Effects of drought stress on photosynthetic physiological characteristics, leaf microstructure, and related gene expression of yellow horn

ABSTRACT

Yellow horn grows in northern China and has a high tolerance to drought and poor soil. Improving photosynthetic efficiency and increasing plant growth and yield under drought conditions have become important research content for researchers worldwide. Our study goal is to provide comprehensive information on photosynthesis and some candidate genes breeding of yellow horn under drought stress. In this study, seedlings’ stomatal conductance, chlorophyll content, and fluorescence parameters decreased under drought stress, but non-photochemical quenching increased. The leaf microstructure showed that stomata underwent a process from opening to closing, guard cells from complete to dry, and surrounding leaf cells from smooth to severe shrinkage. The chloroplast ultrastructure showed that the changes of starch granules were different under different drought stress, while plastoglobules increased and expanded continuously. In addition, we found some differentially expressed genes related to photosystem, electron transport component, oxidative phosphate ATPase, stomatal closure, and chloroplast ultrastructure. These results laid a foundation for further genetic improvement and deficit resistance breeding of yellow horn under drought stress.

KEYWORDS:

• Yellow horn
• drought stress
• photosynthetic
• microstructure
• transcription factors

1 Introduction

Global climate change has brought many problems, among which drought (seasonal, regional water shortage) seriously threatens plant growth and yield. Therefore, improving the efficiency of photosynthesis under drought conditions to improve plant growth and development has become an important research content of researchers worldwide. About 45% of agricultural terrain is permanently or intermittently water deficient, resulting in nearly 50% yearly global production losses¹. Meanwhile, water shortages are expected to become more severe in the coming decades. To reduce the effects of water stress on plants and achieve maximum crop yield potential, plants need to be physiologically adapted to local stress tolerance. Studies in many plant species have explored changes at transcriptional and physiological levels and under varying degrees of drought stress^2–10.

Plants have many responses to drought stress, among which photosynthetic processes are the most sensitive to drought^11,12. Plants wholly or partially close their stomata to limit transpiration and reduce water loss and carbon fixation in leaves under drought stress^13,14. Drought stress reduces photosynthesis, deactivates photoelectron transport and photophosphorylation, and affects organelles and ultrastructure of plants^15–17, such as chloroplast expansion, rupture, disintegration, plastid, and starch grain number and size change^18,19. PGs are lipoprotein particles located in chloroplasts²⁰, and their formation is related to environmental stress, leaf senescence, chloroplast biogenesis, and thylakoid decomposition^20–23. In addition, chlorophyll fluorescence has been widely used as a noninvasive method to study stress²⁴. Therefore, describing the response of plant photosynthesis to water deficit from multiple perspectives is very important for studying plant drought resistance.

Yellow horn (Xanthoceras sorbifolium bunge) is an economically and ecologically important tree species with oily seeds in northern China. As one of the ideal raw materials for biodiesel extraction, the seeds hold a substantial volume of unsaturated fatty acids and have significant value^25,26. Yellow horn oil has better balanced nutrient distribution and antioxidant capacity²⁷. Several studies have investigated the drought-resistance physiology of yellow horn^28,29, but transcriptome research still requires to be completed. Analysis of numerous factors, including photosynthetic physiology, fluorescence, pore microstructure, and chloroplast ultrastructure, was conducted in the course of this research. In addition, high-throughput sequencing technologies were leveraged to measure the moisture of impacted leaves and elucidate the gene transcription network essential for understanding the molecular tolerance of yellow horn against drought conditions. It also laid a foundation for future genetic improvement and cultivation.

2 Materials and methods

2.1 Plant materials and stress treatments

One-year-old seedlings were used in the present study. All seedlings were acquired from the Experimental Station of the Shanxi Agricultural University (112°18′112″E，37°15′36″N), and healthy plants were selected. Before the stress treatment, plants were irrigated under controlled conditions for 3 months at 22–25°C (16 light, 8 h darkness). After an adaptation period, the seedlings were randomly divided into three groups: the control group (CK，soil water content = 75 ± 2% − 80 ± 2%), the moderate drought stress group (MD, no water for 8 days, soil water content = 35 ± 2% − 40 ± 2%), and severe drought stress group (SD, no water for 17 days, soil water content = 5% ± 2%–10% ± 2%). The leaf samples were immediately frozen in liquid nitrogen and stored in a refrigerator at −80°C.

2.2 Physiological traits in leaves

Leaf RWC was calculated according to the formula: RWC (%) = (FW − DW)/(TW − DW) × 100. The seedlings were randomly harvested and weighed to determine their fresh weight (FW). Turgid weight (TW) was determined from leaves soaked in sterile water for 24 h at room temperature. Then, samples were placed in an oven at 60°C for 24 h and dried to dry weight (DW). Starch content was measured according to Galmes et al.³⁰. Rubisco activity was measured using the method described by Long et al.³¹.

2.3 Measurements of stomatal conductance and leaf greenness

The stomatal conductance of leaves was measured using an LI-6400×T Portable Photosynthesis System (Li-COR Environmental, Lincoln, NE, USA) from 9:00 to 10:00 (a.m.) (three repetitions). Measurements were performed in CO₂ concentration of 400 μmol mol⁻¹, a light intensity of 800 µmol m⁻² s⁻¹, air temperature of approximately (25–28°C), and air relative humidity of appropriately (60–70%).

Leaf greenness was determined in seedlings using a noninvasive method using a chlorophyll meter (SPAD 502; Konica Minolta, Tokyo, Japan) 5 times in each treatment, and the average value was taken.

2.4 Measurement of chlorophyll fluorescence parameters

The chlorophyll fluorescence transients were determined with Handy PEA (Hansatech Instruments Ltd, King’s Lynn, England) and a chlorophyll fluorescence imaging system (PAM 2500, Walz GmbH, Effeltrich, Germany) after leaves being dark adaption for 30 min with leaf clips, and determined five times in each treatment. The saturating intensity of 3000 μmol•m⁻²•s⁻¹ was set to induce the fluorescence of chlorophyll. The PEA automatically records fluorescence signals from 10 μs to 1 s. The fluorescence parameters – Fv/Fm, maximal photochemical efficiency of PSII; ETR— (Quantum photosynthetic yield) × PAR × 0.84 × 0.5, linear electron transport rate; NPQ— (Fm – F’m)/F’m, non-photochemical quenching; ABS/RC, absorption flux per reaction center; DIo/RC, dissipated energy flux per RC; ETo/RC, electron transport flux per RC; φPo, the maximum quantum yield of primary photochemistry (at t = Fo); φEo, quantum yield for electron transport (at t = Fo); φO, the probability that a trapped exciton moves an electron into the electron transport chain beyond QA (at t = Fo); VJ, relative variable fluorescence at the J-step; VI, Relative variable fluorescence at the I-step; Sm, normalized total complimentary area; ABS/CSm, absorption flux per CS (at t = Fm); TRo/CSm, trapped energy flux per CS (at t = Fm); DIo/CSm, dissipated energy flux per CS (at t = Fm); ETo/CSm, electron transport flux per CS (at t = Fm); PIabs, performance index on absorption basis.

2.5 Cellular microstructure analysis

Stomatal scanning electron microstructures and chloroplast ultrastructures were sampled at 10 am at each time point: 5 × 5 mm leaves of leaf margin and midvein were removed and placed into 2.5% glutaraldehyde, followed by treatment of slices with 1% osmium tetroxide as fixator, and dehydrated in increasing concentrations of ethanol and further treatment as described by Fang et al.³². The cured resin blocks were photographed under JSM-6490LV (JEOL Co., Akishima, Japan) scanning electron microscope (SEM) and JEM-1400 (JEOL Co., Akishima, Japan) transmission electron microscope (TEM). Starch content was measured by the anthrone method³³.

2.6 RNA extraction, library preparation, and RNA sequencing

Total RNA was extracted from the leaves of the control plants and plants subjected to severe drought stress using the Quick RNA isolation Kit (Huayueyang Biotech Co., Ltd., Beijing, China) according to the instruction manual. RNA integrity was checked through agarose gel electrophoresis (1.2%), and RNA concentration was estimated using an Agilent 2100 Bioanalyzer (Agilent Technologies, Inc., Santa Clara, CA, USA). Biomarker Technologies Corporation (Beijing, China) performed sequencing and cDNA library construction on the Illumina Nova seq 6000 (San Diego, CA, USA) by Biomarker Technologies Corporation (Beijing, China). In line with the manufacturer’s guidance, the cDNA library was established, and low-quality sequences were discarded by purification. And clean reads in each library mapped to the Xanthoceras sorbifoliaum reference genome³⁴. The raw RNA-seq data are available in the National Center for Biotechnology Information (NCBI) under SRA accession number: SRP335329. Analysis of differently expressed genes (DEGs) between samples was performed using the DESeq package. FDR ≤0.05 and | log2 (fold change) |≥2 were set as the thresholds for the significance of the gene expression difference. Then, the DEGs were annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment³⁵. DEGs involved in photo-dependent responses and related pathways in photo cooperation were identified based on KEGG and GO annotations. Their co-regulatory cis-regulatory elements of 2 KB promoter sequences were evaluated using MEME Suite software (version 4.9.0)³⁶ to identify transcription factors that might target these genes. The expression profiles of photosynthesis and TF genes were obtained from transcriptome data and then, based on Pearson correlation (p < 0.05, | r |≥0.75), the detection of gene expression related to the network. The gene regulatory network was constructed by Cytoscape software (version 3.9.0)³⁷.

2.7 Equations and mathematical expressions

To validate the reliability of transcriptome data, 8 genes were randomly selected from DEGs for RT-qPCR. RT-qPCR experiments were analyzed on ABI 7500 (Applied Biosystems, Carlsbad, USA) using the same RNA samples. UBC2 (EVM0006862) was used as an internal control. Primer3Plus designs the specific primer pairs of the selected genes, and the primer sequences are listed in Table S1. The relative expression levels of genes were analyzed using the 2^−ΔΔCt method, and each sample was repeated three times. Pearson correlation analysis was performed between the data of RT-qPCR and transcriptome sequencing.

2.8 Statistical analysis

The data are presented as the average mean values of four biological replications. Statistical analyses were processed with the help of SPSS version 19.0 (SPSS Inc., Chicago, IL, United States). The significant differences between mean values were determined using One-way ANOVA with Duncan multiple range tests among group means (p < 0.05).

3 Results

3.1 Effects of drought stress on photosynthetic characteristics and fluorescence parameters of seedlings

Studies have shown that stomatal conductance is the best physiological indicator for early drought response. Photosynthetic parameters and chlorophyll fluorescence have been widely used in stress research as a noninvasive method³⁸. Therefore, under drought conditions, we measured the physiological parameters related to photosynthesis to describe better the physiological state of plants affected by drought stress and the changes in water deficit response from the perspective of photosynthesis.

The water content of leaves before stress treatment was 89.67%, which decreased by 69% and 81% compared with the control at 8 and 17 days of drought stress, respectively (Figure 1a). At 8 and 17 days of drought stress, stomatal conductance decreased by 68.42% and 85.95%, respectively, compared with the control (Figure 1b), while chlorophyll content (SPAD) significantly decreased by 16.66% only at 17 days of drought stress (Figure 1c). Under different drought stress conditions, the Fv/Fm and ETR of seedlings were lower than those of the control, especially under severe stress, which significantly decreased by 12.52% and 22.74%, respectively. In comparison, NPQ increased dramatically by 64.3% (Fig. 1d-1f). Starch content increased significantly under moderate stress and decreased under severe pressure (Figure 1g). The activity of Rubisco decreased gradually and significantly reduced by 32.20% and 56.98% under moderate and severe drought stress compared with the control, respectively (Figure 1h).

Figure 1. Physiological analysis of seedlings in response to drought stress: (a) the leaf water content (RWC); (b) the stomatal conductance (gs); (c) the chlorophyll value (SPAD); (d) Maximum quantum efficiency (Fv/Fm); (e) Linear electron transport rate (ETR); (f) Non-photochemical reaction quenching coefficient (NPQ); (g) the starch content; (h) 1,5-diphosphate ribulose oxygenase (RUBP). CK- Control group; 8DASI–8 days after drought stress; 17 DASI- 17 days after drought stress; Significant differences are indicated (P ≤ 0.05).

3.2 Effects of drought stress on chlorophyll fluorescence dynamics curve of seedlings

To further assess the impact of drought on the photochemical properties of seedling photosystem II, the transient oxygenation-dependent chlorophyll fluorescence (OJIP) curve was employed to evaluate changes in chlorophyll fluorescence^39,40. Under different drought stresses, higher fluorescence intensity was detected at the JI stage (Figure 2a). In contrast, fluorescence intensity decreased at the IP stage, resulting in significant changes in the shape of the OJIP curve. Compared with the control, an apparent rise in the Fo value of seedlings was noticed under moderate drought stress, with an even more conspicuous enhancement being seen under high pressure. In addition, a decrease in FM was observed after drought stress was applied, especially for severely stressed plants.

Figure 2. Chlorophyll fluorescence induction curves and fluorescence parameters of seedlings exposed to drought stress: (a) the effects of drought on the OJIP transients; (b) Radar diagram of chlorophyll fluorescence parameters of seedlings. a.U.—arbitrary units. ABS/RC: Absorption flux per reaction center; DIo/RC: Dissipated energy flux per RC; ETo/RC: Electron transport flux per RC; φPo: Maximum quantum yield of primary photochemistry; φEo: Quantum yield for electron transport; φO: Probability that a trapped exciton moves an electron into the electron transport chain beyond; VJ: Relative variable fluorescence at the J-step; VI: Relative variable fluorescence at the I-step; Sm: Normalized total complimentary area; ABS/CSm: Absorption flux per CS; TRo/CSm: Trapped energy flux per CS; DIo/CSm: Dissipated energy flux per CS; ETo/CSm: Electron transport flux per CS; PIabs: Performance index on absorption basis.

Several physical parameters were obtained from the chlorophyll fluorescence kinetics curve, plotted in Figure 2b. Compared with the control, ABS/RC, TRo/RC, and DIo/RC in each reaction center increased after different drought stress, and the increase of DIo/RC was more prominent. Meanwhile, we observed that φPo, φEo, and φO all decreased in response to drought, which indicated that the reduced efficiency of photosynthesis under drought stress limited the number of active reaction centers of PSII, which further led to the decrease of captured energy in each leaf cross section and the decrease of performance index PI_abs.

3.3 Effects of drought stress on stomatal microstructure and chloroplast ultrastructure in leaf

Since stomatal closure is the most rapid physiological response to water deficiency, we studied stomatal microstructure and conductance. SEM images showed that stomata were open, guard cells were whole, and surrounding cells were smooth and smooth under the control condition (Figure 3a). After 8 days of drought stress, stomata closed, guard cells began to lose water, and surrounding leaf cells began to shrink (Figure 3b). After 17 days of drought stress, the guard cells lost water and shriveled, the stomata were deeply trapped in the surrounding leaf cells, the stomata were shorter, narrower, and thinner, and the surrounding leaf cells were severely shriveled (Figure 3c). In addition, the stomatal width and stomatal aperture of drought-treated leaves decreased significantly while stomatal density increased gradually.

Figure 3. Scanning electron microscope (SEM) and chloroplast ultrastructure (TEM) images of leaves: (a) Stomatal structure under normal conditions; (b) Stomatal structure in moderate drought; (c) stomatal structure under severe drought; (d) Chloroplast ultrastructure in normal condition; (e) Chloroplast ultrastructure in moderate drought; (f) Ultrastructure of chloroplast in severe drought. ST: starch granules; CH: chloroplast; W: cell wall; PG: plastoglobules. The stomatal structure was 50 μm, and the chloroplast ultrastructure was 200 nm.

We observed leaves at the seedling stage using transmission electron microscopy to compare chloroplast ultrastructure under different drought stresses. Under the control condition, the chloroplasts in the leaves were ovally arranged, close to the cell membrane, and the thylakoids were well organized, with fewer starch particles and plastid distributed (Figure 3d). Under moderate drought stress, chloroplasts surrounded and accumulated more starch grains and plastid (Figure 3e). Under severe drought stress, chloroplasts expanded significantly, their contours tended to be wavy, thylakoids were disordered, lamellar gaps were enlarged, starch particles were degraded, and the number and volume of plastoglobules increased significantly (Figure 3f).

3.4 Function analysis of differentially expressed genes in response to drought and comment on photosynthetic metabolic pathways

We annotated the GO function of 4,672 differentially expressed genes in drought stress and identified five significant GO terms in each GO category. We found that among 1,672 upregulated gene biological processes (BP), the most representative ones are “response to stimuli” and “Regulation of transcription, DNA-templated” (Figure 4a). While in the case of 3,000 downregulated genes, the most important BP is “photosynthesis,” “metabolic process,” and “metabolic process” (Figure 4b).

Figure 4. Gene Ontology enrichment of DEGs under drought stress (p ≤ 0.05): (a) GO category of up-regulated DEGs; (b) GO category of down-regulated DEGs.

In addition, we extracted the following genes represented by GO terms: photosynthesis, photosynthesis-light harvesting, photosystem II assembly, photosynthesis-light harvesting in photosystem I, photosystem II, photosystem I, photosystem II oxygen-evolving complex, photosystem I reaction center. After removing the redundant genes, KEGG functional annotation was performed on 47 DEGs (Table S2). The most abundant approach was “Photosynthesis – antenna proteins,” Photosynthesis,” Porphyrin and chlorophyll metabolism,” including seven subunits encoding photosystem II (11 differentially expressed genes), seven subunits encoding photosystem I (9 differentially expressed genes), and a component of the electron transport chain (1 differentially expressed gene). Two subunits of ATPase (1 differentially expressed gene) (Fig. S1A); 12 differentially expressed genes were involved in “antenna proteins” (encoding 6 LHCA and 6 LHCB proteins) (Fig. S1A-1B); Six of them were engaged in Porphyrin and Chlorophyll metabolism (four encoding Protochlorophyllide reductase, one encoding Geranylgeranyl diphosphate reductase, one encoding Magnesium-chelatase subunit Chll).

3.5 Promoter analysis of photosynthesis-related genes and RT-Qpcr validation

Twenty-three candidate regulators were defined by promoter analysis (Table S3). A correlation network between TFs and photosynthesis-related genes was subsequently constructed (Figure 5), and AP1 (EVM0024438) was found to be associated with a large proportion of photosynthetic genes (degree ≥22).

Figure 5. Correlation between qPCR and RNA sequencing for the eight selected genes.

Eight photosynthesis-related genes were selected for quantitative real-time PCR validation from genes significantly differentially expressed under drought treatment. Each sample was repeated three times to verify the reliability of transcriptome expression data. This experiment’s Pearson correlation analysis indicated significant positive correlations between RT-qPCR and RNA-seq data (R² = 0.87, Fig. S2). Therefore, the results provided transcriptome and expression profile data for further studies on the essential genes of yellow horn,^41,42.

4 Discussion

Balancing photosynthesis under abiotic stress is essential to improve plants’ survival, biomass, and yield. The purpose of this study was to reveal the physiological and molecular basis of the photosynthesis process in yellow horn under drought stress. To achieve this goal, photosynthetic physiological characteristics, stomatal microstructure, and chloroplast ultrastructure were analyzed, and leaf transcriptome was analyzed using high-throughput sequencing technology.

The Fv/Fm of seedlings decreased gradually with the deepening of drought degree, indicating that drought stress reduced the electron transport capacity and primary photochemical activity of PSII and the adverse effects of excessive excitation energy accumulation on photosynthesis⁴³. The more Fv/Fm decreased, the higher the inhibition degree was, indicating the more severe damage, which was also the manifestation of the loss of the photosynthetic membrane function of PSII. When seedlings were subjected to extreme drought stress, ETR decreased significantly under high pressure, which may be caused by the activation of non-photochemical extinguishing mechanisms⁴⁴. Both NPQ and energy dissipation DIo/RC ratio increased significantly under severe drought stress, demonstrating that excess excitation energy dissipated as heat and thus protected PSII from excessive exposure^45–47. The OJ curve of seedlings treated with drought stress was higher than that of control plants. This indicates that QA reoxidation was inhibited, and QA accumulation was more significant due to electron reduction efficiency⁴⁸. At the IP stage, the plants had a lower curve than the control plants, indicating that the electron donor on the PSII donor side slowed down⁴⁹, reducing the capacity of all PSII electron donors. In addition, PI_abs decreased significantly. Compared with Fv/Fm, PI_abs showed a more significant decline, consistent with the previous results; PI_abs was more sensitive to environmental factors than Fv/Fm. In addition, drought stress reduced Rubisco activity, reducing CO₂ assimilation and plant photosynthesis^50,51. Transcriptional results revealed the downregulation of differentially expressed genes associated with photosynthesis. PsbQ is necessary to regulate the activity of PS II⁵², while PsbP and PsbQ can stabilize PS II and six other genes (PsbA, PsbD, PsbC, PsbI, PsbZ, Psb27)⁵³, and PsaO plays a role in the binding of light-trapping pigment complexes⁵⁴. In addition, the deficiency of LHCB1 and LHCB2 reduces light absorption, which leads to a decrease in energy transfer efficiency in plants lacking LHCB5 and LHCB6⁵⁵. These results further indicate that the photosystem is damaged and photosynthesis is decreased under drought stress, which may be related to the decreased transcriptional activity of these genes.

Studies have shown that with the increase of drought degree, stomatal density changes with species differences, either increased, decreased, or increased and then decreased^56–58. This study showed that stomatal density per unit area increased gradually with the extension of drought stress time, which may be related to decreased leaf area after drought stress treatment⁵⁹. Scanning electron microscopy (SEM) showed that stomatal width and aperture decreased significantly after drought stress and experienced the process from opening to closing, guard cells from complete to dry, and surrounding leaf cells from smooth to severe shrinkage. CDPK is associated with abiotic stress response and abscisic acid (ABA) signaling. Transcriptional results showed that CPK9 (EVM0023503) was up-regulated under drought stress, consistent with OsCPK9 promoting stomatal closure to impart drought tolerance. In addition, stomatal conductance decreased with the deepening of drought stress. Many studies have shown that drought stress can reduce leaf water content and degrade chlorophyll. The change in chlorophyll content can reflect the evolution of the photosynthetic capacity of leaves to a certain extent. In this study, the decrease of chlorophyll content under severe drought stress was consistent with previous studies^60,61. At the same time, in the KEGG pathway, we found that carbon and nitrogen metabolism activities were inhibited, which resulted in carbon and nitrogen deficiency. The deficiency of carbon and nitrogen seriously affects the development of chloroplast, decreasing chlorophyll SPAD value. At the same time, differentially expressed genes involved in chlorophyll metabolism were significantly down-regulated, which may be the critical limiting genes for chlorophyll content reduction.

PGs are dynamic in size and shape and are thought to be involved in abiotic, biostress adaptation processes or chloroplast development^62,63. PGs contain neutral lipids, isoprene, and carotenoids^21,64–66. With the increase of drought degree, starch granules increased and then decreased, while plastid increased and expanded. Under moderate stress, the internal color of the plastid was lighter, and the edge was pure black, consistent with previous studies⁶⁷. Several studies have reported that jasmonic acid biosynthesis pathways were discovered within PGs, such as a heightened abundance of LOX, AOS, and AOC^65,67. Studies have shown that the upregulation of LOX and AOS leads to a significant accumulation of endogenous JA⁶⁸ and increases plant tolerance to drought⁶⁹. In conclusion, drought stress affected the ultrastructure and stomatal regulation of seedlings.

This study demonstrates that chloroplast thylakoids are reduced, impeding the photosynthetic process. The chlorophyll content, photosynthetic electron transfer capacity, and some chlorophyll fluorescence parameters were reduced, which led to the decline of leaf photosynthetic capacity. Leaf ultrastructure and chloroplast microstructure were also significantly affected by drought stress. The genes related to photosynthesis were down-regulated due to lack of water, which provided some candidate genes for the genetic study of photosynthesis and the improvement of drought tolerance.

Authorship

The authors confirm their contribution to the paper: study conception and design: Jinping. G; data collection: Fang. H; analysis and interpretation of results: Fang. H; draft manuscript preparation: Fang. H; supervision: Yunxiang. Z. All authors reviewed the results and approved the final version of the manuscript.

Compliance with ethical standards

The authors declare that this article complies with the journal’s standards.

Nomenclature

RWC	=	Relative water content
gs	=	Stomatal conductance
SPAD	=	Chlorophyll value
Fv/Fm	=	The maximal photochemical efficiency of PSII
ETR	=	Linear electron transport rate
NPQ	=	Non-photochemical quenching
RUBP	=	1,5-diphosphate ribulose oxygenase
PG	=	Plastoglobules
PQ	=	Plastoquinone
QA	=	Primary PS II quinone electron acceptor
ABS/RC	=	Absorption flux per reaction center
DIo/RC	=	Dissipated energy flux per RC (at t = Fo)
ETo/RC	=	Electron transport flux per RC (at t = Fo)
φPo	=	Maximum quantum yield of primary photochemistry
φEo	=	Quantum yield for electron transport (at t = Fo)
φO	=	Probability that a trapped exciton moves an electron into the electron transport chain beyond QA (at t = Fo)
φO	=	Probability that a trapped exciton moves an electron into the electron transport chain beyond QA (at t = Fo)
VJ	=	Relative variable fluorescence at the J-step
VI	=	Relative variable fluorescence at the I-step
Sm	=	Normalized total complimentary area
ABS/CSm	=	Absorption flux per CS (at t = Fm)
TRo/CSm	=	Trapped energy flux per CS (at t = Fm)
DIo/CSm	=	Dissipated energy flux per CS (at t = Fm)
ETo/CSm	=	Electron transport flux per CS (at t = Fm)
PIabs	=	Performance index on absorption basis

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15592324.2023.2215025

Additional information

Funding

This research was funded by Shanxi Key Laboratory of Cultivation & Development on Functional oil trees in northern China and the Conservation of Fine Seedlings of Xanthoceras sorbifolium Bunge and Clonal Breeding of Excellent Varieties.