of blue light ( Vogelmann and Han, 2000 ; Brodersen and Vogelmann, 2010 ). Green light absorption peaked deeper into leaves, and was more evenly distributed throughout leaves, because of low absorption of green light by chlorophyll ( Vogelmann and Han, 2000 ; Brodersen and Vogelmann, 2010 ). The more even distribution of green light within leaves, as compared to red and blue light, can explain the interactive effects between PPFD and light spectrum on leaf photosynthesis. It was estimated that less than 10% of blue light traveled through the palisade mesophyll and reached the spongy mesophyll in spinach, while about 35% of green light and 25% of red light did so ( Vogelmann and Evans, 2002 ). It was also estimated that chlorophyll in the lowermost chloroplasts of spinach leaves absorbed about 10% of green and <2% of blue light, compared to chlorophyll in the uppermost chloroplasts ( Vogelmann and Evans, 2002 ; Terashima et al., 2009 ).

The more uniform green light distribution within leaves may be a key contributor to higher leaf level QY inc under high PPFD because less heat dissipation of excess light energy is needed ( Nishio, 2000 ; Terashima et al., 2009 ). Reaction centers near the adaxial leaf surface receive more excitation energy under blue, and to a lesser extent under red light, than under green light, because of the differences in absorptance. Consequently, under high intensity blue light, NPQ is up-regulated in the chloroplasts near the adaxial leaf surface to dissipate some of the excitation energy ( Sun et al., 1998 ; Nishio, 2000 ), lowering the QY inc under blue light. Since less green light is absorbed near the adaxial surface, less heat dissipation is required. When incident light increased from 150 to 600 μmol⋅m –2 ⋅s –1 , the fraction of whole leaf CO 2 assimilation that occurred in the top half of spinach leaves remained the same under green light (58%), but decreased from 87 to 73% under blue light. This indicates more upregulation of heat dissipation in the top of the leaves under blue, than under green light ( Evans and Vogelmann, 2003 ). On the other hand, the bottom half of the leaves can still utilize the available light with relatively high QY inc , since the amount of light reaching the bottom half is relatively low, even under high PPFD ( Nishio, 2000 ). By channeling more light to the under-utilized bottom part of leaves, leaves could achieve higher QY inc even under high intensity green light. In our study, high QY inc under green light and low QY inc under blue light at high PPFD ( Figure 6 ) can be thus explained by the large disparities in the light environment in chloroplasts from the adaxial to the abaxial side of leaves due to differences in leaf absorptance. Similarly, differential QY of lettuce leaves was highest under green light and lower under blue and red light at high PPFD (>300 μmol⋅m –2 ⋅s –1 ) ( Figure 7 ), also potentially because of the more uniform distribution of green light and the uneven distribution of blue and red light in leaves.

Along the same line, A n of lettuce leaves was the lowest under blue light at PPFD > 500 μmol⋅m –2 ⋅s –1 ( Figure 3 ). Also, A n of lettuce leaves approached light saturation at lower PPFD s under blue and red light, than under green light ( Figure 3A ). Under blue, green, and red light, lettuce leaves reached 95% of A n,max at PPFD s of 954, 1,110 and 856 μmol⋅m –2 ⋅s –1 , respectively. This can be seen more clearly in the differential QY at high PPFD ( Figure 7 ). At a PPFD of 1,300 μmol⋅m –2 ⋅s –1 , green light had a differential QY of 1.09 mmol⋅mol –1 , while that of red and blue light was only 0.46 and 0.69 mmol⋅mol –1 , respectively ( Figure 7 ). Green light also resulted in a higher A g,max (22.9 μmol⋅m –2 ⋅s –1 ) than red and blue light (21.8 and 19.3 μmol⋅m –2 ⋅s –1 , respectively) ( Figure 5 ). As discussed before, the high A g,max under green light resulted from the more uniform light distribution under green light, allowing deeper cell layers to photosynthesize more. Previous research similarly found that at high PPFD (>500 μmol⋅m –2 ⋅s –1 ), A n of both spinach and cabbage were lower under blue light than under white, red and green light ( Sun et al., 1998 ). Overall, under high PPFD , the differences in light distribution throughout a leaf are important to quantum yield and assimilation rate, since it affects NPQ up-regulation ( Sun et al., 1998 ; Nishio, 2000 ). However, light distribution within a leaf is less important at low than at high PPFD , because upregulation of NPQ increases with increasing PPFD ( Zhen and van Iersel, 2017 ).

Light Spectrum Affects J , but Not V c,max

We examined the effect of light quality and intensity on J and V c,max ( Figure 8 ). For the light-dependent reactions, the interactive effect between light spectra and PPFD found for CO 2 assimilation and quantum yield was also observed for J ( Figure 8A ). At low PPFD (200 μmol⋅m –2 ⋅s –1 ), green light resulted in the lowest J and red light in the highest J among single waveband spectra. But at a PPFD of 1,000 μmol⋅m –2 ⋅s –1 , red and green light resulted in the highest J and blue light in the lowest J ( Figure 8A ), similar to the differences in A g .

There was no clear evidence of Rubisco limitations to photosynthesis at a PPFD of 200 μmol⋅m –2 ⋅s –1 , so the rate of the light-dependent reactions likely limited photosynthesis. This is corroborated by the strong correlation between A g and J at a PPFD of 200 μmol⋅m –2 ⋅s –1 . Although Rubisco limitations to photosynthesis were observed at a PPFD of 1,000 μmol⋅m –2 ⋅s –1 , there were no meaningful differences in V c,max in response to light spectrum, in contrast to J ( Figure 8 ).

When PPFD increased 5×, from 200 to 1,000 μmol⋅m –2 ⋅s –1 , there was only a 1.7 to 2.4× increase in J , indicating a lower QY(J) inc at higher PPFD . This matches the lower QY inc and the asymptotic increase in A n in response to increasing PPFD ( Figure 3 ). The relative increase of J under green light (143%) was greater than that under both blue and red light (73 and 75%, respectively) as PPFD increased. This similarly can be attributed to a more uniform energy distribution of green light among reaction centers throughout a leaf and weaker upregulation of non-photochemical quenching with increasing green light intensity ( Sun et al., 1998 ; Nishio, 2000 ; Evans and Vogelmann, 2003 ), as discussed before.

There was a strong correlation between J and A g under the nine light spectra at both PPFD levels ( Figure 9A ). QY abs and QY(J) abs are similarly strongly correlated ( Figure 9B ). Unlike J , V c,max was largely unaffected by light spectra ( Figure 8B ) and was not correlated with A g (data not shown). There was, however, a strong correlation between J and V c,max at a PPFD of 1,000 μmol⋅m –2 ⋅s –1 ( R 2 = 0.82, Supplementary Figure 3 ), suggesting that J and V c,max are co-regulated. Similarly, Wullschleger (1993) noted a strong linear relationship between J and V c,max across 109 C 3 species. The ratio between J and V c,max in our study (1.5–2.0) similar to the ratio found by Wullschleger (1993) . These results suggest that the interactive effect of light spectra and PPFD resulted from effects on J , which is associated with light energy harvesting by reaction centers, rather than from V c,max .

Figure 9. The correlation between gross CO 2 assimilation rate ( A g ) estimated from light response curves and electron transport rate ( J ) estimated from A/C i curves (A) , and between the quantum yield of CO 2 assimilation ( QY abs ) and the quantum yield of electron transport on an absorbed light basis [ QY(J) abs ] (B) , under low PPFD (200 μmol m –2 s –1 ) and high PPFD (1,000 μmol m –2 s –1 ) under nine light spectra averaged over nine “Green Towers” lettuce plants. The color scheme representing the nine spectra is the same as Figure 8 .

No Interactive Effects Among Blue, Green, and Red Light

The Emerson enhancement effect describes a synergistic effect between lights of different wavebands (red and far-red) on photosynthesis ( Emerson, 1957 ). McCree (1971) attempted to account for interactions between light with different spectra when developing photosynthetic action spectra and applied low intensity monochromatic lights from 350 to 725 nm with white background light to plants. His results showed no interactive effect between those monochromatic lights and white light ( McCree, 1971 ). We tested different ratios of blue, green, and red light and different PPFD s, and similarly did not find any synergistic or antagonistic effect of different wavebands on any physiological parameters measured or calculated.

Importance of Interactions Between PPFD and Light Quality and Its Applications

The interactive effect between PPFD and light quality demonstrates a remarkable adaptation of plants to different light intensities. By not absorbing green light strongly, plants open up a “green window,” as Terashima et al. (2009) called it, to excite chloroplasts deeper into leaves, and thus facilitating CO 2 assimilation throughout the leaf. While red light resulted in relatively high QY inc , QY abs and A n at both high and low PPFD ( Figures 3 , 6 ), it is still mainly absorbed in the upper part of leaves ( Sun et al., 1998 ; Brodersen and Vogelmann, 2010 ). Green light can penetrate deeper into leaves ( Brodersen and Vogelmann, 2010 ) and help plants drive efficient CO 2 assimilation at high PPFD ( Figures 3 , 5 ).

Many early photosynthesis studies investigated the absorptance and action spectrum of photosynthesis of green algae, e.g., Haxo and Blinks (1950) or chlorophyll or chloroplasts extracts, e.g., Chen (1952) . Extrapolating light absorptance of green algae and suspension of chlorophyll or chloroplast to whole leaves from can lead to an underestimation of absorptance of green light by whole leaves and the belief that green light has little photosynthetic activity ( Moss and Loomis, 1952 ; Smith et al., 2017 ). Photosynthetic action spectra developed on whole leaves of higher plants, however, have long shown that green light effectively contributes to CO 2 assimilation, although with lower QY inc than red light ( Hoover, 1937 ; McCree, 1971 ; Inada, 1976 ; Evans, 1987 ). The importance of green light for photosynthesis was clearly established in more recent studies, emphasizing its role in more uniformly exciting all chloroplasts, which especially important under high PPFD ( Sun et al., 1998 ; Nishio, 2000 ; Terashima et al., 2009 ; Hogewoning et al., 2012 ; Smith et al., 2017 ). The idea that red and blue light are more efficient at driving photosynthesis, unfortunately, still lingers, e.g., Singh et al. (2015) .

Light-emitting diodes (LEDs) have received wide attention in recent years for use in controlled environment agriculture, as they now have superior efficacy over traditional lighting technologies ( Pattison et al., 2018 ). LEDs can have a narrow spectrum and great controllability. This provides unprecedented opportunities to fine tune light spectra and PPFD to manipulate crop growth and development. Blue and red LEDs have higher efficacy than white and green LEDs ( Kusuma et al., 2020 ). By coincidence, McCree’s action spectrum ( Figure 1 ; McCree, 1971 ) also has peaks in the red and blue region, although the peak in the blue region is substantially lower than the one in the red region. Therefore, red and blue LEDs are sometimes considered optimal for driving photosynthesis. This claim holds true only under low PPFD . Green light plays an important role in photosynthesis, as it helps plants to adapt to different light intensities. The wavelength-dependent absorptance of chlorophylls channels green light deeper into leaves, resulting in more uniform light absorption throughout leaves and providing excitation energy to cells further from the adaxial surface. Under high PPFD , this can increase leaf photosynthesis. Plant evolved under sunlight for hundreds of millions of years, and it seems likely that the relatively low absorptance of green light contributes to the overall photosynthetic efficiency of plants ( Nishio, 2000 ).

There was an interactive effect of light spectrum and PPFD on leaf photosynthesis. Under low PPFD , QY inc was lowest under green and highest under red light. The low QY inc under green light at low PPFD was due to low absorptance. In contrast, at high PPFD , green and red light achieved similar QY inc , higher than that of blue light. The strong absorption of blue light by chlorophyll creates a large light gradient from the top to the bottom of leaves. The large amount of excitation energy near the adaxial side of a leaf results in upregulation of nonphotochemical quenching, while chloroplasts near the bottom of a leaf receive little excitation energy under blue light. The more uniform distribution of green light absorption within leaves reduces the need for nonphotochemical quenching near the top of the leaf, while providing more excitation energy to cells near the bottom of the leaf. We also found that the interactive effect of light spectrum and PPFD on photosynthesis was a result of the light-dependent reactions; gross assimilation and J were strongly correlated. We detected no synergistic or antagonistic interactions between blue, green, and red light.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author Contributions

JL and MI designed the experiment, discussed the data, and revised the manuscript. JL performed the experiment, analyzed data, and prepared the first draft. Both authors contributed to the article and approved the submitted version.

This study was funded by the USDA-NIFA-SCRI award number 2018-51181-28365, project Lighting Approaches to Maximize Profits.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2021.619987/full#supplementary-material

Supplementary Figure 1 | (Related to Figure 6 ) Quantum yield of CO 2 assimilation of “Green Towers” lettuce as a function of incident ( QY inc ) (A,C,E,G) and absorbed PPFD ( QY abs ) (B,D,F,H) under nine light spectra (see Table 1 ). Error bars represent standard deviation ( n = 9).

Supplementary Figure 2 | (Related to Figure 7 ) Differential quantum yield of CO 2 assimilation ( differential QY ) of “Green Towers” lettuce under nine light spectra as a function of the PPFD . Inserts show differential QY at PPFD s of 1,000–1,300 μmol⋅m –2 s –1 s to better show differences at high PPFD (note the different y -axis scale). The composition of the nine light spectra is shown in Table 1 . The light spectra in the graphs are (A) 100B, 100G and 100R; (B) 100B, 80B20G, 20B80G and 100G; (C) 100G, 80G20R, 20G80R and 100R; and (D) 20B80R, 16B20G64R and 100G.

Supplementary Figure 3 | (Related to Figure 6 ) The correlation between electron transport ( J ) and maximum Rubisco carboxylation rate ( V c,max ) of “Green Towers” lettuce estimated from A/C i curves under PPFD (1000 μmol m –2 s –1 ) under nine light spectra ( p < 0.001).

Supplementary Figure 4 | (Related to Figure 6 ) The comparison between QY inc before (A) and after (B) correcting for light-suppression of respiration under blue, green, and red LED light. Note that the initial increase in QY inc became more pronounced after correction of light suppressed respiration.

Supplementary Figure 5 | The comparison between QY abs before (A) and after (B) correcting for alternative electron sinks under blue, green, and red LED light. Assuming a simplified electron sink that diverts energy of 15 μmol m –2 s –1 of absorbed photons (an arbitrary value used for illustrative purposes only) away from the Calvin cycle under all PPFD s, the corrected QY abs was calculated based on remaining photons available to support Calvin cycle processes (B) . Note that the pattern of QY inc after correcting of alternative electron sink (B) is similar to quantum yield of PSII measured by chlorophyll fluorescence by Weaver and van Iersel (2019) .

Supplementary Table 1 | Dark respiration rate (R d ), maximum quantum yield of CO 2 assimilation (QY m,inc ) and maximum gross assimilation rate (A g,max ) of “Green towers” lettuce derived from the light response curves for nine different spectra using Eq. 1. The light response curves are shown in Figure 3 . *See light composition of nine lights presented here in Table 1 .

Abbreviations

PPFD , photosynthetic photon flux density; RuBP, ribulose 1,5-bisphosphate; Rubisco, ribulose-1,5-bisphosphate carboxylase/oxygenase; VPD, vapor pressure deficit; FWHM, full width at half maximum; A n , net CO 2 assimilation rate; R d , dark respiration rate; QY m,inc , maximum quantum yield of CO 2 assimilation; A g,max , light-saturated gross assimilation rate; QY m,abs , maximum quantum yield of CO 2 assimilation on absorbed light base; QY inc , quantum yield of CO 2 assimilation based on incident PPFD ; A g , gross CO 2 assimilation rate; QY abs , quantum yield of CO 2 assimilation on absorbed light base; QY , quantum yield of CO 2 assimilation; A/Ci curve, assimilation – internal leaf CO 2 response curve; RACiR, rapid A/C i response technique; V c,max , maximum rate of Rubisco carboxylation; J , rate of electron transport; CA1P, 2-carboxy- D -arabinitol-1-phosphate; NPQ, non-photochemical quenching.

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Keywords : photosynthesis, quantum yield of CO 2 assimilation, light spectrum, photosynthetic photon flux density, electron transport, V c, max , light intensity, light quality

Citation: Liu J and van Iersel MW (2021) Photosynthetic Physiology of Blue, Green, and Red Light: Light Intensity Effects and Underlying Mechanisms. Front. Plant Sci. 12:619987. doi: 10.3389/fpls.2021.619987

Received: 21 October 2020; Accepted: 11 February 2021; Published: 05 March 2021.

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Copyright © 2021 Liu and van Iersel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jun Liu, [email protected]

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Published: 17 October 2024

Potential for photosynthesis on Mars within snow and ice

Aditya R. Khuller ORCID: orcid.org/0000-0002-9866-781X 1 ,
Stephen G. Warren ORCID: orcid.org/0000-0001-5429-7100 2 ,
Philip R. Christensen 3 &
Gary D. Clow 4

Communications Earth & Environment volume 5 , Article number: 583 ( 2024 ) Cite this article

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Astrobiology
Cryospheric science
Inner planets

On Earth, solar radiation can transmit down to multiple metres within ice, depending on its optical properties. Organisms within ice can harness energy from photosynthetically active radiation while being protected from damaging ultraviolet radiation. On Mars, the lack of an effective ozone shield allows ~30% more damaging ultraviolet radiation to reach the surface in comparison with Earth. However, our radiative transfer modelling shows that despite the intense surface ultraviolet radiation, there are radiatively habitable zones within exposed mid-latitude ice on Mars, at depths ranging from a few centimetres for ice with 0.01–0.1% dust, and up to a few metres within cleaner ice. Numerical models predict that dense dusty snow in the martian mid-latitudes can melt below the surface at present. Thus, if small amounts of liquid water are available at these depths, mid-latitude ice exposures could represent the most easily accessible locations to search for extant life on Mars.

Introduction

Dusty water ice (<~1% dust by mass) is exposed at the surface of Mars at latitudes poleward of 75° 1 , 2 . In the martian mid-latitudes ( ${{30}}{{-}}{{60}}{{^{\circ} \, }}$ latitude), dusty ice is typically overlain by desiccated material 3 , 4 , 5 . However, recent observations indicate that the overlying desiccated material can be removed by impact processes 6 or by slumping on steep slopes, to expose dusty ice at the surface in the mid-latitude regions of Mars 7 , 8 , 9 . The ice is thought to have been deposited as dusty snow during numerous periods of high obliquity that occurred over the last few million years 4 , 10 , 11 . While the precise grain size and density of exposed martian ice is currently unknown, snow on Mars is estimated to metamorphose into coarser-grained firn and eventually glacier ice on timescales ranging from decades/centuries 12 , 13 to millions of years 14 .

Snow, firn, and ice are very weakly absorbing at ultraviolet (0.2–0.4 ${{\mu }}{{\rm{m}}}$ ) and photosynthetically active radiation (PAR, 0.4–0.7 ${{\mu }}{{\rm{m}}}$ ) wavelengths, where solar radiation peaks, so the radiation is transmitted through these media to depths down to a few metres 15 , 16 , 17 , 18 , 19 , 20 . On Earth, organisms are protected from damaging ultraviolet radiation by atmospheric ozone and can harness the energy from PAR in ‘radiatively habitable zones’, even within ice 21 , 22 , 23 , 24 . But the lack of an effective ozone shield on Mars allows ~30% more damaging ultraviolet radiation to reach the surface of Mars than on Earth 25 .

Despite higher surface ultraviolet radiation levels, previous martian simulations suggested that radiatively habitable zones could exist within polar snow and ice on Mars, at depths between 0.05 and 4.5 m 26 , 27 , 28 . These radiatively habitable zones occur where damaging ultraviolet radiation is attenuated to safe levels while the flux of PAR is large enough for photosynthesis to occur. Previous martian studies used optical properties of various natural and synthetic snow analogues 26 , 28 , 29 and sea ice found on Earth 30 for their simulations. However, the optical properties used by these previous martian studies do not accurately represent the observed exposures of dusty ice on Mars, because martian snow has likely metamorphosed into coarser-grained firn or glacier ice 12 , 13 , 14 , which allow solar radiation to penetrate far deeper than snow 15 , 31 , and sea ice does not occur on Mars. Furthermore, polar locations on Mars are too cold for snow and ice to melt 12 , 32 . But exposed dusty ice in the mid-latitudes ( ${{30}}{{-}}{{50}}{{^{\circ} }}$ latitude) might be melting at present 4 , 9 , 12 , 32 .

To investigate whether radiatively habitable zones exist within mid-latitude ice exposures on Mars, we have developed a radiative transfer model for ice, based on work validated previously using measurements of snow, as well as snow that has metamorphosed into coarser-grained firn and glacier ice on Earth 33 , 34 , 35 , 36 , 37 and Mars 38 (see Methods). The model uses the Delta-Eddington method 39 , modified to account for varying refractive boundaries 40 , 41 , and can simulate vertically heterogeneous layers containing mixtures of snow, firn, ice, and impurities such as martian dust. We use the spectral solar radiation flux and incorporate the large (10 orders of magnitude) spectral variation in the imaginary (absorptive) part of the refractive index of H 2 O ice, which determines light absorption in the solar spectrum, in addition to accounting for absorption by martian dust. Martian dust is seven orders of magnitude more absorbing than ice (per unit mass) at visible and UV wavelengths, primarily due to the presence of ferric iron 42 , 43 ; it therefore significantly reduces both the ice’s albedo 38 and the penetration-depth of solar radiation 12 . Many previous models of martian ice 14 , 44 , 45 , 46 , 47 have ignored this spectral variation, either by assuming that all incoming solar radiation is absorbed within the topmost snow/ice model layer (typically a few mm) or by using a single broadband value, resulting in an underestimation of the amount of energy transmitted to depth up to a few orders of magnitude 15 . We therefore account for this large spectral variation, because it is crucial in accurately characterizing the transmission of radiation through snow and ice.

Spectral solar flux has not yet been measured within ice on Mars. Therefore, as an analogue for martian ice, we compare our model results to spectral irradiance measurements made within vertically heterogeneous glacier ice in Greenland containing impurities equivalent to small amounts ( ~ 1–2 parts per billion) of black carbon 17 . Overall, the model shows excellent agreement with the observations (Fig. 1 ), despite key input parameters such as grain size and impurity content not being measured directly.

The dashed curves represent results from our solar radiation model, and the solid-coloured curves represent measurements made in Greenland. Many existing ice models 14 , 44 , 45 , 46 , 47 either assume that no solar radiation penetrates below the top few millimeters, or use a single broadband extinction value indicated by the horizontal black line, which can lead to errors in the energy absorbed at depth up to a few orders of magnitude 15 .

Many snow and ice models for Mars 14 , 44 , 45 , 46 , 47 use a broadband approximation to calculate the fluxes of solar radiation at depth. As an illustrative example, Fig. 1 compares the Greenland measurements to the modelled broadband flux at 12 cm depth (black horizontal line) using an attenuation length of 0.8 m previously used by McKay 48 . The use of a constant attenuation length causes up to a ~ 60% underestimation of flux at wavelengths short of 0.7 ${{\rm{\mu }}}{{\rm{m}}}$ and up to a factor-of-17 overestimation at longer wavelengths where H 2 O ice is more absorptive.

Bohren and Barkstrom 49 showed that only 3% of the radiation scattered by a single ice grain is externally reflected, whereas 89% is transmitted after refraction and 8% is transmitted after internal reflections (their Eq. 24). So, as the grain radii and density of a snowpack increase over time, the number of scattering events at air-ice boundaries decreases. Thus, solar radiation penetrates to greater depth in coarse-grained snow, firn, and glacier ice than in fresh, fine-grained snow. Figure 2 shows the spectral variation of actinic flux with depth for dense snow, firn, and glacier ice on Mars. Actinic flux (sometimes referred to as scalar irradiance) is the radiance integrated over solid angle without cosine-weighting, summed over both upward and downward hemispheres and including both direct and diffuse radiation 50 . It is the quantity relevant for photosynthesis, because photosynthetic organisms utilize the photons available from all directions within snow and ice, independent of angle 28 , 51 . The results shown in Fig. 2 are for 33°S, the lowest latitude on Mars where H 2 O ice has been detected 9 .

Vertical panels are grouped by ice grain radius and density whereas horizontal panels are grouped by dust content (by mass). Note that the vertical (depth) scale is different in the three rows: 0–700 cm in the top row, 0–40 cm in the middle row, and 0–6 cm in the bottom row. The solar zenith angle is zero in all cases, and the peak solar flux over the course of the year is used.

In clean ice, the spectral distribution of subsurface actinic flux with depth mimics the spectral dependence of pure ice’s absorption coefficient, with the greatest penetration occurring at 0.42 ${{\mu }}{{\rm{m}}}$ , followed by wavelengths short of 0.4 ${{\mu }}{{\rm{m}}}$ . The greatest absorption within the PAR range occurs at wavelengths near 0.7 ${{\mu }}{{\rm{m}}}$ . In all cases, most of the solar radiation is attenuated within the top few metres for clean ice, with penetration increasing strongly with increasing grain size, because of the increased mean free path between scattering events. PAR penetrates deeply in clean ice, with radiation near 0.4 ${{\mu }}{{\rm{m}}}$ reaching down to ~6.5 metres (Fig. 2a–c and Supplementary Data Fig. 2a–c ). The weak absorption also leads to biologically damaging ultraviolet radiation (0.2–0.4 ${{\mu }}{{\rm{m}}}$ ) penetrating down to ~6 metres in clean ice.

Including small amounts of martian dust within the ice leads to two major changes in the modelled distribution of actinic flux at depth (Fig. 2d–i and Supplementary Data Fig. 2d–i ). The first change is to alter the spectral distribution of the actinic flux. The inclusion of even 0.01% dust causes the greatest penetration depth to shift toward long wavelengths near 0.7 ${{\mu }}{{\rm{m}}}$ , with the overall spectral distribution now following the spectral dependence of martian dust’s absorption coefficient. Between 0.2 and 0.4 ${{\mu }}{{\rm{m}}}$ martian dust is seven orders of magnitude more strongly absorbing than pure ice, which causes ultraviolet radiation to be attenuated more strongly by a factor of ~25. The second change is to drastically reduce the depth to which solar radiation can penetrate within the ice due to the combination of dust’s greater absorption and an increase in the number of scatterers within the ice. [Note the change of the depth scale in Fig. 2 (extending to 700 cm in a, b, c; 40 cm in d,e,f; 6 cm in g, h,i).] PAR penetrates an order of magnitude less with the inclusion of 0.01% dust, down to only 40 cm below the surface (Fig. 2f ). A further increase in dust concentration to 0.1% dust leads to a corresponding order of magnitude decrease in PAR penetration depth of down to just 5.5 cm below the surface (Fig. 2i ). The peak penetration depths for ultraviolet radiation are also reduced similarly to ~15 cm and 2 cm for ice containing 0.01% dust and 0.1% dust, respectively.

The penetration of actinic flux within martian ice leads to zones of radiative habitability that vary in depth and thickness by a few orders of magnitude depending on dust content, ice grain radius, latitude, and solar zenith angle, as shown in Fig. 3 and Supplementary Data Fig. 3 . Because there is some debate as to what the limit for PAR is on Earth, we present results using two commonly used PAR limits based on observations ( ${{10}}\,{{\rm{nmol\; photons}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}\,{{{\rm{s}}}}^{{{-}}{{1}}}$ , equivalent to 2.2 m ${{\rm{W}}}\,{{{\rm{m}}}}^{{{-}}{{2}}}$ , and referred to here as the PAR lower limit) 52 and theoretical studies ( ${{20}}\,{{\mu }}{{\rm{mol\; photons}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}\,{{{\rm{s}}}}^{{{-}}{{1}}}$ , equivalent to 4.353 ${{\rm{W}}}\,{{{\rm{m}}}}^{{{-}}{{2}}}$ , the PAR upper limit) 53 .

Zones where levels of DNA-damaging irradiance are safe and there is enough photosynthetically active radiation (PAR) for photosynthesis to occur are shown as the green areas, as a function of ( a ) dust content, ( b ) ice radius, ( c ) latitude, and ( d ) solar zenith angle. Two limits for PAR shown: a lower limit of ${{10}}\,{{\rm{nmol\; photons}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}\,{{{\rm{s}}}}^{{{-}}{{1}}}$ (2.2 m ${{\rm{W}}}\,{{{\rm{m}}}}^{{{-}}{{2}}}$ ; red dashed lines), and an upper limit of ${{20}}\,{{\mu }}{{\rm{mol\; photons}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}\,{{{\rm{s}}}}^{{{-}}{{1}}}$ (4.353 ${{\rm{W}}}\,{{{\rm{m}}}}^{{{-}}{{2}}}$ ; purple dotted lines). The DNA-damaging limit was taken to be ${{0}}{{.}}{{1}}\,{{\rm{W}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}$ 25 , 26 . The reference values for the sensitivity analysis are ice grain radius 2.5 mm, density 775 ${{\rm{kg}}} \, {{{\rm{m}}}}^{{{-}}{{3}}}$ , 0.01% dust (by mass), solar zenith angle zero, and a latitude of 40°S. Note that the vertical (depth) axis in part ( a ) is on a log scale. In part ( c ), at each latitude the peak solar flux over the course of the year is used.

Figure 3a and Supplementary Data Fig. 3a show that for clean firn (10 −8 % dust, grain radius 2.5 mm, density 775 ${{\rm{kg}}} \, {{{\rm{m}}}}^{-3}$ ) at 40° latitude in the southern and northern hemispheres, respectively, a radiatively habitable zone is present between 2.15 and 3.10 metres using the lower PAR limit. However, no such radiatively habitable zone exists when the upper PAR limit is used. The effect of increasing the dust content of the ice is to move the zone of radiative habitability to shallower depths. For example, ice containing large amounts of dust (1%) has radiatively habitable zones between 2 and 6 mm for the lower PAR limit, or between 2 and 3 mm for the upper limit (Fig. 3a ). Lower values of dust content around 0.1% result in an order-of-magnitude increase in width of the radiatively habitable zone.

For ice containing 0.01% dust, an increase in grain radius leads to the radiatively habitable zone moving deeper and increasing in thickness (Fig. 3b and Supplementary Data Fig. 3b ). For coarse-grained snow ( ~ 360 ${{\mu }}{{\rm{m}}}$ , 390 ${{\rm{kg}}} \, {{{\rm{m}}}}^{-3}$ ), the radiatively habitable zone lies at 5 – 18 cm for the lower PAR limit and 5–7.5 cm for the upper limit. On the other extreme, for glacier ice with few bubbles (15 mm, 910 ${{\rm{kg}}} \, {{{\rm{m}}}}^{-3}$ ) the radiatively habitable zone depth ranges are 10–38 cm and 10–17 cm.

The effect of latitude on the radiatively habitable zones is relatively small because the thresholds for PAR and DNA damage are a few orders of magnitude smaller than the latitudinal variation of the peak annual solar fluxes reaching the martian surface. Thus, a change in latitude from 30° to 90° causes the depth at which the PAR upper limit is reached to shift by only a few centimetres (Fig. 3c and Supplementary Data Fig. 3c ).

The solar zenith angle, which varies diurnally and seasonally, also alters the solar fluxes at the surface. A larger solar zenith angle indicates the Sun is at a lower elevation. Increasing the solar zenith angle leads to a greater probability that an incoming photon will be scattered away from the surface, thereby reducing the depth to which solar radiation can penetrate below the ice surface. When the upper PAR limit is used, an increase in solar zenith angle from 0° to 60° causes the radiatively habitable zone to decrease in thickness from approximately 5 cm to 3 cm (Fig. 3d and Supplementary Data Fig. 3d ). By contrast, when the lower PAR limit is used, an increase in solar zenith angle has a relatively small impact on the radiatively habitable zones.

In conclusion, while the radiatively habitable zone of ice containing large amounts (1%) of dust is narrow (2 – 6 mm) and unlikely to support photosynthesis (Fig. 3a and Supplementary Data Fig. 3a ), its width increases by an order-of-magnitude at lower dust contents ( < 0.1%), where it overlaps with depth ranges imposed by other constraints (Fig. 3b–d and Supplementary Data Fig. 3b–d ).

Implications for life on Mars

Our analysis shows that despite higher surface ultraviolet radiation levels on Mars than on Earth, it is possible for terrestrial photosynthetic organisms to find locations within exposed ice on Mars with favourable solar radiative conditions. However, terrestrial microbes also require temperatures greater than 255 K for cell division to occur, and photosynthesis requires the presence of liquid water 54 . While martian polar ice deposits are too cold for melting to occur at these depths, and ice present within soil pores 55 is unlikely to melt 4 , 56 , numerical models developed specifically for martian snow 12 , 32 suggest that small amounts of melt and runoff (up to 0.33 mm per day for ~50 days each martian year) can be produced within exposed mid-latitude martian snowpacks containing ~0.1% dust, centimetres below the surface.

Although liquid water at the surface of Mars is highly likely to evaporate due to the low mean partial pressure of ~1 Pa for H 2 O vapor, liquid water produced within snow can be stable against evaporation. The gas within snow pores is typically saturated with water vapor 57 , and overlying snow/ice and dust can act as barriers against vapor diffusion to the dry martian atmosphere 4 , 12 , 45 , 57 , 58 , 59 , 60 . Thus, despite high energy losses from sublimation 61 , 62 , subsurface temperatures within dusty snow exposed on steep slopes can reach the melting point (273 K) 12 , 32 , where the local H 2 O partial pressure within snow is saturated at 611 Pa, allowing liquid water to be stable below the surface.

The predicted amounts of melt and runoff are very sensitive to the ice grain size and dust content 12 , 32 . The grain size of exposed ice in the martian mid-latitudes is currently unknown, but if the ice exposures on steep slopes 7 , 9 represent dusty firn or dusty glacier ice, terrestrial analogues suggest greater rates of subsurface melting than in snow because greater amounts of solar radiation penetrate below the surface (Fig. 2 ; refs. 31 , 63 ). The dust contents are also not well constrained for martian ice, but the ice is likely to contain less than 1% dust based on its albedo because ice with greater amounts of dust would be indistinguishable from nearby lithic material at wavelengths short of 1 ${{\mu }}{{\rm{m}}}$ 9 , 38 . However, as the ice melts and sublimates, it will gradually build up a lag of dust 64 , thereby increasing the dust content of the ice. Once the ice contains ${{\ge }}{{1}}{{ \% }}$ dust, the resulting opaque layer of dust can block incoming solar radiation and prevent subsurface melting 32 , 65 unless the dust lag layer forms below the surface 66 , in which case subsurface melting could be enhanced by increased solar absorption by a darker substrate within the ice 16 , 63 . Throughout the buildup of a surface dust lag, winds and surface frost-related processes can remove the overlying dust to re-expose the ice (as may be observed on steep slopes in the martian mid-latitudes 7 , 8 , 9 , 67 ) so that subsurface melting can occur once again under favourable conditions.

Under similar ephemeral near-freezing conditions, widespread microbial habitats are found in the shallow subsurface (top few centimetres to metres) of ice sheets, glaciers, and lake ice on Earth. Typically, these shallow subsurface habitats are formed by dark dust and sediment present at the surface of the ice absorbing greater amounts of solar radiation than the surrounding ice, heating up, and forming holes within the ice by melting 68 , 69 , 70 . These “cryoconite” holes continue to deepen until the amount of solar radiation transmitted to the dust and sediment is insufficient to melt further into the ice at some depth. Then, while liquid water is present around the sediment at the bottom of the hole, an ice lid forms at the surface, isolating the hole interior from the atmosphere. In the summer, photosynthesis occurs in the subsurface below the translucent ice lid, with nutrients scavenged from the dust and sediment present in the water-filled hole. During winter, the subsurface liquid refreezes, and photosynthesis ceases until the next summer.

A variety of organisms are found in these shallow subsurface habitats within terrestrial ice, such as cyanobacteria, chlorophytes, fungi, diatoms, and heterotrophic bacteria 71 . Typically, the most dominant organisms in these habitats are cyanobacteria 72 . Cyanobacteria have developed appropriate mechanisms to deal with a wide range of temperatures, nutrient deficiency, UV radiation, and desiccation 72 , 73 . These communities can persist even if temperatures are above freezing for only a few days per year 72 . The results presented here indicate that radiatively habitable zones exist within exposed mid-latitude ice on Mars at depths ranging from a few centimetres for ice with 0.01–0.1% dust, and up to a few metres within cleaner ice. Thus, if exposures of dusty mid-latitude martian ice are melting below the surface for a fraction of the year as predicted by numerical models 12 , 32 , then, like on Earth, microbes such as cyanobacteria could scavenge nutrients from the martian dust 74 mixed in with the ice, and utilize the small amounts of melt whilst being in a radiatively favourable habitat below the surface. These potential present-day habitats are centimetres to metres below the surface and could be the most easily accessible locations to find extant life on Mars via future robotic and human missions.

Downward solar spectrum

The Planetary Spectrum Generator 75 was used to simulate the downward spectral solar radiation flux at the surface of Mars. As inputs, the mean Mars-Sun distance of 1.52 AU was used with a solar zenith angle of 0 ${\scriptstyle{{\circ} \, \, \, }}$ , for a solar longitude of ${{0}}{{^{\circ} }}$ , at ${{0}}{{^{\circ} }} \, {{\rm{N}}}{{,}}\,{{0}}{{^{\circ} }} \, {{\rm{E}}}$ (using the ‘Looking up to the Sun’ viewing geometry). The Planetary Spectrum Generator’s standard martian atmospheric profile with no atmospheric aerosols (dust or water ice) was used. After dividing the downward solar spectrum ( ${{\rm{W}}} \, {{{\rm{m}}}}^{{{-}}{{2}}} \, {{\mu }}{{{\rm{m}}}}^{{{-}}{{1}}}$ ) by its spectrally integrated value ( ${{\rm{W}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}$ ) we obtained the result shown in Supplementary Data Fig. 1 . Then, we multiplied peak annual broadband solar flux values ( ${{\rm{W}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}$ ) from the validated Mars Climate Database 76 , 77 to obtain surface spectral fluxes for each latitude ( ${{\rm{W}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}\,{{\mu }}{{{\rm{m}}}}^{{{-}}{{1}}}$ ).

Optical properties for dusty snow, firn and glacier ice on Mars

At present, there is some uncertainty about the precise H 2 O ice refractive index values at wavelengths short of 0.6 ${{\rm{\mu }}}{{\rm{m}}}$ . Thus, following Flanner, et al. 41 , we use a blend of values for the imaginary part of the complex refractive index of H 2 O ice. For 0.32 – 0.6 ${{\rm{\mu }}}{{\rm{m}}}$ we use values from Picard, et al. 78 ; for 0.6 – 3 ${{\rm{\mu }}}{{\rm{m}}}$ we use values from Warren and Brandt 79 . The Picard et al. 78 value at 0.32 ${{\rm{\mu }}}{{\rm{m}}}$ is used for 0.2 – 0.32 ${{\rm{\mu }}}{{\rm{m}}}$ . The use of this blend of imaginary refractive indices leads to relatively conservative estimates of solar radiation penetration depths when compared to results using the lower values of Warren and Brandt 79 . For the real part of the refractive index, we use values from Warren and Brandt 79 . For martian dust, we incorporate the spectral absorption properties derived by Wolff et al. 80 . Optical properties of snow, firn, and glacier ice mixtures with dust are computed using the method of Khuller et al. 38 .

Radiative transfer model for dusty snow, firn and glacier ice on Mars

Our radiative transfer model uses the solar transmission formulation of the Snow, Ice, and Aerosol Radiative Adding-Doubling model Version 4 SNICAR-ADv4; 35 . SNICAR-ADv4 is based on the Delta-Eddington method modified to include media with differing refractive indices such as snow, liquid water, or ice in the same vertical column 33 , 36 , 37 , 39 , 40 . The model outputs upward and downward spectral fluxes ${F}_{{\rm{up}}}$ and ${F}_{{\rm{down}}} \, ({{\rm{W}}} \, {{{\rm{m}}}}^{-2} \, {{\rm{\mu }}}{{{\rm{m}}}}^{-1})$ , which we convert into actinic flux. The total actinic flux within snow and ice is simply $2({F}_{{\rm{up}}}+{F}_{{\rm{down}}})$ 50 , 51 .

Solar radiation results for Greenland glacier ice

The glacier ice in Greenland was measured at four depths for density, but neither the grain size nor the impurity content was measured 17 . Additionally, because these types of measurements within ice are challenging, other key uncertainties are present: (a) the density of the quasi-granular layer in the upper ~12 cm is somewhat uncertain, and (b) excess solar radiation could have entered from the side-wall of the experimental setup, into which the probe was inserted horizontally to make these measurements. Thus, we chose a plausible set of model inputs to match the measured values. Based on the measurements, the estimated ice absorption coefficient at $0.4\,{{\rm{\mu }}}{{\rm{m}}}$ suggested that the ice contained the equivalent of ~1 ng/g of black carbon 17 , which is a typical value found on the Greenland Ice Sheet 63 . Thus, keeping this black-carbon concentration constant throughout, we used four layers in our model corresponding to each density measurement at depth, with the following grain radii, and densities for each layer: (1) 6.5 mm, 775 ${{\rm{kg}}} \, {{{\rm{m}}}}^{-3}$ , (2) 20 mm, 800 ${{\rm{kg}}} \, {{{\rm{m}}}}^{-3}$ , (3) 9 mm, 884 ${{\rm{kg}}} \, {{{\rm{m}}}}^{-3}$ , and (4) 7 mm, 888 ${{\rm{kg}}} \, {{{\rm{m}}}}^{-3}$ . The downward solar spectrum measured at the surface was used as input (grey upper curve in Fig. 1 ).

Photosynthetically Active Radiation (PAR)

Photosynthetically active radiation (PAR) is the spectrally integrated solar flux between 0.4 and 0.7 μm,

where both PAR ( ${{\rm{W}}}\,{{{\rm{m}}}}^{{{-}}{{2}}}$ ) and ${{S}}\left({{\lambda }}{{,}}{{z}}\right)$ , the spectral solar flux ( ${{\rm{W}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}\,{{\mu }}{{{\rm{m}}}}^{{{-}}{{1}}}$ ), vary with depth ${{z}}$ (m). PAR is often expressed in units of ${{\rm{mol\; photons}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}\,{{{\rm{s}}}}^{{{-}}{{1}}}$ , which can be converted to ${{\rm{W}}}\,{{{\rm{m}}}}^{{{-}}{{2}}}$ by a multiplier, $\frac{{{hc}}{{{N}}}_{{{a}}}}{{{{\lambda }}}_{{{\rm{peak}}}}}$ , where ${{h}}$ is Planck’s constant, ${{c}}$ is the speed of light in vacuum, ${{{N}}}_{{{a}}}$ is Avogadro’s number, and ${{{\lambda }}}_{{{\rm{peak}}}}{{\approx }}{{0}}{{.}}{{55}}\,{{\mu }}{{\rm{m}}}$ is the wavelength of peak solar flux. We used values of 20 ${{\mu }}{{\rm{mol\; photons}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}\,{{{\rm{s}}}}^{{{-}}{{1}}}$ (4.353 ${{\rm{W}}}\,{{{\rm{m}}}}^{{{-}}{{2}}}$ ) and 10 ${{\rm{nmol\; photons}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}\,{{{\rm{s}}}}^{{{-}}{{1}}}$ (2.2 m ${{\rm{W}}}\,{{{\rm{m}}}}^{{{-}}{{2}}}$ ) as the upper and lower limits of PAR, based on observations and theory on Earth 26 , 52 , 53 .

DNA damaging irradiance

The DNA damaging irradiance at a given depth is given by the integral from 0.2 to 0.4 μm of the product of the spectral solar flux and the biological spectral weighting function for damage, ${{\varepsilon }}\left({{\lambda }}\right)$ :

The weighting function ${{\varepsilon }}\left({{\lambda }}\right)$ we use is taken from Cockell and Raven 26 . It was derived from a combination of DNA absorbance and the DNA action spectrum 81 , 82 . It has been used successfully to represent the relative amount of damage to DNA structures from ultraviolet radiation 26 , 27 , 28 . Following previous studies, we use a value of ${{0}}{{.}}{{1}}\,{{\rm{W}}} \, {{{\rm{m}}}}^{{{-}}{{2}}}$ as the irradiance limit for DNA damage, which is the terrestrial, equatorial value during vernal equinox, at midday 25 , 26 . This limit is conservative because numerous terrestrial organisms grow and survive under stronger DNA damage conditions 83 . Additionally, it may be possible for organisms to mutate and adapt to thrive under stronger DNA damage conditions, as is thought to have occurred on Archean Earth 83 .

Data availability

The spectral irradiance data 84 from the Greenland glacier ice study 17 is available at https://doi.org/10.1594/PANGAEA.930278 . Results from our radiative transfer modelling are available here 85 : https://doi.org/10.5281/zenodo.13277435 .

Code availability

The SNICAR-ADv4 code we use is available at https://github.com/chloewhicker/SNICAR-ADv4 .

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Acknowledgements

A part of this work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. We would like to thank Joe Aslin, Candice Bedford, Kathleen Williamson, Matt Cooper, Carol Stoker, and one anonymous reviewer for very helpful feedback that greatly improved the paper. We would also like to thank Matt Cooper for providing the Greenland glacier radiation measurements, along with Erin Burkett, Scott Perl, Alejandro Martinez, Rahul Kushwaha, and Arnav Banerji for helpful discussions.

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Khuller, A.R., Warren, S.G., Christensen, P.R. et al. Potential for photosynthesis on Mars within snow and ice. Commun Earth Environ 5 , 583 (2024). https://doi.org/10.1038/s43247-024-01730-y

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Could life exist below Mars ice? Study proposes possibilities

by Andrew Good, Karen Fox, Molly Wasser, NASA

While actual evidence for life on Mars has never been found, a new NASA study proposes microbes could find a potential home beneath frozen water on the planet's surface.

Through computer modeling, the study's authors have shown that the amount of sunlight that can shine through water ice would be enough for photosynthesis to occur in shallow pools of meltwater below the surface of that ice. Similar pools of water that form within ice on Earth have been found to teem with life, including algae, fungi, and microscopic cyanobacteria, all of which derive energy from photosynthesis.

"If we're trying to find life anywhere in the universe today, Martian ice exposures are probably one of the most accessible places we should be looking," said the paper's lead author, Aditya Khuller of NASA's Jet Propulsion Laboratory in Southern California.

Mars has two kinds of ice: frozen water and frozen carbon dioxide. For their paper, published in Communications Earth & Environment , Khuller and colleagues looked at water ice, large amounts of which formed from snow mixed with dust that fell on the surface during a series of Martian ice ages in the past million years. That ancient snow has since solidified into ice, still peppered with specks of dust.

Although dust particles may obscure light in deeper layers of the ice, they are key to explaining how subsurface pools of water could form within ice when exposed to the sun: Dark dust absorbs more sunlight than the surrounding ice, potentially causing the ice to warm up and melt up to a few feet below the surface.

Mars scientists are divided about whether ice can actually melt when exposed to the Martian surface. That's due to the planet's thin, dry atmosphere, where water ice is believed to sublimate—turn directly into gas—the way dry ice does on Earth. But the atmospheric effects that make melting difficult on the Martian surface wouldn't apply below the surface of a dusty snowpack or glacier.

Thriving microcosms

On Earth, dust within ice can create what are called cryoconite holes—small cavities that form in ice when particles of windblown dust (called cryoconite) land there, absorb sunlight, and melt farther into the ice each summer. Eventually, as these dust particles travel farther from the sun's rays, they stop sinking, but they still generate enough warmth to create a pocket of meltwater around them. The pockets can nourish a thriving ecosystem for simple lifeforms..

"This is a common phenomenon on Earth," said co-author Phil Christensen of Arizona State University in Tempe, referring to ice melting from within. "Dense snow and ice can melt from the inside out, letting in sunlight that warms it like a greenhouse, rather than melting from the top down."

Christensen has studied ice on Mars for decades. He leads operations for a heat-sensitive camera called THEMIS (Thermal Emission Imaging System) aboard NASA's 2001 Mars Odyssey orbiter. In past research, Christensen and Gary Clow of the University of Colorado Boulder used modeling to demonstrate how liquid water could form within dusty snowpack on the Red Planet. That work, in turn, provided a foundation for the new paper focused on whether photosynthesis could be possible on Mars.

In 2021, Christensen and Khuller co-authored a paper on the discovery of dusty water ice exposed within gullies on Mars, proposing that many Martian gullies form by erosion caused by the ice melting to form liquid water.

This new paper suggests that dusty ice lets in enough light for photosynthesis to occur as deep as 9 feet (3 meters) below the surface . In this scenario, the upper layers of ice prevent the shallow subsurface pools of water from evaporating while also providing protection from harmful radiation. That's important, because unlike Earth, Mars lacks a protective magnetic field to shield it from both the sun and radioactive cosmic ray particles zipping around space.

Could life exist below Mars ice? NASA study proposes possibilities

The study authors say the water ice that would be most likely to form subsurface pools would exist in Mars' tropics, between 30 degrees and 60 degrees latitude, in both the northern and southern hemispheres.

Khuller next hopes to re-create some of Mars' dusty ice in a lab to study it up close. Meanwhile, he and other scientists are beginning to map out the most likely spots on Mars to look for shallow meltwater—locations that could be scientific targets for possible human and robotic missions in the future.

Journal information: Nature Communications Earth & Environment , Communications Earth & Environment

Provided by NASA

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Photosynthetic Research in Plant Science

Ayumi tanaka, amane makino.

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Issue date 2009 Apr.

The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and the Japanese Society of Plant Physiologists are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact [email protected]

Photosynthesis is a highly regulated, multistep process. It encompasses the harvest of solar energy, transfer of excitation energy, energy conversion, electron transfer from water to NADP + , ATP generation and a series of enzymatic reactions that assimilate carbon dioxide and synthesize carbohydrate.

Photosynthesis has a unique place in the history of plant science, as its central concepts were established by the middle of the last century, and the detailed mechanisms have since been elucidated. For example, measurements of photosynthetic efficiency (quantum yield) at different wavelengths of light (Emerson and Lews 1943 ) led to the insight that two distinct forms of Chl must be excited in oxygenic photosynthesis. These results suggested the concept of two photochemical systems. The reaction center pigments of PSII and PSI (P680 and P700, respectively) were found by studying changes in light absorbance in the red region (Kok 1959 , Döring et al. 1969 ). Chls with absorbance maxima corresponding to these specific wavelengths were proposed as the final light sink. These Chls were shown to drive electron transfer by charge separation. The linkage of electron transfer and CO 2 assimilation was suggested by studies on Hill oxidant (Hill 1937 ). A linear electron transport system with two light-driven reactions (Z scheme) was proposed based upon observations of the redox state of cytochromes (Hill and Bendall 1960 , Duysens et al. 1961 ), and photophosphorylation was found to be associated with thylakoid fragments (Arnon et al. 1954 ). The metabolic pathway that assimilates carbon by fixation of CO 2 was discovered by Calvin's group who used 14 CO 2 radioactive tracers in the 1950s (Bassham and Calvin 1957 ). This was the first significant discovery in biochemistry made using radioactive tracers. The primary reaction of CO 2 fixation is catalyzed by Rubisco (Weissbach et al. 1956 ), initially called Fraction 1 protein (Wildman and Bonner 1947 ). Rubisco is the most abundant protein in the world, largely because it is also the most inefficient with the lowest catalytic turnover rate (1–3 s –1 ). Another CO 2 fixation pathway was then found in sugarcane (Kortschak et al. 1964, Hatch and Slack 1965) and named C 4 photosynthesis.

Although photosynthesis plays the central role in the energy metabolism of plants, historically there have not been strong interactions between photosynthesis research and other fields of plant science. Many techniques and tools developed for photosynthesis research have not been widely used in other fields because they were developed to examine phenomena unique to photosynthesis. For example, excitation energy transfer and charge separation are fundamental but unique processes of photosynthesis. Another reason for the historic isolation of photosynthesis research within plant science is that it was long believed that CO 2 fixation and carbohydrate production are the sole function of photosynthesis, with carbohydrates representing the only link between photosynthesis and other biological phenomena.

However, this situation has begun to change. Recent research has revealed that photosynthesis is closely related to a variety of other physiological processes. It is a major system for controlling the redox state of cells, playing an important role in regulating enzyme activity and many other cellular processes (Buchanan and Balmer 2005 , Hisabori et al. 2007 ). Photosynthesis also generates reactive oxygen species, which are now appreciated as being regulatory factors for many biological processes rather than inevitable by-products of photosynthesis (Wagner et al. 2004 , Beck 2005 ). Precursor molecules of Chl, which are a major component of photosynthesis, act as a chloroplast-derived signal, and are involved in regulating the cell cycle (Kobayashi et al. 2009 ). In light of this new information, it seems important to re-evaluate the function(s), both potential and demonstrated, of photosynthesis from a variety of view points. Photosynthesis research now employs the methods and tools of molecular biology and genetics, which are central methods for plant science in general. Meanwhile, Chl fluorescence and gas exchange measurements, developed especially for photosynthesis research, are now widely used in stress biology and ecology.

Photosynthesis research also contributes to our understanding of ecological phenomena and even the global environments (Farquhar et al. 1980 , de Pury and Farquhar 1997 , Monsi and Saeki 2005 ). Indeed, photosynthesis is now an integral component of simulation models used to predict the future of our planet. Improving the efficiency of photosynthesis by artificial modification of photosynthetic proteins and pathways has long been considered impossible or at best problematic, because, over evolutionary time, photosynthesis has become complex and tightly regulated. However, recent advances have made it possible to manipulate photosynthesis using molecular genetic technology (Andrews and Whiney 2003 , Raines 2006 ). These advances may have positive influences on crop productivity (Parry et al. 2007 ) as photosynthetic rates have frequently been correlated with biomass accretion (Kruger and Volin 2006 ). Thus, we can expect many more novel concepts to be added to this history of photosynthetic research.

As photosynthesis research tackles new challenges, we should also continue to re-evaluate past research. Oxygen evolution, energy dissipation and cyclic electron transport are crucial processes during photosynthesis, yet their mechanisms still remain to be clarified. We have very limited knowledge of the formation and degradation of photosynthetic apparatus. Also, although photosynthesis plays a central role in C and N metabolism in plants, we do not yet understand how potential photosynthesis is related to crop productivity.

Plant and Cell Physiology would like to contribute to the development of novel concepts, pioneering new fields and solving the unanswered questions of photosynthesis. This special issue covers a wide range of topics in photosynthesis research. Terashima et al. (pp. 684–697) readdress the enigmatic question of why leaves are green. They show that the light profile through a leaf is steeper than that of photosynthesis, and that the green wavelengths in white light are more effective in driving photosynthesis than red light. Evans (pp. 698–706) proposes a new model using Chl fluorescence to explore modifications in quantum yield with leaf depth. This new multilayered model can be applied to study variations in light absorption profiles, photosynthetic capacity and calculation of chloroplastic CO 2 concentration at different depths through the leaf.

Singlet oxygen, 1 O 2 , is produced by the photosystem and Chl pigments. 1 O 2 not only causes physiological damage but also activates stress response programs. The flu mutant of Arabidopsis thaliana overaccumulates protochlorophyllide that upon illumination generates singlet oxygen, causing growth cessation and cell death. Coll et al. (pp. 707–718) have isolated suppressor mutants, dubbed ‘singlet oxygen-linked death activator’ (soldat), that specifically abrogate 1 O 2 -mediated stress responses in young flu seedlings, and they discuss the processes of acclimation to stresses. Phephorbide a is a degradation product of Chl and one of the most powerful photosensitzing molecules. Mutants defective in pheophorbide a oxygenase, which converts phephorbide a to open tetrapyrrole, accumulate pheophorbide a and display cell death in a light-dependent manner. Hirashima et al. (pp. 719–729) report that pheophorbide a is involved in this light-independent cell death.

Plants regulate the redox level of the plastoquinone pool in response to the light environment. In acclimation to high-light conditions, the redox level is kept in an oxidized state by the plastoquinone oxidation system (POS). Miyake et al. (pp. 730–743) investigated the mechanism of POS using the Chl fluorescence parameter, qL.

Nagai and Makino (pp. 744–755) examine in detail the differences between rice and wheat, the two most commercially important crops, in the temperature responses of CO 2 assimilation and plant growth. They find that the difference in biomass production between the two species at the level of the whole plant depends on the difference in N-use efficiency in leaf photosynthesis and growth rate. Sage and Sage (pp. 756–772) examine chlorenchyma structure in rice and related Oryza species in relation to photosynthetic function. They find that rice chlorenchyma architecture includes adaptations to maximize the scavenging of photorespired CO 2 and to enhance the diffusive conductance of CO 2 . In addition, they consider that the introduction of Kranz anatomy does not require radical anatomical alterations in engineering C 4 rice.

Bioinformatics has become a powerful tool, especially in photosynthetic research, because photosynthetic organisms have a wide taxonomic distribution among prokaryotes and eukaryotes. Ishikawa et al. (pp. 773–788) present the results of a pilot study of functional orthogenomics, combining bioinformatic and experimental analyses to identify nuclear-encoded chloroplast proteins of endosymbiontic origin (CRENDOs). They conclude that phylogenetic profiling is useful in finding CPRENDOs, although the physiological functions of orthologous genes may be different in chloroplasts and cyanobacteria.

We hope you enjoy this special issue, and would like to invite you to submit more excellent papers to Plant and Cell Physiology in the field of photosynthesis.

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The effect of light quality on plant physiology, photosynthetic, and stress response in Arabidopsis thaliana leaves

Introduction

Materials and methods

Light treatment

Physical and biochemical analyses

Biomass content determination.

Pigment content determination.

Net photosynthetic rate determination

Photosynthate content determination

Antioxidative enzyme activity estimation

Gene expression analysis

Primer design.

Quantitative real time-PCR (qRT-PCR) analysis.

Data analysis.

Statistical analysis

Effect of light quality and natural genotype variation on leaf area growth, biomass content, net photosynthetic rate, and pigment content in A . thaliana

Changes in transcription of photosynthetic marker genes, content of photosynthates, and activity of antioxidant in A . thaliana Col-0 under AL and RL

Regulation patterns of PSBA , NPQ1 , GSH2 and FAD6 transcripts in A . thaliana Col-0 under AL and RL

Photosynthates content in A . thaliana Col-0 under AL and RL

Antioxidative enzyme activity in A . thaliana Col-0 under AL and RL

Importance of geographic habitats on light quality response of leaf growth and biomass

Findings on BL supports its role on activation of protective pigments

Plants showed high antioxidative and photo-protective under AL

RL modulated plant adaptation and energy assimilation

Supporting information

S1 Table. List of primers sequences used in qPCR experiments.

S1 Fig. Proteins involved in ATP synthase and CET complex of A . thaliana Col-0 are upregulated under AL (595 nm) compared to RL (650 nm).

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Effects of growth under different light spectra on the subsequent high light tolerance in rose plants

Plant material and growth conditions

Chl fluorescence and OJIP test measurements

Pigment measurements

Determination of hydrogen peroxide content and lipid peroxidation

Determination of carbohydrates

Determination of activities of antioxidant enzymes

Statistical analysis

Polyphasic Chl a fluorescence (OJIP) transients

Antioxidant enzymes and oxidative damage

Carbohydrate concentrations

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The role of photosynthesis related pigments in light harvesting, photoprotection and enhancement of photosynthetic yield in planta

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