Introduction

Wheat (Triticum aestivum L.) is one of the world’s most important food crops, accounting for more farmland than any other. A secure supply of food is in jeopardy due to both climate change and the world’s expanding population. More frequent and severe heat waves and droughts are consequences of climate change, which also causes less precipitation overall and changes in its distribution and pattern. These factors have an effect on crop yields and the quality of the food we eat1. Due to ongoing changes in the global climate, high temperature stress, which affects the yield of vital crops like wheat, is predicted to get worse. According to climate projections, wheat yields will fall 4.1–6.4% by the end of the twenty-first century due to an average temperature increase of 1–4 °C2,3. Excessive heat significantly hinders physiological processes, grain production, growth and development of plants, and ultimately, yield4,5. The ideal temperature range for wheat during the anthesis to grain maturity stage is 22 to 25 °C; any higher than this results in irreparable damage6. A high temperature of 25 to 32 °C during the anthesis and grain filling stage of late-planting wheat genotypes influences the crop’s early maturation, which significantly reduces grain production7,8. By 2050, it is predicted that there will be 9.1 billion people on the planet. Consequently, in order to meet the food demands of the rapidly expanding population, it is necessary to enhance wheat yield and productivity by creating varieties that can withstand high temperatures. Climate change negatively impacts wheat performance during the crop cycle due to extreme temperature stress situations. Therefore, breeders must identify genotypes that are tolerant to heat. Growing advanced wheat lines in both normal and stressed conditions could be a means of selecting genotypes for stress resistance. Plant breeders can create genotypes more stress tolerant by using genetic diversity. Therefore, the most crucial task for breeders in identifying heat-resistant cultivars is to improve the selection strategy.

Another growing source of worry for wheat productivity is drought. Due to many morphological, physiological, and biochemical alterations at the cellular and molecular levels, wheat’s reaction to drought is a very complex phenomenon9. The complex multi-trait and polygenic control of drought tolerance, high genotype and environment (G×E) interactions, low heritability, and difficulty in mass screening of plant traits and genes are the main challenges in the breeding of drought-tolerant wheat cultivars10,11,12. Genetic advancement in drought tolerance breeding has been slowed by the temporal and spatial variability in the imposition of drought stress across many habitats and experiments, which has contributed to low selection efficiency. Depending on the stage of growth, length, and severity of the drought, it can weaken both source and sink strengths. This can lead to up to 92% less wheat production when both sources and sinks are limited13. Wheat grain number decreases due to drought stress, especially during reproductive development14. Researchers found that drought stress negatively impacts important agronomic parameters such as grain production, grain numbers per spike, 1000-kernel weight, plant height, and overall plant health15,16.

Wheat improvement programs have uncovered a multitude of extremely important alleles through the exploitation of genetic resources such as landraces, synthetics, and wild relatives. The best genetic sources to employ in pre-breeding and breeding programs are landraces and stress-adapted cultivars17. Rich in traits that farmers and consumers value, these genetic resources exhibit great compatibility and extensive adaptation12. Landraces and related species haven’t been used much in breeding programs because we don’t know much about their lineage or usefulness, there isn’t a lot of descriptive data, important alleles have been lost through domestication and evolution, and there are unwanted alleles that could cause linkage drag19. Prioritizing landrace exploitation can help breeding programs incorporate important alleles and traits, such as tolerance to drought and heat.

Triticum sphaerococcum, more often known as Indian dwarf wheat, was farmed for millennia prior to the Green Revolution. It was native to India and Pakistan20. Farmers in the area prefer this wheat because of its improved tolerance to environmental constraints, such as high temperatures and drought tolerance. The presence of the Brassinosteroid Insensitive 2 (BIN2) gene, which helped adapt this round-grain wheat variety to the dry climate of India and Pakistan, gave it better drought tolerance and allowed it to accumulate nitrogen and phosphate21. Recently, Cao et al.22 discovered the heat tolerance gene TaSG-D1E286K in Indian dwarf wheat and explained how it improves heat tolerance. Furthermore, they discovered that the spread of TaSG-D1E286K is limited to India and Pakistan. Heat waves during the month of March are becoming a common occurrence. The extreme March temperatures of 2022—the highest since the nation’s temperature records date back to 1901—had an effect on wheat production. The projected wheat production for India’s market year (April-March) 2022/23 was reduced from 110 million metric tons (MMT) to 99 MMT due to a 10–15% drop in yields (FAS, USDA 2022). In this situation, the widely grown wheat varieties in North and Central Indian farmers’ fields were not been able to withstand the heat17. It is therefore necessary to spend an hour investigating wheat species that are related to and tolerant of heat and drought stress in order to address the issue of abiotic stresses. It would be wise to investigate the possibility of introgression of T. sphaerococcum into bread wheat with abiotic stress tolerance. Many stress tolerance indicators have been proposed by researchers to identify cultivars that are tolerant to stress; nevertheless, only a few numbers of these indices are more effective in selecting heat-tolerant genotypes in wheat. Indices like mean productivity index, stress tolerance index, the stress susceptibility percentage index, relative stress index, harmonic mean, mean relative performance, the yield stability index, yield index, and percent yield reduction were employed by researchers in bread wheat22,23. It is preferable to select for stable and tolerant genotypes with high values for MP, GMP, HM, YSI, MRP, and YI and low values for SSI, SSPI, RSI, and PYR.

Addressing the issue of abiotic stresses requires an hour of investigation into wheat species that are related to and tolerant of heat and drought stress. Therefore, in the current study, we assessed 116 T. sphaerococcum accessions and six high-yielding bread wheat varieties in the field under optimum, terminal heat stress, and restricted irrigation conditions to calculate stress tolerance indices. These stress indices have not been worked out in the Indian dwarf wheat as yet. With this evaluation, we were able to identify potential accessions that are tolerant to heat and drought stress and can be used as donors to improve bread wheat tolerance to these stresses.

Materials and methods

Location, experimental site and environments

The study was conducted in the subtropical region of India’s North Western Plain Zone, at the research fields of the ICAR- Indian Agricultural Research Institute in New Delhi. The institute is located at N 28° 38’ 24.0252”, E 77° 10’ 26.328”, and at an elevation of 228.61 m (750 feet) above sea level. A timely sown-irrigated environment (TS-IR), a timely sown restricted irrigation environment (TS-RI), and an irrigated late sown environment (IR-LS) were the three different types of production conditions that were used for the experiment. In the 2021–2022 cropping season (CS1) for restricted irrigation conditions, the trial was sown on October 30, 2021, and for timely sowing conditions, it was sown on November 10, 2021. December 20, 2021, was the planting date of the late-sown trial. India’s winter of 2022 was so unusual that a severe heat wave reduced the nation’s wheat output by at least 15%. The T. sphaerococcum accessions planted had the best conditions for reaching their full potential under optimum, terminal heat stress and drought conditions. In the 2022–2023 cropping season (CS2), only a selected set of accessions were planted in all three environmental conditions. The trial was planted on October 31, 2022, under restricted irrigation conditions, then on November 15, 2022, under timely sowing conditions. The late-sown trial was planted on December 25, 2022. We have chosen to offer statistics from a total of six production scenarios across two years, with all the genotypes spanning the years 2021–22 and a selected set of entries from the years 2022–23.

Plant material

The experimental materials include 116 accessions of T. sphaerococcum and six commercially farmed bread wheat cultivars that were employed as checks based on their production environments. The varieties HD 3226 and HD 3086 are recommended for TS-IR conditions, HD 3171 and C 306 for TS-RI conditions, and HD 3298 and HD 3271 for IR-LS conditions. HD 3226 and HD 3086 are mega varieties and very popular among the farmers. Despite being an extremely old variety, C 306 is still planted in farmers’ fields because of its exceptional chapati-making qualities and capacity to withstand drought. Both HD 3298 and HD 3271 can withstand higher temperatures during the grain filling stage.

Experimental layout and agronomic requirements

The experiment was conducted in two replications using Randomized Block Design (RBD) in both years. In each replication, genotypes were grown on a 2 m2 plot. We regularly irrigated the field based on the amount of rainfall, adhering to normal cultural and agronomic techniques to ensure a healthy crop. We irrigated the IR-TS and IR-LS experiments according to crop needs (generally 20–25 days interval) in both years. In both cropping seasons, the TS-RI trial received its first irrigation 30 days after seeding, with no further irrigation provided. In the CS1, January’s rainfall fulfilled the TS-RI trial’s requirement for a second irrigation. In the CS2, rain was received in the last fortnight of March.

Environmental evaluation

The weather parameters for both the crop growing season were obtained from the Division of Agricultural Physics, ICAR–IARI, New Delhi (Figs. 1 and 2). The TS-RI and TS-IR trials experienced a temperature of around 29.4 °C during CS1, while the late-seeded conditions experienced a temperature of 20.6 °C during the sowing time. The TS-RI and TS-IR trials experienced a temperature of around 30.9 °C and 28.7 °C during CS2, respectively, while the late-sown conditions experienced a temperature of 19.7 °C during the sowing time. The anthesis-to-grain filling stage is very crucial and sensitive to heat stress. High temperatures (> 28–30 °C) during the anthesis and post-anthesis stages of wheat can significantly reduce the weight of ripe grains, which in turn lowers yields8. In the TS-RI trial of CS1, the mean maximum temperature at the anthesis stage was approximately 21 °C, with 91% relative humidity and 8.5 h of sunshine; in the TS-IR trial, the mean maximum temperature was approximately 25.3 °C, with 91% relative humidity and 6.7 h of sunshine; in the IR-LS trial, the mean maximum temperature was approximately 32.4 °C, with 83% relative humidity and 8.4 h of sunshine. A significant rainfall event that occurred on the 8th and 9th of January 2022, totalling 95 millimetres, fulfilled the requirement for one irrigation. In the CS2, in the TS-RI trial, the mean maximum temperature at the anthesis stage was approximately 27.2 °C, with 82.8% relative humidity and 7.7 h of sunshine; in the TS-IR trial, the mean maximum temperature at the anthesis stage was approximately 30.3 °C, with 83.2% relative humidity and 7.5 h of sunshine; in the IR-LS trial, the mean maximum temperature was approximately 29.8 °C, with 84.7% relative humidity and 6.8 h of sunshine. A significant rainfall event occurred in the last fortnight of March 2023, totalling 102 millimetres. In all three experiments, there was no precipitation following the anthesis stage. Heat stress affected the TS-IR and TS-RI crops at the grain filling stage, while the late-sown crop was affected by heat stress from the anthesis to the grain filling stage (Figs. 3 and 4). Wheat crops in India suffered terminal heat stress during the latter two weeks of March 2022 and the first week of April 2022 as a result of a rapid increase in temperature. These crops were in the anthesis and grain-filling stages of development. The unusually high temperatures that occurred in March 2022 resulted in a decrease in wheat production of between 4 and 5 million metric tons. During the 2022–2023 cropping season, starting from April 5th, 2023, the temperature began to rise above 33 °C, which had a significant impact on the late-sown crop, which was in the grain filling stage.

Fig. 1
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Weekly weather parameter data of 2021-2022 wheat growing season of IARI, New Delhi.

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Fig. 2
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Weekly weather parameter data of 2022-23 wheat growing season of IARI, New Delhi.

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Fig. 3
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Weather parameter data from second fortnight of March 2022 to first fortnight of April 2022.

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Fig. 4
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Weather parameter data for the month of April 2023.

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Traits recorded

The grain yield (q/ha) of each genotype of Indian dwarf wheat and released cultivars planted in three production conditions was measured for two cropping seasons. All stress indices were calculated using the grain yield (Yp and Ys) of each genotype and the mean yield (Xp and Xs) of all genotypes under normal and stress conditions (heat and drought stress), respectively. For the released varieties that were utilized as checks, stress indices were also computed. Stress indices were compared between the T. sphaerococcum accessions and T. aestivum released varieties. The following calculations were used to compute heat and drought tolerance stress tolerance indices:

Stress susceptibility index (SSI) = 1-(Ys/Yp)/1-(Xs/Xp) Fischer and Maurer24.

Stress susceptibility percentage index (SSPI) = Yp − Ys/ 2(Xp) × 100 Moosavi et al.25.

Yield index (YI) = Ys/Xs Gavuzzi et al.26.

Yield stability index (YSI) = Ys/Yp Bouslama and Schapaugh27.

Relative stress index (RSI) = (Yp/Ys)/(Xs/Xp) Fischer and Wood28.

Mean productivity (MP) = (Yp + Ys)/2 Rosielle and Hamblin29.

Geometric mean productivity (GMP) = √(Ys × Yp) Fernandez30.

Harmonic mean (HM) = 2(Yp × Ys)/(Yp + Ys) Bidinger et al.31.

Mean relative performance (MRP) = (Ys/Xs) + (Yp/Xp) Ramirez and Kelly32.

Percent yield reduction (PYR) = (Yp − Ys)/Yp × 100 Farshadfar and Javadinia33.

where Yp and Ys are the yield performance of varieties, while Xp and Xs are the mean yield of all varieties under normal and stress conditions, respectively. The stress tolerance indices were calculated for both the years separately.

Statistical analysis

We performed the analysis of variance (ANOVA) of the two-year trial using a randomized block design in R Studio. The stress indices were calculated in Microsoft Excel. We statistically analyzed the acquired data and calculated the least significant difference (LSD) values for the yield trait and stress indices at 5%, 1%, and 0.1% probability levels. In R Studio, boxplots, K-means clustering, PCA analysis, and ridgeline plots were completed. The “corrplot” package34 in R studio was used to analyse the correlation between the traits under investigation in this study.

Results

ANOVA for grain yield and stress tolerance indices

Analysis of variance revealed significant differences among T. sphaerococcum accessions for yield under optimum heat and drought stress conditions for both years. Stress tolerance indices for drought and heat also varied a lot between the genotypes that were studied over the two years (Tables 1 and 2).

Table 1 Analysis of variance for yield and stress indices traits of all the genotypes across the drought and heat stress conditions in 2021-22 cropping season.
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Table 2 Analysis of variance for yield and stress indices traits of selected genotypes across the drought and heat stress conditions in 2022-23 cropping season.
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Comparison of means in cropping season 1

No stress condition

The box plots (Figs. 5 and 6) illustrate the genetic variation among T. sphaerococcum accessions and the bread wheat cultivars utilized as checks, assessed under drought and terminal heat stress conditions. The grain yield of bread wheat varieties was higher than that of T. sphaerococcum accessions under timely sown conditions (no stress) (Figs. 5 and 6; Table S1, S2). The grain yield range for T. sphaerococcum accessions was 9.72 to 47.44 q/ha. None of the T. sphaerococcum accessions surpassed the yield of the best check (HD 3226); however, 47 accessions exhibited significantly higher yields compared to the drought-tolerant variety C 306 (Table S1). This study calculated various stress indices, including SSI, SSPI, YI, YSI, RSI, MP, GMP, HM, MRP, and PYR, based on yield under both normal and drought and heat stress conditions (Tables S1 and S2).

Fig. 5
figure 5

Boxplot illustrates the variation among accessions of T. sphaerococcum and T. aestivum (check) cultivars for grain yield and stress indices under drought stress conditions. T. sphaerococcum accessions showed lesser susceptibility to drought against T. aestivum accessions when compared in terms of SSI, SSPI, RSI and PYR.

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Fig. 6
figure 6

Boxplot shows variation among accessions of T. sphaerococcum and T. aestivum (check) cultivars for grain yield and stress indices under heat stress conditions. T. sphaerococcum accessions showed higher yield stability as indicated by higher value for YSI and lower values for SSI, SSPI, RSI and PYR.

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Drought stress conditions: grain yield and stress tolerance indices

Under drought-stress conditions, T. sphaerococcum accessions exhibited a grain yield range of 5.51–42.13 q/ha, with TS 49 demonstrating the highest yield. The yield range of 29.22 to 46.83 q/ha was noted among the checks (Fig. 5, Table S1). The drought-tolerant variety HD 3171 exhibited the highest grain yield. None of the T. sphaerococcum accessions exhibited a grain yield superior to the best check, HD 3171. However, two accessions, TS49 and TS68, demonstrated significantly higher yields compared to HD 3086. In comparison to HD 3271 and HD 3298, 12 and 14 accessions showed significantly higher grain yields under drought conditions. Multiple accessions demonstrated a significantly increased grain yield when compared to C 306. TS 49 and TS 68 demonstrated significantly greater grain yield compared to four bread wheat checks under drought conditions (Table S1). To classify a genotype as stress-tolerant, it must display the lowest values for SSI, SSPI, RSI, and PYR, while higher values signify a lack of stress tolerance. The current study identifies five accessions of T. sphaerococcum: TS11 (0.26), TS36 (0.24), TS52 (0.27), TS57 (0.23), and TS82 (0.19), which exhibit significantly lower SSI_D values compared to the best check, HD 3171 (0.45) (Table S1). All of these accessions exhibit superior yield levels as well. Accessions such as TS49, TS31, TS47, TS68, and TS55 exhibit tolerance to moderate drought conditions while also demonstrating high grain yield, in comparison to other T. sphaerococcum accessions. A range of 1.39 to 26.50 was observed for T. sphaerococcum accessions, while bread wheat varieties exhibited a range of 5.37 to 26.05 for SSPI_D. Tolerant to drought, the bread wheat variety C 306 exhibited the lowest SSPI value among the check varieties. In comparison to C 306, T. sphaerococcum had 44 accessions with significantly lower value values for this trait. Among these, 33 accessions exhibit grain yields exceeding 35 q/ha under drought stress conditions. The relative stress index is a significant parameter in the assessment of stress tolerance indices. All accessions, except for eight, exhibited significantly lower RSI_D values compared to the best check, HD 3171 (Table S1). Aligned with the RSI, percent yield reduction (PYR) serves as a significant indicator of stress tolerance. For T. sphaerococcum, the PYR_D values ranged from 2.53% (TS 82) to 48.05% (TS 37), and for T. aestivum, they ranged from 14.88% (HD 3171) to 42.10% (HD 3226). Sixty-two T. sphaerococcum accessions exhibit a significantly lower yield reduction of less than 12% in comparison to HD 3171.

Other stress tolerance indices, including YI, YSI, MP, GMP, HM, and MRP, with high trait values, are significant parameters for identifying stress-tolerant, stable genotypes. In the case of the trait YI_D, 20 T. sphaerococcum accessions exhibited significantly higher trait values compared to the best check, HD 3171, with a value of 0.85. Though HD 3171 exhibited a high grain yield under drought stress conditions, a few T. sphaerococcum accessions, including TS 49, TS 27, TS 68, TS6, TS5, TS28, and TS 1, had higher yields and YI_D trait values. The Yield Stability Index (YSI_D) for over 60 T. sphaerococcum accessions under drought conditions was significantly greater than that of the best check, HD 3171 (1.76) (Table S1). None of the T. sphaerococcum accessions exhibited trait values exceeding those of the T. aestivum. Check HD 3226 for MP, GMP, and HM. However, many accessions exhibited higher trait values for these traits compared to C 306. Accessions such as TS 49, TS1, TS5, TS28, TS6, TS31, TS41, TS27, TS68, TS56, and PAUTS16 exhibited superior trait values for MP, GMP, and HM relative to other accessions. In terms of mean relative performance (MRP_D), 30 accessions had significantly higher values than the best check, HD 3226 (2.38). TS 49 (2.89) and TS1 (2.76) exhibited the highest values for this trait. Overall, TS 49, TS 31, TS 27, TS 68, PAUTS 16, TS 17, and TS 11 were identified as the most drought-tolerant accessions, exhibiting high stress tolerance along with improved grain yield (Table S1).

Heat stress conditions: grain yield and stress tolerance indices

Under terminal heat stress conditions, T. sphaerococcum accessions had grain yields ranging from 3.31 to 39.09 q/ha, with TS 68 having the greatest yield, followed by TS 49 (38.74 q/ha). The observed yield range among the checks was 18.56 to 39.17 q/ha (Fig. 6, Table S2). The heat-tolerant variety HD 3298 demonstrated the highest grain yield. None of the T. sphaerococcum accessions demonstrated a grain yield that exceeded that of the highest-performing checks, HD 3298 and HD 3271. Four accessions, TS3, TS49, TS61, and TS68, exhibited significantly higher yields than HD 3086. Many accessions exhibited significantly higher grain yields under terminal heat stress conditions when compared to HD 3171 and C306. TS3, TS 49, TS 61, and TS 68 exhibited significantly higher grain yield than three bread wheat checks when subjected to terminal heat stress conditions (Table S2).

The stress tolerance index (SSI_H) was significantly higher in 56 T. sphaerococcum accessions compared to the best check, HD 3298; however, not all exhibited superior yield performance. A limited number of accessions, including TS 24, TS 26, TS 68, PAUTS1, PAUTS17, PAUTS19, TS 36, TS 61, TS 82, and TS 3, demonstrated superior grain yield (> 35 q/ha) in conditions of terminal heat stress. The PYR_H values for T. sphaerococcum varied from 1.76% (PAUTS4) to 75.80% (TS 70), while for T. aestivum genotypes, they ranged from 33.03% (HD 3271) to 45.21% (C 306). PAUTS 4 exhibited low yield under both optimal and heat stress conditions, indicating that such genotypes are not suitable for breeding programs. Consequently, low values do not necessarily indicate high performance, and genotype grain yield must be considered. Accessions such as TS68, TS3, TS61, PAUTS16, Sugar Free, TS56, TS2, and PAUTS 1 demonstrate superior genotypic performance, achieving grain yields exceeding 35 q/ha with a maximum reduction of 15% in grain yield under terminal heat stress conditions. Many accessions exhibit markedly lower values for SSPI_H and RSI_H in comparison to the best checks (Table S2).

Many T. sphaerococcum accessions exhibited significantly higher values of YI_H and YSI_H compared to the best checks, HD 3298 and HD 3271, respectively. However, the top line for these traits, despite its stability, demonstrated a lower grain yield. Notable lines such as TS24, TS26, TS68, PAUTS1, Sugar Free, and PAUTS17 exhibited superior grain yields exceeding 35 q/ha, along with significant values for YI_H and YSI_H, and MRP_H. In relation to MP_H, GMP_H, and HM_H, none of the T. sphaerococcum accessions exceeded the highest value recorded for the best check, HD 3226. For MRP_H, TS 24, TS26, TS68, PAUTS1, Sugar Free, and PAUTS17 demonstrated significantly higher trait values compared to HD 3226 (2.39) (Table S2). These accessions also exhibited superior SSI_H, SSPI_H, PYR_H, and RSI_H, indicating their suitability for breeding programs.

Correlation between grain yield and stress tolerance indices

In order to determine the best stress tolerance criterion, the correlation coefficient between stress tolerance indices and grain production under normal, drought stress, and heat stress conditions was computed in CS1 (Figs. 7 and 8). In all situations, YLD_TS and YLD_RI were discovered to have a positive and statistically significant correlation of 0.87*** (Fig. 7), suggesting that they might be utilized to identify genotypes with high yields. Under drought stress, there was a negative corelation of -0.18*, -0.28**, and − 0.52*** between YLD_RI and SSPI_D, RSI_D, and PYR_D, respectively. However, under normal conditions, there was a positive correlation of 0.31*** for SSPI_D and 0.21* for RSI. The relationship between YLD_RI and YSI_D was also statistically significant (0.52***). To find genotypes that can withstand drought stress, it is helpful to select for higher YSI and lower SSI_D and SSPI_D values. Grain yield was positively and significantly correlated with YI_D, MP_D, GMP_D, HM_D, and MRP_D under YLD_TS and YLD_RI conditions. These indicators were chosen because they were the most effective in identifying genotypes that produced high yields in both situations. According to these indices, the drought-tolerant accessions with the best grain production and stress tolerance were TS 49, TS 31, TS 27, TS 68, PAUTS 16, TS 17, and TS 11. We found a significant positive association of YI_D and YSI_D with YLD_RI, but a negative correlation with SSI_D and SSPI_D, suggesting that we can use these two indices to differentiate between stable and drought-tolerant genotypes. We can identify genotypes as heat-tolerant by using the genotypes with the lowest values of SSI_D and SSPI_D, which demonstrated good yield under heat stress conditions.

Fig. 7
figure 7

Correlation among grain yield and stress indices under drought stress conditions.

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Fig. 8
figure 8

Correlation among grain yield and stress indices under heat stress conditions.

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We discovered a significant positive association between YLD_TS and YLD_LS (0.77***) under terminal heat stress conditions (Fig. 8), indicating their potential to identify high-yielding genotypes in both situations. Under heat stress, there was a strong negative correlation between YLD_RI and SSI_H, SSPI_H, RSI_H, and PYR_H (-0.73***, -0.37***, -0.64***, and − 0.67***, correspondingly), while under normal conditions, there was a positive correlation for SSPI_D (0.28**). Under YLD_TS and YLD_RI conditions, the grain yield was highly correlated positively with the YI_H, MP_H, GMP_H, HM_H, and MRP_H. Selection based on a greater YI and lower SSI_H and SSPI_H values can thus identify heat stress-tolerant genotypes. The heat-tolerant accessions were determined to be TS 24, TS 26, TS 68, PAUTS1, PAUTS17, PAUTS19, TS 36, TS 61, TS 82, and TS 3. These accessions demonstrate excellent stress tolerance and improved grain production. Genotypes that demonstrated good yield under heat stress conditions can be identified as heat-tolerant by utilizing the genotypes with the lowest values of SSI_H and SSPI_H.

Principal component and biplot analysis

The stress tolerance indices and grain yield (YLD_TS, YLD_RI, and YLD_LS) were used in principal component analysis (PCA) to find genotypes that could withstand drought and terminal heat stress (Table 3). Two of the twelve PCs—the first two with an eigenvalue greater than 1.0—contribute the most variation 96.5% for both the stresses. The first principal component (PC1) accounted for 64.09% of the overall variation under drought stress conditions, whereas the second principal component (PC2) accounted for 32.35% (Table 3). The first principal component (PC1) demonstrated a strong positive association (> 0.90) for all values of YLD_RI, YI_D, MP_D, GMP_D, HM_D, and MRP_D). There was a strong positive association between SSPI_D, RSI_D, and PYR_D and the second principal component (PC2). YI_D, MP_D, GMP_D, and MRP_D are the stress indicators that exhibit the greatest degree of variance among all of them. Under the terminal heat stress conditions, the first (PC1) and second (PC2) principal components contributed to the total variations by 70.14% and 26.39%, respectively (Table 3). There was a strong positive association (> 0.90) between the first principal component (PC1) and YLD_LS, YI_H, GMP_D, HM_H, and MRP_D. The second principal component (PC2) showed a strong positive relationship with YLD_TS and SSPI_H. The stress indices YI_H, MP_H, GMP_H, and MRP_H also exhibit the greatest diversity when it comes to terminal heat stress.

Table 3 Principal component analysis based on grain yield and stress tolerance indices.
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By combining PC1 and PC2, a biplot was created to examine the relationships between heat tolerance indices and genotypes evaluated (Figs. 9 and 10). As shown in Fig. 9, the T. sphaerococcum accessions TS49, TS1, TS27, TS28, TS31, and TS5 stayed stable in both normal and drought stress conditions, as shown by their high PC1 and low PC2 scores. In contrast, accessions like TS37, TS28-1, TS67, TS74, PAUTS12, TS71, and TS73 exhibit lower performance or are more vulnerable to drought stress due to their high PC2 and low PC1 scores, respectively. In terms of PC1 scores and trait values for stress indices such as MP_D, GMP_D, HM_D, YLD_D, and MRP_D, TS 49 stood out among the T. sphaerococcum accessions. This accession outperformed all 116 that were tested for drought stress.

Fig. 9
figure 9

Principal component analysis (PCA) based biplot showing correlation among the grain yield and stress indices under drought condition.

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Fig. 10
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Principal component analysis (PCA) based biplot showing correlation among the grain yield and stress indices under terminal heat stress conditions.

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Under terminal heat stress conditions, T. sphaerococcum accession TS 49, TS3, TS11-1, TS61, and TS68 were stable under normal and terminal heat stress conditions, as indicated by the higher PC1 but low PC2 values presented in Fig. 10. Accessions TS21, TS50, TS46-4, TS69, TS65, TS59, TS46-2, TS46-1, TS70, and TS73 have a high PC2 and a low PC1, making them less performing or terminally heat susceptible. The accessions viz., TS49, TS3, and TS79 exhibited the best trait values for stress indices such as MP_H, GMP_H, HM_H, YLD_LS, YI_H, and MRP_H, as well as the highest PC1 score. These accessions are consequently the best of the 116 examined for terminal heat stress.

Cluster analysis

Based on the drought and terminal heat tolerance stress indices, the T. sphaerococcum accessions and bread wheat released varieties were grouped into five clusters, respectively (Table 4; Fig. 11) Under drought stress, cluster 5 had the most genotypes (50), while clusters 1, 3, and 2 had 39, 16, and 13 genotypes, respectively. The released varieties were grouped into cluster 4. When the mean performance (Table 5) of T. sphaerococcum accessions was assessed, Cluster 5 had accessions with high trait values for YLD_RI, YI_D, YSI_D, MP_D, GMP_D, HM_D, MRP_D, and PYR_D. The improved performance and tolerance to drought stress were accounted for by the lower values of SSI D, SSPI D, and PYR D in this cluster. Overall, the released varieties had the best values for YLD_TS, YLD_RI, MP_D, GMP_D, and HM_D. Cluster 2 accessions were more vulnerable to drought stress because they exhibited high SSI_D, SSPI_D, and PYR_D values. Cluster 3 accessions had a somewhat higher grain yield and moderate drought tolerance.

Fig. 11
figure 11

K means clustering pattern among T. sphaerococcum accessions and checks based on grain yield and drought tolerance indices.

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Table 4 Clustering of T. sphaerococcum accessions and bread wheat released varieties based on drought tolerance indices.
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Table 5 Cluster mean of grain yield and drought and heat tolerance indices.
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Under terminal heat stress, cluster 1 included the most genotypes (67), while clusters 5, 4, and 2 had 25, 17, and 08 genotypes, respectively (Table 6; Fig. 12). Cluster 3 was formed by the released varieties. When the mean performance (Table 5) of T. sphaerococcum accessions was taken into account, Cluster 1 had accessions with high trait values for YLD_LS, YI_H, YSI_H, MP_H, GMP_H, HM_H, and MRP_H. Cluster 5’s superior performance and resilience to drought stress were accounted for by their lowest values for SSI_H, SSPI_H, RSI_H, and PYR_H. Cluster 2 accessions were more likely to experience terminal heat stress due to their high SSI_H, RSI_H, and PYR_H values. There was a moderate level of tolerance to terminal heat stress in the released varieties, and they also exhibited the highest values for YLD_TS, YLD_LS, MP_D, GMP_D, and HM_D. Cluster 5 accessions can withstand high temperatures; however, they don’t produce as much grain as cluster 1 accessions, which can withstand high temperatures as well but produce more grain yield overall.

Fig. 12
figure 12

K means clustering pattern among T. sphaerococcum accessions and checks based on grain yield and heat tolerance indices.

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Table 6 Clustering of T. sphaerococcum accessions and bread wheat released varieties based on heat tolerance indices.
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Comparison of means cropping season 2

Drought stress conditions: grain yield and stress tolerance indices

We tested 45 selected accessions under normal, drought, and terminal heat stress conditions during the 2022–23 growing season (CS2). The criterion for selecting accessions was the plant type for which the species is most well-known. Because there is diversity in the phenotypes of plants we have. The 45 accessions showed significant variation for the stress indices (Fig. 13). Grain production under timely seeded normal conditions was nearly identical to CS1. Many T. sphaerococcum accessions did better than C306, another drought-tolerant variety, but none of them did better than HD 3171 (44.89 q/ha) when they were stressed by drought (Table 7). Accessions such as TS49, TS56, Nanhe Samrat, and PAUTS16 demonstrated promising grain yield when compared to other checks. When compared to the best check, C306, three accessions—Nanhe Samrat, TS18, and TS69—had noticeably reduced SSI_D. In all, 30 accessions exhibited tolerant SSI_D values ranging from 0.29 to 0.99. Considering the other important traits like PYR_D, 16 accessions showed significantly lower grain yield reduction (up to 10%) over best check C 306 (13.98%). With the exception of 3, all of the accessions exhibited a markedly lower relative stress index (RSI_D) when compared to the best check, C 306. None of the accession outperformed the best check, HD 3226, for grain yield attributes; nevertheless, accessions like TS6, TS49, and Nanhe Samrat have shown considerable advantage for MRP_D. These accessions were more drought-tolerant and produced superior grain yields overall (Table 7).

Fig. 13
figure 13

Ridgeline plot showing variation among selected accessions of T. sphaerococcum and T. aestivum (check) varieties for grain yield and stress indices under drought and heat stress conditions. The vertical black lines indicate the mean trait value in the respective production environment. TA_N, T. aestivum under normal condition; TA_D, T. aestivum under drought condition; TA_H, T. aestivum under heat condition; TS_N, T. sphaerococcum under normal condition; TS_D, T. sphaerococcum under drought condition; TS_H, T. sphaerococcum under heat condition.

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Table 7 Mean performance of selected T. sphaerococcum accession and checks under drought stress in CS2.
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Heat stress conditions: grain yield and stress tolerance indices

Under terminal heat stress conditions, T. sphaerococcum accessions exhibited a significant variation in the traits that were examined (Fig. 13). When comparing SSI_H to the best check HD 3271, no accession of T. sphaerococcum showed statistical significance; nonetheless, eleven accessions were numerically superior (Table 8). In total, 24 accessions showed heat stress tolerance with SSI_H values up to 0.99. The best check, HD 3271, showed a loss in grain yield of 24%; 34 T. sphaerococcum accessions, on the other hand, had reductions as low as 19%. Two accessions, TS49 and TS61, had much higher MPR_H values for traits related to grain yield compared to HD 3226. All the other accessions, on the other hand, had lower values for MRP_H and traits related to grain yield (Table 8). When we analyzed the data from both seasons, we discovered that TS49, TS1, TS5, TS28, TS6, TS31, TS41, TS27, TS56, Nanhe Samrat, TS68, PAUTS16, and TS61 performed well in drought conditions. Under terminal heat stress, TS49, TS 61, TS3, TS68, PAUTS16, TS56, TS31, Sugar Free, and TS2 were some of the accessions that showed improved grain production with a lower grain yield loss.

Table 8 Mean performance of selected T. sphaerococcum accession and checks under heat stress in CS2.
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Discussion

The genetic composition of wheat landraces exemplifies an evolutionary strategy for adaptability and survival, particularly in moisture deficit and heat stress environments. However, following the introduction of high-yielding cultivars and advances in wheat agricultural systems, wheat landraces have experienced a decline in genetic diversity. The fact that some wheat landraces like T. sphaerococcum are still farmed suggests that they will be significant to farmers in the future or that they are better for nutrition or agronomy17. In a recent study, the genetic diversity of T. sphaerococcum accessions has been assessed through SNP markers. This diversity could be potentially explored for breeding heat and drought tolerant cultivars in bread wheat35. Wheat production faces numerous global constraints that present significant challenges for both farmers and breeders. Heat and drought are the two primary abiotic factors that constrain global wheat production. In such a scenario, exploring novel sources of stress tolerance from related wheat species will increase the chances of making bread wheat more tolerant to heat and drought. This study calculated stress indices based on grain yield under optimal, restricted irrigation, and late sown conditions to analyze drought and terminal heat tolerance in 116 accessions of T. sphaerococcum, along with 6 released bread wheat varieties used as checks. Additionally, it identified accessions with superior performance in drought and heat conditions. This report presents an initial investigation of stress tolerance indices in T. sphaeorocccum; no prior studies on these indices exist for this species. Consequently, the results are discussed in light of the findings observed in T. aestivum.

ANOVA results for drought and heat tolerance indices in CS1 and CS2 indicated highly significant differences (p < 0.01) among genotypes across all indices. There was notable variation for most measured indices, demonstrating the effectiveness of these indices in highlighting genetic diversity among the accessions evaluated (Tables 1 and 2). Various stress tolerance indices are effectively utilized for identifying tolerant genotypes in wheat under drought stress36,37,38,39,40, heat stress22,41,42,23,43, and combined drought and heat stress conditions44,45,46.

Crop improvement is based on genetic variation, which is indicated by differences in agronomic performance. When compared to other checks, accessions like TS49, TS56, Nanhe Samrat, and PAUTS16 showed promising grain yield under drought stress conditions. In heat stress conditions, TS2, TS3, TS68, PAUTS16, TS56, and TS31 performed better. These accessions have the potential to be excellent sources of stress tolerance or enhance adaptation and grain yield. The value of tolerance increases as SSI and SSPI values decrease, but they are unable to differentiate between genotypes that have higher yield in both conditions. Among the 116 accessions assessed under both stress conditions in CS1, 57% demonstrated tolerance to drought, while 63% exhibited tolerance to heat stress (Table S1 and S2). Genotypes with low values of SSI and SSPI can potentially have developed abilities to adjust to osmotic stresses through better root growth and productivity. The drought tolerant variety C 306 used in this study has lower SSI and SSPI among the checks, which also possess longer root length and root volume47 which is a measure of drought tolerance ability. Furthermore, the regulation of root architecture is mediated by various phytohormones, such as auxin, abscisic acid (ABA), and ethylene, which form complex signalling networks in response to osmotic stress48,49. However, if the genotypes exhibit lower grain yield under optimum conditions while showing minimal reduction in grain yield under stress conditions, they also tend to have low SSI and SSPI values. So, the two indices YI and PYR are very important because they help find genotypes that produce high yield in both optimal and stress conditions. A genotype exhibiting superior performance in both normal and stressed environments is characterized by higher values for YI, MP, GMP, and HM. These indices could be indicative of better water use efficiency of the tolerant genotypes50. The selections derived from these indices generally enhance the average performance of genotypes under both stress and non-stress conditions, lagging the ability to differentiate between stress-tolerant and high-yielding genotypes. These genotypes may exhibit higher yields under optimal conditions; however, their SSI value could exceed 1. Some accessions, like TS1, TS5, TS28, and TS41, have high trait values for YI, MP, GMP, and HM in CS1 when it’s stressed by drought and heat, but their SSI values were higher than 1 (Tables S1 and S2). MP, GMP, and HM typically favor increased yield potential while exhibiting reduced stress tolerance51. Heat stress induces photoinhibition in photosystem II and causes reduced photosynthetic efficiency of plants. The measurement of non-photochemical quenching (ϕNPQ, a photo-protective mechanism that dissipates the excess excitation energy as heat) showed that ϕNPQ had positive effect on grain yield in bread wheat under heat stress conditions52. Such physiological adaptations could suggest the tolerance mechanisms of genotypes under stress conditions and produce optimum yields. In both seasons, our study shows that TS49 and TS27 did better in drought stress, while TS49, TS61, and PAUTS16 did better in heat stress, as shown by significantly lower values of SSI and PYR and higher values of YI, MP, GMP, MRP, and HM (Tables 7 and 8). Similar findings were reported in durum wheat, where genotypes with higher yields and heat tolerance were identified based on higher values of MRP, GMP53, and YI54 in bread wheat. In the current study, bread wheat varieties had greater trait values for grain yield under normal and stress conditions, MP, GMP, HM, and MRP than T. sphaerococcum accessions, but considerably lower values for SSI, YSI, RSI, and PYR, and vice versa. This is clear since the released varieties are the result of systematic breeding targeted at increased yield in optimal conditions, but T. sphaerococcum, being a landrace, excels at surviving in adverse situations.

The mean grain yield reduction in CS1 under drought conditions was 14.16% for T. sphaerococcum and 31.69% for T. aestivum. We observed a similar range in CS2, with reductions of 14.47% and 29.14% for these two species, respectively (Table 7). Under terminal heat stress conditions, yield reduction in CS1 was 22.36% for T. sphaerococcum and 39.41% for T. aestivum, compared to 16.80% and 31.40% in CS2 for these two species, respectively (Table 8). This species exhibits a smaller decline in grain production under stress conditions compared to bread wheat17. The reduction in grain yield was higher in CS1 than CS2 because wheat production was hindered by excessive temperatures in March 2022 (CS1), the highest since the nation’s temperature records began in 1901. India’s anticipated market year 2022/23 (April-March) wheat production fell from 110 MMT to 99 MMT due to 10–15% lower yields (FAS, USDA 2022). Previous report indicate that drought stress causes a 20–60% reduction in grain yield in bread wheat55,56,36,57,38,58, while heat stress causes a 25–50% reduction22,23,43,59. The observed values indicate that the accessions in this study experience greater grain yield reduction due to heat stress than drought. This species is well adapted to the dry environments of India and Pakistan. The S1 locus encodes a GSK3-like kinase, similar to the Arabidopsis BIN2 protein, that acts as a negative regulator of brassinosteroid signalling, contributing to the species’ adaptability to dry conditions. The S1 protein exhibits insensitivity to brassinosteroid, which enhances the expression of brassinosteroid biosynthesis genes and significantly increases drought tolerance20.

Relying solely on values from various stress indices is insufficient for the selection of stress-tolerant or susceptible genotypes. To identify the most appropriate stress indices for drought and heat stress tolerance, the correlation coefficients between grain yields (YLT_TS, YLD_RI, and YLD_LS) under all three conditions and the respective drought and heat stress indices were analyzed. Our study in T. sphaerococcum accessions shows a positive correlation between YLD_TS and both YLD_RI and YLD_LS (Tables 6 and 5). These findings align with the investigations in bread wheat under heat stress53,41,23,59, drought stress60,61,62,36,37,57,40,58, and combined heat and drought63,46. Based on this correlation, these studies suggest that we can identify high-performing genotypes under both optimal and stress conditions. The results of the normal conditions will therefore be useful for the indirect selection of genotypes under stress conditions. In CS1, grain yield exhibited a negative correlation with SSPI and RSI under drought and heat stress conditions, while it showed a positive correlation under normal conditions. Additionally, YSI demonstrated a significant positive correlation with YLD_RI, but no correlation with YLD_TS (Tables 6 and 5). We observed similar findings in conditions of drought stress64,65 and heat stress22,23,43. The results indicated that lower values of SSI and higher values of YSI facilitate the selection of stress-tolerant genotypes. The current study discovered a strong and positive link between YI, MP, GMP, MRP, and HM and grain yield, both under normal and stress conditions. Similar correlations have been documented in wheat subjected to heat stress22,23,43,59, drought stress35,38,58,61,62, and combined heat and drought stress46.

Principal Component Analysis (PCA) was conducted to assess the percentage contribution of major components and indices to the total variance, utilizing grain yield data under normal and both stress conditions. The correlation coefficient can be used to look at how two variables are related, but PCA is a better way to choose the best yielding genotypes in both normal and stress conditions66,67. In the present study, the first two principal components accounted for over 96% of the total variation under both drought and heat stress conditions. PC1 exhibits a positive association with YLD, YI, YSI, MP, GMP, HM, and MRP in both stress conditions. Consequently, this component (PC1) may be referred to as a “yield potential and heat tolerance component” in the context of both drought and heat stress conditions. PC2 exhibits a significant correlation with SSI, SSPI, RSI, and PYR under both stress conditions, thus qualifying it as a “stress susceptibility component”. In our study, PCA confirmed the correlation results, indicating a positive correlation between grain yield under normal conditions and both stress conditions, as well as stress indices such as MP, GMP, HM, YI, and YSI (Table 3). This means that these indices can also find genotypes that can handle drought stress58,38, heat stress23,43,59, and combined heat and drought. It is important to note that the stress indices we observed in T. sphaerococcum for both types of stress align with the available results in T. aestivum. In wheat breeding, SSI serves as a significant selection criterion under severe drought stress, while GMP, MP, HM, TOL, and STI are crucial under less severe drought conditions68.

The identification of highly correlated stress indices through PCA biplot aids breeders in selecting the most critical traits for enhancing stress tolerance in crops. The current study indicates that the T. sphaerococcum accessions TS49, TS1, TS27, TS28, TS31, and TS5 exhibited stability and superior performance under both normal and drought stress conditions (Fig. 9). Additionally, under terminal heat stress conditions, accessions TS49, TS3, TS11-1, TS61, and TS68 demonstrated enhanced performance (Fig. 10). All accessions were categorized in the first quadrant, indicating their tolerance to drought and heat stress, as well as their capacity to enhance yield under improved conditions in the target environments. Genotypes that show dynamic stability are the best because they make good use of resources when they are stressed and could increase yield when environmental conditions get better69. This study found that under drought and heat stress conditions, PC-1 exhibited high loading values for MP, GMP, HM, MRP, and YLD, whereas PC-2 demonstrated high loading values for SSI, SSPI, RSI, and PYR. The results show that breeders should focus on improving tolerance, the stress susceptibility percent index, and the mean productivity-related indices for both types of stress. The biplot illustrated that YLD_TS, YLD_RI, and YLD_LS showed positive correlations with YI, HM, MP, MRP, and GMP, whereas YLD_RI and YLD_LS were negatively correlated with SSI, SSPI, RSI, and PYR, as evidenced by the obtuse and acute angles between their vectors, respectively (Figs. 9 and 10). The inverse relationship between the yield stability index and various stress indices indicates that enhancing yield stability in stress environments may necessitate compromises with other stress metrics. The findings of this study are consistent with the results reported in bread wheat under heat stress22,23,46 and drought stress38,40,64.

We divided 116 T. sphaerococcum accessions and six bread wheat varieties into five clusters based on drought and heat stress tolerance indices (Figs. 11 and 12). Under conditions of drought and heat stress, the bread wheat varieties were categorized into distinct clusters and exhibited higher values for MP, GMP, HM, and MRP (Table 5). Their high grain yield under both normal and stress conditions clearly demonstrates this point. Even so, some T. sphaerococcum accessions did very well in both seasons (Tables S1, S2, 7 and 8). These included TS49 and TS27 in times of drought stress and TS49, TS61, and PAUTS16 in times of heat stress). Among the T. sphaerococcum accessions, those exhibiting high trait values for MP, GMP, HM, and MRP were classified in clusters 5 and 1 under drought and heat stress, respectively. These clusters consisted of accessions that are tolerant to moderately tolerant, exhibiting high stability and minimal yield reduction under stress conditions (Table 5). Lamba et al.23 and Kumar et al.43 documented similar findings in bread wheat under heat stress, and Thana et al.70 under drought stress conditions. A genotype exhibiting higher values of MP, GMP, HM, YI, and YSI demonstrates optimal performance and stress tolerance, making it suitable for use as a parent in breeding programs aimed at developing stress-tolerant genotypes. Given the complexity of the heat-tolerant trait, which is influenced by numerous genetic and environmental factors and their interactions, a comprehensive understanding of the genetic basis and plant responses to these stresses, as well as their environmental interactions, is essential.

The superior accessions of T. sphaerococcum that have been identified are able to be crossed with bread wheat with relative ease because of their identical genome and ploidy level. Possible effective methods for introducing desirable traits into bread wheat include creating recombinant inbred lines (RILs) or introgression lines (ILs) by backcrossing. It is important to test RILs or ILs for physiological traits, including osmotic adjustment, water use efficiency, chlorophyll fluorescence metrics, and yield performance under stress circumstances71,52. Use of these species in bread wheat improvement has received little attention. The scarcity of available accessions is one possible explanation. Regardless that, one wheat variety, HD 2888 (*C306/T.sphaerococcum/ HW 2004), was released for planting in rainfed areas of India’s northeastern plains by the ICAR-IARI in New Delhi72. Askhadullin et al.73 used this species in their hybridization program and got a better line, Sh-359-11-5, which had a higher yield than the Indian dwarf wheat progenitor, k-45,738. The success of these two projects demonstrates that desirable characteristics of T. sphaerococcum can be preserved through selective breeding.

Indian dwarf wheat, presents a unique opportunity for marker-assisted selection (MAS) and genome-wide association studies (GWAS) due to its distinct genetic traits and adaptability to various environmental conditions. In the context of MAS, the morphological traits specific to T. sphaerococcum are governed by a single recessive gene, suggesting that targeted breeding could exploit this genetic simplicity for trait enhancement74. GWAS can further enhance our understanding of the genetic basis of traits in T. sphaerococcum. Population sequencing can provide insights into genetic variation and adaptation in wheat, which is essential for identifying adaptive traits in T. sphaerococcum75. Moreover, the identification of genes such as TaSG-D1, which contributes to heat stress tolerance, underscores the potential of GWAS in uncovering genetic factors that can be utilized to enhance resilience in breeding programs76. Furthermore, the integration of T. sphaerococcum into breeding programs can be facilitated by utilizing advanced genomic tools, such as CRISPR and other gene editing technologies, which can expedite the incorporation of beneficial traits into elite wheat lines75.

Conclusion

This research introduces the drought and heat tolerance indices in ancient landrace Indian dwarf wheat for the first time. The current study statistically represented significant variation in the accessions. The correlation coefficient, PCA, and biplot analysis revealed a strong positive association of YI, MP, GMP, HM, and MRP with yield in both normal and stress conditions, whereas SSI and SSPI demonstrated a negative correlation with yield under both stress scenarios. Consequently, these stress indices emerged as superior predictors for identifying desirable high-yielding genotypes under both conditions. This species is noteworthy for breeding climate-resilient wheat cultivars, as it exhibits a smaller decline in grain production under stress conditions compared to bread wheat. Under optimal, drought, and heat stress conditions, accessions such as TS49, TS27, TS61, and PAUTS16 demonstrated superior performance as genotypes. Landraces like T. sphaerococcum should be encouraged for use in breeding programs, even though they cannot be directly compared to modern, improved cultivars. This will promote the ongoing evolutionary processes that influence landraces, especially in their centers of diversity. The application of MAS and GWAS in the context of T. sphaerococcum holds significant promise for advancing wheat breeding efforts. By focusing on the unique genetic attributes of this ancient wheat species, breeders can enhance the nutritional quality and environmental resilience of modern wheat varieties, ultimately contributing to food security and agricultural sustainability.