Introduction

Soybean (Glycine max [L.] Merr.) is one of the most widely grown economically important field crops, producing around 370 million tons annually1,2. Soybean is a highly nutritious legume used for both human consumption and livestock feed, valued for its protein and edible oil. As of 2023, the United States is the second-largest soybean producer in the world (120.5 million metric tons), following Brazil (129.5 million metric tons), and its production contributes $124 billion to the US economy3. In addition, as a legume, it enhances soil fertility through a symbiotic association with microorganisms and fixes atmospheric nitrogen4. However, abiotic stresses have severely affected soybean production potential due to climate change, with an average yield reduction accounting for more than 50%5,6,7,8. Suboptimal moisture conditions negatively impact the growth and production of soybeans9,10,11,12. The soybean crop in the southeastern US often suffers from drought due to inadequate rainfall, leading to a 13% variability in yield13,14. Thus, understanding the effects of drought stress on early plant growth traits and identifying tolerant genotypes are crucial for sustaining yield in low-rainfall rainfed regions.

Drought stress at any soybean growth stage can cause a significant decline in growth and productivity15,16. Under drought conditions, plants limit their ability to convert sunlight into chemical energy due to damage to cell membranes15 and photosynthetic apparatus17. In addition, canopy temperature increases as transpiration rate and stomatal conductance decrease18. These physiological changes affect the photochemistry and lead to an imbalance between the production of free radicals and the ability of plants to neutralize them19. These events increase oxidative stress and accelerate cell death19, contributing to poor seedling vigor at the vegetative stage. As soil moisture decreases, plants reduce transpiration by decreasing stomatal conductance. This is due to increased abscisic acid levels in xylem sap caused by decreased root water potential20. On the other hand, roots serve as vital plant sensors, and they undergo morphological changes to match above-ground transpiration demand in response to soil moisture stress21,22. To avoid drought stress, plants produce deeper roots, fulfilling transpiration demand during later stages, particularly at flowering23. These adaptation strategies have shown to increase increased water use efficiency and yield in monocots24 and dicots25. For instance, slow-wilting soybean genotypes exhibited cooler canopies under drought stress than fast-wilting genotypes, ultimately resulting in higher grain yields26. Therefore, cooler canopy temperatures have been used as a proxy for drought tolerance in legumes and other crops27. In addition, drought-tolerant soybean genotypes exhibit low canopy temperatures, while sensitive genotypes show high canopy temperatures. Plants with lower stomatal conductance transpire less, act as water-savers, which leads to higher canopy temperatures. Conversely, those with higher stomatal conductance transpire more, maintaining a cooler canopy as water spenders28.

Previous studies have highlighted a broad genetic variability in root architectural traits in soybean genotypes during early growth stages under drought stress10,29,30,31,32,33. Drought adaptation and high yield are closely linked to canopy architecture, water uptake, and root traits33,34. Studies indicate that under drought conditions, specific root traits, such as increased root length and high adventitious and lateral root densities, were associated with improved nutrient uptake efficiency and higher grain yield21. Studies also highlight the importance of root system architecture in water and nutrient acquisition for soybean, with wild soybean alleles showing the potential to enhance root traits for drought adaptation. These findings emphasize the significance of characterizing the shoot and root traits to enhance soybean resilience to drought conditions. Variability in root traits is associated with considerable change in shoot traits, evidenced by a positive relationship between shoot dry weight and root traits (total root length, root surface area, and root volume) in different crops35,36,37,38. Thus, early seedling root vigor could be one of the most important traits for genotype selection under drought conditions. However, root phenotyping has been slow compared to above-ground traits in crops, including soybeans. Therefore, root characterization along with shoot traits helps to identify soybeans with balanced root-to-shoot networks, making them better equipped for water uptake and use under drought conditions.

In soybeans, a deeper taproot system and profuse lateral roots are considered as a crucial adaptive features for drought tolerance, contributing to higher average yields or reducing variability33,39. Under drought, soybean with larger root systems develops more metaxylem elements, promoting stress tolerance40. In addition, genotypes that yield high are also characterized by enhanced water use efficiency and increased root penetrability through hardpans under stress10,41. Although roots play a significant role in perceiving and responding to drought stress, their efficiency in improving soybean aboveground parameters across different growth stages, environmental conditions, and management practices remains uncertain. However, few studies have focused on the variability of early-stage plant development among soybean genotypes grown in the Southern US under different soil moisture regimes. The objectives of this study were to assess drought stress induced i) changes in morpho-physiological and root traits and ii) identify early vegetative stage drought tolerant genotypes.

Materials and methods

Plant material

The study used 64 soybean genotypes involving maturity groups (MG) III, IV, and V from the Mississippi Agricultural and Forestry Experiment Station variety trial. These are mostly grown in the Midsouth US (Supplementary Table S1).

Crop husbandry and Stress treatments

Four uniform size seeds per pot were sown in polyvinyl chloride (PVC) pots (15.2 cm diameter × 31 cm height) filled with fine sand and topsoil mix (87% sand, 2% clay, and 11% silt) at a 3:1 ratio by volume and later thinned down to one. The Soil–Plant-Atmosphere Research (SPAR) units at Mississippi State University (33o28´N, 88o47´W), USA, were used to execute this experiment following the appropriate institutional guidelines. Detailed features of the SPAR units are described in the study by Reddy et al.42. The SPAR units comprise a plexiglass chamber for aerial plant parts and a steel bin for the root system. Each unit was designed to control air temperature and atmospheric composition, mainly the CO2 concentration. All the units were set in optimum conditions (30/22 °C and 100% evapotranspiration, ET). A standard Hoagland's nutrient solution was provided thrice daily using an automated drip irrigation system43.

This study used 384 pots and two treatments with three replications (64 genotypes × 3 replications × 2 treatments) to explore the phenotypic variability of soybean genotypes for drought tolerance. The treatments were one control (30/22 °C, and 100% ET) and one drought stress (DS, 50% ET of the control). The control treatment received irrigation at 100%, maintaining the average volumetric water content (VWC) of ~ 0.15 m3 m−3 throughout the experiment. Seven days after emergence, stress was imposed by stopping irrigation for four days to create the drought treatment. After that, the soil moisture was kept at 50% ET of control, 0.075 m3 m−3 VWC for the drought treatment. The amount of irrigation for each unit was determined based on the ET from the previous day. Volumetric water content was monitored using a moisture sensor (ECH2O, EC-5, Decagon Devices, Inc., Pullman, WA, USA) across treatments.

Data collection

Physiological parameters

Chlorophyll index, chlorophyll fluorescence, and canopy temperature were measured 19 days after stress (DAS). The chlorophyll index was measured on the uppermost fully expanded leaf using a handheld self-calibrating SPAD chlorophyll meter (Minolta Camera Co. Ltd., Osaka, Japan). Chlorophyll fluorescence (Fv/Fm) was measured using FluorPen (FP 100, Photon System Instruments), and canopy temperature was measured using an infrared thermometer (MI-230, Apogee Instruments, Inc., Logan, UT, USA).

Shoot parameters

Plant height and number of nodes were recorded 22 DAS. Leaf area was measured using the LI-3100 leaf-area meter (LI-COR, Inc., Lincoln, NE, USA). Plants were harvested at 22 DAS and separated into leaf, stem, and root tissues. Total shoot (leaf + stem) and root dry weights were measured after drying them in the oven at 75 °C for five days.

Root parameters

To evaluate the impact of drought on soybean root traits, roots were cut at the root-to-shoot junction, and stems were separated from roots and washed thoroughly in running water. The cleaned roots were floated in 5 mm of water in a 0.4 × 0.3 m Plexiglas tray and were untangled to avoid overlap. The roots were scanned with an Epson Expression 11000XL scanner at 800 dots per inch resolution. Scanned images were analyzed using WinRHIZO Pro 2009C software (Regent Instruments, Inc., Québec, QC, Canada). The acquired root images were analyzed to determine the variability in total root length (TRL), root surface area (RSA), root volume (RV), root diameter (RD), number of root tips (RT), number of root forks (RF), and number of root crossings (RC). The difference in resource allocation between roots and shoots was determined by calculating the root-to-shoot ratio (RS) as the root and shoot weights ratio.

Statistical analysis

Analysis of variance (ANOVA) was performed for all traits to estimate the significance of treatment, genotype, and their interaction using the library (“agricolae”) in RStudio 3.6.1 (https://www.R-project.org/, R Core). Principal component analysis (PCA) was performed using the JMP program (SAS Institute, Inc., Cary, NC; https://www.jmp.com). Pearson correlation matrix was developed using the library “PerformanceAnalytics” in R. Each trait's individual genotype response index was calculated to evaluate the genotype response to drought stress. In brief, the drought response index was calculated by dividing the value of a trait under stress by the value of the same trait under control. The sum of all the values for each category trait for a given genotype was then added up to determine the physiological drought response index (PDRI), shoot drought response index (SDRI), and root drought response index (RDRI). The cumulative drought response index (CDRI) was calculated by aggregating PDRI, SDRI, and RDI using the same method previously described44. Further, to identify soybean genotypes tolerant to drought stress, the cumulative indices were used to group the genotypes with similar phenotypes using the library "pheatmap" in RStudio.

Results and discussion

Effects of drought stress on physiological parameters

The parameters associated with photosynthesis, such as chlorophyll index and fluorescence, provide valuable insights into the impact of drought stress on the growth and development of soybean45. These traits are crucial for CO2 assimilation and positively correlate with the photosynthetic rate. This study found that these parameters exhibited different responses under drought and control conditions. There was no significant interaction between genotype and treatment, but a treatment or genotype recorded considerable difference for chlorophyll index (P < 0.05). The chlorophyll index increased 13.7% in soybean genotypes grown under drought compared to the control (P < 0.001; Table 1). The highest chlorophyll index values under drought were observed in DG 4825RR2/STS and DG 5170RR2/STS, and the lowest in 4714LL and S56RY84 (Fig. 1a). Previous studies reported no notable differences in chlorophyll content when subjected to drought stress during vegetative, full bloom (R2), and full pod (R4) stages11,46,47. Conversely, shaded soybeans increased chlorophyll content in response to drought stress48. Higher chlorophyll content levels correlate with photosynthetic rate and drought tolerance in soybeans and can be considered a reliable trait under drought stress48,49,50.

Table 1 Descriptive statistics of physiological, shoot, and root traits of 64 soybean genotypes under control (CNT) and drought stress (DS).
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Figure 1
figure 1

Boxplots showing the differences in chlorophyll index (SPAD, a), chlorophyll fluorescence (Fv′/Fm′, b), and canopy temperature (CT °C, c) of 64 soybean genotypes under control (CNT) and drought (DS). The whiskers indicate the interquartile range, and the outer dots are outliers. The middle line represents the mean of the 64 genotypes, and the box shows the range of the 25th–75th percentiles of the data.

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Reduced CO2 uptake under drought indicates decreased energy utilization by the PSII, which means low chlorophyll fluorescence (Fv′/Fm′) and potentially damages photosynthetic machinery under drought51. On average, a 15% reduction in Fv′/Fm′ was observed under drought conditions compared to the control (Table 1 and Fig. 1b). R2C5225S had a relatively high Fv′/Fm′ and chlorophyll index under drought stress, indicating higher photosynthetic efficiency among all the genotypes (Supplementary Table S1). However, on the contrary, 51A56 had a relatively low chlorophyll index and Fv′/Fm′, suggesting that drought stress significantly affected its photosynthetic efficiency52.

Canopy temperature serves as a surrogate measurement for plant water relations under drought stress26,27 and is also used as a promising proxy trait for seed yield prediction53,54. A higher canopy temperature (+ 3.1 °C) was observed under drought than control (Fig. 1c and Table 1). This finding is consistent with previous studies on soybean and other crops55,56,57, where an increase in the canopy temperature was attributed to insufficient moisture to meet the evapotranspiration demand, consequently leading to decreased stomatal conductance. Genotype 48L63 maintained a 3.7 °C cooler canopy temperature compared to S58-Z4 (35.2 °C) under drought conditions (Fig. 1c). Cooler canopy genotypes with higher stomatal conductance contribute to high grain/seed yield18,28,]58. Further, non-significant correlations between control and drought for all measured physiological traits suggest that genotypes have varied responses to treatments, indicating the complex response of soybean genotypes (Table 1).

Effects of drought stress on shoot traits

Early vegetative stage vigor is the foundation for sustaining yields under drought conditions. Plant growth and developmental processes are vulnerable to drought stress in the early vegetative stage. Thus, selecting a genotype that can withstand stress with minimal disruption to physiology and growth produces a higher yield than the sensitive genotype. On the other hand, the tolerant genotype establishes a robust root system that serves as a strong foundation for producing more pods and seeds. Significant treatment effects (P < 0.001) on all shoot traits indicate phenotypic plasticity under drought stress. The genotype × stress interaction demonstrated a significant (P < 0.01) difference only for leaf area, whereas it was non-significant for plant height and number of nodes (Table 1). Drought stress resulted in significantly lower values in plant height (− 20.1%), number of nodes (− 12.3%), leaf area (− 36.9%), leaf weight (− 12.6%) and shoot weight (− 18.9%) compared to control (Table 1). Large variability in these traits was attributed to decreased plant height and leaf area under drought (Fig. 2a–c), indicating the low assimilation and cell elongation due to lower tissue water content59. Plants minimize water loss and conserve resources during drought by reducing leaf size and total leaf area. This reduces energy investment in shoot growth, thus decreasing plant height, node number, and leaf area. Genotypes 57R21, 483.C, and CZ 5225 LL maintained high leaf area, node number, and plant height under drought (Supplementary Table S1). Among the tested genotypes, S58-Z4 and CZ 5225 LL demonstrated no significant change between control and drought (Supplementary Table S1). A significant positive correlation was noted between control and drought for plant height (r = 0.69, P < 0.001) and leaf area (r = 0.34, P < 0.01).

Figure 2
figure 2

Effect of drought on plant height (PH, cm; a), number of nodes (NN, b), and leaf area (LA, cm2 plant−1; c) of 64 soybean genotypes. The measurements were taken at 22 days after stress was initiated. The middle line represents the mean of the 64 genotypes, and the box shows the range of the 25th–75th percentiles of the data. The whiskers indicate the interquartile range, and the outer dots are outliers. CNT and DS denote control and drought stress, respectively.

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Drought stress-induced variability in root traits

Root system architecture governs the plant’s ability to acquire water and nutrients, influencing shoot biomass. Roots have various strategies to respond to drought and avoid stress60. Under drought, an increase in the root morphological traits facilitates efficient forage of soil moisture. Significant genetic variability in root traits has been reported30,31,41 and is often found to be controlled by multiple factors, such as genetics and intensity/duration of drought stress20. Root traits such as root length, root volume, root surface area, and root diameter confer drought tolerance in soybeans at different growth stages. Soybean genotypes showed significant variability for root traits, except for the total root length and root forks (Fig. 3a–f). Genotype × stress interaction did not affect the root traits (Table 1).

Figure 3
figure 3

Effect of drought on total root length (cm plant−1; a), root volume (RV, cm3 plant−1; b), root surface area (RSA, cm2 plant−1; c), root tips (RT, no. plant−1; d), root forks (no. plant−1; e) and root diameter (RD, cm; f) of 64 soybean genotypes. The measurements were taken at 22 days after stress was initiated. The middle line represents the mean of the 64 genotypes, and the box shows the range of the 25th–75th percentiles of the data. The whiskers indicate the interquartile range, and the outer dots are outliers. CNT and DS denote control and drought stress, respectively.

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Among root development (tips, forks, and crossings) traits, tips (− 19.6%) and crossing (− 16.9%) decreased significantly in response to drought (Fig. 3 and Table 1). The genotypes 5N424R2 and S55LS75 had the highest number of root tips under drought stress, while JTN-5110 and S55LS75 had the highest number of root crossings compared to P47T36R and others under drought (Supplementary Table S1). Key root growth traits such as root length, root volume, root surface area, and root diameter confer drought tolerance in soybeans at different growth stages20. On average, across genotypes, root volume (14.5%), root surface area (6.4%), and root diameter (8.4%) were increased under drought stress compared to control (Fig. 3b, c, and f; and Table 1). A similar observation was reported in soybean at the V3 stage under drought stress30. Total root length ranged from 3002.8 (P47T36R) to 5105.4 cm (JTN-5110) under drought and 2547.5 (S55-Q3) to 6124.5 cm (JTN-5110) in control. Drought-tolerant genotypes tend to have longer root systems compared to drought-sensitive genotypes. Unlike other studies11,61,62, no change in total root length was observed in response to drought in this study. However, significant differences in total root length were noted among genotypes (Table 1). Moreover, there are inconsistent findings regarding the increase in root length at different growth stages30,63. Genotypes S49LL34 and DG 5170RR2/STS produced larger diameter roots than AG4632 under drought (Fig. 3f); suggest that genotypes may have efficient channels for transporting water and nutrients to the shoot. JTN-5110 and P 4247LL are the top two genotypes with a high root surface area in both control and drought conditions. Moreover, P 4247LL had a high root surface area and diameter under drought stress, while JTN-5110 had the maximum total root length and volume. These combinations of traits are known to contribute to the accumulation of more photo-assimilates, benefiting the overall photosynthetic process, plant growth, and yield24. A significant positive correlation was observed for root length (r = 0.46, P < 0.001), root diameter (r = 0.32, P < 0.001), root volume (r = 0.42, P < 0.001), root surface area (r = 0.44, P < 0.001), and root weight (r = 0.61, P < 0.001) between drought and control conditions (Table 1). Based on the structural features, deep root length and diameter with more lateral roots are associated with high root surface area or biomass (Fig. 6)64.

Root biomass was significantly varied in response to drought. Drought stress increased root dry matter accumulation, with a reduction in shoot biomass (Fig. 4a,b). Reduction in soybean growth under drought has been well documented at different plant growth stages15,59,65. In this study, maximum root dry weight was observed in DG 5170RR2/STS, followed by P 4247LL (Fig. 4b) under drought. Among these, P 4247LL ranked high in both control and drought. Because of the intrinsic competition between growing shoots and roots for available resources, roots possessing superior characteristics utilize more energy and resources, limiting shoot growth66. Plants prioritizing root growth helps them survive under drought by reducing the risk of dying. However, it comes at the cost of reduced shoot growth, especially during critical development stages. Under drought, increased root weight declined shoot weight by 19% (Table 1), contributing to an increase in the root-to-shoot ratio (Fig. 4c). Thus, an increase in the root-to-shoot ratio is widely recognized as a drought avoidance strategy, fostering the improved acquisition of water and nutrients67. DG 4680RR2, S39-C4, and DG5067LL had higher root-to-shoot ratios than CZ 5225 LL and S55LS75 under drought. A similar response of increased root-to-shoot ratio has been documented in tap root systems67. In this study, a negative relationship between root-to-shoot ratio and shoot biomass (r = -0.49, P < 0.001) indicates a shift in carbohydrate allocation from the shoot to the root system under drought. Thus, the genetic diversity in the root traits of soybean genotypes under drought stress can be utilized to improve drought tolerance, through breeding studies.

Figure 4
figure 4

Drought impact on shoot weight (SWT, g plant−1; a), root weight (RWT, g plant-1; b), and root-to-shoot ratio (RS; c) of 64 soybean genotypes. The measurements were taken at 22 days after stress initiation. The middle line represents the mean of the 64 genotypes, and the box shows the range of the 25th to 75th percentiles of the data. The whiskers indicate the interquartile range, and the outer dots are outliers. CNT and DS denote control and drought stress, respectively.

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Relationship between physiological, shoot, and root traits

Principal component (PC) analysis was performed using all physiological, shoot, and root traits to identify traits that explain the maximum variability. The two PCs cumulatively explained > 61% and > 57% of the total phenotypic variations under control and drought, respectively (Fig. 5a,b). The variability in the first PC was mostly explained by root (TRL, RSA, RF, RC, and RV) and shoot traits (TDM, LWT, SWT) in both treatments, which are found to be the main growth and yield-attributing traits62. Under control conditions, most root traits were found in the first quadrant, while most shoot traits were in the second quadrant. However, in drought stress, there was a noticeable shift in the quadrants for both root and shoot traits. These results suggest a clear difference in how the shoot and root levels adapt to growing conditions, which results in distinct phenotypic variations. There was no clear separation between maturity groups under both control and drought, indicating that root traits or drought adaptation are not specific to a particular maturity group of soybeans.

Figure 5
figure 5

Principle component (PC) analysis for morphological and physiological traits of 64 soybean genotypes in maturity groups (MG) III, IV, and V under control (a) and drought stress (b). Acronyms are given in Table 1.

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Understanding the phenotypic relationships between traits is essential, as changes in one trait can positively or negatively affect other traits. Pearson’s correlation matrix analysis using the drought response index revealed that shoot and root traits are significantly correlated (Fig. 6). Both leaf area and shoot weight positively correlated with root surface area (r = 0.41 and 0.52, P < 0.001, respectively) and root weight (r = 0.60 and 0.65, P < 0.001, respectively). No physiological parameters showed a correlation with different root and shoot traits. There was a strong negative correlation between shoot traits and root-to-shoot ratio (P < 0.001). SDRI strongly (P < 0.001) is associated with root traits except for root thickness and diameter. RDRI was positively correlated with the shoot weight, leaf weight, and leaf area (P < 0.001). Further, CDRI showed a significant positive correlation with roots, and the strongest relation was noted for total root length and surface area (r = 0.90, P < 0.001). Leaf weight strongly correlated with CDRI (r = 0.71, P < 0.001). We found a strong positive correlation (P < 0.001) between CDRI and RDRI and SDRI. However, no correlation was observed between CDRI and PDRI (Fig. 6), suggesting physiological traits are more sensitive to drought stress68. Differences in these correlations could be linked to structural or anatomical variations in the sink69. These phenotypic associations between shoot and root traits suggest they can be used as selectable traits for drought tolerance. Additionally, root traits at seedling stage may serve as an indirect selection for shoot performance.

Figure 6
figure 6

Pearson correlation matrix among 64 soybean genotypes using drought response index. Correlations values with ± indicate a strong relationship between two traits. Asterisks (*, **, ***) indicate significance at P < 0.05, P < 0.01, and P < 0.001, respectively; correlation coefficients without asterisks were not significant. PDRI—physiological drought response index, SDRI—shoot drought response index, RDRI—root drought response index, and CDRI indicats the cumulative drought response index. Acronyms are given in Table 1.

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Early vegetative drought-tolerant soybean

Drought response index scores calculated using shoot, root, and physiological traits were used to identify drought-tolerant, intermediate, and sensitive genotypes using the hierarchical clustering method (Fig. 7). The clustering analysis divided the 64 genotypes into four groups: G1 (13 genotypes), G2 (15 genotypes), G3 (11 genotypes), and G4 (25 genotypes). The mean values of root traits (RDRI) for cluster G3 were greater than those for cluster G1, followed by G2. Similarly, the mean SDRI values were highest for G4 compared to G2. Above-ground traits were correlated with root traits, highlighting the importance of below-ground traits in drought tolerance. On the other hand, G3 had maximum CDRI values compared to G2. Clustering analysis grouped vigorous or tolerant genotypes (S55-Q3, DG5067LL, and R2C4775) in G3. Among all genotypes in G3, S55-Q3 was the best performer based on the shoot and root traits. On the other hand, R2C4775 had a high root-to-shoot ratio and vigor traits. Genotypes AG4632, 55-R68, S56RY84, GT-476CR2, and 5115LL fall into poor performing genotypes in G2 (Fig. 7). Considering SDRI, RDRI, and CDRI, genotypes S55-Q3 and R2C4775 were identified as drought-tolerant during the early vegetative stage. These genotypes significantly increased root traits, including the root-to-shoot ratio under drought conditions. These results suggest that some genotypes have positive root plasticity that helps adjust physiological traits such as tissue-water relation under drought conditions. For instance, genotypes S55-Q3 and R2C4775, with high cumulative drought tolerance, demonstrated high root vigor, resulting in a cooler canopy than the shallow root genotypes (P47T36R and AG4632). Conversely, genotypes with deep and high root biomass types allow plants to access water from deeper soil profiles that help cope with transpiration demand, leading to higher growth and yields of pods and seeds under drought. Therefore, planting deep and high-root biomass genotypes can tolerate short-term drought during the vegetative stage. The study suggests that root traits can be used to identify drought-tolerant genotypes during the early vegetative stage. Further, evaluating selected genotypes under irrigated and rainfed conditions would help confirm trait stability and their association with yield potential for developing improved cultivars.

Figure 7
figure 7

Grouping of soybean genotypes based on drought response index values using a hierarchical clustering method. Each dark red and dark blue column indicates a trait's top and least performing genotypes, respectively. Each column represents the average drought indices (PDRI, SDRI, RDRI, and CDRI; see statistical analysis section). Each row represents a genotype. Acronyms are given in Table 1.

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Conclusions

Drought stress during the early stages of soybean seedling development significantly impacts root, shoot, and physiological traits. Identifying drought-tolerant genotypes could be the most significant approach to combat early episodes of short-term drought stress in the current climate conditions. The genotypes S55-Q3 and R2C4775 demonstrated the ability to maintain growth and development under drought stress, indicating their potential as valuable donors for understanding molecular networks and breeding programs to improve drought tolerance at the early stages of soybean development.