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Composite microbial agent improves cotton yield and resource use efficiency under mild salt stress by optimizing plant resource allocation

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  • Zhao, Xiao
  • Guo, Panpan
  • Wu, Xiong
  • Zhu, Meng
  • Kang, Shaozhong
  • Du, Taisheng
  • Kang, Jian
  • Chen, Jinliang
  • Tong, Ling
  • Ding, Risheng
  • Xu, Wanli
  • Tang, Guangmu

Abstract

Soil salinization and low resource utilization efficiency present significant challenges to cotton production. The application of salt-tolerant composite plant growth-promoting rhizobacteria (STC-PGPR) is considered an effective strategy to address these issues. However, its broad adaptability and regulatory mechanisms require further exploration. We hypothesize that under non-saline or moderately saline conditions, STC-PGPR directs resources to shoots, especially reproductive organs, by altering the rhizosphere bacterial community, thereby enhancing seed cotton yield (SY) and resource use efficiency. To validate our hypothesis, we conducted an experiment using two cotton varieties: Xinluzao 72 (G1) and Zhongmiansuo 49 (G2); two microbial treatments: without STC-PGPR (B1) and with STC-PGPR (B2); and three salinity levels: 0, 4, and 8 g NaCl kg−1 soil (S1, S2, S3). The results demonstrated that STC-PGPR enhanced SY and resource use efficiency under both S1 and S2 salinity levels, with significant improvements observed in G2S1 and G1S2 . Under G2S1, STC-PGPR increased nitrogen uptake efficiency, optimized shoot resource allocation to stems and squares, enhanced stem support, and improved resource storage and transport. Consequently, SY and nitrogen partial factor productivity (NPFP) increased by 9.1 % and 9.0 %, respectively. Under G1S2, STC-PGPR reduced the root-shoot ratio, directing more resources to shoots, which led to increases in SY, irrigation water productivity, and NPFP by 46.2 %, 44.8 %, and 45.9 %, respectively. These changes were primarily due to altered indigenous biomarkers after STC-PGPR application, rather than the bacteria in STC-PGPR. This study highlights the potential of STC-PGPR, emphasizing the importance of optimizing resource allocation rather than merely promoting growth. Additionally, it underscores the significant role of indigenous biomarkers in mediating these effects.

Suggested Citation

  • Zhao, Xiao & Guo, Panpan & Wu, Xiong & Zhu, Meng & Kang, Shaozhong & Du, Taisheng & Kang, Jian & Chen, Jinliang & Tong, Ling & Ding, Risheng & Xu, Wanli & Tang, Guangmu, 2025. "Composite microbial agent improves cotton yield and resource use efficiency under mild salt stress by optimizing plant resource allocation," Agricultural Water Management, Elsevier, vol. 310(C).
    • Handle: RePEc:eee:agiwat:v:310:y:2025:i:c:s0378377425000721
    DOI: 10.1016/j.agwat.2025.109358
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    1. Fang, Heng & Li, Yuannong & Gu, Xiaobo & Yu, Meng & Chen, Pengpeng & Li, Yupeng & Liu, Fulai, 2022. "Optimizing the impact of film mulching pattern and nitrogen application rate on maize production, gaseous N emissions, and utilization of water and nitrogen in northwest China," Agricultural Water Management, Elsevier, vol. 261(C).
    2. Zhao, Xiao & Gu, Xiaobo & Yang, Zhichao & Li, Yuannong & Zhang, Li & Zhou, Jiaming, 2022. "Effects of soil preparation and mulching practices together with different urea applications on the water and nitrogen use of winter wheat in semi-humid and drought-prone areas," Agricultural Water Management, Elsevier, vol. 263(C).
    3. Wang, Jiangtao & Du, Gangfeng & Tian, Jingshan & Zhang, Yali & Jiang, Chuangdao & Zhang, Wangfeng, 2020. "Effect of irrigation methods on root growth, root-shoot ratio and yield components of cotton by regulating the growth redundancy of root and shoot," Agricultural Water Management, Elsevier, vol. 234(C).
    4. Liao, Qi & Ding, Risheng & Du, Taisheng & Kang, Shaozhong & Tong, Ling & Gu, Shujie & Gao, Shaoyu & Gao, Jia, 2024. "Stomatal conductance modulates maize yield through water use and yield components under salinity stress," Agricultural Water Management, Elsevier, vol. 294(C).
    5. Liang, Jiaping & Shi, Wenjuan, 2021. "Poly-γ-glutamic acid improves water-stable aggregates, nitrogen and phosphorus uptake efficiency, water-fertilizer productivity, and economic benefit in barren desertified soils of Northwest China," Agricultural Water Management, Elsevier, vol. 245(C).
    6. Chen, Xinyue & Zhang, Kai & Gao, Xiaopeng & Ai, Xin & Chen, Guoyue & Guo, Xiaomeng & Wu, Chengcheng & Zhang, Lu, 2025. "Effect of irrigation with magnetized and ionized water on yield, nutrient uptake and water-use efficiency of winter wheat in Xinjiang, China," Agricultural Water Management, Elsevier, vol. 308(C).
    7. Bi, Yanpeng & Zhou, Beibei & Ren, Peiqi & Chen, Xiaopeng & Zhou, Dehua & Yao, Shaoxiong & Fan, Dongliang & Chen, Xiaolong, 2024. "Effects of Bacillus subtilis on cotton physiology and growth under water and salt stress," Agricultural Water Management, Elsevier, vol. 303(C).
    8. Guoqiang Zhang & Bo Ming & Dongping Shen & Ruizhi Xie & Peng Hou & Jun Xue & Keru Wang & Shaokun Li, 2021. "Optimizing Grain Yield and Water Use Efficiency Based on the Relationship between Leaf Area Index and Evapotranspiration," Agriculture, MDPI, vol. 11(4), pages 1-14, April.
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