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. 2024 Apr 19;14(5):132. doi: 10.1007/s13205-024-03980-1

Concurrent effect of drought and heat stress in rice (Oryza sativa L.): physio-biochemical and molecular approach

Kongkong Mondal 1, Rup Kumar Kar 2, Abhra Chakraborty 3, Narottam Dey 1,✉
PMCID: PMC11031549  PMID: 38645792

Abstract

The present study was carried out to investigate the physio-biochemical and molecular responses of two rice genotypes (Noichi and N22) under drought, heat and combined drought/heat stress conditions. The antagonistic stomatal activity was found under the combined stress conditions; stomata were open under control and heat stress, conversely, stomata remained closed under drought and combined stress levels. Photosynthetic activity and chlorophyll content are decreased by the overproduction of reactive oxygen species and increased lipid peroxidation in both rice genotypes. To prevent oxidative damage, many antioxidant enzymes like catalase (CAT), ascorbate peroxidase (APX) and superoxide dismutase (SOD) are produced in both genotypes under these conditions. Under the single stress conditions, CAT activity were increased in N22, whereas combined stress levels, SOD and APX activity were higher for both genotypes. Proline accumulation was also increased under single as well as combined stress conditions for both genotypes to combat stress injuries. Pollen viability was lost under all stress levels but severe loss was found under combined stress levels, which causes spikelet sterility leading to yield losses for both genotypes. As evident from transcript levels, HSP71.18 and HSP71.10 expressions were higher under single and combined conditions, butHSP72.57 gene expression increased only by individual stress levels. WRKY11, WRKY 55, DREB 2A, LEA3 and DHN1 were positively expressed under all stress levels. Conversely, expression of DREB2B genes was higher only under single stress levels. In summary, these results suggest that the effect of combined stress is different from the single stress and it is more severe than the individual stress.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-03980-1.

Keywords: Drought, Heat stress, Combined stress, Photosynthetic activity, ROS, Pollen viability, Spikelets sterility, Yield, Transcripts

Introduction

Since global warming causes elevated temperatures and a lowering of precipitation, drought and heat waves are becoming common issues in many parts of the world. Among the different stresses, drought and heat stresses are major threats to crop yield and productivity (Lipiec et al. 2013; Awasthi et al. 2017). In the past, most of the studies have been carried out on the single effect of drought and heat stress on plants under laboratory conditions. However, in field conditions, drought and heat stresses occur most often concurrently, which appears to be more severe than their singular effect (Mittler 2006; Suzuki et al. 2014). Interestingly, plants usually show an antagonistic response under single or combined stress; for example, under drought plant closes its stomata to check water loss while under heat plant opens its stomata to keep the plant body cool through transpiration. Conversely, under the combined condition stress stomata remain closed to check water loss, therefore, increasing leaf temperature (Rizshky et al. 2002; Mittler 2006). Under the drought and heat stress individually, plant growth, biomass, leaf area, and photosynthetic efficiency become low, however, such decline becomes more aggravated when these stresses occur simultaneously (Awasthi et al. 2017; Hussain et al. 2019; Alhaithloul 2019; Yadav et al. 2022). Practically, under these stress conditions, plants produce different reactive oxygen species (ROS) like superoxide anion (O2−), hydrogen peroxide (H2O2) etc., which are increased in cells causing increased lipid peroxidation and inhibition of photosynthetic efficiency, termed as oxidative damages (Mittler 2004; Choudhury et al. 2016). To mitigate this ROS production and check the cellular damage plants produce many antioxidant enzymes, like superoxide dismutase (SOD), catalase (CAT), and ascorbate peroxidase (APX) (Mittler, 2004). Apart from the antioxidant machinery, under these stressful conditions, plants also accumulate many osmoregulators, like proline, amino acids, soluble sugar, and glycine-betaine (GB) to maintain cellular water levels. In a recent study, it is revealed that many genes are expressed under the combined drought and heat stress that helps the plants to acclimatize under these stressful conditions (Alhaithloul 2019; Raja et al. 2020). The effect of stress varies among plant species and depends upon the stages of plants. Thus, the reproductive phases are more affected than vegetative stages under these combined stress conditions (Cohen et al. 2021). Pollen sterility and female reproductive sterility are the major causes of yield loss in crops (Kaushal et al. 2013; Fábián et al. 2019).

Rice (Oryza sativa L.) is one of the staple crops in Asia and more than half of the world population’s feeding depends upon it (Wassmann 2009; Da Costa et al. 2021a, b). Rice is grown under well-watered conditions where soil matric potential is almost zero (Todaka et al. 2015). For rice cultivation, the optimum temperature (27–32 °C) and water availability (nearly 3000–5000 L water for 1 kg of grain production) are crucial; therefore, it is more sensitive to drought and extreme temperature conditions as compared to other cereal crops, such as maize and wheat (Bouman 2009; Ji et al. 2012; Da Costa et al. 2021a, b). It is predicted that by 2025, approximately 20–25 million hectares of land area will be suffering from water scarcity (Ben et al 2017). Along with drought stress, heat stress also hampers the normal growth and productivity of rice (Hoque et al. 2020). Increasing temperatures of more than 33 °C can severely affect rice yield and quality (Jagadish et al. 2007; Lawas et al. 2018). In addition, by 2030, 16% of rice-growing land may be affected by heat waves and it could exceed 27% by 2050 (Gourdji et al. 2013). During drought and heat stress plants exhibit many physiological, metabolic, and molecular responses that are different from their single effect (Silva et al., 2010; Jin et al., 2016). Many studies have been done about the combined effect of drought and stress on different crops (Awasthi et al. 2017; Hussain et al. 2019; Fábián et al. 2019; Raja et al. 2020), but few reports are available about rice (Jagadish et al. 2011; Li et al. 2015; Lawas et al. 2018, 2019; Yadav et al. 2022).

In the southwestern districts of West Bengal (India), where drought and high temperatures are recurring issues year after year, some indigenous rice landraces are grown by a few farmers and growers (Karmakar et al. 2012; Bhunia et al. 2020). These landraces have the potential to tolerate osmotic stress (Karmakar et al. 2012). Keeping this in mind, we have selected one upland, drought-tolerant rice landrace Noichi, usually grown in Bankura (Karmakar et al. 2012) along with a rice cv. N22, which is known to be tolerant of both drought and heat stress (Jagadish et al. 2010; Yadav et al. 2022), to investigate their morpho-physiological, biochemical and molecular responses under drought and heat stress, independently as well as in combination. We have also explored how these responses affect pollen viability and yield-related attributes.

Material and methods

Plant materials and plant growth

The present investigation involves two rice lines, one is an improved rice variety N22 (Drought and heat stress tolerant) and another is a West Bengal upland drought-tolerant rice landrace Noichi (details in Supplementary file S1). Seeds were germinated in plastic pots filled with artificial soil in a plant growth chamber (Daihan Labtech India Pvt. Ltd., New Delhi, India). Germinated seedlings were then transferred to the plastic pots (15 cm height × 12 cm diameter) containing soil with three plants planted in each pot. From the seedling stage to the mature stage (Just before the onset of the booting stage) plants were maintained under natural environmental conditions.

Imposition of stress

Just before the onset of the booting stage of rice plants, drought (7 days of water withdrawal) and heat stress (39 °C for 6 h/day for 5 days) were induced individually and jointly (combined drought and heat stress). In the case of control groups a normal temperature (27  C) and sufficient water was provided. Four experimental groups were established for each rice line: Control (sufficient water at 27 °C), drought stress (water withdrawal until the leaf RWC decreased to 60%), heat stress (sufficient water at 39 °C for 6 h/day for 5 days) and severe drought and heat stress (5 days water withdrawal with 39ºC temperature for 6 h/day) applied jointly. The whole experiment was conducted with three sets in a plant growth chamber and 70% relative humidity was maintained all along. After the end of the stress condition, one sets of plants were maintained in the natural environment for recovery until the harvesting of grain and another two sets of plants were used for different morpho-physiological, biochemical and molecular studies. Each set was maintained in triplicate. The experimental setup and experimental design were modified from earlier protocol by Jagadish et al. (2011), Zandalians et al. (2018) and Hussain et al. (2019) (Fig. 1a and b).

Fig. 1.

Fig. 1

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a Experimental setup: The effect of Drought (D), Heat (H), and their combined (D + H) conditions on N22 and Noichi Cultivars compared with Control(C) condition. b Experimental design used to subject N22 and Noichi Cultivars to control, drought, heat, and a combination of drought and heat stress with details of period times for each stress treatment

Sample collection

When stress occurred on the plants (7 days after drought treatment and 5 days after heat and drought + heat stress), then stressed and non-stressed (control) leaf tissues were collected for different morpho-physiological, biochemical and molecular assessments.

For yield parameters, seeds of mature plants (after the recovery of plants) were harvested. Yield parameters like panicle length, total number of spikelets per panicle, sterile spikelets per panicle and 100-grain weight were recorded.

Morphological parameters

For assessment of morphological traits, shoot and root tissue were collected from treated and untreated plants and shoot and root fresh and dry weights were measured. Dry weight was measured after drying the tissue in an oven at 60 ◦C for 72 h. The leaf area (LA) of rice plants was assessed following the formula of Montgomery (1911): LA = L × W × 0.75, where L indicates leaf length, W represents the maximum leaf width, and 0.75 is the factor used for the determination of leaf area in rice.

Physiological parameters

Relative water content (RWC)

Rice leaf tissues were collected and weighed immediately to get the fresh weight (FW). The leaf tissues were then rehydrated in water for 24 h until they attained full turgidity, surface-dried and reweighed to get the turgid weight (TW). Finally, the tissues were oven dried at 80 °C for 48 h (until constant weight), and were reweighed to obtain the dry weight (DW). The RWC was calculated using the formula of Bhushan et al. (2007).

RWC%=FW-DW/TW-DW×100

Where, RWC = relative water content, FW = fresh, weight, DW = dry weight, TW = turgid weight.

Histochemical study

Stressed and non-stressed leaf tissues of both genotypes (Noichi and N22) were collected and incubated in DAB and NBT solution (4–16 h at 37 °C) for detection of H2O2 or O2− respectively. Chlorophyll was removed by immersing in absolute ethanol at boiling temperature for proper visualization of the stain (Kumar et al. 2014).

Quantum yield (Fv/Fm)

Fv/Fm was measured using the PAR-FluorPen FP 110/D as per the manufacturer’s instructions. The leaf of a dark-adapted plant (for 30 min) exposed to actinic light of 3000 µmol photons m−2 s−1 and maximum Quantum yield (Fv/Fm) was measured.

Pigment estimation

After the occurrence of stress, leaf tissues were collected and ground in 80% chilled acetone (Arnon 1949). The supernatant was taken for the determination of photosynthetic pigments using a spectrophotometer (Spectra Max M3). The absorbance values at 663 nm, 645 nm and 470 nm were measured and the pigment concentrations were calculated using the following formula (Bhushan et al. 2007).

Chlorophyll amg/g=12.7∗A 663-2.69∗A 645v/w
Chlorophyll bmg/g=22.9∗A 645-4.68∗A 663v/w
Total chlorophyllmg/g tissueD652 V/34.5 W/Chl a+Chl b
Carotenoidmg/g=1000∗A470-3.27∗chlorophyll a+1.04∗chlorophyll b/227 v/w

Biochemical parameter

Membrane stability index (MSI)

The Membrane stability index was determined following the method of Alhaithloul (2019). Leaf samples (100 mg each) were cut into small pieces and immersed in 10 ml double distilled water in two sets. One set was kept at 40 °C for 30 min and another set at 100 °C in a boiling water bath for 15 min and their respective electric conductivities, C1 and C2 were recorded. The following formula was used to calculate the MSI: Membrane stability index = [1− (C1/C2)] × 100

Lipid peroxidation

Malondialdehyde (MDA) content was measured using the thiobarbituric acid method according to Chen and Zhang (2016) and Sahu and Kar (2018). Absorbance was taken at 532 and 600 nm. A molar coefficient of 155 mM.cm−1 was used for calculation and expressed as µmol g−1 FW.

Hydrogen peroxid

100 mg fresh tissue was homogenated in 0.1% trichloroacetic acid (2 mL, TCA). Homogenate was centrifuged at 12,000× g for 15 min and 0.5 mL of supernatant was mixed with 0.5 mL potassium phosphate buffer (10 mM, pH-7.0) and 1 M potassium iodide (1 mL). Absorbance was determined at 390 nm (Velicova et al. 2000) and the content was calculated using the standard curve with a known concentration of H2O2 and expressed as µMol.g-1FW

Electrolyte leakage

Electrolyte leakage was estimated by immersing leaf discs in a test tube containing 10 ml of deionized water, and the initial electrical conductivity (ECa) was measured. The tissue-containing tubes were then heated in a water bath at 50 °C for 25 min and 100°ºC for 10 min to measure the respective electrical conductivities (ECb) and (ECc) respectively (Alhaithloul 2019). The following formula was used for calculation:

Electrolyte Leakage%=ECb-ECa/ECc×100

Estimation of enzymatic antioxidants

Enzyme extraction

Enzyme were extracted according to method of Chen et al. (2016). Briefly, 200 mg leaf sample was homogenized in frozen in liquid nitrogen and finely ground by a pestle in a chilled motor and the frozen powder was added to 3 mL of phosphate buffer (pH 7.0). The homogenate was centrifuged at 15,000 × g for 15 min at 4 °C and supernatant was used as crude enzyme source for catalase (CAT), superoxide dismutase (SOD) and ascorbate peroxidase (APX).

Catalase activity

The assay mixture in the total volume of 3 mL contained 0.5 mL of 0.2 M phosphate buffer (pH 7.0), 0.3 mL of (v/v) H2O2 (0.3%) and 0.1 ml of the enzyme. The final volume was made 3 ml by adding distilled water. The reaction was started by adding enzyme extract and change in optical density was measured at 240 nm at 0 min and 3 min in a spectrophotometer (Luck 1974; Aebi 1983).

Ascorbate peroxidase (APX) activity

Three (3.0) ml of the reaction mixture consisting of 1.5 ml 100 mM phosphate buffer(pH-7), 300 μl ascorbate (5 mM), 600 μl H2O2 (0.3%) and 600 μl enzyme extract was taken and the reaction was started after the added H2O2. The decrease in absorbance was recorded for 1 min at 290 nm and and the amount of ascorbate oxidized was calculated from the extinction coefficient of 2.8 mM−1 cm−1 (Nakano and Asda et al. 1981).

Superoxide dismutase (SOD) activity

Three ml of reaction mixture containing 0.1 ml of 1.5 M Na2CO3, 0.2 ml of 200 mM methionine, 0.1 ml of 3 mM EDTA, 0.1 ml of 2.25 mM p-nitroblue tetrazolium chloride (NBT), 1.5 ml of 100 mM potassium phosphate buffer (pH 7.5), 1 ml of distilled water was added with 0.05 ml of enzyme samples. The tube without enzyme was taken as a control. The reaction was started by adding 0.1 ml 60 μM riboflavin and placing the tubes below a light source of two 15 W fluorescent lamps for 15 min. The reaction was stopped by switching off the light and covering the tubes with black cloth. Absorbance was recorded at 560 nm. An illuminated blank without enzyme gave the maximum reduction of NBT, and therefore, the maximum absorbance at 560 nm. The activity of SOD was expressed as unit.min−1.g−1. (Giannopolitis and Ries 1977).

The enzyme activity was estimated using the formula: (∆A × T)/(t × v × w) where, ∆A = change in absorbance, T = total volume of the enzyme extract, t = incubation time in minutes, v = volume of enzyme in the reaction, w = dry weight of the tissue The enzyme activity was expressed as unit.min−1.g−1 DW (Sahu and Kar 2018).

Osmolyte accumulation

Free proline contents were determined by following the acid ninhydrin method (Bates et al. 1973). 50 mg leaf tissue was crushed with 2 ml of 3% sulphosalicylic acid and centrifuged at 5000 rpm for 10 min. Two ml of supernatant mixed with 2 ml of acid ninhydrin and 2 ml of glacial acetic acid and incubated for 1 h in 100 °C water bath. The reaction was stopped by placing the tubes in ice. Then, 4 ml of toluene was added with the mixture, vortexed and left for 30 min at room temperature. Absorbance (520 nm) was taken of the upper phase of the mixture (chromophore of toluene). Toluene was used as the blank and the standard curve of L-proline was used to determine free proline content (mg/g FW).

Microscopic study

Stomatal aperture

The leaves of treated and untreated plants were fixed in 2.5% glutaraldehyde for 1 h and washed in 0.1 M sodium–potassium phosphate buffer solution for 10 min followed by dehydration in acetone for 10 min. To dry samples completely, each sample was placed in a critical point dryer (Hu et al. 2017). Samples were mounted on aluminum stubs, attached with carbon sticky tabs, and coated with approximately 20 nm of gold via an ion. Finally, stomatal pictures were observed under a scanning electron microscope (Gemini-450, ZEISS).

Pollen viability test

Six anthers before flowering were removed from a spikelet and placed on a glass slide. The anthers were crushed into a fine powder and stained with 10 mL of 1% (v/v) of I2 in 3% (v/v) KI, and 1 mL was sampled to observe fertile and infertile pollen using a light microscope (Chhun et al. 2007).

Measurement of grain yield parameters

For the analysis of yield parameters, panicle length, total number of spikelets panicle−1, spikelet sterility rate (percentage of sterile spikelets over the total number of grains panicle−1) and 100-grain weight were estimated at harvesting time (Hussain et al. 2019). Each mature plant was harvested individually. The panicles were manually threshed, and the 100-grain weight was measured using a precision balance.

Gene expression study

RNA isolation and cDNA synthesis

Total RNA isolation from control and stressed rice leaves of Noichi was done using RNA isolation kit (Qiagen RNeasy Plant Mini Kit, Germany) and cDNA was synthesized using Thermo Fisher Scientific Revert Aid First-Strand cDNA Synthesis Kit following the manufacturer’s instruction. These synthesized cDNAs were then used for expression analysis of eleven stress-responsive genes and ubiquitin (UBQ) was used as a reference gene. The qRT-PCR was done in the BIORAD CFX™ Duet RT-PCR system with SYBR Green Master mix. The sequences of the primers used in RT-PCR are listed in Supplementary file S1. Gene expressions were calculated following 2−∆∆CT method (Schmittgen and Livak 2008).

Statistical analysis

All experiments were conducted with three replications and data were presented as mean ± standard error around mean (SEM). Significance differences between control and treatment sets were determined by ANOVA with Tukey’s Honestly Significant Difference (Tukey’s HSD) test (p < 0.05) using R version 3.6.0 software. P-values from ANOVA with Tukey’s HSD test for different parameters have been provided in supplementary file S2. Microsoft Excel 2016 was used for the graphical presentation of data and a heat map was created through SRplot. To find out the correlation among different morpho-physiological, biochemical and yield-related parameters correlation heat map was prepared through SRplot.

Results

Normal plant morphological characters like shoot and root fresh weight, as well as dry weight, were decreased by drought, heat stress and their combination for both the rice lines but more reduction occurs under combined conditions. At the individual and combined stress levels, shoot fresh weight was reduced by 41% and 55% respectively in comparison to control. Shoot dry weight is also reduced by 39–46% under drought and heat stress conditions and it is higher (75%) under combined stress conditions irrespective of control conditions. Similarly, root fresh weight significantly decreased under drought and combined stress levels (65–70%). Root dry weight was decreased 38–40% under single stress levels for both genotypes. However, under the combined stress levels reduction rate is higher in N22 (74%) than occurs in Noichi (50%) (Fig. 2a–d).

Fig. 2.

Fig. 2

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Influence of single and combined drought/heat stress on different morpho-physiological parameters: a shoot fresh weight, b shoot dry weight, c root fresh weight, d root dry weight, e Leaf area, f RWC. Data represents means ± SE (n = 3) and significant difference calculated at p < ‘*’0.05 < ‘**’ 0.01 < ‘***’0.001

Leaf area and RWC

Leaf area decreased in both rice lines under drought, heat stress, or their combination in comparison to the control condition. Greater leaf area decreases were noted in N22 than Noichi under single or combined stress (Fig. 2e). On the other hand, under drought and heat stress conditions RWC decreased 35–40% and 25–30%, respectively compared to control for both the rice lines. Moreover, RWC decreased by 65–70% under the combined stress condition in both genotypes (Fig. 2f).

Quantum yield (Fv/Fm)

Fv/Fm ratio decreased under combined stress levels in both genotypes. Under combined stress level quantum yield decreased up to 50–65% with respect to control, decline being more in the case of N22 than Noichi. Conversely, under the drought stress conditions, minimal reduction occurs and under the heat stress conditions there was no significant changes occurred in Fv/Fm ratio for both genotypes. (Fig. 3a).

Fig. 3.

Fig. 3

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Effect of individual and combined drought and heat stress on chlorophyll fluorescence and chlorophyll pigments: a Fv/Fm ratio, b chlorophyll-a, c chlorophyll-b, d total chlorophyll, e carotenoid content. Data represent means ± SE (n = 3) and the significant difference calculated at p < ‘*’0.05 < ‘**’ 0.01 < ‘***’0.001

Pigment content

Chlorophyll and carotenoid

In comparison to control conditions, Chl-a, Chl-b, total chlorophyll and carotenoid content decreased under single or combined stress. Chl-a decreased significantly under drought and combined drought and heat stress in both genotypes (Fig. 3b) while Chl-b and total chlorophyll declined more in both the genotypes under all stress levels (3c and 3d). Carotenoid content was severely reduced under heat stress and combined drought and heat stress in both rice lines, reduction rate being higher in Noichi (Fig. 3e).

ROS generation

Endogenous H2O2 and O2− accumulation were visualized on the leaf surface under all stress conditions through ROS-specific staining. Thus, H2O2 that reacts with DAB producing a radish brown color was apparent intensely on leaf surface receiving stress (Fig. 4a). Similarly, O2− was visualized as a blue color due to its reaction with NBT forming dark blue formazan compound, again more intensely in case of stressed leaves (Fig. 4b).

Fig. 4.

Fig. 4

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ROS generation under single and combined drought/heat stress conditions: a DAB staining for determination of endogenous H2O2, b NBT staining to determine endogenous O2−, c Electrolyte leakage, d MSI, e MDA, f H2O2. Data represent means ± SE (n = 3) and the significant difference calculated at p < ‘*’0.05 < ‘**’ 0.01 < ‘***’0.001

Electrolyte leakage

Electrolyte leakage significantly increased under combined drought/heat stress for both rice lines. In the case of individual stress levels electrolyte leakage was more significant in Noichi than in N22 (Fig. 4c).

Membrane stability index (MSI)

The membrane stability index is important to understand the behavior of cell membranes under stress conditions. In this study, MSI decreased under individual as well as combined stress conditions. In the case of individual stresses, loosening of MSI was more under heat stress. Under the combined drought/heat stress conditions, MSI decreased in both the rice lines (N22 and Noichi) but the decline was more in Noichi (Fig. 4d).

MDA content and H2O2 accumulation

The content of MDA and H2O2 content increased at both individual and combined stress levels with respect to control conditions. However, the rate of increase in MDA and H2O2 content was more pronounced under combined stress levels in both rice lines. Nevertheless, MDA and H2O2 content was higher in Noichi than in N22 under the combination of drought and heat stress conditions (Fig. 4e and f).

Antioxidant enzyme activity

Catalase activity

In the case of individual stresses, under heat stress catalase activity significantly increased in both the rice lines while drought stress caused an increase in catalase activity in N22 and decline in Noichi. Under combined drought and heat stress conditions catalase activity decreased in both rice lines but the the extent of decrease was higher in Noichi in relation to the control (Fig. 5a).

Fig. 5.

Fig. 5

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Antioxidant enzyme activities and proline accumulation under individual and their combined stress level. a catalase, b APX, c SOD activity and d proline content. Data represents means ± SE (n = 3) and the significant difference calculated at p < ‘*’0.05 < ‘**’ 0.01 < ‘***’0.001

Ascorbate peroxidase (APX) activity

In both rice lines, N22 and Noichi, higher APX activity was found under drought individually as well as the combination of drought and heat stress conditions. On the other hand, under individual heat stress conditions, APX activity was higher in N22 than in the Noichi (Fig. 5b).

Superoxide dismutase (SOD) activity

SOD activity increased in both rice lines under single or combined stress in comparison to the control condition. In a single stress level, under drought conditions, Noichi showed higher SOD activity than N22. On the other hand, SOD activity was higher in the case of N22 under the combined stress levels. (Fig. 5c).

Proline content

In comparison to the control, proline content significantly increased under a combination of drought and heat stress conditions for both rice lines (N22 and Noichi). At the individual level of drought stress, proline content increased in Noichi but lowered in N22 with respect to the control. In drought stress conditions no significant changes were observed for both rice lines (Fig. 5d).

Stomatal activity

Stomatal apertures were open under control and heat stress conditions but remained closed under drought and combined stressed conditions for both the genotypes (Fig. 6).

Fig. 6.

Fig. 6

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Activity of stomata under drought, heat and their combination. Stomata are open under control and heat stress conditions (pointed by red arrow) and closed under drought and combined drought and heat stress conditions (pointed by green arrow)

Pollen viability

Pollen viability decreased under single as well as combined stress conditions, but rate of pollen sterility increased more under heat and combined stress conditions. Pollen grains that were round in shape and stained black were judged as viable or living pollen, and sterile or dead pollen stained yellow or light red as shown in Fig. 7a.

Fig. 7.

Fig. 7

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Effect of drought, heat stress and combined drought and heat stress on pollen viability and yield parameters a pollen viability under single and combined conditions; deeply black coloured pollen grains are viable and light yellow coloured pollen grains are non-viable (pointed out with black arrow), b panicle length, c total number of spikelets, d spikelet sterility, e 100-grain weight, f photograph showing the effect of single and combined stress on spikelet sterility; sterile spikelets have been pointed out with a black arrow. Box plots were created through SRolots. Data represents means ± SE (n = 3) and the significant difference calculated at p < ‘*’0.05 < ‘**’ 0.01 < ‘***’0.001

Yield parameters

In comparison to control, drought, heat stress or their combination negatively impacted different yield parameters like panicle length, total number of spikelets/panicles, spikelet sterility rate and 100-grain weight. Under drought and heat stress conditions panicle length, the total number of spikelets/panicles and 100-grain weight declined in both rice lines (Fig. 7b–e). At the individual level, both stresses negatively affected above mentioned yield parameters. However, heat stress had greater effects on both rice lines than drought stress. The rate of spikelet sterility increased by 30–40% and 50–60% under drought and heat stress conditions, respectively. Under the combined stress conditions spikelet sterility increased by almost 65–70% for both genotypes (Fig. 7d). Here, panicle length, spikelets/panicle and 100 grain weight are negatively correlates with H2O2, MDA and EL (Fig. 8) Hence, at individual stress level, the effect of heat stress on both rice lines was more pronounced than that of drought stress and spikelet sterility rate highly increased when the plant was exposed to a combination of drought and heat stress (Fig. 7f).

Fig. 8.

Fig. 8

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Correlation heat map showing correlation among different morpho-physiological, biochemical and yield parameters. SFW Shoot Fresh Weight, RFW Root Fresh weight, SDW Shoot Dry Weight, RDW Root Dry Weight, LA Leaf Area, RWC Relative Water Content, Chl Chlorophyll, Pr Proline, EL Electrolyte leakage, MSI Membrane Stability Index, PL Panicle length, TNS Total Number of Spikelets, SS Spikelets Sterility, HGW Hundreds grain Weight

Gene expression analysis

To explore the differential expression level of drought and heat stress-responsive genes under individual as well as combined stress conditions. Only one genotype (Noichi) was selected for gene expression study. Studied genes belong to HSP gene family (HSP71.10, HSP71.18 and HSP72.57), WRKY (WRKY11and WRKY55), DREB (DREB2A and DREB2B), LEA3 and DHN1 (Fig. 9a).

Fig. 9.

Fig. 9

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a Transcriptional expression of different drought and heat-responsive genes under individual and combined stress levels b Heat map showing the expression levels of respective stress-responsive genes (created through SRplot)

Expression of HSP71.18 increased under both single or combined stress conditions but higher expression occurred under heat stress. HSP71.10 expression significantly increased under drought and combined stress levels. In the case of HSP72.57, expression increased in individual stress levels but not under combined stress levels (Fig. 9a).

Expression of both DREB2A and DREB2B significantly increased in the case of a single stress level but in the combined stress level, expression increased only in the case of DREB2A (Fig. 9a).

In the case of the WRKY gene family both genes, WRKY11 and WRKY55 showed higher expression under drought and combined drought/heat stress conditions (Fig. 9a). LEA3 and DHN1 were expressed under drought and combined drought/heat stress, but not under heat stress alone (Fig. 9a). All gene expression data are summarized through a heat map which has been shown in Fig. 9b.

Statistical analysis

The results of ANOVA followed by Tukey’s HSD test indicate the different significance levels (p < ‘*’0.05 < ‘**’ 0.01 < ‘***’0.001) of morpho-physiological, biochemical, molecular and yield parameters under different stress conditions irrespective to control conditions, which are presented in the supplementary files S2. Correlation analysis revealed that, MDA, H2O2, EL are negatively correlated with the all morpho-physiological, biochemical and yield parameters except APX and SOD, proline and spikelets sterility (Fig. 8).

Discussion

Drought and heat stress are the major abiotic stresses that have negative influences on plant performance and productivity and their simultaneous effects are more severe than that alone (Mittler 2006). Moreover, in these stressful conditions, many metabolic disparities occur at the cellular level, leading to ROS production in cells which hinders the plant’s acclimatization. To overcome these situations, plants produce many antioxidant enzymes (Catalase, APX, SOD etc.) against the ROS. In the present study, drought, heat stress and their interaction reduced the plant biomass, leaf area and plant productivity (Fig. 2a–f). Nevertheless, the combined effect of drought and heat stress are more detrimental than their individual effect for both rice cultivars, N22 and Noichi. These results correlate with the past studies, in which it is reported that the combination of drought and heat stress had more severe effects, possibly due to high temperature and water deficit conditions obstructing the cell growth-related metabolism (Rollins et al. 2013; Sehgal et al. 2017; Hussain et al. 2019). Also, stomata were found to be closed under drought conditions to maintain cellular water levels, while, on the contrary, to maintain leaf temperature through transpiration stomata opened under heat stress conditions. Interestingly, in case of combined stress conditions, stomata remain closed to maintain water levels but leaf temperature would be higher (Rizhsky et al. 2002). Plants maintain their RWC mainly by controlling the rate of transpiration and it was found that RWC decreased in both rice genotypes under single or combined stress levels but significant reduction occurred under drought and combined drought and heat stress conditions which is consistent with the findings on Solanum (Raja et al. 2020), Maize (Hussain et al. 2019), Artemisia (Alhaithloul 2019), Tobacco (Rizhsky et al. 2002). Chlorophyll pigments are directly involved in plant metabolism and its reduction directly hamper plant growth and productivity (Raja et al. 2020). During drought stress reduction in chlorophyll level might be due to the degradation of chlorophyll biosynthetic enzymes, while under heat shock condition thylakoid membrane degeneration is another cause of chlorophyll degradation. Here, in rice cultivars Ch-a, b, total chlorophyll, and carotenoidcontent declined under all stress levels and significant reduction occurred under combined stress levels (Fig. 3a–e). At combined level of stresses severe reduction would be possible because of the chloroplast damage (Raja et al. 2020). Similar results were also recorded in Maize (Hussain et al. 2019) and Solanum (Raja et al. 2020). In addition, Fv/Fm, a component reflecting PSII activity, decreased under combined stress condition as a result of blockage of the electron acceptor side (Suzuki et al. 2014; Zandalinas et al. 2018). In our findings also, Fv/Fm ratio significantly decreased under combined stress conditions for both genotypes, possibly due to the severe damage of PSII. This result is consistent with that of the Solanum (Raja et al. 2020) and chickpea (Awasthi et al. 2017).

Under the stressful condition like drought, heat, or their combined condition different ROS, like superoxide (O2−), and hydrogen peroxide (H2O2) are accumulated in the cell, which alters membrane stability due to the lipid peroxidation of the plasma membrane leading to the formation of MDA. Oxidative molecules are formed by the leakage of electrons from the electron transport chain of mitochondria and chloroplast (Suzuki et al. 2012). In our results, levels of MDA and H2O2 were markedly increased in both genotypes under combined stress levels resulting in more increased leaf injuries (electrolyte leakage) and losses the membrane integrity or MSI (Fig. 4c–f). MDA, H2O2 and electrolyte leakage were negatively correlates with morpho-physiological, biochemical and yield parameters (Fig. 8). So, their increments negatively effects on normal plant growth and yielding. These findings are matches with the study of chickpeas (Awasthi et al. 2017), and Artemisia (Alhaithloul 2019). To protect from such oxidative damage and lowering cellular toxicity plants produce many ROS-scavenging antioxidant enzymes like catalase, APX and SOD (Mittler et al. 2004). SOD converts O2− to O2 and H2O2 reducing injuries of plants. In the present study, SOD activity increased in both genotypes, Noichi and N22 under all stress levels with respect to control (Fig. 5c). This increasing SOD is probably involved to maintain MDA levels and antioxidant defense (Gill and Tuteja 2010; Zandalinas et al. 2018). In addition, catalase and APX are mainly involved to convert H2O2 to H2O and oxygen (Gill and Tuteja 2010; Carvalho et al. 2015). In our findings, catalase activity increased at all single-stress levels in N22 and in the case of Noichi catalase activity increased only under heat stress, in comparison to the control (Fig. 5a). However, APX activity increased for both genotypes under all stress levels (Fig. 5b). This increment of APX might compensate for the activity of catalase in case of Noichi, which is disproportionate to the H2O2 to H2O and oxygen, which could protect the plant from oxidative damage. The increment of activity of catalase, APX and SOD under different stress conditions have also been reported in previous works done by other workers (Zandalinas et al. 2018; Raja et al. 2020).

Plants accumulate proline as an osmoprotectant to sustain and protect the plant from stressful conditions and it also serves as an energy source and maintains cellular water content which is used up after the stress relief (Tang et al. 1986; Kishor et al. 2005; Akram et al. 2017). In our findings, proline accumulation increased in all stress levels, increase being higher under the drought and combined stress levels rather than heat stress (Fig. 5d). Under heat stress conditions proline might be converted into soluble sugar to avoid cellular toxicity (Mittler 2006; Rizhsky et al. 2002). This finding was consistent with the recent report by Raja et al. (2020) and Hussain et al. (2019). They also reported that, to protect the plant more proline accumulates under drought and combined drought and heat stress conditions.

Under the single and combined stress levels, an antagonistic effect on stomata was noted. As shown in Fig. 6, under the heat stress stomata remained open probably to cool their body through transpiration. Conversely, stomata remain closed under drought and combined drought and heat stress probably to check the water loss but unable to maintain leaf temperature (Rizhsky et al. 2002).

Pollen loses its viability under the pronged drought and heat episodes and it is severe under the combined drought and heat stress conditions (Cohen et al. 2021). In the present study, the rate of pollen viability decreased under drought and heat stress conditions but more severely under combined levels (Fig. 7a). A similar loss of pollen viability was also found in wheat under drought and heat stress and their combination (Fábián et al. 2019). Impaired sucrose metabolism under these stress conditions is the major cause of pollen sterility (Kaushal et al. 2013). The number of viable pollen determines the pollen germination percentage which ultimately affects fruit sets (Ruan et al. 2010).

Plants frequently face drought and heat stress that reduce yield but their concurrent effect is more severe than their single effect (Mittler 2006; Cohen et al. 2021). In the present study, different yield parameters like panicle length, spikelet number per panicle and 100-grain weight decreased and spikelet sterility increased under all stress levels but the effect is more pronounced under combined conditions (Fig. 7a–f). In an earlier study on maize (Hussain et al. 2019), there was also yield reduction that was more severe under combined stress levels. Actually, yield losses may vary on the imposition of stress at different growth stages of crops. The reproductive stages are more affected by drought or heat stress than the vegetative stages (Fahad et al. 2017; Cohen et al. 2021). During reproductive stages, pollen sterility or female reproductive organ sterility is a major cause of yield penalty of crops (Fábián et al. 2019).

In the present study, we have studied different drought and heat-responsive genes for unique patterns of their expression found under the combined stress. Expression patterns of these genes were found to be totally different under combined stress from that of single stress levels. Different genes belonging to families like HSP (HSP71.18, HSP 71.10, and HSP 72.57), WRKY (WRKY11 and WRKY55), DREB (DREB2A and DREB2B), LEA3 and DHYDRIN are well established as key genes which are expressed under heat and drought stress (Ye et al. 2012; Lee et al. 2018; Huang et al. 2021; Lim et al. 2022). Although available reports documented their role under drought and heat stress conditions individually, their role under combined stresses is not studied well. In the present study, increased expression of HSP71.18, HSP 71.10, and HSP 72.57 genes under single stress levels correlate with the previous work done by Ye et al. (2012). Under combined stress, expression of HSP71.18 and HSP 71.10 genes was enhanced further with respect to control, while the expression of HSP 72.57 decreased (Fig. 9a). In the case of the WRKY gene family, WRKY11 and WRKY55 genes were expressed positively under all levels of stress conditions but to a greater extent under drought and combined stress levels (Fig. 9a). Such finding has also been reported by other researchers (Lee et al. 2018 and Huang et al. 2021) and in the case of tobacco, WRKY transcript level was higher under combined drought and heat stress conditions (Rizhsky et al. 2002). Among the different genes of DREB2 type transcription factors, DREB 2A and DREB2B are induced under drought, heat and salinity stress (Nakashima et al. 2000; Matsukura et al. 2010; Priya et al. 2019). In our study, DREB 2A was expressed pronouncedly in all stress conditions. On the other hand, the expression of DREB2B increased under drought and heat stress conditions, but not under the combined stress (Fig. 9a). Dehydrin (DHN) and LEA are molecular chaperones, that maintain membrane structure, enzyme activity, nucleic acid and protein structure under stressful conditions and it has also been reported that OsDHN1 detoxifies ROS and improve drought tolerance (Lee et al. 2005; Priya et al. 2019). In our study also, LEA3 and DEHYDRIN1 were significantly expressed under drought and combined stress conditions (Fig. 9a). These results corroborate earlier studies on Solanum (Raja et al. 2020), Artemisia (Alhaithloul 2019) and Rice (Yadav et al 2022).

Conclusion

The present study shows different morpho-physiological, biochemical, and molecular changes that occurred under drought, heat stress and their interactions. Yield-related parameters are negatively influenced by drought and heat stress and it is more severe under the combined stress conditions. ROS accumulation and lipid peroxidation are enhanced under all stress conditions for both genotypes affecting morphology and photosynthetic efficiency. In addition, pollen viability decreased under single or combined stress levels, being more pronounced under combined stress. Decreased photosynthetic efficiency and loss of pollen viability most probably affected yield parameters. At the molecular level, the expression patterns of stress-responsive genes are unique and different under combined stress compared to those under single stress. The genes that are upregulated under the combined stress conditions, reflecting their role under combined stress conditions remained unrevealed. However, more detailed studies are required to know the pathway that helps the rice to acclimatize under combined stress conditions. Although this study is quite different from the field study however, this preliminary study could pave the way for future research.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 180 KB) (182.1KB, docx)
Supplementary file2 (DOCX 60 KB) (51.3KB, docx)

Acknowledgements

We are greatly thankful to UGC (University Grants Commission) for their financial support. The authors gratefully acknowledge the Department of Biotechnology, Visva-Bharati, India for providing research facilities.

Author contribution

KM and ND designed the work. KM performed the experiments. KM wrote the original article and prepared the illustration. KM, ND and RKK edited the final manuscript. AC provided the plant materials. The final draft was read and approved by all authors.

Funding

KM receives fellowship from UGC, Govt. of India [744/(CSIR-UGC NET DEC. 2018)].

Data availability

The data that support the findings of this research work will be available upon request.

Declarations

Conflict of interest

There is no conflict of interest relating to this article.

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Supplementary Materials

Supplementary file1 (DOCX 180 KB) (182.1KB, docx)
Supplementary file2 (DOCX 60 KB) (51.3KB, docx)

Data Availability Statement

The data that support the findings of this research work will be available upon request.

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