LIU Zhaoyang, LI Shuyue, MAO Jingying, et al. Effect of magnesium nutrition on growth and root system architecture traits of soybean seedlings[J]. Journal of South China Agricultural University, 2024, 45(3): 321-328. DOI: 10.7671/j.issn.1001-411X.202311009
    Citation: LIU Zhaoyang, LI Shuyue, MAO Jingying, et al. Effect of magnesium nutrition on growth and root system architecture traits of soybean seedlings[J]. Journal of South China Agricultural University, 2024, 45(3): 321-328. DOI: 10.7671/j.issn.1001-411X.202311009

    Effect of magnesium nutrition on growth and root system architecture traits of soybean seedlings

    More Information
    • Received Date: November 11, 2023
    • Available Online: March 03, 2024
    • Published Date: March 11, 2024
    • Objective 

      Magnesium (Mg) is an essential mineral nutrient for plant growth. This study was aimed to investigate the growth and dynamic changes in three-dimensional root system architecture traits of soybean seedlings under different Mg concentrations.

      Method 

      The phosphorus-efficient soybean genotype ‘Yuechun 03-3’ was selected as the research object, and Mg concentrations were set in hydroponics as 0, 262.5, 525.0, 787.5 and 1 050.0 μmol/L to explore the effect of Mg nutrition on the growth and development of soybean seedlings. Furthermore, the optimized three-dimensional root quantification system was used to analyze the dynamic quantitative changes in the root system architecture traits of soybeans under control Mg treatment (525.0 μmol/L) and Mg deficiency treatment (0 μmol/L).

      Result 

      Compared with the control of 525.0 μmol/L Mg, the soybean shoot dry mass, root-to-shoot ratio, SPAD of old leaves, total root length, and total root surface area under the 0 μmol/L Mg deficiency treatment decreased by 89.04%, 48.67%, 51.42%, 93.36% and 94.31% respectively. Under other three Mg concentration conditions, the growth of soybeans showed relatively small differences compared with the control. The results of three-dimensional root system quantification found that compared with the control Mg treatment, Mg deficiency treatment significantly reduced the total root length, total root surface area, root centroid, number of root tips, convex hull volume, maximum root width, minimum root width, maximum root depth and maximum width/maximum depth of soybean roots with the extension of treatment time. However, it affected root solidity, bushiness and root volume distribution feebly.

      Conclusion 

      This study elucidates the wide adaptability range of soybeans to external Mg availability. By utilizing optimized three-dimensional root reconstruction techniques, it is found that Mg deficiency significantly reduces the total root length, number of root tips, root centroid and maximum root width of soybeans, while it does not significantly affect the dynamic changes in root solidity, bushiness and volume distribution. These findings have certain implications for rational use of Mg fertilizer and Mg nutrition diagnosis in soybeans.

    • [1]
      HERMANS C, BOURGIS F, FAUCHER M, et al. Magnesium deficiency in sugar beets alters sugar partitioning and phloem loading in young mature leaves[J]. Planta, 2005, 220(4): 541-549. doi: 10.1007/s00425-004-1376-5
      [2]
      CAKMAK I. Magnesium in crop production, food quality and human health[J]. Plant and Soil, 2013, 368(1/2): 1-4.
      [3]
      MENGUTAY M, CEYLAN Y, KUTMAN U B, et al. Adequate magnesium nutrition mitigates adverse effects of heat stress on maize and wheat[J]. Plant and Soil, 2013, 368(1/2): 57-72.
      [4]
      李延, 刘星辉, 庄卫民. 植物Mg素营养生理的研究进展[J]. 福建农业大学学报, 2000, 29(1): 74-80.
      [5]
      TIAN X Y, HE D D, BAI S, et al. Physiological and molecular advances in magnesium nutrition of plants[J] Plant and Soil, 2021, 468(1/2): 1-17.
      [6]
      李春俭, 王正, 张福锁. 镁肥在我国主要作物上的提质增效作用[J]. 中国土壤与肥料, 2022(3): 1-6. doi: 10.11838/sfsc.1673-6257.20707
      [7]
      黄鸿翔, 陈福兴, 徐明岗, 等. 红壤地区土壤镁素状况及镁肥施用技术的研究[J]. 土壤肥料, 2000(5): 19-23.
      [8]
      LYNCH J. Root architecture and plant productivity[J]. Plant Physiology, 1995, 109(1): 7-13. doi: 10.1104/pp.109.1.7
      [9]
      BOWMAN D C, DEVITT D A, ENGELKE M C, et al. Root architecture affects nitrate leaching from bentgrass turf[J]. Crop Science, 1998, 38: 1633-1639. doi: 10.2135/cropsci1998.0011183X003800060036x
      [10]
      LI X, ZENG R, LIAO H. Improving crop nutrient efficiency through root architecture modifications[J]. Journal of Integrative Plant Biology, 2016, 58(3): 193-202. doi: 10.1111/jipb.12434
      [11]
      赵静, 付家兵, 廖红, 等. 大豆磷效率应用核心种质的根构型性状评价[J]. 科学通报, 2004, 49(13): 1249-1257. doi: 10.3321/j.issn:0023-074X.2004.13.006
      [12]
      肖爽, 刘连涛, 张永江, 等. 植物微根系原位观测方法研究进展[J]. 植物营养与肥料学报, 2020, 26(2): 370-385. doi: 10.11674/zwyf.19186
      [13]
      CLARK R T, MACCURDY R B, JUNG J K, et al. Three-dimensional root phenotyping with a novel imaging and software platform[J]. Plant Physiology, 2011, 156(2): 455-465. doi: 10.1104/pp.110.169102
      [14]
      LOBET G, DRAYE X, PÉRILLEUX C. An online database for plant image analysis software tools[J]. Plant Methods, 2013, 9: 38. doi: 10.1186/1746-4811-9-38
      [15]
      余常兵, 陆星, 廖星, 等. 油菜高通量根系构型定量分析与三维重建系统[J]. 中国油料作物学报, 2016, 38(5): 681-690.
      [16]
      LIU S, BARROW C S, HANLON M, et al. DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)[J]. Plant Physiology, 2021, 187(2): 739-757. doi: 10.1093/plphys/kiab311
      [17]
      钟南, 罗锡文, 秦琴. 基于生长函数的大豆根系生长的三维可视化模拟[J]. 农业工程学报, 2008, 24(7): 151-154. doi: 10.3321/j.issn:1002-6819.2008.07.031
      [18]
      HAN L, GRESSHOFF P M, HANAN J. A functional-structural modelling approach to autoregulation of nodulation[J]. Annals of Botany, 2011, 107(5): 855-863. doi: 10.1093/aob/mcq182
      [19]
      祁旺定, 尚明瑞. 中国大豆产业发展问题研究[J]. 中国农学通报, 2014, 30(17): 88-96.
      [20]
      程凤娴, 涂攀峰, 严小龙, 等. 酸性红壤中磷高效大豆新种质的磷营养特性[J]. 植物营养与肥料学报, 2010, 16(1): 71-81.
      [21]
      余常兵, 陆星, 李银水, 等. 植物根系三维固定培养装置: CN204579393U[P]. 2015-08-26 [2023-11-12]

      .
      [22]
      李丹萍, 刘敦一, 张白鸽, 等. 不同镁肥在中国南方三种缺镁土壤中的迁移和淋洗特征[J]. 土壤学报, 2018, 55(6): 1513-1524.
      [23]
      李亚洲, 李沸, 高铭, 等. 土壤中过量镁对大豆几项生理指标的影响[J]. 农业环境保护, 1990, 9(2): 41-42.
      [24]
      丁玉川, 焦晓燕, 聂督. 镁水平对不同类型土壤大豆生长、养分吸收以及产量的影响[J]. 中国农学通报, 2010, 26(17): 201-205.
      [25]
      曾秀成, 王文明, 罗敏娜, 等. 缺素培养对大豆营养生长和根系形态的影响[J]. 植物营养与肥料学报, 2010, 16(4): 1032-1036.
      [26]
      CAKMAK I, MARSCHNER H. Magnesium deficiency and high light intensity enhance activities of superoxide dismutase, ascorbate peroxidase and glutathione reductase in bean leaves[J]. Plant Physiology, 1992, 98(4): 1222-1227. doi: 10.1104/pp.98.4.1222
      [27]
      GRUBER B D, GIEHL R F H, FRIEDEL S, et al. Plasticity of the Arabidopsis root system under nutrient deficiencies[J]. Plant Physiology, 2013, 163(1): 161-179. doi: 10.1104/pp.113.218453
      [28]
      IYER-PASCUZZI A S, SYMONOVA O, MILEYKO Y, et al. Imaging and analysis platform for automatic phenotyping and trait ranking of plant root systems[J]. Plant Physiology, 2010, 152(3): 1148-1157. doi: 10.1104/pp.109.150748
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