The experimental material was identified based on the phenotypic screening of 123 bread wheat cultivars under open field conditions during rabi season 2020-21 at BUAT-Banda. Out of 123 cultivars, eight contrasting wheat cultivars viz., four heat tolerant (DBW 150, WH 730, AKAW 2862-1, and Halna) and four heat sensitive (K 1006, PBW 550, WH 1105, and HD 2967) cultivars were identified based on Heat Tolerance Index (HTI), Heat Susceptibility Index (HSI), Canopy Temperature (CT), Capacity for Grain Filling (KWR %) and Yield Stability Index (YSI). All of these genotypes were of the spring type and were collected from ICAR- Indian Institute of Wheat and Barley Research, Karnal (India). These eight contrasting cultivars were evaluated to study the effect of heat stress on different phenological, physiological, and biochemical traits in bread wheat during crop season 2021-22.

The weather in Banda is characterized by high temperatures, frequent droughts, and unpredictable precipitation, with an average annual rainfall of 850 mm. The climatic conditions in this region make it an ideal location for conducting terminal heat stress screening for cool-season crops, such as wheat. The data on weather parameters was obtained from the Meteorological Observatory Unit (MOU) at the BUAT campus. The annual rainfall (mm), maximum, minimum temperature, and relative humidity during the entire crop growth period are presented in Figure 1 .

The experimental material was planted in a two-row plot measuring 2 m in length, with two replications following a randomized complete block design. The distance between plants and rows was maintained at 10 cm and 25 cm, allowing for approximately 40 plants in each plot (per genotype). Experiments were conducted in three different environments, as described below:

Both the OE and HSE experiments were irrigated five times to avoid the effect of drought on the test material. The EHSE experiment was irrigated every 8-10 days to avoid the confounding effects of heat and drought stress. The recommended practice packages for this region in terms of fertilization, weeding, and crop protection were adopted to grow healthy wheat crops.

A total of 21 traits such as phenological, physiological, and biochemical traits were recorded in each contrasting cultivar, as mentioned below.

Data on 10 important phenological traits were recorded in all three environments. The traits included 50% flowering (FLW), days to maturity (DM), plant height (PH in cm), number of tillers per plant (NT), spike length (SL in cm), spikelet/spike (SS), grain number/spike (GS), test kernel weight (TKW in g), biological yield (BY), and seed yield (SY). The FLW and DM were recorded on a plot basis when 50% of the plants reached heading and when the whole plot crop reached physiological maturity. PH, NT, SL, SS, and GS were measured on five randomly selected plants, and average values were taken for further analysis. The BY and SY were recorded in kg per plot for each genotype, while the TKW was estimated by counting 100 seeds in grams (g).

Data on four relevant physiological traits, viz., canopy temperature (CT), normalized difference vegetation index (NDVI), chlorophyll content index (CCI), and chlorophyll concentration in µmol m² (Chl), were recorded at the heading and grain filling stages of the crop (Pask et al., 2012).

The canopy temperature of the plot was measured using a portable infrared radiometer (Apogee, MI-210) at the heading and mid-grain filling stages. The readings were recorded between 11:00 and 14:00, when plants were exposed to the highest temperatures. The five CT readings from each plot were recorded, and the mean values were used for analysis.

The NDVI was measured using a portable infrared radiometer (Apogee, AT-100) at the heading and grain filling stages for each plot. The readings were measured under bright, sunny, and clear skies. The five observations from each plot were recorded for 20 seconds and the mean values were used for analysis.

The chlorophyll content index (CCI) and the chlorophyll concentration in µmol m² (Chl) of the middle part of the flag leaf were measured using a chlorophyll concentration meter (Apogee, MC-100) at the mid grain-filling stage. The three readings were taken from plant leaves, and five plants were selected from one plot and connected directly to the data logger. The average values of each of the 15 samples were used for data analysis.

Leaf samples were collected at 15 DAA (days after anthesis) and subjected to biochemical studies.

All enzymes were extracted in triplicate (replication-wise) with appropriate extraction buffers at 4°C and assayed at 37°C. Glutathione reductase (GR) and SOD were extracted by homogenizing the samples in 0.1 M phosphate buffer (pH 7.5) containing 1% polyvinylpyrrolidone (PVP), 1 mM EDTA, and 10 mM β-mercaptoethanol using a pre-chilled pestle and mortar. CAT and APX were extracted with 0.05 M phosphate buffer (pH 7.5) containing 1% PVP (Kaur et al., 2008). After centrifugation of the homogenates at 10,000g for 20 min, the supernatant was used for the assay.

The activity of SOD was determined by adding 100 mM Tris HCl buffer (pH 8.2), 6 mM EDTA, and 6 mM pyrogallol solution to the enzyme extract as described by Marklund and Marklund (1974), with partial modifications in the concentrations of the components (Singh et al., 2023). The change in absorbance was recorded at 420 nm after an interval of 30 sec up to 3 min. One unit of enzyme activity was defined as the amount of enzyme that caused 50% inhibition of the auto-oxidation of pyrogallol observed in the blank in one minute in one gram of fresh tissue.

GR activity was assayed by adding 200 mM potassium phosphate buffer (pH 7.5), 1.5 mM MgCl₂, 0.2 mM EDTA, and 0.025 mM NADPH to the enzyme extract, followed by 0.25 mM oxidized glutathione in the reaction mixture (Esterbauer and Grill, 1978). Partial modifications of the original method included the use of phosphate buffer (0.2M, pH 7.5) instead of Tris-HCl (0.1 M, pH 7.4) and modified concentrations of the other assay components to achieve better results (Kaur et al., 2023). The decrease in absorbance at 340 nm was recorded after an interval of 30 sec up to 3 min. One unit of GR activity was expressed as nmoles of NADP⁺ formed min^-1g^-1 of FW and was calculated using €_NADPH of 6.22 mM^-1 cm^-1.

The assay mixture of APX included 50 mM sodium phosphate buffer (pH 7.0), 0.5 mM ascorbic acid in enzyme extract, and H₂O₂ solution (Nakano and Asada, 1987). Absorbance was recorded at 290 nm in a spectrophotometer after an interval of 30 sec up to 3 min. The molar extinction coefficient of monodehydroascorbic acid (MDAA) was 2.8 mM^-1cm^-1 and the enzyme activity was expressed as nmoles of MDAA formed min^-1g^-1 of FW.

CAT activity was determined by preparing a reaction mixture containing 50 mM sodium phosphate buffer (pH 7.5) and enzyme extract. The reaction was initiated by the addition of H₂O₂ solution: its consumption was recorded at 240 nm for 3 min at 30-sec intervals (Chance and Maehly, 1955). The extinction coefficient for H₂O₂ was 0.0394 mM^-1cm^-1. Enzyme activity was expressed as μmoles of H₂O₂ decomposed min^-1g^-1 of FW.

The method by Bates et al. (1973) was used to measure the amount of proline. Extraction was performed in a sulfosalicylic acid solution (3% w/v), followed by centrifugation at 6000 g for 15 min. The assay mixture included an acid-ninhydrin solution and glacial acetic acid in addition to the extract. The reaction mixture was boiled at 100°C for 1 h, followed by the addition of toluene. The toluene-containing chromophore was aspirated from the aqueous phase, and the absorbance was read at 520 nm and measured in a spectrophotometer. Proline content was calculated using the standard curve and expressed as mg g⁻¹ FW.

The combined analysis of variance for all pheno-physiological and biochemical traits was computed using the STAR, I (2014). The genotypes, treatments, their interactions, standard errors, and least significant difference (LSD) test along with Tukey’s Honest Significant Difference (HSD) test, were performed. Correlation analysis was performed for each environment and combined using the corr_plot function of the “metan” package (Olivoto and Lúcio, 2020) in R software. The linear regression analysis and scatter plot of SY taken as a dependent variable with all traits considered independent variables were performed using tidyverse, coherent rstatix (Wickham et al., 2019), and ggplot2 (Wickham, 2016) packages in R software.

There were significant effects of a gradual increase in temperature observed in each genotype for all phenological traits ( Figure 2 ).

i. Days to 50% flowering (FLW): The average FLW under OE was 81 days, 66 days in HSE, and 58 days in EHSE ( Figure 2A , Table 2 ). The FLW ranged from 63 to 91 days in OE, 54-72 days in HSE, and 48-62 days in EHSE. Halna was the earliest parental line among 64 days in OE, 55 days in HSE, and 49 days in EHSE. The HD 2967 was the last and took the maximum amount of time to head into each environment. The FLW showed an 18% reduction in HSE and a 28% reduction in time in EHSE as compared to the FLW in OE ( Supplementary Material, Table A1 ).

ii. Days to maturity (DM): The duration of crop maturity is an important factor to avoiding terminal heat stress. The average DM in the heat-tolerant and heat-susceptible parents was 131 and 139 days, respectively, under optimum environment (OE) ( Table 2 ). The average maturity duration was reduced to about 25 days (18%) under HSE and EHSE (36%) in heat-tolerant and heat-susceptible parents (Figure 2B; Supplementary Material, Table A2 ). The crop cycle was drastically shortened, leading to forced maturity in EHSE as compared to OE. Parent HD2967 took the maximum amount of time to reach maturity and was of longer duration in all environments.

iii. Plant Height (HT): Plant height was significantly reduced, to about 36% under EHSE as compared to OE. Plant height showed less reduction (4%) under HSE as compared to OE (Figure 2C; Supplementary Material, Table A3 ). Halna was the shortest line and remained unaffected in all conditions, and WH730 was the tallest genotype in all environments.

iv. Number of Tillers/Plant (NT): TN ranged from 9-19 under OE, 7-12 under HSE, and 6-10 under EHSE. The average number of tillers per plant was high in heat-susceptible parents (15) as compared to heat-tolerant parents (11) under OE (Figure 2D). The number of tillers per plant showed a reduction of 39% under EHSE ( Supplementary Material, Table A4 ). A maximum reduction of 38% and 62% was observed in HD 2967 under HSE and EHSE, respectively.

v. Spike length (SL): Spike length ranged from 9.0-13.67 under OE, 8.67-13.0 under HSE, and 7-12 under EHSE (Figure 2E; Table 2 ). Spike length was drastically reduced under EHSE, and the maximum reduction (15.56%) was observed under EHSE. Spike length was more affected in HD2967.

vi. Number of spikelets/spike (SS): The number of spikelets/spike was not significantly affected by temperature stress. The average number of spikelets per spike was 21 in OE, 20 in HSE, and 18 in EHSE (Figure 2F; Table 2 ). The maximum reduction of 20% in SS was recorded in EHSE.

vii. Number of grains per spike (GS): The average GS recorded a reduction of 32% and 14% under EHSE and HSE, respectively, in comparison to OE (Figure 2G; Supplementary Material, Table A7 ). The highest reduction in GS (47%) was observed in WH 1105, while the minimum reduction (16%) was observed in WH 730 under EHSE ( Figure 2 ).

viii. Test kernel weight (TKW): The average 100 seed weight was reduced by 17.54% and 27.33% under HSE and EHSE, respectively, compared to OE. The maximum shriveled grain (42.31%) was recorded in cultivar HD 2967, while the minimum reduction (6.42%) was observed in DBW 150 ( Figure 2H , Supplementary Material, Table A8 ).

ix. Biological yield (BY): Biological yield was also severely affected by heat stress under HSE and EHSE. The average BY (1.85 kg/plot) was recorded under OE, 1.34 kg/plot under HSE, and 0.78kg/plot under EHSE. The BY showed a reduction of 17% in HSE and 42% in EHSE in heat-tolerant parents, whereas a reduction of 23% and 54% was observed under HSE and EHSE in heat-susceptible parents, respectively ( Figure 2I ; Supplementary Material, Table A9 ).

x. Seed Yield (SY): The heat-tolerant parental lines showed the highest yield reduction under HSE (28.57%) and EHSE (50.0%), whereas a yield reduction of 51% and 81% was observed under HSE and EHSE environments in heat-susceptible parents ( Figure 2J ; Supplementary Material, Table A10 ). HD 2967 (89% reduction) was highly affected by prolonged heat stress, showing yield in EHSE.

The canopy temperature (CT) at the heading stage was <35°C, which does not affect the reproductive ability of the plant. The average CT recorded at the heading stage was 21.82°C and 20.14°C in OE and HSE, respectively. The CT at the heading stage was 32.24°C in the very late-sown experiment. At the grain filling stage, the average CT was 23.33°C in OE and 31.86°C in HSE, and a high temperature of 40.85°C was recorded in EHSE at the mid-grain filling stage of the crop. Thus, the late-sown crop was exposed to extensive heat stress under the prolonged heat stress environment of EHSE ( Figures 3A, B ). The NDVI (Normalized Difference Vegetation Index) is a simple graphical indicator that is used to analyze the sample based on the difference in measurement of near-infrared and red light. The NDVI was high at the heading stage (622 measured in OE, 573 measured in HSE, and 461 measured in EHSE), whereas the NDVI values showed a reduction at the grain filling stage (600 in OE, 490 in HSE, and 370 in EHSE). Plant greenness was significantly reduced in the heat-stress environment as compared to the optimum environment ( Figures 3C, D ). The CCI was higher in OE as compared to the heat-stress environment at the grain filling stage. The average chlorophyll concentration was 556 μmol m² in OE, 483 μmol m² in HSE, and 411 μmol m² in EHSE ( Figures 3E, F ).

The biochemical studies related to understanding the mechanism of heat tolerance were also undertaken with a major focus on the antioxidant system ( Figure 4 ). It was observed that the activity of SOD was moderately to significantly induce in all the tolerant genotypes under heat stress as compared to the control samples, with a maximum increase of 33% recorded in AKW2862-1, while all the susceptible genotypes showed a decline in activity in heat-stressed samples, with the highest decrease of 26% observed in PBW 550. All heat-tolerant and heat-susceptible genotypes showed a decrease in SOD activity under extended heat stress conditions when compared with controls. The trend for POX activity was also found to be similar to that of SOD. The rise in POX activity in tolerant genotypes ranged from 10.4% (Halna) to 41% (DBW 150). Like SOD, POX activity in susceptible genotypes also showed a decreasing trend under stress conditions, with the highest decrease of 24% recorded for PBW 550 under heat stress, while other susceptible genotypes also showed moderate to slight decreases in activity. Both sets of genotypes showed decreased POX activity under extended heat stress; however, this reduction was more pronounced in heat-susceptible genotypes as compared to heat-tolerant ones.

APX activity was significantly increased in tolerant genotypes under heat stress compared to controls. The increase in activity ranged from 193% (DBW 150) to 56.6% (AKAW 2862-1) when compared to control samples, whereas only a slight increase in activity was observed in the case of all the susceptible genotypes. A decrease in APX activity under extended heat stress was observed in both genotypes except in DBW 150, where the activity was 37% higher than the control samples, although the activity was 53% lower than the activity under heat stress. CAT activity was found to either remain unchanged (DBW 150 and Halna) or significantly decreased (WH 730 and AKW 2862-1) in tolerant genotypes, while the activity was significantly decreased in all the susceptible genotypes except for K 1006, in which the activity remained unchanged. All genotypes showed a decline in APX activity under extended heat stress as compared to the activity recorded under optimum and heat stress conditions.

The data presented in Table 2 and Figure 4 showed that both the tolerant and susceptible genotypes accumulated higher proline content under heat stress conditions as compared to the control samples. The highest increase of 72% in proline content was recorded for DBW 150. followed by WH 730, which showed an increase of 44% in proline content as compared to control samples. However, variation in the pattern could be observed under prolonged heat stress in terms of proline synthesis, as tolerant genotypes exhibited a moderate increase in proline content under extended heat conditions, whereas a moderate decrease was observed in heat-susceptible genotypes as compared to the samples analyzed in optimum environments.

Correlation analysis: Correlation heat maps were generated to understand the relationship between phenological, physiological, and biochemical variables in all three individual environments and pooled across environments.

Optimum environment: SY was significantly and negatively correlated with CT_HS (r = - 0.84***) and CT^GFS (r = - 0.73**) ( Figure 5A ). The TKW (r=-0.27) and NT (r = -0.06) were not significantly or negatively correlated with SY. SY was significantly and positively correlated with BY (r = 0.82***), SL (r = 0.73**), PH (r = 0.70**), SS (r = 0.80***), and NDVI_HS (r = 0.60*), while APX (r =0.20), CAT (r =0.25), FLW (r =0.44), and DM (r =0.41), showed a positive but insignificant correlation. DM was negatively correlated with CT_HS, CT_GFS, TKW, POX, SOD, proline, GS CCI_GFS, Chl_GFS, and NDVI_GFS, while phenological traits had a positive correlation. The CT_HS and CT_GFS were highly negatively correlated with all the traits studied, while both traits were positively correlated with Chl_{GFS and} TKW.

Heat stress environment: Under a heat stress environment, SY was highly significant and negatively correlated with CT_HS (r = -0.83***), and CT_GFS (r = -0.66**) ( Figure 5B ), but FLW (r = -0.11), DM (r = -0.22), and NDTV_HS (r = -0.04) showed a non-significant negative correlation. SY was significantly and positively correlated with GS (r =0.54*), Chl_GFS (r =0.69**), TKW (r =0.56*), proline (r =0.86**), SOD (r =0.89**), POX (r =0.80**), and CCI_GFS (r =0.90**).

Extended heat stress environment: Under EHSE, SY was significantly but negatively correlated with the crop cycle traits FLW (r = -0.80***) and DM (r = -0.72**) ( Figure 5C ), but the traits CT_HS (r =0.05), CAT (r = - 0.01), TKW (r = - 0.29), and NT (r = - 0.05) showed a non-significant negative correlation with SY. Traits GS and NDVI_GFS had a non-significant positive correlation with seed yield. SY under high-temperature stress was significantly and positively correlated with the PH (r =0.66**), Proline (r =0.58**), POD (r =0.80**), SOD (r =0.53*), POX (r =0.72**), and BY (r =0.67**), while SL (r =0.06), SS (r =0.17), CT_GFS (r =0.31), APX (r =0.37), and CCI_GFS (r =0.49), had a non-significant positive correlation.

Combined correlation: A correlogram ( Figure 5D ) was generated for all three environments, showing the relationship between the parameters. The combined correlation analysis shows that all studied traits are positively correlated with SY except CT_HS (r = -0.71**), and CT_HFS (r = -0.88**). The correlation between traits and SY changed under different stress environments. For some of the traits, the correlation changed from positive to negative. A few important traits that showed a positive correlation with SY even under EHSE, should be highlighted for the selection of heat-tolerant lines.

Regression analysis: A regression analysis was performed to determine the relationship between phenological-physio-biochemical traits and seed yield. Among the phenological traits, DM (R^2 = 0.52) and BY (R^2 = 0.44) have shown a positive effect on seed yield, indicating that biomass and crop duration contributed to the yield advantage under stress conditions ( Figure 6 ). CT_HS and CT_GFS had a positive impact on seed yield, with R² = 0.70 and R² = 0.54 under OE and R² = 0.88 and R² = 0.43 under HSE, respectively ( Figure 7 ). In EHSE, CT had a non-significant association with seed yield. The NDVI_HS showed a significant association (R² = 0.36) with seed yield under OE, while a non-significant association was observed under HSE and EHSE. The NDVI_GFS and Chl_GFS showed a consistently significant positive effect on grain yield under HSE and EHSE. The strong effect of CCI and Chl_GFS on grain yield was observed under HSE, which was found to be reduced under EHSE. Among biochemical traits, SOD, POX, APX, and proline had the maximum positive relationship under HSE and EHSE, while the effect was very low under OE conditions ( Figure 8 ).