Exogenous application of hormones and chemicals to mitigate heat stress in strawberry under tropical summer conditions

Najra-Tan-Nayeem Salwa; Sadia Shabnam Swarna; Md Masudur Rahman; Sharifunnessa Moonmoon

doi:10.1371/journal.pone.0331496

. 2025 Sep 11;20(9):e0331496. doi: 10.1371/journal.pone.0331496

Exogenous application of hormones and chemicals to mitigate heat stress in strawberry under tropical summer conditions

Najra-Tan-Nayeem Salwa ^1,^#, Sadia Shabnam Swarna ¹, Md Masudur Rahman ¹, Sharifunnessa Moonmoon ^1,^*

Editor: Ramegowda Venkategowda²

PMCID: PMC12425329 PMID: 40934286

Abstract

Resilience of Strawberries in tropical and subtropical climates, including Bangladesh, faces severe challenges due to rising summer temperatures and sporadic heatwaves exacerbated by climate change. The experiment evaluated the physiological and biochemical responses of three Strawberry genotypes of which G1 (RABI-3) was heat tolerant and G2 (BARI Strawberry-2) and G3 (BARI Strawberry-3) were heat susceptible and assessed the effectiveness of five exogenous substances like 5% Molasses (T1), 10 ppm Melatonin (T2), 5% Kaolin (T3), 10 mM CaCl₂ (T4) and 5 ppm Abscisic acid (T5) in mitigating heat induced damage. The experiment was conducted in pots under field conditions following CRD (Completely Randomized Design) set was repeated thrice. Exogenous treatments were applied as foliar spray at five days intervals for three months in comparison to the control. The hourly temperature and relative humidity (%RH) data was recorded using digital data logger. Leaf fluorescence parameters, temperature differentials, photosystem II efficiency and leaf attributes such as thickness and greenness were analyzed. The plant data was recorded three time viz. at the end of March, at the end of April and at the end of May using a handheld fluorometer (Multispeq V.02). The result showed that the heat tolerant genotype (G1) consistently maintained higher photosynthetic activity and chlorophyll content, while the susceptible genotype (G3) showed significant improvement under treatments. All the exogenous substances possess the ability to help the plant to mitigate the effects of heat stress and support photosynthetic activity. The organic spray like kaolin and molasses effectively reduced internal leaf temperature by developing surface coating, while ABA enhanced internal physiological regulation. The results suggest that the integration of heat tolerant genotypes with suitable treatments can enhance Strawberry resilience to heat stress, which provides a practical alternative for sustainable Strawberry cultivation in tropical regions.

Introduction

Strawberry is a dicotyledonous perennial herb belongs to genus Fragaria of family Rosaceae, grown throughout the world for their sweet fragrance, taste, nutritional, and medicinal value [1, 2]. Globally, Strawberry production exceeds 9.1 million metric tons, largely driven by its’ rich content of phytonutrient, antioxidant and poly-phenolic chemicals which can reduce chronic disease like cancer, heart disease etc. [3,4]. In fact, Strawberries contain more vitamin C than lemon [5]. While it typically cultivated as a summer crop in temperature region [6], in tropical and subtropical regions like Bangladesh, Strawberry is grown as a winter crop [7], yielding over 789 metric tons annually. In Bangladesh, the demand of strawberry is rapidly increasing. However, Strawberry cultivation faces significant climatic challenges. The optimal temperature range for Strawberry growth is 20–26 ℃ during day and 12–16 ℃ at night. This condition is only prevails in winter in Bangladesh thus strawberries cultivated in Bangladesh at winter [8]. The country lacks improved multiplication technique and heavily relies on the conventional easiest vegetative propagation (by runner, sucker) [9,10]. Vegetative preparation requires a mother plant; thus, farmers kept the plants till September of the next year after ending the winter season. Consequently, these mother plants must endure the tropical summer, during which temperatures regularly exceed 26℃, significantly impairing plant growth [11]. Nonetheless, the heat wave develops at the mid and late summer raise the temperature and worsen the situation. Extended exposure to heat stress results in visible symptoms like leaf wilting and burn and a prolonged heat stress may lead to mother plant mortality. To make the situation worse climate change impacts heavily. The changed climate destroyed the seasonal and weather pattern; thus, it became really hard for the farmers what to expect when. High temperatures and unpredictable heat waves are now among the main constraints to Strawberry production in tropical and subtropical climates. Despite this growing concern, limited research has focused on alleviating heat stress in Strawberries under tropical conditions. Despite the promising results of exogenous treatments in other crops and controlled conditions, little is known to suggest their effectiveness in Strawberry cultivation in tropical climates, like Bangladesh. In addition, the comparative efficacy of different hormone-based treatments and the effects of genotypic variation in the effectiveness of treatment remains largely unexplored. Further, there is a need to determine whether these treatments can sustain plant health and photosynthetic performance under prolonged periods of extreme environmental heat.

Several exogenous substances have showed potential in reducing the effects of heat stress in plants. For instance, the application of molasses in strawberry plants under heat stress conditions has been shown to have a significant effect on plant physiology and therefore has a potential tool for improving heat tolerance. According to Gulen and Eris [12], molasses increases leaf relative water content (LRWC) and assists the plant in having good turgidity for the management of water loss under high temperatures. Moreover, Kesici and colleagues, [13] also revealed that molasses increases the chlorophyll content and vigor, which is crucial for the plants to continue photosynthesis during hot and unfavorable temperatures. Melatonin is another effective compound known for its’ role in enhancing the antioxidant activity of strawberries, particularly under heat stress, due to the involvement in oxidative stress regulation, protecting fruit quality and nutrient content. Wang and colleagues, [14] confirmed that melatonin regulates the photos system electron transport in tall fescue under heat stress. The increased number of reaction centers weakens the electron transfer efficiency at the receptor and donor sides of Photosystem II (PSII), enhancing the rate of plant survival under heat shock treatment. In general, melatonin is great for reducing heat stress practically on different crops through increasing antioxidant activity, improving plant photosynthesis process and increasing the general plant condition. Melatonin application at varying concentrations (1, 5, and 10 ppm) has been reported to enhance yield, fruit quality, and antioxidant levels in multiple strawberry cultivars under both greenhouse and open-field conditions [15]. Kaolin, which is an organic mineral compound high in kaolinite, has a long history of use in reducing heat stress and drought stress on a wide variety of crops. Kaolin, when applied as a foliar spray, produces a film of white, reflective particles covering a leaf surface that reflects infrared (IR), photosynthetically active radiation (PAR), and ultraviolet (UV) radiation [16–18]. This property is important for use under heat stress since it will limit the absorption of IR by the canopy and cool the leaf. The cooling properties of kaolin were apparent with the kaolin-treated (T3) plants where the internal leaf temperature was lower than for other treatments with the surface readings slightly higher with the toxic coating from the kaolin spray. Therefore, kaolin is thought to work as an antitranspirant to avoid water loss and improve water use efficiency [19,20]. This may explain the improved SPAD values, photosystem II efficiency (Fv/Fm), and maintenance of photochemical activity (φII, qL) observed in plants treated with kaolin in our study. The protective coverage by the kaolin treatment probably decreased transpiration water loss, decreased light activated stress, resulting in maintaining leaf structure and function at high temperatures. Kaolin particle film, at rates like 3% and 6%, reduced light and heat stress and improved quality of nut and kernel in Persian walnut [21]. Calcium chloride (CaCl2) has also proven effective in enhancing plant heat tolerance. According to Tan and colleagues [22], heat tolerance improved in tobacco due to CaCl₂ treatment in terms of stomatal conductance and higher net photosynthetic rate, stabilizes the PS II reaction center and lower Reactive Oxygen Species (ROS) accumulation through increased antioxidant enzyme activity. There was further indication of enhanced heat stress resistance by indicated improvement levels of HSP70. Foliar application of CaCl₂ at concentrations of 5, 10 and 20 mM improved growth, photosynthesis, and antioxidant responses in Zoysia japonica under drought stress [23]. The exogenous application of abscisic acid (ABA) has been identified as an effective method for enhancing heat stress tolerance in strawberry plants, providing multiple interconnected advantages for both physiological and morphological adaptations. Notably, Tao and colleagues [24] found that ABA significantly improves the development of root and water absorption, helping the plants not to wilt and tolerate high temperatures. Additionally, the work of Islam and colleagues [25] highlighted that ABA promotes the accumulation of proline, an osmoprotectant that combined with an upregulated antioxidant defending system reduces the oxidative harm in the plant. Tao and colleagues [24] highlighted another feature of ABA, regulating stomatal behavior, specifically by minimizing stomatal opening, which reduces water loss. This ability to conserve moisture and ensure they remain hydrated during prolonged heat exposure.

Besides the application of these protective compounds, it is also essential to identify which genotype can cope up with high temperature. Understanding the genotypic variation in response to heat stress and the effectiveness of chemical treatment is vital for developing heat resilient Strawberry cultivation in tropical regions. Therefore, this present study was conducted to find out the suitable heat-tolerant Strawberry genotypes for summer cultivation and to investigate the impact of hormonal treatments on strawberry genotypes under heat stress conditions.

Materials and methods

2.1. Study location, duration, work permission and ethical considerations

The study was conducted in the Department of Crop Botany and Tea production technology field laboratory, Sylhet Agricultural University, Sylhet-3100, Bangladesh, from October-November of 2023 to April - May of 2024. No such body is existed at both institutional and country level and no such permission is needed or applicable for conduction of any research work or experiments regarding ethical considerations of plant culture and growth.

2.2. Genotype collection

Six genotypes of strawberries were collected from different locations in Bangladesh in October-November 2023. Among these genotypes, three genotypes of one RABI-3, which is heat tolerant (G1) and two heat susceptible, BARI Strawberry-2 (G2) and BARI Strawberry-3 (G3) were selected for the experiment.

2.3. Plant multiplication

The collected genotypes were morpho-physiologically evaluated and reared in the pot concomitantly. The mother plant grown in the pot produces runner in case of some genotypes and sucker in rest others. The runner was provided with new pots containing rotting media for obtaining new plant. The sucker was separated from the mother plant periodically and grown in the separate pot having growing media. The full gown seedlings were transplanted in the main experimental field.

2.4. Pot preparation and plant establishment

Black colored buckets with an 8 L capacity were used as the growing pot with perforated bottoms for drainage. Each pot was filled with a 2 inches base layer of sand and pebbles followed by 5 kg of soil mixed thoroughly with following recommendation. 250g vermicompost, 1.67 g TSP, 1.83 g MoP and 0.08 g MgSO₄ as per the BARC BARC (2012) guidelines. After the pot became ready, seedling produced in the polybag was planted in the pot. Three selected genotypes (G1, G2 and G3) were taken and 9 plants from each genotype were planted in the 9 different plot (Fig 1).

2.5. Experimental design and treatment application

The experiment for heat stress evaluation the selected genotypes and investigating mitigation strategy were laid in the field placing the planted pot following the Completely Randomized Design CRD model [26] with three replications (Fig 2). In each replication, there was 3 plants. Five exogenous chemicals consisting of organic, inorganic and PGRs (Plant Growth Regulator) hormone were selected (Molasses-[Aarong –BARC, BD], Melatonin-[UT enterprise Co. Ltd; China], Kaolin-[UT enterprise Co.Ltd; China], CaCl₂-[UT enterprise Co.Ltd; China] and Abscisic acid-[Nanjing Huaxi Chemicals; China] for the mitigation of impacts of heat stress on the plants in comparison to control (Water spray) (Fig 3). All the reagents were stored at 4° C.

At the first week of March when night temperature raised and day becomes hotter the application of the exogenous chemicals was started. Organic molasses was purchased from the local market and diluted to 5% Molasses solution (T1) and stored in the freeze for the application. Likewise, 10 ppm Melatonin (T2), 5% Kaolin (T3) and 10 ppm CaCl₂ (T4) and 5 ppm Abscisic acid (T5) were prepared and stored in the freezer for the periodic application. The spray solution was brought to room temperature after taking out from the freezer and applied at five (5) days intervals to the specified experimental units till plants became fully soaked, whereas the control plants were sprayed with distilled water at the same manner. Other operations like irrigation water application, recommended fertilizer application, pesticides and fungicides etc. application were the same for all the treatments. The spraying was continued till the end of May and stopped after collecting the final data.

2.6. Environmental monitoring

Meteorological data (Temperature and Relative Humidity) was collected by placing digital data loggers at the experimental site from the first week of March to end of the May to record the heat stress. The data logger was well protected from the outer environment but allowed record temperature and Relative Humidity (%RH) data from the environment without obstacle. Data were collected using the mobile app and then transferred to Microsoft excel to process and visualize.

2.7. Plant fluorescent data collection

Plant fluorescent response recording is a state-of-art perfect strategy to assess the plant’s physical condition under heat stress and the response under the treatments. To collect the fluorescent data a handheld fluorometer (Multispeq V.2) [27] made in USA was used. Fluorescent data were collected first half of the day of three times viz. th March, 30th April and in 30th May to get contrast insights about plant response under different intensities of heat stress. Data were recorded in the first part of the day. The fluorometer submitted the data to the server and downloaded it later on for further processing. The following parameters were recorded: Leaf surface and internal temperature, Leaf thickness and greenness (SPAD), Chlorophyll fluorescence (Fv/Fm, LEF, φII, φNO, φNPQ and qL), steady-state proton flux (vH) and proton conductivity (gH).

2.8. Data analysis

In the study, treatment and genotype were considered as fixed effects, and replication as a random effect within the linear mixed model (LMM) framework. All the recorded data were transferred in Microsoft Excel and data curating, sorting, arranging, processing, visualization etc., were performed. To generate clear summaries for visualization, two separate pivot tables were created from the raw data for each parameter, one summarizing data by genotype for overall treatment effects and the other summarizing data by treatment. Data was then loaded in the R software [28] and RStudio (Version: 2025.05.0 + 496) to carry out all kinds of statistical analysis. Linear mixed modelling was used to perform ANOVA in the light-dependent parameters. The light-independent parameters were analyzed by performing two-way ANOVA. The mean of the significant parameters was separated using the fisher LSD test [26] at 0.05 level of p-value. The “tidyverse” package was used for the calculation of mean and sem. The data was visualized in graph form using the “ggplot2” package along with others. Pearson’s correlation test was implied in the parameters using the “metan” package along with performing the significant test.

Results

3.1. Environmental data

The data were recorded every 10-minute interval for the entire period (March, April and May) with digital data logger. The daily maximum, minimum and average were calculated for the temperature and relative humidity (% RH).

3.1.1. Maximum, minimum and average daily air temperature.

The presented graph (Fig 4) of maximum, minimum and average daily air temperature shows the trend of air temperature during the study period. In March the day and night temperatures started to rise. By the end of the month, the day temperature exceeded 35 °C while the night temperature exceeded 20 °C. In that month the average day temperature was 35.5 °C while the average night temperature of the month was 25.1 °C with a total average of 18.4 °C. In April, the temperature fluctuated more and days became hotter. The day temperature was always higher than 35 °C and exceeded 40 °C deliberately. In that month the average maximum temperature was 39.4 °C and the average minimum temperature was 22.88 °C with a total average of 31.1 °C. The May was hottest month among the three with periodic heat-wave. The day temperature was always around 40 °C with a warm night around 25 °C. The average of maximum temperature was 41 °C and average of minimum temperature was 24.8 °C with a daily average of 32.9 °C.

3.1.2 Maximum, minimum and average daily relative humidity (%RH).

March was relatively dry, with relative humidity ranging from an average minimum of 49.5% to a maximum of 87% and a mean daily value of 68% (Fig 5). The April was a little bit of wetter with rain but May is wetter. The maximum average relative humidity (%RH) was 87 and the minimum average of 51% with a daily average of 69%. In May, first part of the month was drier but later part was extremely humid with maximum average of 89% and minimum average of 64% with daily average of 76%.

3.2. Leaf temperature of the strawberry plant

The ambient temperature of the leaf surface (Fig 6), leaf internal temperature (Fig 7) and the differential temperature (Fig 8) is an important parameter to describe leafy plant condition under the heat stress. In every figure, panel a, c, and e show the effects of different genotypes under various treatments and panel b, d, and f show the overall effects of treatments averaged across genotypes (Fig 6–18.). The data were obtained from the fluorometer in all the plants of three genotypes and analyzed at p ≤ 0.05. The result shows that leaf of plant from Control (T0) and Abscisic acid (T5) treatment had slightly lower temperature while leaf under other treatments has slightly higher temperature in March.

Fig 8 — Treatment and genotypes having different letter varies significantly at p ≤ 0.05.

Fig 18 — Treatment and genotypes having different letter varies significantly at p ≤ 0.05.

In both April and May, the surface temperature was slightly higher in the treatments than Control (38.7 °C in April and 40.7 °C in May). The leaf surface temperature of the genotypes didn’t vary among them in March and April but it was slightly lower in the G3 genotype.

The leaf internal temperature under the treatments were reduced in all the treatments than surface ambient temperature but did not vary in March and April in comparison to the Control (37.5 and 37.7 °C respectively), later on, which reduced significantly in April than 39.4 °C in control (Fig 7). The leaf internal temperature was lowest in Kaolin (T3) (37.5 °C) followed by Molasses (T1) (37.9 °C). The genotypes showed no significant differences among them in any month.

The plant response under the heat stress govern by the treatments and genotypes are best depicted by the temperature differential (difference between surface temperature and leaf internal temperature). All the treatments reduced the leaf internal temperature significantly in compared to the control plants in all three leave of heat stress in three month (Fig 8). The Kaolin (T3) treatment reduced internal temperature by −4.2 °C in March, −5.3 °C in April and −5.3 °C in May in compare to the −1.5 °C, −1 °C and −1.2 °C reduction in the control. The Kaolin (T3) treatments were followed by Molasses (T1) and CaCl2 (T4) for the internal temperature reduction ability. The temperature reduction capability of the genotypes was almost similar and didn’t vary significantly in March and April, but in May in G1 genotypes.

3.3 Leaf attributes of the strawberry plant

Two important leaf attributes like leaf thickness (Fig 9) and leaf greenness (SPAD) were measured with the help of the fluorometer of all the plants of all genotypes and significance was analyzed at p ≤ 0.05. In March, the leaf thickness (μm) was not significant among the treatments but in April and May it was significantly higher in the treatments than Control. In Control (T0), the leaf thickness was 0.23 μm in March and April, which reduced to 0.17 μm in May. On the other hand, leaf thickness in Kaolin (T3) was 0.25 μm in March that increases to 0.30 μm in April and 0.32 μm in the May. Among the genotypes, leaf thickness of G3 was significantly thicker in the March (0.27 μm) but reduced to 0.21 μm in April and 0.24 μm in May while it was 0.21 μm, 0.24 μm, and 0.23 μm in the G1.

The greenness of the leaves is an indicator of the green pigments content, that is the main apparatus of the photosynthesis system. The SPAD (leaf greenness) of the leaves under the treatments were higher in March but not significant than control but became significantly higher in April and May (Fig 10). Actually, SPAD (leaf greenness) didn’t increases over the period in the treatments but preserved with slight decrement, while control loss the greenness of the leaves over the months drastically (42. 1 in March, 34.1 in April and 36.4 in May). Melatonin (T2), CaCl2 (T4) and Abscisic acid (T5) perform better to preserve the greenness over the time. In genotypes, leaf greenness was significantly higher in G1 in March (44.6) and April (43.7) than others but become almost level by May (41.9 in G1, 42.8 in G2 and 42 in G3).

Fig 10 — Treatment and genotypes having different letter varies significantly at p ≤ 0.05.

3.4 Leaf fluorescence of the strawberry plant

Maximum quantum efficiency of Photosystem II denoted as Fv/Fm is a widely used indicator to observe the stress level in the plants. It is a proportion value which can be maximum of 0.83 and the higher the value, the health condition of the plant is better and vice versa. In March, plants under Abscisic acid (T5) show significantly better maximum quantum efficiency than other treatments (Fig 11). In April and May, the Maximum quantum efficiency was reduced in control drastically with some other treatments but Kaolin (T3) has highest Maximum quantum efficiency followed by Molasses (T1) and Abscisic acid (T5). In the genotype, Maximum quantum efficiency didn’t vary in March but reduced over the time in all genotypes and most reduction was seen in G2 genotype while least variation was observed in G3 genotype.

Fig 11 — Treatment and genotypes having different letter varies significantly at p ≤ 0.05.

Linear electron flow (LEF) in the photosystem II is an indicator of photosynthetic activity in the plant leaves. This parameter is a product of photosynthetically active radiation (PAR) received by the leaves, the quantum yield produced by the leaves from the harvested light and a coefficient given by the protocol. The LEF was significantly higher in Melatonin (T2), followed by Molasses (T1), CaCl2 (T4) and Abscisic acid (T5) in the heat stress of March (Fig 12). By April and May, LEF in the control drastically reduces and was significantly higher in the treatments but highest in Abscisic acid (T5) followed by CaCl2 (T4), Melatonin (T2) and Molasses (T1). The treatments didn’t increase the LEF but preserved from the reduction like control. The genotypes didn’t vary significantly among them in terms of LEF but G1 has slightly higher LEF than others.

Fig 12 — Treatment and genotypes having different letter varies significantly at p ≤ 0.05.

Quantum yield (φII) is the product of photosystem II (PSII) takes place in the leaves during photosynthesis, is an indicator of plant health under the condition. The quantum yield (φII) was significantly higher in the Abscisic acid (T5) treatments than other in March, but under the heat stress on April and May Molasses (T1), Kaolin (T3) and Abscisic acid (T5) preserved the Quantum yield (φII) significantly while drastic reduction was observed in the control (Fig 13). In genotypes, G3 has significantly higher Quantum yield (φII) in March but get reduced by April and May, becomes similar to the G1, which didn’t loss much yield over the stress period.

Fig 13 — Treatment and genotypes having different letter varies significantly at p ≤ 0.05.

The amount of Non-regulatory Energy loss through dissipation in the heat form from the PSII is denoted as φNO. The excess energy dissipation from the system was consistent from month to month and was not varied significantly p ≤ 0.05 among the treatment, not the genotypes (Fig 14).

Fig 14 — Treatment and genotypes having different letter varies significantly at p ≤ 0.05.

The harvested light which plant can’t utilize due destruction in apparatus of PSII is released from the leaves by regulated Non photochemical quenching (φNPQ). The amount of Non photochemical quenching is directly associated with the stress level of the plant. It was significantly lower in the Abscisic acid (T5) in the month of March in comparison to the Control (Fig 15). By the April and May, it was stable and didn’t increase in Molasses (T1), Kaolin (T3) and Abscisic acid (T5) treatments while increased in other treatments with maximum in control (0.47 in March, 0.65 in April and 0.65 in May). In the genotypes, it was significantly lower in G3 in March but become level with the G1 through increment while G1 was stable. By May, φNPQ decreases slightly in G3 genotypes.

Fig 15 — Treatment and genotypes having different letter varies significant at p ≤ 0.05.

Photosystem II Redox State (qL) describes activity of the plant cell for the proper functioning. The higher the qL is the PSII apparatus are functioning better for carrying out the photosynthetic activity. The qL was significantly lower in control followed by Melatonin (T2) in March while it was better in Molasses (T1), Kaolin (T3), CaCl2 (T4) and Abscisic acid (T5) treatments (Fig 16). The qL was further reduced in the control in April and May subsequently while the value was preserved in Molasses (T1), Kaolin (T3), CaCl2 (T4) and Abscisic acid (T5) were significantly higher than the Control. In genotypes, though difference was not significant among them, the G1 genotype has slightly better qL in March.

Fig 16 — Treatment and genotypes having different letter varies significantly at p ≤ 0.05.

3.5 Proton activity of the strawberry plant

Steady-State Proton Flux (vH) is the indicator of H⁺ transportation in the photosynthetic system during the photosynthesis under light. It was almost similar among the treatments in comparison to control in March (Fig 17). But vH decreases drastically in the control in alleviate heat stress in April and May, while preserved in all the treatments. However, Melatonin (T2) and Abscisic acid (T5) seems to have slight better proton flux than others. In the genotypes, vH was not significant among the treatments but G1 has slight better vH.

Fig 17 — Treatment and genotypes having different letter varies significantly at p ≤ 0.05.

Proton conductivity (gH) was significantly higher in the Abscisic acid (T5) treatment than others in March (Fig 18). By the April and May, gH drastically decreased in the control and preserved in the treatments with higher in Molasses (T1), Kaolin (T3) and Abscisic acid (T5). In genotypes, conductivity was higher in G3 than others in March and April but it increases in G1 and decreases in G3 by May and become similar.

3.6 Pearson correlation between the variables

Photosynthetically active radiation (PAR) is one of the mandatory elements for the Photosynthesis to be carried out that ignite the process. Pearson’s correlation suggest that PAR positively significantly increases the leaf surface ambient temperature, leaf internal temperature, linear electron flow in leaves, steady-state proton flux as well as regulatory-non photochemical quenching. Fv/Fm showed a strong positive correlation with SPAD (r = 0.83, p < 0.001) andPhi2 (r = 0.71, p < 0.001), indicating greater chlorophyll content and photochemical efficiency supported more effective PS II performance. Similarly, LEF and vH showed positively correlations with Phi2 (r = 0.71, p < 0.001) and vH (r = 0.60, p < 0.001), indicating that electron and water transport were more efficient under the optimum environment. In contrast, PhiNPQ had a negative correlation with Phi2 (r = −0.62, p < 0.001) and Fv/Fm (r = −0.58, p < 0.001), indicating increased energy dissipation under heat stress. Additionally, ambient and leaf temperatures showed negative associations with photosynthesis variables, especially with Phi2 and Fv/Fm, reflecting heat induced physiological limitations (Fig 19).

Fig 19 — A positive sign relates to positive correlation and negative sign relates to negative relation. Here, “***” is significant at 0.001, “**” is significant at 0.01 and “*” is significant at 0.05 p value. Parameters are, “LEF” Linear electron flow, “vH” = S eady state proton flux, “Ambient_Temp” = L af surface ambient temperature, “Leaf_Temp” = L af internal temperature, “PAR” = Photosynthetically active radiation, “PhiNPQ” = R gulated non-photochemical quenching, “LeafTempDiff” = Temperature differential between surface and internal, “gH” = Proton conductivity, “Phi2” = Quantum yield of PSII, “qL” = P II redox state, “Leaf_thickness” = Thickness of the leaf, “FvP_over_FmP” = Maximum quantum efficiency of PSII, and “PhiNO” = Non-regulatory energy dissipate.

Treatment wise phenotypic variation regarding growth and development of different strawberry genotypes were given below (Fig 20)

Discussion

March is the start of the summer in Bangladesh when both day and night temperatures start to rise and exceed 35 °C at day and 20 °C at night. The temperature intensified in April which fluctuated around 40 °C but remain higher than 35 °C due to sporadic rain. At May, heat waves can keep the air temperature above 40 °C for a few days to a prolonged period. At the onset of summer at march it was around 49.5% daily average but increased to 69% in April and become highly humid of 76% daily average at May. Humid conditions do not dry out wet surfaces thus leaf temperature might rise. Kadir and colleagues [29] demonstrated that leaf temperature increased under 40/35’C, reaching an average of 39.3 ºC within a week in two cultivars (Chandler and Sweet Charlie), indicating heat stress impact on the cultivars. Our study supports this, showing the ambient leaf surface temperature was high in all the plants but it was comparatively slightly higher in the treatments than Control (T0) and Abscisic acid (T5). This one might seem conflicting since kaolin and molasses are reflective or coating materials that affect surface-level infrared measurements but not always internal leaf temperature. To the contrary, ABA and water sprays left no residues, but since no reflectance was altered, they have slightly lower surface temperature. The shiny surface of the G3 might be a reason to slightly lower surface temperature. The application of Kaolin (T3) and Molasses (T1) leave a coating trace on the leaf surface, which might help to reduce the leaf internal temperature. Plants naturally keep its leaves’ internal parts cooler than the surface temperature for proper functioning. These capabilities of cooling increase upon aid with the applied exogenous substances. However, the higher differential in Kaolin (T3), and molasses (T1) reduction might be due to thick coating on leaves and in CaCl₂ (T4) might be due to stomatal regulation. The tolerant genotype G1 is better at cooling the internals and maintaining the differential, likely due to intrinsic thermoregulation mechanisms. The reduction in the thickness in the leaves of the control plant might be associated with impaired photosynthetic activity or the heat stress-reducing mechanism of the plants. The increment in the thickness in plants under Kaolin (T3) application might be due to the improvement of the health of leaves or the deposition of a layer on the surface of the leaves. The leaves of G3 were genetically thicker but became thinner might be due to impaired photosynthetic activity. The SPAD (leaf greenness) level was almost similar in the treatments at the onset of summer but it reduces with the heat stress in the upcoming months. The lessening of SPAD (leaf greenness) denotes destruction of pigments and photosynthetic apparatus. Kadir and colleagues [29] similarly reported a 21% decrease in SPAD in Sweet Charlie after one week of heat exposure and 13% in Chandler after two weeks. In our study, preservation of SPAD (leaf greenness) in Melatonin (T2), CaCl₂ (T4) and Abscisic acid (T5) might be associated with the internal cell regulation process by these chemical mitigating substances. The greenness was higher in the tolerant genotype (G1) signifies the importance of better greenness for heat tolerance. The maximum quantum efficiency of Photosystem II indicates the stress condition of the plants [30]. Under the stress, Fv/Fm reduced drastically in the control but kaolin (T3), Molasses (T1) and Abscisic acid (T5) is capable of preventing the reduction, might be associated with preservation of greenness in the leaves. It was lower in susceptive G2 genotype suggest G2 is most pruned to heat stress as neither it does have own tolerant property nor response to mitigating substance properly. Rashid and colleagues [31], found that extended heat stress led to a progressive decline in chlorophyll fluorescence by 5.1% after 7 days and up to 43.7% after 28 days compared to ambient conditions. These highlight the cumulative damage caused by prolonged high temperature. Linear electron flow (LEF) in is the product of photosynthetically active radiation (PAR) received by the leaves, the quantum yield produced by the leaves from the harvested light and a coefficient given by the protocol [27]. The LEF reduces in control might be related to PS apparatus damage and preserving in Melatonin (T2), Molasses (T1), CaCl₂ (T4) and Abscisic acid (T5) might be due to internal regulation of the cells. The tolerant genotype has better LEF as it can utilize PAR more efficiently. Similar to Zhang and Sharkey [32], who showed reduced LEF in pgr5 mutants under high temperature due to impaired cycle electron flow regulation. Quantum yield (φII) of photosystem II (PSII), another critical parameter, is an indicator of plant health under the stress [30], which declined sharply with the increment of heat in control due to the damage of PSII system. Treatment like Molasses (T1), Kaolin (T3) and Abscisic acid (T5) reduces leaf internal temperature, or regulates the cell to keep up the quantum yield under the stress. Exogenous spray might increase tolerance in G3 genotypes but does not sustain under high heat but tolerant G1 genotypes can keep the yield due to own mechanism. High temperatures lead to photoinhibition of PS II, and subsequent decreased rates of carbon assimilation, resulting in a reduction in photosynthesis, as found in Maize [33]. Lower net photosynthesis and less chlorophyll fluorescence, as Fv/Fm, after 7 days of heat stress further verify damage to PS II and established stress in the leaves [34]. Non photochemical quenching (φNPQ) is a good indicator assessing impact of stress [30,27,35]. NPQ increased under heat stress, especially when Rubisco deactivation limited electron transport. This was attributed to the need for dissipating excess light energy as heat [36]. Experiment on Arabidopsis leaves showed that NPQ increased more at 44 than at 40, and was significantly higher after 30 min of heat stress compared to only 4 min, reflecting rapid stress response [37]. When high heat damage the leaf organelles, plant cannot process all the harvested light to produce the food. Thus, leaves expelled excess light or energy through non-photochemical quenching. The higher the damage, the higher the φNPQ from the leaves. In our findings, a lower φNPQ in Abscisic acid (T5) implies better utilization of light in photochemical pathway. Along with Abscisic acid (T5), Kaolin (T3) and Molasses (T1) application increases better utilization of light in photochemical pathway. The stability of φNPQ in G1 further highlights its tolerance capability with the heat and lower in G3 at early summer and increment in late summer denotes exogenous substance support the susceptible plant up to a level, not more. A proper functioning machinery in the plant cell result in high photosystem II Redox State (qL) [38]. The lower qL value in control implies less activity and uses of photosynthetic machinery in the leaves. However, Molasses (T1), Kaolin (T3), T4 (CaCl₂) and Abscisic acid (T5) support the PS machinery and proper activity in the pathway results in better qL. The tolerant G1 genotypes has better qL for better activity at the pathway. The parameter qL, a measure of the fraction of open PS II centers, showed a significant decrease under heat stress, so plastoquinone became more oxidized [37], further confirming the impact of heat on photosynthetic efficiency. The linear electron flow and redox state of the cell PS II is related to the Steady-State Proton Flux (vH), indicating mobilization of H⁺ in the photochemical pathway [39]. Likewise, Melatonin (T2) and Abscisic acid (T5) is better at regulating cell internal process thus results in better vH as well as in tolerant G1 genotypes. The same impact of Abscisic acid increases the proton conductivity (gH) in the leaves. From the correlation analysis, it is apparent how heat stress can cause physiological changes in plants, particularly to the photosynthetic apparatus. The strong negative correlations between both ambient and leaf temperatures with Phi2 and Fv/Fm indicate that under elevated thermal conditions, photosystem II efficiency is negatively impacted and that photochemistry would be impaired by reduced photochemical energy conversion efficiency. This result aligns with previous research that high temperature leads to structural changes in the thylakoid membrane and impose damage to the protein of photosystem II, leading to a decrease in quantum yield [37]. Given the strong negative correlation between PhiNPQ and both Phi2 and Fv/Fm, the response is indicative of an enforced shift away from photochemistry during heat stress, to non-photochemical quenching, which is a protective mechanism that dissipates excess excitation energy as heat. This response is important for avoiding photoinhibition but also necessarily reduces the energy available for photochemistry. Moreover, the positive association between SPAD and Fv/Fm supports the contribution for chlorophyll content to sustaining PS II function under heat stress. The strong association of Phi2 with both LEF and vH illustrates the way in which coordinated water transport and electron flow can ensure efficient photosynthesis under heat stress. Efficient water transport may allow the leaf to maintain a cooler temperature via transpiration and a capable electron transport chain ensures consistent energy flow while approaching thermally limited photochemistry. PAR had a positive correlation with LEF, but a negative correlation with PhiNPQ, indicating that light levels supported photochemistry until a limit, at which point energy could be dissipated as non-photochemical quenching as temperature increases from heat stress. The results show that plants that were exposed to heat stress for a prolonged period experiences phenomena that indicate both protective (NPQ) and compensatory (maintained chlorophyll, LEF and vH) mechanisms to avoid damage, but ultimately damage builds over time or with intense heat stress if the limits of the plant’s protective and compensatory capabilities are compromised. These physiological interactions emphasize the importance of selecting genotypes which have stable photochemical responses and capable efficacy transport system for better heat tolerance. Finally, while photosynthetically active radiation (PAR) is essential for photosynthesis, but excess PAR under heat can cause photodamage, leading to increased φNPQ and decreased Fv/Fm and φII. Thus, a balanced PAR is demanding for the plants. Heat stress of up to 36 ºC reduced the light radiation efficiency significantly [40]. Plants attributes like thickness and SPAD (leaf greenness) is very important for the plant to lessen impact of the heat stress. Leaf thickness can increase the temperature differential thus cooling the leaf internals, prevent chlorophyll damage and maintain proper photosynthetic activity. The organic substance treatment those develop surface coating like kaolin and Molasses is very good for the development of temperature differential. The chemical substances like melatonin, CaCl₂ and Abscisic acid is good at regulating internal cell processes to keep up the photosynthetic activity.

Conclusions

Strawberry production in warmer climates such as Bangladesh, is increasingly being challenged by extreme summer temperatures and unpredictable heat waves. This study found that the heat tolerant genotype (G1) maintained more photosynthetic performance, leaf greenness and internal cooling efficiencies over the heat-susceptible genotypes. Additionally, the kaolin and molasses treatments were the only treatments that decreased internal leaf temperatures by forming protective coating on leaves, while melatonin, CaCl₂ and abscisic acid treatments had direct regulatory effects on internal physiological processes (stomatal regulation, oxidative process and radioprotection etc) and were able to maintain photosystem efficiency due to the identified heat stress, The combination of heat tolerant genotypes with targeted exogenous treatments, found in this study, is a realistic approach to Strawberry production during summer in tropical regions. However, the study had certain limitations. This was conducted under pot based, field like conditions rather than open field planting which likely had some influence on microclimatic effects and root zone interactions. Only three genotypes and five treatments were examined and did not evaluate long-term yield and fruit quality. Future work should aim at validating these findings on a wide variety of genotypes and under open field growing conditions. Moreover, assessing the interaction between exogenous treatments and soil health under stress, will be essential. Lastly, it may also offer deeper insight into mechanisms of heat tolerance by exploring the molecular and gene expression response to these treatments.

Supporting information

S1 File. Data.

(ZIP)

pone.0331496.s001.zip^{(936.7KB, zip)}

Data Availability

The data underlying the results presented in the study are available as supplementary file in the submission.

Funding Statement

This work was supported by the Special research grant (SRG), Ministry of Science and Technology, Government of The People’s Republic of Bangladesh (grant number: SRG – BS – 307; 2023-24)” https://grant.most.gov.bd/en/services/most/special-research-grant received by corresponding author S. Moonmoon. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. 2025 Sep 11;20(9):e0331496. doi: 10.1371/journal.pone.0331496.r001

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19 Mar 2025

PLoS One. doi: 10.1371/journal.pone.0331496.r002

Decision Letter 0

Ramegowda Venkategowda

7 May 2025

Dear Dr. Moonmoon,

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: No

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Reviewer #1: Dear authors,

In this work, it has been studied the effects of exogenous application of different compounds on strawberries during field study. A detailed analysis of photosynthetic parameters is provided, and evidence that the treatments contribute for reducing the leaf temperature differential. The research is relevant in the context of alleviating heat stress, which is expected to increase due to climate change.

However, there are some major points that should be addressed. Certain aspects of the methodological setup require further clarification. I also provide a list of minor points for consideration. I see potential in the data acquired by the authors, and I hope my comments help to improve their work.

Kind regards

Major points

• English writing requires deep revision.

• Please provide the precise identification (variety) of the tested genotypes, as research reproducibility is fundamental for its acceptance. This information is also very relevant for future studies as, for instance, aiming at understanding why G1 is tolerant, while G2 and G3 are susceptible to heat stress.

• I think that is necessary a better description of how the G and P lines are related (sections 2.3 and 2.6). I suggest the authors to create a schematic representation.

• In the context of the comment above, it was also not clear for me which variety was used for the treatments. For instance, in Figures 6-18, three varieties are represented on panels b, d and f (P1-3). Do they correspond somehow with the genotype used for the treatments test (panels a, c, and e)?

• Please provide the full details of soil fertilization (concentration and manufacturer, amount and source of the manure, etc), fungicide and pesticide (manufacturer, concentrations).

• Please also mention at which time of the day, and at which day of the month the measurements were made. This is important for understanding why some of the observed effects did not appear on the first month of the analysis.

• The manuscript would benefit from a deeper bibliography input. That goes from the decision for the selection of the compounds for treatments to the analysis of the results. Statements in the Results should be supported by a source reference, even if the information is taken for granted. The impact of heat stress on the photosynthetic apparatus has been greatly studied in other species, often in combination with biotic or chemical stimulants. The deeper bibliographic review would also help to improve the Discussion, which has only 5 cited references.

Minor aspects

• Regarding the experimental setup (point 2.2), the authors mention that the treatments were performed during constant intervals over three months and repeated thrice, between October-November 2023 to April-May 2024. Next (point 2.7), I understand that an initial set was prepared and from this set, the three experiment rounds were started in parallel. However, this point is elusive and I do suggest to clarify it. Was there a time window between the start of each experimental round? If not, I would consider these not as three independent experiments, but rather as one larger experiment with a good number of replicates (Figure 3). While this design can be valuable for statistical analysis, especially in a field experiment, I would still recommend repeating the study to confirm the results.

• Scientific names should be italicizes (e.g. Fragaria, Rosaceae)

• Some abbreviations are lacking their full description next to its first mention (e.g. RCBD, PGR; RH);

• Please provide the reference for the RCBD model.

• I suggest to move the description of treatments that are now in the section 2.7 to section 2.8, so it would be next to the full description of the treatment application. Also, please provide the manufacturer of each reagent used. I would also suggest to clearly specify the temperature at which the reagents were stored;

• All Figures would benefit from better legends. Please introduce more details, including full description of what they are representing, description of the error bars, statistical test applied, number of individuals tested per condition (n), etc.

• Please also provide the version of each software and R package used.

• I suggest that each treatment be described by both its full name and abbreviation (T1–T5) when presenting the results. This would make the reading easier. Also, please add the description of each treatment o the figures’ legend.

• I suggest to increase the font size of Figure 19 for easier reading. Also, although not really critical, blue and red are usually used for denoting negative and positive values/correlation, so I suggest to swap them to avoid any misinterpretation. I understand that data across all genotypes and treatments were combined and used to plot the Pearson’s correlation. This information should be clear. Furthermore, I do suggest to review the data analysis and interpretation, as for instance the observation that “SPAD increases ambient temperature”, which is unlikely. Still, I wonder whether it might be more informative to represent the correlations of the tested parameters separately for each genotype and treatment. This way one would be able to evaluate their inputs independently.

Reviewer #2: Comments to the author (PONE-D-25-14863)

The manuscript titled “Mitigation of heat stress using hormones during summer season for survivability of strawberry plants” is an interesting study. The study by Salwa et al is mainly focusing on the use of five exogenous substances (Molasses, Melatonin, Kaolin, CaCl₂, and Abscisic Acid) to mitigate heat stress in three strawberry genotypes under tropical summer conditions which involves physiological and fluorescence measurements across different months. To be honest, the study is interesting and I truly enjoy the reading of manuscript. Overall, the research is valuable and relevant, particularly in the context of climate resilience in horticultural crops. However, some extensive improvements are needed to enhance the scientific clarity, rigor, and writing quality. As per my observation, in the current form, it lacks hypothesis-driven design clarity, and some methodological and interpretational issues need attention. Some suggestions are as follow:

It is extremely embarrassing to review the paper without line numbers to point-out the specific corrections. But I have following suggestions to consider:

I would strongly suggest to change the title as: Exogenous Application of Hormones and Chemicals to Mitigate Heat Stress in Strawberry Under Tropical Summer Conditions.

Overall, the abstract should be carefully revised as it lacks clarity and scientific soundness. Terms like “some sort of capability” are vague and has incomplete phrasing. Please provide better summary of the most effective treatments and genotype response needed.

In the introduction section, it needs better framing of research gaps. For example, what is unknown about hormone-based mitigation strategies in strawberry under field-like summer stress particularly in Bangladesh. Further, inconsistent tenses and awkward phrasing are present throughout, e.g. “It is establishing climatic change...” is an unclear statement. Further, “…mandatorily has to endure high heat” is overly informal. In Introduction, it doesn’t clearly state the hypothesis and research question as well as key gaps.

Material and methods are the most important section and it should have clear citations/protocol used in the present study. There are some key parts to improve. In this section, genotypes are inconsistently labeled, as sometimes G1/G2/G3, elsewhere P1/P2/P3 there must be uniformity throughout the manuscript. Please use scientific or cultivar names of strawberry genotypes if available and specify the concentration basis for each treatment (e.g., ppm or % w/v, and how these concentrations were finalized/selected. Please provide justification why these 5 treatments were chosen or provide appropriate literature citations/physiological rationales.

It is unclear that how many number of replicates per treatment/per genotype were used. Was the fluorometer standardized/calibrated before use? Any internal checks? Please elaborate the statistical models in more depth. Was random effect for replication included and interaction terms analyzed?

In the results section, many figures show overlapping trends please consider consolidating. Leaf surface temperature being higher in treatment than control contradicts expectation. Explanation is speculative; check methodology or measurement error. Graph captions needed improvements as some are mislabeled (e.g., gH shown but figure caption mentions ϕNPQ Fig. 18).

Please provide numerical values with statistical summaries (e.g., mean ± SE) in text for major parameters.

In statistical analysis part, please clarify what variables were considered random vs fixed in LMM. Further, Pearson correlation matrix (Fig. 19) is dense but informative and interpret more in text.

Overall discussion is descriptive, not mechanistic. Please include some information on the roles of ABA in stomatal regulation under heat, Melatonin as antioxidant/protective compound, Kaolin and molasses as physical shields against radiation, and also genotype differences are needed to be discussed. Please provide recent literature and add more context from global strawberry stress physiology.

Conclusion Needs to state clear practical recommendations, e.g., which combination(s) are best for growers. It must be concise to the point. Also, clarify that this is a first step, and in future long-term, field-based, and reproductive/yield trait studies are needed. add these as future directions.

Reviewer #3: Comments for Author

� This manuscript “mitigation of heat stress using hormones during summer season for survivability of strawberry plants” is very interesting in which Author focused on effect of heat stress on strawberry and its alleviation through Hormones.

� In abstract Author did not mention the levels or concentrations of hormones used to alleviate heat stress.

� Authors required to write novelty statement about their research

� Introduction is insufficient, Author should compare their research with studies of previous researchers

� Hypothesis of study is not clear in introduction section

� In material and methods section too much headings are used by Authors, it is required to write under minimum headings. Particularly second and third heading of the material and methods.

� Why Author used RCBD design? Whereas experiment was conducted under pots.

� Results are written well by authors but still revision is required to improve results. Author should add significance level or p values in results section.

� Graphical presentation also required to improve. Authors need to write in correct manners on axis of graphs.

� Pearson’s correlation diagram is not clear. It is advised to add clear diagram

� In discussion section Author no need to indicate treatments as T1, T2.. etc Moreover, Author needs to write discussion in well mechanized form.

� Conclusion section needs improvement and required to write limitation and future prospects of their study.

� References should be balanced in reference list as well as in manuscript text.

Reviewer #4: In the present manuscript, the authors evaluated the effect of different PGRs sprays on three different strawberry genotypes to observe the tolerance response of plants from the onset of tropical summer to peak summer. The experimental approach is well justified and well described; however, the results are not adequately presented. In the result sections 3.2, 3.3 (number repeated in this section) and 3.4, there is no indication of which phenotype the data for the different treatments are (Figures, a, c, & e) or from which treatment the data in the phenotype graphs are (Figures, b, d & f). All of the above does not allow for understanding the interpretation of the results or their discussion.

Other minor concerns are:

- All abbreviations must be defined in the abstract and when they are first used in the introduction or materials and methods sections (RCBD, RH, SPAD, PGRs…).

- P1, P2 & P3 must be G1, G2 & G3 in section 2.6 of MM

- In the result sections 3.2, 3.3 (number repeated in this section) and 3.4, there is no indication of which phenotype the data for the different treatments are (Figures, a, c, & e) or from which treatment the data in the phenotype graphs are (Figures, b, d & f).

- In the MM section, three phenotypes are indicated: G1 (heat tolerant), G2, and G3 (heat susceptible). However, all the corresponding graphics are labeled with the P1, P2, and P3 varieties. Please clarify. These labels are repeated in all the results sections and in the discussion or conclusion sections.

Finally, I recommend that a native English speaker revise the entire manuscript…

**********

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Reviewer #1: Yes: Gustavo Turqueto Duarte

Reviewer #2: No

Reviewer #3: No

Reviewer #4: No

**********

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PLoS One. 2025 Sep 11;20(9):e0331496. doi: 10.1371/journal.pone.0331496.r003

Author response to Decision Letter 1

9 Jun 2025

Author Responses to the Reviewer’s Comments

Section-A : latest part

Editor comments:

In your Methods section, please provide additional information regarding the permits you obtained for the work. Please ensure you have included the full name of the authority that approved the field site access and, if no permits were required, a brief statement explaining why.

Author responses:

No such body is exist at both institutional & country level and no such permission is needed or applicable for conduction of any research work or experiments regarding ethical considerations of plant culture and growth

This was added in section 2.1

Editor comments:

In the online submission form, you indicated that

"The data underlying the results presented in the study are available from corresponding author on request"

All PLOS journals now require all data underlying the findings described in their manuscript to be freely available to other researchers, either

1. In a public repository,

2. Within the manuscript itself, or

3. Uploaded as supplementary information.

This policy applies to all data except where public deposition would breach compliance with the protocol approved by your research ethics board. If your data cannot be made publicly available for ethical or legal reasons (e.g., public availability would compromise patient privacy), please explain your reasons on resubmission and your exemption request will be escalated for approval.

Author responses

All data generated or analysed during this study are included in this manuscript. No more data, other than raw data, which also provided as supplementary file (3 excel file). Pls check declaration section and supplementary file (excel file)

Editor comments:

We note that your author list was updated during the revision process. In order to add or remove authors or update the order of the author byline after initial submission, we ask that authors complete an Authorship Change Request form. You may review our full authorship change policy and download the Authorship Change Request form here: https://journals.plos.org/plosone/s/authorship#loc-authorship-changes.

Please fill out all required sections of the form. If you are adding or removing more than 2 authors, you can complete multiple forms and submit as many forms as needed to reflect the updates. Please return the form(s) as an attachment by emailing plosone@plos.org or by uploading it as a submission file labeled with the file type ‘Other’. The form will be reviewed by PLOS staff for approval. Should the changes be approved, we will require written confirmation from all authors confirming that they approve of the changes. Please note that if your manuscript is accepted, we will not be able to complete the publication process without the completed form.

Author responses

This research was conducted under the direct supervision of the co-authors (Prof. Dr. Sharifunnessa Moonmoon & Prof. Dr. Md. Masudur Rahman - where they played role as Supervisor and co-supervisor respectively of the MS research of the first author (Najra-Tan-Nayeem Salwa). Mistakenly we excluded this co-author name

Now added even all the related formalities were completed and a humble request would like to made to include this co-author name

Authorship Change Request form was downloaded, filled up and uploaded in the system

This co-author name were included in everywhere of the related section (Pls see author name , affiliations , author contribution section)

Editor comments:

Please amend your authorship list in your manuscript file to include author Dr. Md. Masudur Rahman.

Author responses

This co-author name were included in everywhere of the related section (Pls see author name , affiliations , author contribution section)

Editor comments:

Please amend your manuscript to include a reference list. References must be placed at the end of the manuscript and numbered in the order that they appear in the text. For more information on the formatting of references, please visit the author guidelines at: http://journals.plos.org/plosone/s/submission-guidelines#loc-reference-style

Author responses

Amendment of the reference list was completed. References were placed at the end of the manuscript and numbered in the order that they appear in the text

Section –B : previous part

� Reviewer #1: Dear authors,

Kind regards

Major points

� Comments for Author:

English writing requires deep revision.

• Author’s Response

Thank you for your observation. We recognize that certain parts of the manuscript required improvement in English language and expression. To address this, we have thoroughly revised the manuscript to enhance clarity, grammar, and overall readability.

� Comments for Author:

Please provide the precise identification (variety) of the tested genotypes, as research reproducibility is fundamental for its acceptance. This information is also very relevant for future studies as, for instance, aiming at understanding why G1 is tolerant, while G2 and G3 are susceptible to heat stress.

• Author’s Response

We fully agree that providing the precise identification of the tested genotypes is essential for ensuring reproducibility and facilitating future research. In response, we have specified the exact varieties used in the study: G1= RABI-3, G2= BARI Strawberry-2 and G3= BARI Strawberry-3. This information has been added to the Materials and Methods section (Section 2.2).

• Comments for Author:

I think that is necessary a better description of how the G and P lines are related (sections 2.3 and 2.6). I suggest the authors to create a schematic representation.

• Author’s Response

We understand the confusion caused by the inconsistent use of labels in Sections 2.3 and 2.6. Specifically, we mistakenly used “P” instead of “G” in some instances when referring to the genotypes. We have now carefully corrected this throughout the manuscript to consistently use “G” (i.e., G1 G2 and G3) for genotypes.

• Comments for Author:

In the context of the comment above, it was also not clear for me which variety was used for the treatments. For instance, in Figures 6-18, three varieties are represented on panels b, d and f (P1-3). Do they correspond somehow with the genotype used for the treatments test (panels a, c, and e)?

• Author’s Response

We appreciate your attention to the figure layout and labelling. To clarify, the treatments were indeed applied to all three genotypes (G1, G2 and G3). Figures 6-18 were designed to present two separate aspects of the study for each parameter: The effects of genotypes (shown in panels a, c and e) under various treatments and the overall effect of treatments (shown in panels b, d and f) averaged across genotypes.

Thus, both treatment and genotype effects were assessed within the same experimental setup.

Additionally, we acknowledge the labelling error in the genotype panels, where the genotypes were mistakenly labeled as P1, P2 and P3. These have now corrected to G1, G2 and G3 in the figures, figure legends, and relevant sections of the manuscript for clarity and consist

• Comments for Author:

Please provide the full details of soil fertilization (concentration and manufacturer, amount and source of the manure, etc), fungicide and pesticide (manufacturer, concentrations).

• Author’s Response

We agree that providing detailed information on soil fertilization, as well as the fungicide and pesticide applications, is important for transparency and reproducibility. In response, we have revised the Materials and Methods section (section 2.4) to include the following details:

The soil was mixed thoroughly with fertilizers following the BARC (2012) recommendation. Per pot, 250g vermicompost, 1.67 g TSP, 1.83 g MoP and 0.08 g MgSO4 were applied and kept for some days after watering to settle the soil.

• Comments for Author:

Please also mention at which time of the day, and at which day of the month the measurements were made. This is important for understanding why some of the observed effects did not appear on the first month of the analysis.

• Author’s Response

As mentioned in the revised manuscript, chlorophyll fluorescence data were collected during the first half of the day on three specific dates: 30th March, 30th April and 30th May. These points were strategically chosen to capture plant response under progressively increasing heat stress conditions, thereby allowing us to compare physiological performance across varying temperature intensities over time. We have now clearly stated this information in the Materials and Methods section (section 2.7).

� Comments for Author:

The manuscript would benefit from a deeper bibliography input. That goes from the decision for the selection of the compounds for treatments to the analysis of the results. Statements in the Results should be supported by a source reference, even if the information is taken for granted. The impact of heat stress on the photosynthetic apparatus has been greatly studied in other species, often in combination with biotic or chemical stimulants. The deeper bibliographic review would also help to improve the Discussion, which has only 5 cited references.

• Author’s Response

Thank you for your insightful suggestion. We fully agree that strengthening the manuscript with a deeper and more comprehensive bibliographic foundation is essential to support our methodological choices and to place our findings within the context of existing research.

In response, we have significantly expanded the literature review in both the Introduction and Discussion sections.

Minor aspects

• Comments for Author:

Regarding the experimental setup (point 2.2), the authors mention that the treatments were performed during constant intervals over three months and repeated thrice, between October-November 2023 to April-May 2024. Next (point 2.7), I understand that an initial set was prepared and from this set, the three experiment rounds were started in parallel. However, this point is elusive and I do suggest to clarify it. Was there a time window between the start of each experimental round? If not, I would consider these not as three independent experiments, but rather as one larger experiment with a good number of replicates (Figure 3). While this design can be valuable for statistical analysis, especially in a field experiment, I would still recommend repeating the study to confirm the results.

• Author’s Response

To clarify, the three replications mentioned in the manuscript refer to biological replicates arranged simultaneously under the same environmental conditions—i.e., all genotypes and treatments were applied in parallel within a single experimental cycle. There was no time window between the start of each replication. Therefore, we agree that the setup represents one complete experiment with multiple replicates, rather than three temporally independent experimental rounds.

• Comments for Author:

Scientific names should be italicizes (e.g. Fragaria, Rosaceae)

• Author’s Response

We have reviewed and corrected the formatting of all scientific names, including genus and family names, to ensure they are properly italicized in accordance with scientific writing conventions (Pls see first line of Introduction).

� Comments for Author:

Some abbreviations are lacking their full description next to its first mention (e.g. RCBD, PGR; RH-);

• Author’s Response

We have carefully revised the manuscript to ensure that all abbreviation, including RCBD, PGR and RH are now presented with their full forms upon first mention (Pls see ABSTRACT). This correction has been applied consistently throughout the text.

• Comments for Author:

Please provide the reference for the RCBD model.

• Author’s Response

We have now included a reference to support the use of the Completely Randomized Design (CRD) model applied in this experiment. The reference added is:

Gomez, K.A., & Gomez, A.A. (1984). Statistical Procedures for Agricultural Research (2nd ed.). John Wiley & Sons.

� Comments for Author:

I suggest to move the description of treatments that are now in the section 2.7 to section 2.8, so it would be next to the full description of the treatment application. Also, please provide the manufacturer of each reagent used. I would also suggest to clearly specify the temperature at which the reagents were stored;

• Author’s Response

The description of treatments are now in the section 2.5 Specifications of the reagents with stored temperatures were provided (Pls see section 2.5)

� Comments for Author:

All Figures would benefit from better legends. Please introduce more details, including full description of what they are representing, description of the error bars, statistical test applied, number of individuals tested per condition (n), etc.

• Author Response

All the recorded data were transferred in Microsoft Excel and data curating, sorting, arranging, processing, visualization etc., were performed. Data was then loaded in the R software (R Core Team, 2024) and RStudio ( Version: 2025.05.0+496) to carry out all kinds of statistical analysis. Linear mixed modelling was used to perform ANOVA in the light-dependent parameters. The light-independent parameters were analyzed by performing two-way ANOVA. The mean of the significant parameters were separated using the fisher LSD test (Gomez and Gomez, 1984) at 0.05 level of p-value. The “tidyverse” package was used for the calculation of mean and sem. The data was visualized in graph form using the “ggplot2” package along with others. Pearson’s correlation test were implied in the parameters using the “metan” package along with performing the significant test (Pls see section 2.8).

• Comments for Author:

Please also provide the version of each software and R package used.

• Author’s Response

In response, we have updated the Materials and Methods section to include the version details of all software and R packages used in the analysis. Specifically, statistical analyses were performed using R software version: 2025.05.0+496 (Pls see section 2.8).

• Comments for Author:

I suggest that each treatment be described by both its full name and abbreviation (T1–T5) when presenting the results. This would make the reading easier. Also, please add the description of each treatment o the figures’ legend.

• Author’s Response

We have revised the manuscript to present each treatment with both its full name and corresponding abbreviation (T1–T5) for clarity and ease of reading in result section. This includes a clear description of each treatment—5% Molasses (T1), 10 ppm Melatonin (T2), 5% Kaolin (T3), 10 mM CaCl₂ (T4), and 5 ppm Abscisic Acid (T5)—in the text.

• Comments for Author:

I suggest to increase the font size of Figure 19 for easier reading. Also, although not really critical, blue and red are usually used for denoting negative and positive values/correlation, so I suggest to swap them to avoid any misinterpretation. I understand that data across all genotypes and treatments were combined and used to plot the Pearson’s correlation. This information should be clear. Furthermore, I do suggest to review the data analysis and interpretation, as for instance the observation that “SPAD increases ambient temperature”, which is unlikely. Still, I wonder whether it might be more informative to represent the correlations of the tested parameters separately for each genotype and treatment. This way one would be able to evaluate their inputs independently.

• Author’s

Attachment

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PLoS One. doi: 10.1371/journal.pone.0331496.r004

Decision Letter 1

Ramegowda Venkategowda

14 Jul 2025

Dear Dr. Moonmoon,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Aug 28 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Ramegowda Venkategowda, PhD

Academic Editor

PLOS ONE

Journal Requirements:

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

Dear Authors,

Kindly sees the comments from a reviewer especially Reviwer 4. There is a serious issue on labeling the figures and given proper legends or methodological explanation. Kindly correct the same.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #3: All comments have been addressed

Reviewer #4: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions??>

Reviewer #3: Yes

Reviewer #4: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #3: Yes

Reviewer #4: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #3: Yes

Reviewer #4: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #3: Yes

Reviewer #4: Yes

**********

Reviewer #3: Author has addressed all the comments properly with reasons. Therefore my decision is accepted for further publication process

Reviewer #4: The authors have greatly improved the manuscript's language but some revisión is still needed. However, my concerns remain regarding the presentation of results as explained in the first review. The graphs in Figures 6 through 18 (the number in Figure 17 is repeated) represent the different parameters recorded (Ambient temperature on the leaf surface, Leaf internal temperature, Leaf thickness, SPAD, etc., for each treatment (T0-T5)). The primary concern is that authors do not specify whether the data in the graphs in sections a, c, and e of each figure correspond to all plants or a specific variety. Furthermore, the graphs in sections b, d, and f of each figure, which refer to the three varieties used, do not specify which treatment (T0-T5) the data are from. The authors should present the data collected for each Strawberry variety and each treatment used to allow for better interpretation, comparison, and discussion of the results.

**********

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy

Reviewer #3: No

Reviewer #4: Yes: Homero Reyes de la Cruz

**********

Attachment

Submitted filename: accept.docx

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PLoS One. 2025 Sep 11;20(9):e0331496. doi: 10.1371/journal.pone.0331496.r005

Author response to Decision Letter 2

25 Jul 2025

Author Responses to the Additional Editors Comments

[Dear Sir,

Sorry, I tried several time but failed to build PDF appropriately. I observed that, during PDF formation / build figure -18 is converting figure 17, seems to be repetition, though content is is not changing

Therefore total figure number is changing in to 19, instead of 20]

Would like to request to consider the fact or technical error ]

1. Additional editor comments:

Kindly see the comments from a reviewer especially Reviewer 4. There is a serious issue on labeling the figures and given proper legends or methodological explanation. Kindly correct the same.

Author Responses:

We sincerely thank Reviewer 4 for the valuable feedback. We acknowledge the concern regarding figure labeling and the lack of proper legends or methodological explanations. In response, we have thoroughly revised the manuscript to ensure that:

•All figures are correctly labeled with consistent numbering and appropriate captions.

•Figure legends now provide clear and sufficient detail to be understood independently.

Author Responses to the Reviewer’s Comments

Reviewer #4:

1.Reviewer’s Comments

The authors have greatly improved the manuscript's language but some revision is still needed.

Author’s Response

We have carefully reviewed the entire text once again and made further revisions to enhance clarity, grammar, and overall readability. All changes have been highlighted in the revised version of the manuscript for ease of reference.

2. Reviewer’s Comments

However, my concerns remain regarding the presentation of results as explained in the first review.

Author’s Response

The previous comments of reviewer-4 regarding results in the first review was like below

“The experimental approach is well justified and well described; however, the results are not adequately presented. In the result sections 3.2, 3.3 (number repeated in this section) and 3.4, there is no indication of which phenotype the data for the different treatments are (Figures, a, c, & e) or from which treatment the data in the phenotype graphs are (Figures, b, d & f). All of the above does not allow for understanding the interpretation of the results or their discussion”.

Thanks reviewer for above valuable suggestions

In results (section 3.2 and 3.3) repetition was avoided carefully. In 3.2 the ambient temperature of the leaf surface (Fig. 6), leaf internal temperature (Fig. 7) and the differential temperature (Fig. 8) were described in control and treatment groups of the study

The findings were described properly with clarity. Pls see the color changed text (red color) in section 3.2 (line number 335-342; 344-348; 355-357)

In section 3.3, two important leaf attributes like leaf thickness (Fig. 9) and leaf greenness (SPAD) (Fig. 10) were stated clearly. Please see color changed text (red color) where important findings were highlighted (line number 373 – 377; 386 – 391)

In section 3.4, figure denotes the treatment variation of maximum quantum efficiency where, in March ABA showed the best performance but with the time of increasing temperature (April and May) Kaolin (T3) treatment showed the better performance. In case of figure b. d, f, G1 showed the maximum quantum efficiency compared to the other genotypes (Pls see the line 395- 399 ; 399 -401)

3. Reviewer’s Comments

The graphs in Figures 6 through 18 (the number in Figure 17 is repeated) represent the different parameters recorded (Ambient temperature on the leaf surface, Leaf internal temperature, Leaf thickness, SPAD, etc., for each treatment (T0-T5)). The primary concern is that authors do not specify whether the data in the graphs in sections a, c, and e of each figure correspond to all plants or a specific variety.

Author’s Response

Thanks. Repetition of figure 17 is avoided

Yes, now specified

Figure 17: Steady-State Proton Flux (vH) of PSII of Strawberry plants under different treatments

and genotypes. Treatment and genotypes having different letter varies significantly at

p ≤ 0.05

and

Figure 18: Proton conductivity (gH) of PSII of Strawberry plants under different treatment and

genotypes. Treatment and genotypes having different letter varies significantly at

p ≤ 0.05

The data in the graphs in sections (3.2 & 3.3) a, c, and e of each figure (8, 9) correspond to all plants. Pls see color changed text (line number 335 and 367)

4. Reviewer’s Comments

Furthermore, the graphs in sections b, d, and f of each figure, which refer to the three varieties used, do not specify which treatment (T0-T5) the data are from. The authors should present the data collected for each Strawberry variety and each treatment used to allow for better interpretation, comparison, and discussion of the results.

Author’s Response

To clarify, all treatments were indeed applied across all three genotypes (G1, G2, and G3). Figures 6–18 were intentionally designed to illustrate two complementary perspectives for each parameter:

• Panels a, c, and e show the effects of different genotypes under various treatments.

• Panels b, d, and f show the overall effects of treatments averaged across genotypes.

In other words, both genotype and treatment effects were analyzed within the same experimental setup. To generate these visualizations, we created two separate pivot tables from the raw data for each parameter—one summarizing data by genotype and the other summarizing data by treatment.

Attachment

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PLoS One. doi: 10.1371/journal.pone.0331496.r006

Decision Letter 2

Ramegowda Venkategowda

17 Aug 2025

Exogenous application of hormones and chemicals to mitigate heat stress in Strawberry under tropical summer conditions

PONE-D-25-14863R2

Dear Dr. Moonmoon,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Ramegowda Venkategowda, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0331496.r007

Acceptance letter

Ramegowda Venkategowda

PONE-D-25-14863R2

PLOS ONE

Dear Dr. Moonmoon,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

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PERMALINK

Exogenous application of hormones and chemicals to mitigate heat stress in strawberry under tropical summer conditions

Najra-Tan-Nayeem Salwa

Sadia Shabnam Swarna

Md Masudur Rahman

Sharifunnessa Moonmoon

Roles

Abstract

Introduction

Materials and methods

2.1. Study location, duration, work permission and ethical considerations

2.2. Genotype collection

2.3. Plant multiplication

2.4. Pot preparation and plant establishment

Fig 1. selected genotypes and plants for the pot experiment.

2.5. Experimental design and treatment application

Fig 2. experimental layout for pot culture.

Fig 3. selection of the exogenous spray for the experiment.

2.6. Environmental monitoring

2.7. Plant fluorescent data collection

2.8. Data analysis

Results

3.1. Environmental data

3.1.1. Maximum, minimum and average daily air temperature.

Fig 4. maximum, minimum and daily average air temperature (°C) of the experimental field in the month of March, April and May, 2024.

3.1.2 Maximum, minimum and average daily relative humidity (%RH).

Fig 5. maximum, minimum and daily average air relative humidity (RH %) of the experimental field in the month of March, April and May, 2024.

3.2. Leaf temperature of the strawberry plant

Fig 6. ambient temperature (°C) on the leaf surface of strawberry plants under different treatment and varieties.

Fig 7. leaf internal temperature °C of strawberry plants under different treatments and genotypes.

Fig 8. leaf temperature differential °C of strawberry plants under different treatments and genotypes.

Fig 18. proton conductivity (gH) of PSII of strawberry plants under different treatment and genotypes.

3.3 Leaf attributes of the strawberry plant

Fig 9. leaf thickness (μm) of strawberry plants under different treatments and genotypes.

Fig 10. leaf greenness (SPAD) of strawberry plants under different treatments and genotypes.

3.4 Leaf fluorescence of the strawberry plant

Fig 11. maximum quantum efficiency (Fv/Fm) of strawberry plants under different treatments and genotypes.

Fig 12. linear electron flow (LEF) of strawberry plants under different treatments and genotypes.

Fig 13. quantum yield (φII) of PSII of strawberry plants under different treatments and genotypes.

Fig 14. non-regulatory energy dissipation (φNO) of PSII of strawberry plants under different treatments and genotypes.

Fig 15. regulated non photochemical quenching (φNPQ) of PSII of strawberry plants under different treatments and genotypes.

Fig 16. redox state (qL) of PSII of strawberry plants under different treatments and genotypes.

3.5 Proton activity of the strawberry plant

Fig 17. steady-state proton flux (vH) of PSII of strawberry plants under different treatments and genotypes.

3.6 Pearson correlation between the variables

Fig 19. Pearson’s correlation between the parameters of heat stress tolerance in strawberry plants under different treatments and genotypes.

Fig 20. The difference between the genotypes and the effect of the treatments on the plants.

Discussion

Conclusions

Supporting information

Data Availability

Funding Statement

References

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Ramegowda Venkategowda

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Ramegowda Venkategowda

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Ramegowda Venkategowda

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Acceptance letter

Ramegowda Venkategowda

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Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

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