Physiological responses of cotton roots and soil microbial adaptation to drought hardening

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Aims: This investigation employed integrated physiological and metagenomic analyses to unravel the physiological responses of cotton roots and the changes of soil microbial communities induced by drought hardening. Then, by integrating the physiological responses of the aboveground parts and yield performance, a comprehensive analysis was conducted to provide optimized irrigation strategies for cotton fields in moisture-limited regions. Methods: The experiment was conducted in 2024 at Huaxing Farm in Changji, Xinjiang, using the Zhongmian 113 variety, with three drought hardening treatments during the seedling stage. These treatments were saving 20% (D1), 30% (D2), and 40% (D3) of irrigation amount respectively, comparing to the control (CK, conventional full irrigation). Results: The results showed that the D1 treatment was identified as moderate drought hardening, which based on cotton growth and yield; The D1 treatment significantly enhanced the antioxidant capacity and membrane integrity maintenance in cotton roots; Additionally, the D1 treatment altered soil microbial diversity, partially optimizing the microbial community structure and forming a dominant bacterial group— Gemmatimonadales . Conclusions: This integrated microbial-plant analysis hypothesized that Gemmatimonadales might interact synergistically with cotton roots during the budding stage to enhance the drought resistance of cotton. The research provided a foundation for revealing the enhancing drought- resistance- mechanisms of root-microbe interactions in cotton via drought hardening in arid regions. Drought stress Drought hardening Cotton roots Soil microorganisms Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Introduction Global climate change has emerged as one of the most serious environmental challenges of the 21st century, with drought being particularly severe. In recent years, the frequency and intensity of drought events has increased significantly worldwide [ 1 ], significantly impacting agricultural ecosystems, crop production, and human livelihoods. Drought has become a limiting factor on worldwide food security and the sustainable use of water resources [ 2 ]. As one of the world's largest agricultural producers, China also faces severe drought challenges. Statistics showed that average annual drought area in China was more than 20 million hectares, with the threat to agricultural production steadily worsening [ 3 ]. Especially in the northern arid and semi-arid areas, the problem of water shortage is particularly prominent, which seriously restricts the sustainable development of agriculture. As one of the most important economic crops in the world, the growth and development, physiological and biochemical processes, quality and yield of cotton are significantly affected by drought stress [ 4 ]. Studies indicated that drought stress reduced photosynthetic efficiency in leaves [ 5 ], decreased plant height and leaf area index [ 6 ], and slowed overall plant growth. Drought also affects physiological and biochemical processes in cotton, such as reducing chlorophyll content in leaves, altering antioxidant enzyme activity [ 7 ], and triggering oxidative stress responses. Severe drought stress compromises fiber elongation, leading to a decline in cotton fiber quality [ 8 ]. More critically, drought negatively affects cotton yield [ 9 ]. Additionally, drought may influence cotton root systems and their associated soil microorganisms. Research suggests that drought stress alters root distribution and morphology [ 10 ], as well as root physiological processes [ 11 ]. Drought stress also affects the composition of bacterial and fungal populations in soil [ 12 ]. Thus, drought affects cotton planting in multiple ways, posing a major challenge to the sustainable development of the cotton production. To mitigate the adverse effects of drought on cotton production, researchers worldwide have proposed various solutions, including optimizing irrigation techniques [ 13 , 14 ], such as drip irrigation [ 15 ] and sprinkler irrigation [ 16 – 18 ]. There were other solutions such as regulating irrigation volumes [ 19 , 20 ], drought-resistance breeding [ 21 ] and so on. Additionally, recent studies on root-associated soil microorganisms have yielded significant progress. For example, soaking cotton seeds in suspension of growth-promoting rhizobacteria (PGPR) and inoculating arbuscular mycorrhizal fungi (AMF) at the cotton roots respectively enhance cotton stress resistance and promote plant growth [ 22 , 23 ], while co-inoculation in the soil further improved nutrient uptake efficiency, stress tolerance [ 24 ], and soil microecological conditions [ 25 ]. However, the mechanisms underlying the interactions between cotton roots and soil microorganisms under drought hardening remain unclear, and their interactive response effects on cotton growth induced by drought hardening are not clear. Furthermore, the optimal irrigation strategy for cotton production under drought conditions in main planting areas still needs to be further explored. Xinjiang is China's primary cotton-producing region, accounting for over 90% of the country's total cotton output. Therefore, alleviating agricultural- water- scarcity pressure in Xinjiang while ensuring cotton-planting sustainable development is of great significance. This study focused on saving irrigation of cotton production in Xinjiang, implementing different drought hardening treatments. The effects of drought hardening on cotton root physiology, soil microbial community change, cotton aboveground growth and yield performance were investigated. The synergistic stress- resistance- mechanisms between cotton roots and soil microorganisms under drought conditions was revealed. The findings will provide theoretical basis and practical guidance for water-saving irrigation strategies in Xinjiang's cotton fields. Materials and Methods Experimental site and plant materials The field experiment was conducted from April to September 2024 at Huaxing Farm in Changji Hui Autonomous Prefecture of Xinjiang Uygur autonomous region (44°11′ N, 87°26′ E, altitude 31 m). The average annual precipitation in the experimental area was 190 mm, and the soil is sandy loam. An automatic weather station and soil sensors were installed in the cotton field, and meteorological data were shown in Fig. 1 . The planting method employed drip irrigation technology with a "one mulch, three pipes, six rows" pattern. Specific parameters were as follows: wide row spacing of 66 cm, narrow row spacing of 10 cm, mulch width of 2.05 cm, plant spacing of 8–10 cm, and cotton plants along both sides of the irrigation pipes, as shown in Fig. 2 . The experiment used the Zhongmian 113 variety, which is characterized by early maturity, high yield, high-quality fiber, and strong stress resistance. Experimental design The experiment used conventional irrigation levels in local area (4950 m³/ha, including seedling emergence water) as the control (CK) and established three drought hardening treatments with water-saving levels of 20%, 30%, and 40% (D1, D2, D3) compared to CK during the seedling stage. Total water savings throughout the growth cycle were 12.5%, 15%, and 17.5%, respectively, comparing to CK. The irrigation allocation of each treatment was shown in Table 1 . Irrigation frequency and fertilization followed local practices, with irrigation applied every 7–10 days. Each experimental plot measured 6.3 m in width and 15 m in length, covering an area of 94.5 m². The total experimental area was 378 m² (Fig. 3 ). Random sampling was conducted during the seedling, budding, blooming, boll, and boll-opening stages in cotton growth cycle. Table 1 The irrigation amounts for each treatment throughout the entire growth period of cotton and the total irrigation amount. Treatment Irrigation Amount (m 3 /ha) Total Irrigation Amount for the Entire Growth Period (m³/ha) Emergence Seedling Stage Budding Stage Blooming and Boll Stage Boll Opening Stage CK 450 525.00 825.00 2,850.00 300.00 4,950.00 D1 450 420.00 716.25 2,482.50 262.50 4,331.25 D2 450 367.50 705.00 2,430.00 255.00 4,207.50 D3 450 367.50 693.75 2,377.50 247.50 4,083.75 Measurement methods First of all, it is the cotton growth characteristics measurement. Six uniformly growing plants were selected from each plot, labeled, and their heights (from the cotyledon node to the top of the main stem) were measured regularly. The leaf area index (LAI) was calculated using the punch method[ 26 ], with the following formulas: Leaf Area = Number of Punched Leaves × Single Hole Area / Dry Weight of Punched Leaves × Total Leaf Dry Weight; (1) Leaf Area Index = Total Leaf Area / Ground Area. (2) Five cotton plants from each plot were sampled, killed at 105°C for 30 minutes, and then dried at 75°C to a constant weight. The dry weight was recorded and aboveground biomass was achieved. Secondly, it is the cotton root stress- resistance characteristics measurement. Five uniformly growing plants were selected from each plot, and their roots were separated to determine physiological and biochemical measurements. According to the methods of Gao[ 27 ], superoxide anion radical (O₂⁻), malondialdehyde (MDA) content, proline (Pro) content, superoxide dismutase (SOD) and peroxidase (POD) activity were determined. Then, it is the soil microbial community analysis. The root zone soil samples were collected using the five-point sampling method, mixed, and divided into three parts for high-throughput sequencing. The soil samples were sent to Guangzhou Gideo Biotechnology Co., Ltd. The V3-V4 region of the bacterial 16S rRNA gene and the ITS region of fungi were amplified by PCR. The concentration of the amplified products was measured using a QuantiFluor™ fluorometer, and high-throughput sequencing was performed on the Illumina PE250 platform. After quality control using DADA2, ASVs (amplicon sequence variants) were obtained, followed by species annotation, species composition analysis, indicator species analysis, α-diversity analysis, β-diversity analysis, and community function prediction. Lastly, it is the cotton yield measurement. In each plot, a 6.67 m² area with uniform plant growth and density was randomly selected. The number of plants, total bolls (including opened and unopened bolls) were recorded. After drying, the weight was measured, and the seed cotton yield and lint yield were calculated using the following formulas (3) and (4)[ 26 ]. Seed Cotton Yield = Planting Density × Number of Bolls per Plant × Single Boll Weight (3) Lint Yield = Seed Cotton Yield × Lint Percentage (4) Instructions on Plant Seeds and Specimens The "Zhongmian 113" used in this study is a new cotton variety jointly developed by the Cotton Research Institute of the Chinese Academy of Agricultural Sciences and the Crop Research Institute of the Gansu Provincial Academy of Agricultural Sciences. All samples were collected from the experimental fields of Huaxing Farm in Changji, Xinjiang, from June 22, 2024, to September 26, 2024, and were handled by research team members Xin Li、Yuhao Zhao and Yi Chen. The sample collection was permitted by the farm manager. The collected samples were processed in the laboratory according to standardized procedures, including cleaning, drying, and classified storage. All voucher specimens are stored in the laboratory of Jiangsu University, Zhenjiang, China (address: No. 301 Xuefu Road, Jingkou District, Zhenjiang, Jiangsu, China), with the collection dates and collector information consistent with the sample collection. All field studies were conducted in accordance with relevant regulations such as the Biosecurity Law of the People's Republic of China. Data processing Data were organized using Microsoft Excel 2021, and one-way ANOVA was performed using SPSS 26.0. Charts were generated using Origin 2021. Experimental data were presented as mean ± standard error. Differences between treatments were assessed using one-way ANOVA, and multiple comparisons were performed using Duncan's test. ANOSIM was used to analyze differences in Shannon diversity between treatments, and charts were generated using Origin 2021. Principal Coordinate Analysis (PCoA) based on Bray-Curtis distance was performed using the vegan and ggplot2 packages in R. Additionally, two-tailed t-tests and non-parametric tests were used to assess differences in soil microbial relative abundance between treatments and the CK. Results Effects of drought hardening on oxidative stress responses in cotton roots As shown in Fig. 4 (a), in most cases, the drought hardening treatments exhibited significantly higher O₂⁻ levels compared to CK (P D2 > D1 > CK. However, the O₂⁻ content of D3 was lower than that of D1 and D2 treatments during blooming stage. The content of O₂⁻ was the highest during the boll-opening stage, likely due to root senescence and decreasing mitochondrial function, which might have increased O₂⁻ production [ 28 ]. As shown in Fig. 4 (b), except for the D1 treatment, the MDA content in the other drought hardening treatments was significantly higher than that in the CK. The MDA content generally followed the trend: D3 > D2 > CK, while the D1 treatment exhibited significantly lower MDA levels compared to CK. Effects of drought hardening on stress resistance in cotton roots As shown in Fig. 5 (a), in most cases, the SOD content of drought hardening treatment was significantly higher than that of the control. The SOD content under all treatments initially increased and then decreased, and the peak SOD concentration observed at D1 treatment. Similarly, Fig. 5 (b) showed POD activity fluctuations paralleled SOD dynamics throughout all treatments. As shown in Fig. 5 (c), the Pro content in all drought hardening treatments were significantly higher than CK. In most cases, the Pro content fluctuated, which reflecting compensatory interactions among distinct osmoprotectant classes [ 29 ]. Effects of drought hardening on soil microbial α-diversity in cotton roots As showed in Fig. 6 (a), the bacterial Shannon diversity of each drought hardening treatment exhibited a gradual downward trend, except during the budding stage. While in the budding stage, except for the fluctuation of D2 treatment, the overall trend also showed a downward trend. Figure 6 (b) showed that D1 treatment had the highest fungal Shannon diversity across all stages. Effects of drought hardening on soil microbial β-diversity in cotton roots As shown in Fig. 7 (a), the bacterial community composition showed no significant differences among treatments during both the seedling and budding stages. However, during these stages, the D3 treatment exhibited significantly distinct bacterial community composition compared to D1 and D2 treatments. Figure 7 (b) revealed that the fungal community composition showed no significant differences among treatments during the budding and flowering and boll stage. But, during the seeding stage, the bacterial community composition of D1 treatment was significantly different from that of D2 and D3 treatments. Effects of drought hardening on soil microbial taxonomic composition in cotton roots As shown in Fig. 8 and Table 2 , the relative abundance of Blastocatellales in the D1 treatment significantly decreased during the budding stage but rebounded during the flowering and boll stage. Moreover, the relative abundance of Gemmatimonadale s showed consistent significant increases in the D1 treatment during both the budding stage and flowering-boll stage. No significant taxonomic differences were observed between the CK and drought treatments during the seedling stage. Figure 9 and Table 3 demonstrated that no significant taxonomic variations were found between the control and drought hardening treatments. Table 2 Significance levels of differences in the relative abundance of the top 10 bacterial orders between the control and drought hardening treatments. (A is the seedling stage, B is the budding stage, C is the flowering and boll stage.) A B C CK/D1 CK/D2 CK/D3 CK/D1 CK/D2 CK/D3 CK/D1 CK/D2 CK/D3 Cytophagales ** ** * ** Sphingomonadales * Incertae_Sedis ** Chitinophagales * *** Pyrinomonadales * * Pirellulales Gemmatimonadales * ** * Tepidisphaerales * * Blastocatellales * ** * Burkholderiales PS: Asterisks (* P < 0.05, ** P < 0.01, and *** P < 0.001, two-tailed Student's t-test) indicate significance. Light-colored asterisks indicate that the relative abundance of the order in the drought hardening treatment was lower than that in the control. Dark-colored asterisks indicate that the relative abundance of the order in the drought hardening treatment was higher than that in the control. Table 3 Significance levels of differences in the relative abundance of the top 10 fungal orders between the control and drought hardening treatments. (A is the seedling stage, B is the budding stage, C is the flowering and boll stage.) A B C CK/D1 CK/D2 CK/D3 CK/D1 CK/D2 CK/D3 CK/D1 CK/D2 CK/D3 Sordariales Onygenales ** Hypocreales Microascales * Spizellomycetales Pleosporales Pezizales Mortierellales Glomerellales Thelebolales * PS: Asterisks (* P < 0.05, ** P < 0.01, and *** P < 0.001, two-tailed Student's t-test) indicate significance. Light-colored asterisks indicate that the relative abundance of the order in the drought hardening treatment was lower than that in the control. Dark-colored asterisks indicate that the relative abundance of the order in the drought hardening treatment was higher than that in the control. Effects of drought hardening on aboveground growth characteristics in cotton plants As shown in Fig. 10 (a), LAI increased first and then decreased, and reached the peak at blooming stage. The D1 was slightly higher than CK, and there was D1 ≥ CK > D2 > D3 under differential treatments. As shown in Fig. 10 (b), plants under D1, D2, and D3 treatments exhibited sustained height increments throughout the experimental period, consistently surpassing CK. This indicated that moderate drought hardening had no significant impairment on shoot growth. Figure 10 (c) showed that the aboveground biomass reached its highest level during the boll-opening stage. The D1 treatment was always higher than CK, indicating that moderate drought hardening contributed to biomass accumulation. Effects of drought hardening on cotton yield The cotton yield components include total boll number, single boll weight, seed cotton yield, lint yield, and lint percentage. As shown in Table 4 , the D1 treatment showed consistent superiority over the CK across all five evaluated indicators. Specifically, the single boll weight in the D1 treatment was 12.47% higher than that in the CK, and the seed cotton yield was 20.43%, the lint yield was 26.76%, the lint percentage was 4.65%, the total boll number was 6.78% higher than CK, respectively. This indicated that moderate drought hardening not only preserved but also enhanced cotton yield under water-saving conditions. Table 4 Total boll number, single boll weight, seed cotton yield, lint yield, and lint percentage of cotton under control and different drought hardening treatments. Indicator Total Boll Number Single Boll Weight (g) Seed Cotton Yield (kg·hm − 2 ) Lint Yield (kg·hm − 2 ) Lint Percentage CK 487 4.89 7,322.55 3,159.90 0.43 D1 520 5.50 8,818.50 3,960.45 0.45 D2 484 4.71 6,845.55 2,921.40 0.43 D3 570 4.73 8,298.15 3,138.30 0.38 Discussion This study explored the physiological adaptations in cotton roots induced by drought stress, concurrent with analysis of the dynamics in soil microbial communities, while revealing cotton's drought-hardening adaptation mechanisms. The experimental framework coupled drought treatments with rhizosphere microbiome profiling, root system physiological-adaptation analysis, and agronomic productivity measurements. (Fig. 11 ). The results revealed significant oxidative stress acclimation in cotton roots under drought stress, other acclimations are similar as well [ 30 ]. Moderate drought hardening (D1 treatment) effectively activated the upregulation of root antioxidant enzymes, significantly mitigating membrane lipid peroxidation and suppressing ROS overproduction (Fig. 4 – 5 ). The progressive oxidant overload indicated drought-induced oxidative injury through cumulative peroxidative damage to membrane systems [ 31 ]. As a product of membrane lipid peroxidation, MDA content reflects the degree of cell membrane damage. D1 treatment showed significantly lower MDA content than other treatments. This systemic antioxidant defense conferred critical protection against drought-induced oxidative injury while maintaining root cellular homeostasis under water-deficit conditions [ 32 ]. Additionally, Pro content generally increased with the severity of drought stress, while the activities of antioxidant enzymes (SOD and POD) initially increased and then decreased (Fig. 5 ), indicating that Pro accumulates as an osmoregulatory substance to help maintain cellular osmotic pressure and cellular stability under drought stress [ 33 , 34 ]. Meanwhile, cotton roots rapidly upregulated antioxidant enzymes to counteract stress. Similar regulatory mechanisms were reported in sand mustard seedlings involving POD and SOD dynamics under drought stress [ 35 ]. However, plants prioritize survival over defense under extreme stress, with energy diverting from enzyme production to repair processes. When abiotic stress surpasses plant’s tolerance threshold, the antioxidant defense system collapses (such as SOD and POD), leading to irreversible cellular damage [ 36 ]. Drought hardening significantly altered the diversity and structure of soil microbial communities associated with cotton roots. Drought reduced soil moisture, collapsing pore networks and limiting microbial motility, for bacterial communities, the Shannon diversity index generally decreased (Fig. 6 a). It was a critical ecological response, reflecting how microbial systems reorganize under environmental stress [ 37 – 39 ]. However, during the seedling stage, moderate drought acclimation (D2 treatment) increased bacterial diversity (Fig. 6 a). It was possibly due to enhanced root exudates providing additional carbon sources and favorable growth conditions for microorganisms, stress-tolerant specialists increased under moderate drought stress[ 40 , 41 ]. Furthermore, during the flowering and boll stage, the bacterial community composition in each treatment was significantly different (Fig. 7 a). Drought stress notably enriched Gemmatimonadales under D1 treatment (Fig. 8 and Table 2 ), and with similar observations reported in rice rhizosphere communities [ 42 ]. For fungal communities, moderate drought hardening (D1 treatment) enhanced fungal Shannon diversity across all stages (Fig. 6 b). At the seedling stage, the fungal community composition in D1 significantly differed from D2 and D3 (Fig. 7 b), while there were no clear taxonomic changes between drought treatment and CK (Fig. 9 and Table 3 ). It revealed there were stage-specific interactions between drought intensity and fungal ecology, and fungal communities, being more drought-tolerant, maintained a composition similar to CK. This study preliminarily revealed potential synergistic mechanisms between cotton roots and soil microorganisms under drought conditions. At the budding stage, the D1 treatment showed significantly higher fungal Shannon diversity than CK (Fig. 6 b). Concurrently, the relative abundance of Gemmatimonadales significantly increased in D1 at the budding stage. The results suggested that D1 treatment protected plant roots from oxidative stress compared to CK, with significantly lower MDA levels (Fig. 4 b), higher antioxidant enzyme activities (Fig. 5 b and 5 c) and more stable communities for soil microorganisms (Fig. 7 – 9 ). Those adaptive regulation might promote root nutrient and water uptake, collectively enhancing drought resistance [ 43 ]. This phenomenon revealed the complexity of plant-microbe interactions under stress and highlighted the importance of stress intensity in shaping soil microbial communities. Future studies should explore the functions of these unclassified or poorly characterized root-associated bacteria to reveal the molecular mechanism of root-microorganism synergistic stress-resistance under drought-hardening conditions. Alterations in root physiology coupled with dynamic shifts in rhizosphere microbial communities were synergistically regulated plant growth-development and ultimately determined crop yield[ 43 , 44 ], as shown as LAI, plant height and aboveground biomass was the highest under D1 treatment (Fig. 10 ). Furthermore, single boll weight, seed cotton yield, lint yield and lint percentage in D1 treatment plants were superior to CK. (Table 4 ). This root-microbe interaction mechanism achieved a balance between drought resistance and agricultural yield under 20% water-saving conditions. Conclusions The investigation was conducted in commercial cotton cultivation zones within Changji, in Xinjiang, and adjacent agricultural districts, where differential drought hardening treatments were established in parallel with control groups. The research employed a multidimensional analytical framework to establish mechanistic linkages between rhizosphere processes and crop performance, including phyto-biochemical transformations within cotton root systems, rhizosphere-specific soil-microbial communities dynamics, growth characteristics of the aboveground parts, and agronomic productivity determinants. The results showed that moderate drought hardening activated root antioxidant system, enhanced root stress resistance, increased the diversity of soil microorganisms, leaded to the formation of dominant bacteria within the Gemmatimonadales , and maintained normal growth and yield in cotton plants. This study’s conclusion to implement the treatment D1 as a water-saving irrigation strategy in cotton cultivation in Changji was scientific, with the ability to enhance stress-resistance and optimize plant resilience efficiency while safeguarding yield under D1 condition. Future research would explore the interaction mechanisms between cotton roots and Gemmatimonadales , as well as unclassified microorganisms. These coordinated investigations revealed critical linkages between drought-induced root stress-resistance, microbial community regulation, and cotton productivity outcomes, thereby establishing scientific and practical foundation for optimizing water-use efficiency of cotton cultivation systems in Xinjiang's arid. Declarations Acknowledgements We thank the funding support provided by the major national projects. Author contributions X.L., Y.Z., G.L. and Y.C. conducted the experiments. X.L., Y.Z., K.W., and X.L. analysed the data and prepared the figures. L.H. and W.S. designed the study, supervised the experiments and secured the funding for this project. X.L. wrote the manuscript and W.S. revised and edited it. All authors read and approved the manuscript. Funding This work was supported by the National Science and Technology Major Project (2022ZD0115801). Data availability All data generated during this study are available from the corresponding author upon reasonable request. Availability of data and materials All data and materials generated during this study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Clinical trial number Not applicable. References Chen J, Wu X, Yang J, Liu X, Liu Y. Effects of drought and rewatering on plants and soil microorganisms under climate change: review and perspectives. Chin J Ecol. 2023;42(12):3038–49. https://doi.org/10.13292/j.1000-4890.202312.009 . Biswas A, Sarkar S, Das S, Dutta S, Roy Choudhury M, Giri A, et al. 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Plant Soil Environ. 2019;65(10):516–21. https://doi.org/10.17221/506/2019-PSE . Sharma P, Dubey RS. Drought Induces Oxidative Stress and Enhances the Activities of Antioxidant Enzymes in Growing Rice Seedlings. Plant Growth Regul. 2005;46(3):209–21. https://doi.org/10.1007/s10725-005-0002-2 . Rong Z, Zhang X, Yang S, Xu Z, Li J, Zhao J, et al. Involvement of Antioxidant Defense System in Enhancement of Drought Re sistance in Tobacco (Nicotiana tabacum L.) Plants through Circular Drought Hardening. Plant Physiol J. 2012;48(7):705–13. https://doi.org/10.13592/j.cnki.ppj.2012.07.010 . Zhang L, Chen X, Wu Y, Yu M, Cai H, Liu B, et al. Research Progress of Proline in Plant Stress Resistance. J Jianghan Univ (Nat Sci Ed). 2023;51(1):42–51. https://doi.org/10.16389/j.cnki.cn42-1737/n.2023.01.006 . Su S, Li Y, Liu X, Chong P, Shan L, Hou Y. A study of the mechanism of drought stress alleviation by exogenous proline applied to Reaumuria soongorica. Acta Prataculturae Sinica. 2022;31(6):127–38. https://doi.org/10.11686/cyxb2021367 . Zhang X, Wang P, Shi L, Yang J. Root morphology and antioxidant enzyme activity of Pugionium cornutum (L.) Gaertn under drought stress. Agric Res Arid Areas. 2016;34(3):160–4. https://doi.org/10.13469/j.cnki.1000-7600.2016.03.026 . Wu J, Mi N. Effect of heavy metals on antioxidant enzymes in plants. J Zhejiang Agricultural Sci. 2022;63(6):1177. https://doi.org/10.16178/j.issn.0528-9017.20212820 . 81 + 1304. Bian Y, Wu X, Zhu Y, Xiong X, Xi D, Yang Q, et al. Effects of Nitrogen Addition and Drought on Soil Microbial Diversity and Community Composition in a Young Tree Community. Forests. 2025;16(2):276. https://doi.org/10.3390/f16020276 . Zhang H, Goncalves P, Copeland E, Qi S, Dai Z, Li G, et al. Invasion by the weed Conyza canadensis alters soil nutrient supply and shifts microbiota structure. Soil Biol Biochem. 2020;143:107739. https://doi.org/10.1016/j.soilbio.2020.107739 . Wang C, Wu B, Jiang K, Wei M, Wang S. Effects of different concentrations and types of Cu and Pb on soil N-fixing bacterial communities in the wheat rhizosphere. Appl Soil Ecol. 2019;144:51–9. https://doi.org/10.1016/j.apsoil.2019.07.008 . Liang T, Du X, Liu Y, Huang J, Xiong D. Effects of drought on the characteristics of plant root exudates: a review. Chin J Appl Environ Biology. 2024;1–20. https://doi.org/10.19675/j.cnki.1006-687x.2024.03031 . Long J, Jiang Z, Liu D, Miao Y, Zhou L, Feng Y, et al. Effects of drought on plant root exudates and associated rhizosphere priming effect: review and prospect. Chin J Plant Ecol. 2024;48(7):817–27. https://doi.org/10.17521/cjpe.2023.0238 . Wu C, Zhang X, Liu Y, Tang X, Li Y, Sun T, et al. Drought Stress Increases the Complexity of the Bacterial Network in the Rhizosphere and Endosphere of Rice (Oryza sativa L). Agronomy. 2024;14(8):1662. https://doi.org/10.3390/agronomy14081662 . Lv B, Ding L, Guo C, Chen F, Zhou H, Wang X, et al. Effects of Compound Microbial Fertilizer on Soil Nutrients and Rhizosphere Bacterial Community in Cotton Field. Crops. 2024;40(4):209–15. https://doi.org/10.16035/j.issn.1001-7283.2024.04.027 . Cui F, Hou X, Miao H, Jia D, Gu Y, Chen X, et al. Bacterial community structure and function in root soil under cotton-peanut rotation. Chin J Oil Crop Sci. 2024;46(3):625–34. https://doi.org/10.19802/j.issn.1007-9084.2024086 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Dec, 2025 Read the published version in BMC Plant Biology → Version 1 posted Reviewers agreed at journal 10 Jun, 2025 Reviewers agreed at journal 09 Jun, 2025 Reviewers agreed at journal 07 Jun, 2025 Reviewers invited by journal 05 Jun, 2025 Editor assigned by journal 29 May, 2025 Submission checks completed at journal 28 May, 2025 First submitted to journal 28 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6703288","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":468214933,"identity":"323be533-53b0-4015-8e53-56c16fb0ea92","order_by":0,"name":"Xin Li","email":"","orcid":"","institution":"Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Li","suffix":""},{"id":468214934,"identity":"28c87bcc-ea73-4bac-8209-f6436eb30414","order_by":1,"name":"Yuhao Zhao","email":"","orcid":"","institution":"Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Yuhao","middleName":"","lastName":"Zhao","suffix":""},{"id":468214935,"identity":"681ab10d-349e-4cc0-ac92-a106d5276714","order_by":2,"name":"Kunkun Wu","email":"","orcid":"","institution":"Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Kunkun","middleName":"","lastName":"Wu","suffix":""},{"id":468214936,"identity":"6860a600-a427-4db1-8084-bc38ccd0cea1","order_by":3,"name":"Xiaoya Li","email":"","orcid":"","institution":"Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoya","middleName":"","lastName":"Li","suffix":""},{"id":468214937,"identity":"504460e3-f553-43a8-8d4e-c947d50d686e","order_by":4,"name":"Gaoqiang Lv","email":"","orcid":"","institution":"Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Gaoqiang","middleName":"","lastName":"Lv","suffix":""},{"id":468214938,"identity":"143328c4-8874-4ccd-bcb0-bd945b8179f3","order_by":5,"name":"Yi Chen","email":"","orcid":"","institution":"Xinjiang University","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Chen","suffix":""},{"id":468214939,"identity":"e9906445-71b2-4489-88b2-28b2dd28be68","order_by":6,"name":"Liang He","email":"","orcid":"","institution":"Tsinghua University","correspondingAuthor":false,"prefix":"","firstName":"Liang","middleName":"","lastName":"He","suffix":""},{"id":468214940,"identity":"d17a791b-8286-4460-a33e-f7c0c21ab29c","order_by":7,"name":"Weihong Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYFACxjYog/nAgYQKGx5+/gaitbAlPvhwJk1GcsYBgtawQWkeY8OZbYdtDBoS8Ks3ON7c9uDjjlp7g9sNZtK8bed5DBgOMH74mINHy5mD7YYzzxxP3HDnQJo0z7nbPObMDcySM7fh1mJ2I7ENaPixBIMbCcekecpu81g2HGBj5sWn5f5DsBZ7A5BeHrZzPAYHEghoucEI0lLDuOFGMrPhjLYDhLXYn0lsk5zZdiBx5o00RmAgJ/NIzjjYjNcvku3Hn0l8bKuz57uR/wEYlXb2/PzNBz98xKMFCg4jcxgbCKoHgjpiFI2CUTAKRsFIBQAWhluLetBjqAAAAABJRU5ErkJggg==","orcid":"","institution":"Jiangsu University","correspondingAuthor":true,"prefix":"","firstName":"Weihong","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2025-05-20 03:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6703288/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6703288/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12870-025-07992-8","type":"published","date":"2025-12-28T15:58:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84320955,"identity":"4f84a005-4ca4-4079-a9d7-690202c89a16","added_by":"auto","created_at":"2025-06-10 14:11:22","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":901783,"visible":true,"origin":"","legend":"\u003cp\u003eThe average monthly temperature and total monthly precipitation for the year 2024\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/464bbb8d97717afa9093ab76.jpeg"},{"id":84319579,"identity":"64df0b1f-b5dc-4c95-a6f7-a588c2b5d042","added_by":"auto","created_at":"2025-06-10 14:03:22","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":120019,"visible":true,"origin":"","legend":"\u003cp\u003eCotton cultivation model\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/bc33b37c342e6d90a5fd48a2.jpeg"},{"id":84319582,"identity":"269a4081-6c89-4652-9a1e-38c7f5826fb4","added_by":"auto","created_at":"2025-06-10 14:03:22","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":942949,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental Plot Diagram\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/4acfdb4ddbd23cf85c77e150.jpeg"},{"id":84320956,"identity":"bff43406-cfde-4e07-a0a2-d4446de404c7","added_by":"auto","created_at":"2025-06-10 14:11:22","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1414795,"visible":true,"origin":"","legend":"\u003cp\u003eContent of O₂⁻ (a) and MDA (b) in the root systems of cotton at different growth stages under drought hardening treatments. (P \u0026lt; 0.05)\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/79564d6e1e83e4395102538d.jpeg"},{"id":84319584,"identity":"f971e8b0-bc1e-421d-aee7-089caacfc154","added_by":"auto","created_at":"2025-06-10 14:03:22","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2234367,"visible":true,"origin":"","legend":"\u003cp\u003eProline content (a), SOD content (b) and POD content (c) in the root systems of cotton at different growth stages under drought hardening treatments. (P \u0026lt; 0.05)\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/1f9e99ff5b689966c93610f9.jpeg"},{"id":84320960,"identity":"77bdfc07-aacf-4d47-8023-ea5088951599","added_by":"auto","created_at":"2025-06-10 14:11:22","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1001546,"visible":true,"origin":"","legend":"\u003cp\u003eShannon diversity of soil microorganisms in cotton roots under different drought hardening treatments during the seedling, budding, and flowering -boll stages. (a). Bacterial Shannon diversity; (b). Fungal Shannon diversity. Different letters above the boxes indicate P \u0026lt; 0.05 (one-way ANOVA with Tukey's HSD test).\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/e471c8091405135da6f44726.jpeg"},{"id":84320958,"identity":"5fe29180-aabc-445b-8c53-a3fd504130a4","added_by":"auto","created_at":"2025-06-10 14:11:22","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":104771,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Coordinate Analysis (PCoA) of soil microorganisms in cotton roots under different drought hardening treatments during the seedling(A), budding(B), and flowering-boll stages(C) based on the Bray-Curtis dissimilarity matrix (OTU level). Statistical analysis was performed using ANOSIM (analysis of similarities). (a). PCoA of bacteria, R=0.514, P=0.001; (b). PCoA of fungi, R=0.4449, P=0.001.\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/9c8f0c45704b6f0ee79d1f8e.jpeg"},{"id":84319588,"identity":"944e55a3-8919-40e7-aabf-c4b43beb0487","added_by":"auto","created_at":"2025-06-10 14:03:22","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":141556,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of the top 10 bacterial orders in cotton root soil under different drought hardening treatments. (A is the seedling stage, B is the budding stage, C is the flowering and boll stage.)\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/2e770b2575701362b7717a04.jpeg"},{"id":84321233,"identity":"4285d784-b3b7-4805-b01c-55d6d1da5c65","added_by":"auto","created_at":"2025-06-10 14:19:22","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":133775,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of the top 10 fungal orders in cotton root soil under different drought hardening treatments. (A is the seedling stage, B is the budding stage, C is the flowering and boll stage.)\u003c/p\u003e","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/8ba6af6f39aad3ba4b00cde1.jpeg"},{"id":84319591,"identity":"33e1284d-0232-4c0e-a984-9a1611483d2e","added_by":"auto","created_at":"2025-06-10 14:03:22","extension":"jpeg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":2367475,"visible":true,"origin":"","legend":"\u003cp\u003eGrowth characteristics of the aboveground parts of cotton at different growth stages under drought hardening treatments. (a) Leaf area index; (b) Plant height; (c) Aboveground biomass.\u003c/p\u003e","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/aa5c4178514b88f5f5f847b8.jpeg"},{"id":84319611,"identity":"f49d032f-20db-45ee-8080-1e4d1702757e","added_by":"auto","created_at":"2025-06-10 14:03:24","extension":"jpeg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":672615,"visible":true,"origin":"","legend":"\u003cp\u003eMain research pathway and conclusions diagram\u003c/p\u003e","description":"","filename":"floatimage11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/0477b7050d51be66b19e5920.jpeg"},{"id":99172473,"identity":"1872c9a5-5d8e-49cf-90ce-7beb9a063e5d","added_by":"auto","created_at":"2025-12-29 16:10:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11130169,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6703288/v1/a00c1346-94f1-4fd4-8e08-f6a41fb97706.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Physiological responses of cotton roots and soil microbial adaptation to drought hardening","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlobal climate change has emerged as one of the most serious environmental challenges of the 21st century, with drought being particularly severe. In recent years, the frequency and intensity of drought events has increased significantly worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], significantly impacting agricultural ecosystems, crop production, and human livelihoods. Drought has become a limiting factor on worldwide food security and the sustainable use of water resources [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. As one of the world's largest agricultural producers, China also faces severe drought challenges. Statistics showed that average annual drought area in China was more than 20\u0026nbsp;million hectares, with the threat to agricultural production steadily worsening [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Especially in the northern arid and semi-arid areas, the problem of water shortage is particularly prominent, which seriously restricts the sustainable development of agriculture.\u003c/p\u003e \u003cp\u003eAs one of the most important economic crops in the world, the growth and development, physiological and biochemical processes, quality and yield of cotton are significantly affected by drought stress [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Studies indicated that drought stress reduced photosynthetic efficiency in leaves [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], decreased plant height and leaf area index [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and slowed overall plant growth. Drought also affects physiological and biochemical processes in cotton, such as reducing chlorophyll content in leaves, altering antioxidant enzyme activity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and triggering oxidative stress responses. Severe drought stress compromises fiber elongation, leading to a decline in cotton fiber quality [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. More critically, drought negatively affects cotton yield [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Additionally, drought may influence cotton root systems and their associated soil microorganisms. Research suggests that drought stress alters root distribution and morphology [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], as well as root physiological processes [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Drought stress also affects the composition of bacterial and fungal populations in soil [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Thus, drought affects cotton planting in multiple ways, posing a major challenge to the sustainable development of the cotton production.\u003c/p\u003e \u003cp\u003eTo mitigate the adverse effects of drought on cotton production, researchers worldwide have proposed various solutions, including optimizing irrigation techniques [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], such as drip irrigation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and sprinkler irrigation [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. There were other solutions such as regulating irrigation volumes [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], drought-resistance breeding [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and so on. Additionally, recent studies on root-associated soil microorganisms have yielded significant progress. For example, soaking cotton seeds in suspension of growth-promoting rhizobacteria (PGPR) and inoculating arbuscular mycorrhizal fungi (AMF) at the cotton roots respectively enhance cotton stress resistance and promote plant growth [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], while co-inoculation in the soil further improved nutrient uptake efficiency, stress tolerance [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and soil microecological conditions [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, the mechanisms underlying the interactions between cotton roots and soil microorganisms under drought hardening remain unclear, and their interactive response effects on cotton growth induced by drought hardening are not clear. Furthermore, the optimal irrigation strategy for cotton production under drought conditions in main planting areas still needs to be further explored. Xinjiang is China's primary cotton-producing region, accounting for over 90% of the country's total cotton output. Therefore, alleviating agricultural- water- scarcity pressure in Xinjiang while ensuring cotton-planting sustainable development is of great significance.\u003c/p\u003e \u003cp\u003eThis study focused on saving irrigation of cotton production in Xinjiang, implementing different drought hardening treatments. The effects of drought hardening on cotton root physiology, soil microbial community change, cotton aboveground growth and yield performance were investigated. The synergistic stress- resistance- mechanisms between cotton roots and soil microorganisms under drought conditions was revealed. The findings will provide theoretical basis and practical guidance for water-saving irrigation strategies in Xinjiang's cotton fields.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental site and plant materials\u003c/h2\u003e \u003cp\u003eThe field experiment was conducted from April to September 2024 at Huaxing Farm in Changji Hui Autonomous Prefecture of Xinjiang Uygur autonomous region (44\u0026deg;11\u0026prime; N, 87\u0026deg;26\u0026prime; E, altitude 31 m). The average annual precipitation in the experimental area was 190 mm, and the soil is sandy loam. An automatic weather station and soil sensors were installed in the cotton field, and meteorological data were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The planting method employed drip irrigation technology with a \"one mulch, three pipes, six rows\" pattern. Specific parameters were as follows: wide row spacing of 66 cm, narrow row spacing of 10 cm, mulch width of 2.05 cm, plant spacing of 8\u0026ndash;10 cm, and cotton plants along both sides of the irrigation pipes, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The experiment used the Zhongmian 113 variety, which is characterized by early maturity, high yield, high-quality fiber, and strong stress resistance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental design\u003c/h3\u003e\n\u003cp\u003eThe experiment used conventional irrigation levels in local area (4950 m\u0026sup3;/ha, including seedling emergence water) as the control (CK) and established three drought hardening treatments with water-saving levels of 20%, 30%, and 40% (D1, D2, D3) compared to CK during the seedling stage. Total water savings throughout the growth cycle were 12.5%, 15%, and 17.5%, respectively, comparing to CK. The irrigation allocation of each treatment was shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Irrigation frequency and fertilization followed local practices, with irrigation applied every 7\u0026ndash;10 days.\u003c/p\u003e \u003cp\u003eEach experimental plot measured 6.3 m in width and 15 m in length, covering an area of 94.5 m\u0026sup2;. The total experimental area was 378 m\u0026sup2; (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Random sampling was conducted during the seedling, budding, blooming, boll, and boll-opening stages in cotton growth cycle.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe irrigation amounts for each treatment throughout the entire growth period of cotton and the total irrigation amount.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eIrrigation Amount (m\u003csup\u003e3\u003c/sup\u003e/ha)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal Irrigation Amount for the Entire Growth Period (m\u0026sup3;/ha)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmergence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSeedling Stage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBudding Stage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBlooming and Boll Stage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBoll Opening Stage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e525.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e825.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,850.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e300.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4,950.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e420.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e716.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,482.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e262.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4,331.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e367.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e705.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,430.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e255.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4,207.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e367.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e693.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,377.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e247.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4,083.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eMeasurement methods\u003c/h3\u003e\n\u003cp\u003eFirst of all, it is the cotton growth characteristics measurement. Six uniformly growing plants were selected from each plot, labeled, and their heights (from the cotyledon node to the top of the main stem) were measured regularly. The leaf area index (LAI) was calculated using the punch method[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], with the following formulas:\u003c/p\u003e \u003cp\u003eLeaf Area\u0026thinsp;=\u0026thinsp;Number of Punched Leaves \u0026times; Single Hole Area / Dry Weight of Punched Leaves \u0026times; Total Leaf Dry Weight; (1)\u003c/p\u003e \u003cp\u003eLeaf Area Index\u0026thinsp;=\u0026thinsp;Total Leaf Area / Ground Area. (2)\u003c/p\u003e \u003cp\u003eFive cotton plants from each plot were sampled, killed at 105\u0026deg;C for 30 minutes, and then dried at 75\u0026deg;C to a constant weight. The dry weight was recorded and aboveground biomass was achieved.\u003c/p\u003e \u003cp\u003eSecondly, it is the cotton root stress- resistance characteristics measurement. Five uniformly growing plants were selected from each plot, and their roots were separated to determine physiological and biochemical measurements. According to the methods of Gao[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], superoxide anion radical (O₂⁻), malondialdehyde (MDA) content, proline (Pro) content, superoxide dismutase (SOD) and peroxidase (POD) activity were determined.\u003c/p\u003e \u003cp\u003eThen, it is the soil microbial community analysis. The root zone soil samples were collected using the five-point sampling method, mixed, and divided into three parts for high-throughput sequencing. The soil samples were sent to Guangzhou Gideo Biotechnology Co., Ltd. The V3-V4 region of the bacterial 16S rRNA gene and the ITS region of fungi were amplified by PCR. The concentration of the amplified products was measured using a QuantiFluor\u0026trade; fluorometer, and high-throughput sequencing was performed on the Illumina PE250 platform. After quality control using DADA2, ASVs (amplicon sequence variants) were obtained, followed by species annotation, species composition analysis, indicator species analysis, α-diversity analysis, β-diversity analysis, and community function prediction.\u003c/p\u003e \u003cp\u003eLastly, it is the cotton yield measurement. In each plot, a 6.67 m\u0026sup2; area with uniform plant growth and density was randomly selected. The number of plants, total bolls (including opened and unopened bolls) were recorded. After drying, the weight was measured, and the seed cotton yield and lint yield were calculated using the following formulas (3) and (4)[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeed Cotton Yield\u0026thinsp;=\u0026thinsp;Planting Density \u0026times; Number of Bolls per Plant \u0026times; Single Boll Weight (3)\u003c/p\u003e \u003cp\u003eLint Yield\u0026thinsp;=\u0026thinsp;Seed Cotton Yield \u0026times; Lint Percentage (4)\u003c/p\u003e\n\u003ch3\u003eInstructions on Plant Seeds and Specimens\u003c/h3\u003e\n\u003cp\u003eThe \"Zhongmian 113\" used in this study is a new cotton variety jointly developed by the Cotton Research Institute of the Chinese Academy of Agricultural Sciences and the Crop Research Institute of the Gansu Provincial Academy of Agricultural Sciences. All samples were collected from the experimental fields of Huaxing Farm in Changji, Xinjiang, from June 22, 2024, to September 26, 2024, and were handled by research team members Xin Li、Yuhao Zhao and Yi Chen. The sample collection was permitted by the farm manager. The collected samples were processed in the laboratory according to standardized procedures, including cleaning, drying, and classified storage. All voucher specimens are stored in the laboratory of Jiangsu University, Zhenjiang, China (address: No. 301 Xuefu Road, Jingkou District, Zhenjiang, Jiangsu, China), with the collection dates and collector information consistent with the sample collection. All field studies were conducted in accordance with relevant regulations such as the Biosecurity Law of the People's Republic of China.\u003c/p\u003e\n\u003ch3\u003eData processing\u003c/h3\u003e\n\u003cp\u003eData were organized using Microsoft Excel 2021, and one-way ANOVA was performed using SPSS 26.0. Charts were generated using Origin 2021. Experimental data were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error. Differences between treatments were assessed using one-way ANOVA, and multiple comparisons were performed using Duncan's test.\u003c/p\u003e \u003cp\u003eANOSIM was used to analyze differences in Shannon diversity between treatments, and charts were generated using Origin 2021. Principal Coordinate Analysis (PCoA) based on Bray-Curtis distance was performed using the vegan and ggplot2 packages in R. Additionally, two-tailed t-tests and non-parametric tests were used to assess differences in soil microbial relative abundance between treatments and the CK.\u003c/p\u003e "},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eEffects of drought hardening on oxidative stress responses in cotton roots\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(a), in most cases, the drought hardening treatments exhibited significantly higher O₂⁻ levels compared to CK (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Among the treatments, the O₂⁻ content followed the order: D3\u0026thinsp;\u0026gt;\u0026thinsp;D2\u0026thinsp;\u0026gt;\u0026thinsp;D1\u0026thinsp;\u0026gt;\u0026thinsp;CK. However, the O₂⁻ content of D3 was lower than that of D1 and D2 treatments during blooming stage. The content of O₂⁻ was the highest during the boll-opening stage, likely due to root senescence and decreasing mitochondrial function, which might have increased O₂⁻ production [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (b), except for the D1 treatment, the MDA content in the other drought hardening treatments was significantly higher than that in the CK. The MDA content generally followed the trend: D3\u0026thinsp;\u0026gt;\u0026thinsp;D2\u0026thinsp;\u0026gt;\u0026thinsp;CK, while the D1 treatment exhibited significantly lower MDA levels compared to CK.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eEffects of drought hardening on stress resistance in cotton roots\u003c/h3\u003e\n\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e(a), in most cases, the SOD content of drought hardening treatment was significantly higher than that of the control. The SOD content under all treatments initially increased and then decreased, and the peak SOD concentration observed at D1 treatment. Similarly, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e(b) showed POD activity fluctuations paralleled SOD dynamics throughout all treatments. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e(c), the Pro content in all drought hardening treatments were significantly higher than CK. In most cases, the Pro content fluctuated, which reflecting compensatory interactions among distinct osmoprotectant classes [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEffects of drought hardening on soil microbial α-diversity in cotton roots\u003c/h2\u003e \u003cp\u003eAs showed in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e(a), the bacterial Shannon diversity of each drought hardening treatment exhibited a gradual downward trend, except during the budding stage. While in the budding stage, except for the fluctuation of D2 treatment, the overall trend also showed a downward trend. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e(b) showed that D1 treatment had the highest fungal Shannon diversity across all stages.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEffects of drought hardening on soil microbial β-diversity in cotton roots\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e(a), the bacterial community composition showed no significant differences among treatments during both the seedling and budding stages. However, during these stages, the D3 treatment exhibited significantly distinct bacterial community composition compared to D1 and D2 treatments. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e(b) revealed that the fungal community composition showed no significant differences among treatments during the budding and flowering and boll stage. But, during the seeding stage, the bacterial community composition of D1 treatment was significantly different from that of D2 and D3 treatments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEffects of drought hardening on soil microbial taxonomic composition in cotton roots\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the relative abundance of \u003cem\u003eBlastocatellales\u003c/em\u003e in the D1 treatment significantly decreased during the budding stage but rebounded during the flowering and boll stage. Moreover, the relative abundance of \u003cem\u003eGemmatimonadale\u003c/em\u003es showed consistent significant increases in the D1 treatment during both the budding stage and flowering-boll stage. No significant taxonomic differences were observed between the CK and drought treatments during the seedling stage. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e demonstrated that no significant taxonomic variations were found between the control and drought hardening treatments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSignificance levels of differences in the relative abundance of the top 10 bacterial orders between the control and drought hardening treatments. (A is the seedling stage, B is the budding stage, C is the flowering and boll stage.)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK/D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCK/D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCK/D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCK/D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCK/D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCK/D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCK/D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCK/D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCK/D3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCytophagales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSphingomonadales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncertae_Sedis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChitinophagales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePyrinomonadales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePirellulales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGemmatimonadales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTepidisphaerales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlastocatellales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBurkholderiales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePS: Asterisks (* P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, and *** P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, two-tailed Student's t-test) indicate significance. Light-colored asterisks indicate that the relative abundance of the order in the drought hardening treatment was lower than that in the control. Dark-colored asterisks indicate that the relative abundance of the order in the drought hardening treatment was higher than that in the control.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSignificance levels of differences in the relative abundance of the top 10 fungal orders between the control and drought hardening treatments. (A is the seedling stage, B is the budding stage, C is the flowering and boll stage.)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK/D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCK/D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCK/D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCK/D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCK/D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCK/D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCK/D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCK/D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCK/D3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSordariales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnygenales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypocreales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroascales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpizellomycetales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePleosporales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePezizales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortierellales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlomerellales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThelebolales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePS: Asterisks (* P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, and *** P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, two-tailed Student's t-test) indicate significance. Light-colored asterisks indicate that the relative abundance of the order in the drought hardening treatment was lower than that in the control. Dark-colored asterisks indicate that the relative abundance of the order in the drought hardening treatment was higher than that in the control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEffects of drought hardening on aboveground growth characteristics in cotton plants\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e(a), LAI increased first and then decreased, and reached the peak at blooming stage. The D1 was slightly higher than CK, and there was D1\u0026thinsp;\u0026ge;\u0026thinsp;CK\u0026thinsp;\u0026gt;\u0026thinsp;D2\u0026thinsp;\u0026gt;\u0026thinsp;D3 under differential treatments. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e(b), plants under D1, D2, and D3 treatments exhibited sustained height increments throughout the experimental period, consistently surpassing CK. This indicated that moderate drought hardening had no significant impairment on shoot growth. Figure\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e(c) showed that the aboveground biomass reached its highest level during the boll-opening stage. The D1 treatment was always higher than CK, indicating that moderate drought hardening contributed to biomass accumulation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eEffects of drought hardening on cotton yield\u003c/h2\u003e \u003cp\u003eThe cotton yield components include total boll number, single boll weight, seed cotton yield, lint yield, and lint percentage. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the D1 treatment showed consistent superiority over the CK across all five evaluated indicators. Specifically, the single boll weight in the D1 treatment was 12.47% higher than that in the CK, and the seed cotton yield was 20.43%, the lint yield was 26.76%, the lint percentage was 4.65%, the total boll number was 6.78% higher than CK, respectively. This indicated that moderate drought hardening not only preserved but also enhanced cotton yield under water-saving conditions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal boll number, single boll weight, seed cotton yield, lint yield, and lint percentage of cotton under control and different drought hardening treatments.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Boll Number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSingle Boll Weight (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSeed Cotton Yield (kg\u0026middot;hm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLint Yield (kg\u0026middot;hm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLint Percentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,322.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3,159.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,818.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3,960.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6,845.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,921.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,298.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3,138.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study explored the physiological adaptations in cotton roots induced by drought stress, concurrent with analysis of the dynamics in soil microbial communities, while revealing cotton's drought-hardening adaptation mechanisms. The experimental framework coupled drought treatments with rhizosphere microbiome profiling, root system physiological-adaptation analysis, and agronomic productivity measurements. (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results revealed significant oxidative stress acclimation in cotton roots under drought stress, other acclimations are similar as well [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Moderate drought hardening (D1 treatment) effectively activated the upregulation of root antioxidant enzymes, significantly mitigating membrane lipid peroxidation and suppressing ROS overproduction (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The progressive oxidant overload indicated drought-induced oxidative injury through cumulative peroxidative damage to membrane systems [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. As a product of membrane lipid peroxidation, MDA content reflects the degree of cell membrane damage. D1 treatment showed significantly lower MDA content than other treatments. This systemic antioxidant defense conferred critical protection against drought-induced oxidative injury while maintaining root cellular homeostasis under water-deficit conditions [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditionally, Pro content generally increased with the severity of drought stress, while the activities of antioxidant enzymes (SOD and POD) initially increased and then decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), indicating that Pro accumulates as an osmoregulatory substance to help maintain cellular osmotic pressure and cellular stability under drought stress [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Meanwhile, cotton roots rapidly upregulated antioxidant enzymes to counteract stress. Similar regulatory mechanisms were reported in sand mustard seedlings involving POD and SOD dynamics under drought stress [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However, plants prioritize survival over defense under extreme stress, with energy diverting from enzyme production to repair processes. When abiotic stress surpasses plant\u0026rsquo;s tolerance threshold, the antioxidant defense system collapses (such as SOD and POD), leading to irreversible cellular damage [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDrought hardening significantly altered the diversity and structure of soil microbial communities associated with cotton roots. Drought reduced soil moisture, collapsing pore networks and limiting microbial motility, for bacterial communities, the Shannon diversity index generally decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). It was a critical ecological response, reflecting how microbial systems reorganize under environmental stress [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. However, during the seedling stage, moderate drought acclimation (D2 treatment) increased bacterial diversity (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). It was possibly due to enhanced root exudates providing additional carbon sources and favorable growth conditions for microorganisms, stress-tolerant specialists increased under moderate drought stress[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Furthermore, during the flowering and boll stage, the bacterial community composition in each treatment was significantly different (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). Drought stress notably enriched \u003cem\u003eGemmatimonadales\u003c/em\u003e under D1 treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and with similar observations reported in rice rhizosphere communities [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor fungal communities, moderate drought hardening (D1 treatment) enhanced fungal Shannon diversity across all stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). At the seedling stage, the fungal community composition in D1 significantly differed from D2 and D3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb), while there were no clear taxonomic changes between drought treatment and CK (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). It revealed there were stage-specific interactions between drought intensity and fungal ecology, and fungal communities, being more drought-tolerant, maintained a composition similar to CK.\u003c/p\u003e \u003cp\u003eThis study preliminarily revealed potential synergistic mechanisms between cotton roots and soil microorganisms under drought conditions. At the budding stage, the D1 treatment showed significantly higher fungal Shannon diversity than CK (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). Concurrently, the relative abundance of \u003cem\u003eGemmatimonadales\u003c/em\u003e significantly increased in D1 at the budding stage. The results suggested that D1 treatment protected plant roots from oxidative stress compared to CK, with significantly lower MDA levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb), higher antioxidant enzyme activities (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec) and more stable communities for soil microorganisms (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Those adaptive regulation might promote root nutrient and water uptake, collectively enhancing drought resistance [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis phenomenon revealed the complexity of plant-microbe interactions under stress and highlighted the importance of stress intensity in shaping soil microbial communities. Future studies should explore the functions of these unclassified or poorly characterized root-associated bacteria to reveal the molecular mechanism of root-microorganism synergistic stress-resistance under drought-hardening conditions.\u003c/p\u003e \u003cp\u003eAlterations in root physiology coupled with dynamic shifts in rhizosphere microbial communities were synergistically regulated plant growth-development and ultimately determined crop yield[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], as shown as LAI, plant height and aboveground biomass was the highest under D1 treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). Furthermore, single boll weight, seed cotton yield, lint yield and lint percentage in D1 treatment plants were superior to CK. (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This root-microbe interaction mechanism achieved a balance between drought resistance and agricultural yield under 20% water-saving conditions.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe investigation was conducted in commercial cotton cultivation zones within Changji, in Xinjiang, and adjacent agricultural districts, where differential drought hardening treatments were established in parallel with control groups. The research employed a multidimensional analytical framework to establish mechanistic linkages between rhizosphere processes and crop performance, including phyto-biochemical transformations within cotton root systems, rhizosphere-specific soil-microbial communities dynamics, growth characteristics of the aboveground parts, and agronomic productivity determinants. The results showed that moderate drought hardening activated root antioxidant system, enhanced root stress resistance, increased the diversity of soil microorganisms, leaded to the formation of dominant bacteria within the \u003cem\u003eGemmatimonadales\u003c/em\u003e, and maintained normal growth and yield in cotton plants. This study\u0026rsquo;s conclusion to implement the treatment D1 as a water-saving irrigation strategy in cotton cultivation in Changji was scientific, with the ability to enhance stress-resistance and optimize plant resilience efficiency while safeguarding yield under D1 condition. Future research would explore the interaction mechanisms between cotton roots and \u003cem\u003eGemmatimonadales\u003c/em\u003e, as well as unclassified microorganisms. These coordinated investigations revealed critical linkages between drought-induced root stress-resistance, microbial community regulation, and cotton productivity outcomes, thereby establishing scientific and practical foundation for optimizing water-use efficiency of cotton cultivation systems in Xinjiang's arid.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the funding support provided by the major national projects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX.L., Y.Z., G.L. and Y.C. conducted the experiments. X.L., Y.Z., K.W., and X.L. analysed the data and prepared the figures. L.H. and W.S. designed the study, supervised the experiments and secured the funding for this project. X.L. wrote the manuscript and W.S. revised and edited it. All authors read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Science and Technology Major Project\u0026nbsp;(2022ZD0115801).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data and materials generated during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChen J, Wu X, Yang J, Liu X, Liu Y. 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Chin J Oil Crop Sci. 2024;46(3):625\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.19802/j.issn.1007-9084.2024086\u003c/span\u003e\u003cspan address=\"10.19802/j.issn.1007-9084.2024086\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Drought stress, Drought hardening, Cotton roots, Soil microorganisms","lastPublishedDoi":"10.21203/rs.3.rs-6703288/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6703288/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eAs global climate changing significantly exacerbated the frequency and intensity of drought stress, posing severe challenges to the sustainable development of agriculture in arid regions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAims:\u003c/strong\u003e This investigation employed integrated physiological and metagenomic analyses to unravel the physiological responses of cotton roots and the changes of soil microbial communities induced by drought hardening. Then, by integrating the physiological responses of the aboveground parts and yield performance, a comprehensive analysis was conducted to provide optimized irrigation strategies for cotton fields in moisture-limited regions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e The experiment was conducted in 2024 at Huaxing Farm in Changji, Xinjiang, using the Zhongmian 113 variety, with three drought hardening treatments during the seedling stage. These treatments were saving 20% (D1), 30% (D2), and 40% (D3) of irrigation amount respectively, comparing to the control (CK, conventional full irrigation).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The results showed that the D1 treatment was identified as moderate drought hardening, which based on cotton growth and yield; The D1 treatment significantly enhanced the antioxidant capacity and membrane integrity maintenance in cotton roots; Additionally, the D1 treatment altered soil microbial diversity, partially optimizing the microbial community structure and forming a dominant bacterial group—\u003cem\u003eGemmatimonadales\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e This integrated microbial-plant analysis hypothesized that \u003cem\u003eGemmatimonadales\u003c/em\u003e might interact synergistically with cotton roots during the budding stage to enhance the drought resistance of cotton. The research provided a foundation for revealing the enhancing drought- resistance- mechanisms of root-microbe interactions in cotton via drought hardening in arid regions.\u003c/p\u003e","manuscriptTitle":"Physiological responses of cotton roots and soil microbial adaptation to drought hardening","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-10 14:03:18","doi":"10.21203/rs.3.rs-6703288/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"203802136570931511233900607953108398625","date":"2025-06-10T10:49:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"313220636419843888247208661219102405096","date":"2025-06-10T03:52:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"247527671425409933032304874982809065171","date":"2025-06-07T12:47:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-05T10:34:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-29T04:23:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-28T09:14:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2025-05-28T09:13:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6e782754-e52b-495f-abac-fbde2e282f89","owner":[],"postedDate":"June 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T16:05:45+00:00","versionOfRecord":{"articleIdentity":"rs-6703288","link":"https://doi.org/10.1186/s12870-025-07992-8","journal":{"identity":"bmc-plant-biology","isVorOnly":false,"title":"BMC Plant Biology"},"publishedOn":"2025-12-28 15:58:01","publishedOnDateReadable":"December 28th, 2025"},"versionCreatedAt":"2025-06-10 14:03:18","video":"","vorDoi":"10.1186/s12870-025-07992-8","vorDoiUrl":"https://doi.org/10.1186/s12870-025-07992-8","workflowStages":[]},"version":"v1","identity":"rs-6703288","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6703288","identity":"rs-6703288","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}