types of soil research paper

A critical review on soil structure: research methods, structured indexes, and constitutive models

• Review Paper
• Published: 09 September 2022
• Volume 15 , article number  1509 , ( 2022 )

Cite this article

• Chuanyang Liang 1 , 2 ,
• Yuedong Wu 1 , 2 ,
• Jian Liu 1 , 2 ,
• Dashuo Chen 1 , 2 &
• Yongyang Zhu 1 , 2  

425 Accesses

Explore all metrics

To determine and evaluate the soil structure in situ conditions, a lot of research methods have been proposed. However, ascertaining the applicability of these methods to soils of entirely different “types of structure,” which they can express and evaluate, is still a point of debate. With this in view, efforts have been made in this review to critically evaluate all the established and emerging soil structure research thinking, theories, and methods with respect to their merits and demerits. Then, a detailed analysis concerning published structured indexes and constitutive models based on these methods is done to evaluate the applicability. Also, this paper puts forward some suggestions and key points for their developments. Based on the analysis of literature, each existing research method can merely dictate one type of soil structure, and combination of multiple research methods may be an effective access to reveal the structure characteristics of soil comprehensively. Moreover, it will be the focus of soil structure research to quantitatively link the microstructure characteristics with the macro-structure characteristics. These results will be useful for geotechnical engineers and researchers who consider the soil structure in engineering survey and design.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Soil Properties: Physics Inspired, Data Driven

A Bibliometric Review of Reinforced Soil Wall Research Topics

Combination of Decisive Properties of Soil in Science and Geotechnics

Data availability.

Data sharing is not applicable. No new data were created or analyzed in this study.

Akbarimehr D, Eslami A, Imam R (2021) Correlations between compression index and index properties of undisturbed and disturbed Tehran clay. Geotech Geol Eng 39:5387–5393. https://doi.org/10.1007/s10706-021-01821-z

Article   Google Scholar  

Alimohammadi H, Amirmojahedi M, Tahat JN. (2022) A case history of application of deep compaction method with comparison to different ground improvement techniques. Transp Infrastruct Geotechnol 1–26. https://doi.org/10.1007/s40515-022-00229-3

Alimohammadi H, Tahat J (2022) A case study experimental pile load testing (PLT) for evaluation of driven pile behaviors. Arab J Geosci 15(9):1–11. https://doi.org/10.1007/s12517-022-10176-5

Bian X, Wang ZF, Ding GQ et al (2016) Compressibility of cemented dredged clay at high water content with super-absorbent polymer. Eng Geol 208:198–205. https://doi.org/10.1016/j.enggeo.2016.04.036

Burland JB (1990) On the compressibility and shear strength of natural clays. Geotechnique 40:329–378. https://doi.org/10.1680/geot.1990.40.3.329

Castro-Filgueira U, Alejano LR, Arzúa J et al (2017) Sensitivity analysis of the micro-parameters used in a PFC analysis towards the mechanical properties of rocks. Procedia Eng 191:488–495. https://doi.org/10.1016/j.proeng.2017.05.208

sediments in depositional basins: the geotechnical cycle, Quarterly J. of Engrg. Geol Hydrogeol 33:7–39. https://doi.org/10.1144/qjegh.33.1.7

Chen CL, Hu ZQ, Gao P (2006) Research on relationship between structure and deformation property of intact loess. Rock Soil Mechanics 28:1891–1896. https://doi.org/10.16285/j.rsm.2006.11.006

Cotecchia F, Chandler RJ (2000) A general framework for the mechanical behavior of clays. Geotechnique 50:431–447. https://doi.org/10.1680/geot.2000.50.4.431

Dang JQ, Li J (2001) The structural strength and shear strength of unsaturated loess. J Hydraul Eng 46:79–83. https://doi.org/10.3321/j.issn:05599350.2001.07.014

Deng GH (2009) Research on structure parameter of loess and structure constitutive relations under true tri-axial condition, Doctor, Xi'an University of Technology, Xi'an, China. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CDFD&dbname=CDFD0911&filename=2010139844.nh&uniplatform=NZKPT&v=byMTuVSOJnfFPMIQrVwNIHOGObovAKPV4AIuJ74DLDPCr2J9lh4YlweYT6MU2qIS Accessed 6 Jun 2022

Deng GH, Shao SJ, She FT (2012) Modified Cam-clay model of structured loess. Chinese J Geotech Eng 34:834–841. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD2012&filename=YTGC201205010&uniplatform=NZKPT&v=y4s38X5DhZcNSEBwzbgSzEZQea4iZK0qmi-vdkdweE0aOeqf34gMeZMdXHxbT2Tl Accessed 6 Jun 2022

Desai CS (1974) A consistent finite element technique for work-softening behavior, Proceedings of International Conference on Computer Methods and Nonlinear Mechanics, Austin, TX, USA, March, pp. 403–419. https://xueshu.baidu.com/usercenter/paper/show?paperid=0487f61944585fcccd127a01a87e85e9&site=xueshu_se&hitarticle=1 Accessed 6 Sep 2022

Desai CS (2013) Disturbed state concept (DSC) for constitutive modeling of geologic materials and beyond, Constitutive modeling of geomaterials. Springer, Berlin, Heidelberg, pp. 27–45. https://doi.org/10.1007/978-3-642-32814-5_3

Desai CS (2018) Constitutive modeling of geologic materials and interfaces: significant for geomechanics, International Congress and Exhibition" Sustainable Civil Infrastructures: Innovative Infrastructure Geotechnology". Springer, Cham, pp. 1–31. https://doi.org/10.1007/978-3-030-01926-6_1

Desai CS, Ma Y (1992) Modeling of joints and interfaces using the disturbed state concept. Int J Numer Anal Meth Geomech 16:623–653. https://doi.org/10.1002/nag.1610160903

Eslami A, Akbarimehr D (2021) Failure analysis of clay soil-rubber waste mixture as a sustainable construction material. Constr Build Mater 310:125274. https://doi.org/10.1016/j.jclepro.2020.122632

Fang XW, Chen ZH, Shen CN, et al. (2008) Meso-testing research on structure damage evolution of natural Q 2 loess, Journal of Hydraulic Engineering 39, 940–940. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD2008&filename=SLXB200808008&uniplatform=NZKPT&v=Nbv_F2JHHy3CtgAEX0EV6HtzE6vwjl0pp3obb7fDX5Ezcg9ugoLJ_c63z1kavHSi Accessed 6 Jun 2022

Fang XW, Li YY, Shen CN, Chen ZH (2017) Constitutive model of unsaturated intact Q 2 loess based on disturbed state concept. J Logist Eng Univ 33:1–8. https://doi.org/10.3969/j.issn.1672-7843.2017.04.001

Fu TT, Zhu ZW, Ma W, Zhang FL (2021) Damage model of unsaturated frozen soil while considering the influence of temperature rise under impact loading. Mech Mater 163:104073. https://doi.org/10.1016/j.mechmat.2021.104073

Girgis N, Li B, Akhtar S, Courcelles B (2020) Experimental study of rate-dependent uniaxial compressive behaviors of two artificial frozen sandy clay soils. Cold Reg Sci Technol 180:103166. https://doi.org/10.1016/j.coldregions.2020.103166

Hajitaheriha MM, Akbarimehr D, Motlagh AH, Damerchilou H (2021) Bearing capacity improvement of shallow foundations using a trench filled with granular materials and reinforced with geogrids. Arab J Geosci 14(15):1–14. https://doi.org/10.1007/s12517-021-07679-y

Hanzawa H (2008) Undrained strength characteristics of normally consolidated aged clay. Soils Found 24:114–115. https://doi.org/10.3208/sandf1972.23.3_39

Hong Z, Onitsuka K (1998) A method of correcting yield stress and compression index of Ariake clays for sample disturbance. J Japanese Geotech Soc 38:211–222. https://doi.org/10.3208/sandf.38.2_211

Hu HJ, Jiang MJ (2016) Constitutive model of structured loess incorporating the breakage law obtained by discrete element method. Chin J Rock Mech Eng 35:3241–3248. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFDLAST2016&filename=YSLX2016S1073&uniplatform=NZKPT&v=l9-anTEMSES4BgYWRngyJDAw49I5IquOIRW-egvzTxGlhIwGJs57L-6nsHrqUQDV Accessed 6 Jun 2022

Hu RL (1995) Study on microstructure quantitative model and engineering geological characteristics of cohesive soil, Geological Publishing House, pp. 29–32. https://xueshu.baidu.com/usercenter/paper/show?paperid=7affe75281637efd9f00421872d134e6&site=xueshu_se&hitarticle=1 Accessed 6 Sep 2022

Hu RL, Wang SJ (1999) Soil micromechanics-concept, view and core. Acta Geoscientica Sinica 20:150–156. https://doi.org/10.3321/j.issn:1006-3021.1999.02.006

Huang WX (1983) Engineering properties of soil, Water Resources and Electric Power Press, pp. 58–59. https://xueshu.baidu.com/usercenter/paper/show?paperid=b3cdd97049d3819f6909ed78724f29c6&site=xueshu_se Accessed 6 Sep 2022

Jiang MJ (2019) New paradigm for modern soil mechanics: geomechanics from micro to macro. Chin J Geotech Eng 41:6–65. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFDLAST2019&filename=YTGC201902002&uniplatform=NZKPT&v=fGnHEyOha_Cfkr0xe7j5t3iN60aSByoaLQZxcz_9lvW4zRfqZLoGMDcjxlqWJ1Nx Accessed 6 Jun 2022

Jiang MJ, Li T, Cui Y et al (2017) Mechanical behavior of artificially cemented clay with open structure: cell and physical model analyses. Eng Geol 221:133–142. https://doi.org/10.1016/j.enggeo.2017.03.002

Katti DR, Desai CS (1995) Modeling and testing of cohesive soil using disturbed-state concept. J Eng Mech 121:648–658. https://doi.org/10.1016/0148-9062(96)86972-5

Kruyt NP, Rothenburg L (1996) Micromechanical definition of the strain tensor for granular materials. J Appl Mech 63:706–711. https://doi.org/10.1115/1.2823353

Lambe T (1958a) The engineering behavior of compacted clay. J Soil Mech Found Div 84:1655–1–1655–35. https://doi.org/10.1061/JSFEAQ.0000115

Lambe TW (1958b) The structure of compacted clays. J Soil Mech Found Div 84:1654–1–1654–34. https://doi.org/10.1061/JSFEAQ.0000114

Li CH (2020) Research and development of soil microstructure. Sci Technol Innov 25:109–110. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFDLAST2020&filename=HLKX202003064&uniplatform=NZKPT&v=8Hcw0g4FL0Sd3uzM7nQVd8zd383GKGGpYYZal2lP3MGHKyckIALbaYUUCtekUdU_ Accessed 6 Jun 2022

Li LL (2007) Behavior of structured clay and its application, Doctor, Zhejiang University, Zhejiang, China. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CDFD&dbname=CDFD9908&filename=2008046205.nh&uniplatform=NZKPT&v=HqyvfjqC97juxCax17sIu1UARpMSWS66mMTYGnPOfGbHK4s56im6S-ll6XcAWVl Accessed 6 Jun 2022

Li T, Qian SY (1987) Evaluation of soil sample disturbance and determination of its pre-consolidation pressure. Chin J Geotech Eng 9:23–32. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD8589&filename=YTGC198705002&uniplatform=NZKPT&v=zVeSrblWFLB4uSJzYMvVw8E1rRYNirUVBLFwG8KsRZcWYPNwzDcGsI51-bcg-Wa7 Accessed 6 Jun 2022

Liu HL, Hong ZS (2003) Effect of sample disturbance on unconfined compression strength of natural marine clays. China Ocean Eng 17:407–416. https://doi.org/10.3321/j.issn:0890-5487.2003.03.009

Liu HT, Guo YC (2014) Evaluation of structure and disturbance of soft ground. J Zhengzhou Univ (Eng Sci) 35:54–58. https://doi.org/10.3969/j.issn.1671-6833.2014.05.013

Liu MD, Carter JP (2000) Modeling the destructuring of soils during virgin compression. Geotechnique 50:479–483. https://doi.org/10.1680/geot.2000.50.4.479

Liu MD, Carter JP (2002) A structured cam clay model. Can Geotech J 39:1313–1332. https://doi.org/10.1139/t02-069

Liu SY, Fang L (1992) Discussion on fractal structure of particle size distribution of cohesive soil. Geotech Investigation Survey 2:1–4. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD9093&filename=GCKC199202000&uniplatform=NZKPT&v=_Mvk34YG1JnMCuTIMgXNfV4v0Sl6I72vBkOYudH--rGcYZgtnYSwCpZC19lVOL6D Accessed 6 Jun 2022

Liu WZ, Shi ML, Miao LC (2010) Evaluation of soil structural characteristics of Taihu lacustrine-swamp natural sedimentary soils. Chin J Geotech Eng 32:1616–1620. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD2010&filename=YTGC201010024&uniplatform=NZKPT&v=H8NGq_iBN1UAUIM5Q5qdEHZRBiq5GtOcHaXruywr1OHv64fjRBEZUfwjysNpmhd2 Accessed 6 Jun 2022

Low HE, Phoon KK, Tan TS et al (2008) Effect of soil microstructure on the compressibility of natural Singapore marine clay. Can Geotech J 45:161–176. https://doi.org/10.1139/T07-075

Lu TH (2002) Soil mechanics, Hohai University Press, pp. 17–19. https://xueshu.baidu.com/usercenter/paper/show?paperid=2ff661c121cd86f0b854835bfc9298a5&site=xueshu_se Accessed 6 Sep 2022

Luo YS, Xie DY, Shao SJ et al (2004) Structural parameter of soil under complex stress conditions. Chin J Rock Mech Eng 23:4248–4251. https://doi.org/10.3321/j.issn:1000-6915.2004.24.027

Miao TD (2001) Research status of loess collapsible deformation mechanism, National Loess Academic Conference of Collapsible Loess Committee of China Engineering Construction Standardization Association, Lanzhou, China, Sep. pp.73–82. https://d.wanfangdata.com.cn/conference/6403699 Accessed 6 Sep 2022

Miao TD, Liu ZY, Ren JS (1999) Deformation mechanism and constitutive relation of collapsible loess. Chin J Geotech Eng 21:383–387. https://doi.org/10.3321/j.issn:1000-4548.1999.04.001

Nagaraj TS, Miura N, Chung SG et al (2003) Analysis and assessment of sampling disturbance of soft sensitive clays. Geotechnique 53:679–683. https://doi.org/10.1680/geot.2003.53.7.679

Northey RD, Skemption AW (1952) The sensitivity of clays. Géotechnique 3:30–53. https://doi.org/10.1680/geot.1952.3.1.30

Pal S, Wathugala GW (1999) Disturbed state model for sand-geosynthetic interfaces and application to pull-out tests. Int J Numer Anal Meth Geomech 23:1873–1892. https://doi.org/10.1002/(SICI)1096-9853(19991225)23:15%3c1873::AID-NAG12%3e3.0.CO;2-K

Qian S, Shi J, Ding JW (2015) Variation regularity of stress sensitivity of natural clay during compression. J Southeast Univ (Nat Sci Ed) 45:1180–1184. https://doi.org/10.3969/j.issn.1001-0505.2015.06.028

Qiu GR, Shi YC, Liu HM, Wang P, Zhong XM (2011) Microstructural damage model of seismic subsidence of loess. J Nat Disaster 20:210–215. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD2011&filename=ZRZH201105033&uniplatform=NZKPT&v=vabljFE26YGDAEjGQSZQ8DKLtI9q_YJRxJ7RowbBHa-m3_rqfMmL4r0NVltSrZrh Accessed 6 Jun 2022

Rochelle PL, Sarrailh J, Tavenas F et al (1981) Causes of sampling disturbance and design of a new sampler for sensitive soils. Can Geotech J 18:52–66. https://doi.org/10.1139/t81-006

Rosenqvist TI (1953) Considerations on the sensitivity of Norwegian quick-clays. Géotechnique 3:195–200. https://doi.org/10.1680/geot.1953.3.5.195

Saxena SK, Lastrico RM (1978) Static properties of lightly cemented sand. J Geotech Eng Div 104:1449–1464. https://doi.org/10.1061/AJGEB6.0000728

Seed HB, Chan CK (1959) Structure and strength characteristics of compacted clays. Proceeding Am Soc Civ Eng 85:87–128. https://doi.org/10.1061/JSFEAQ.0000229

Shao SJ, Deng GH (2008) The strength characteristics of loess with different structures and its application in analyzing the earth pressure on loess tunnel. Chin Civil Eng J 41:93–98. https://doi.org/10.3321/j.issn:1000-131X.2008.11.014

Shao SJ, Long JY, Yang S et al (2006) Analysis of structural deformation properties of collapsible loess. Rock Soil Mech 28:24–28. https://doi.org/10.3969/j.issn.1000-7598.2006.10.005

Shao SJ, Zheng W, Wang ZH, Wang S (2010) Structural index of loess and its testing method. Rock Soil Mech 31:15–19. https://doi.org/10.3969/j.issn.1000-7598.2010.01.003

Shao SJ, Zhou FF, Long JY (2004) Structural properties of loess and its quantitative parameter. Chin J Geotech Eng 26:531–536. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD2004&filename=YTGC200404026&uniplatform=NZKPT&v=TsUbBj6AFenUeMZrd5d89yhVhUekoamNZ8ZTfOFGXys_f1Ox_7wswHE9Y9S62XSh Accessed 6 Jun 2022

Shen ZJ (1993a) An elasto-plastic damage model of cemented clays. Chin J Geotech Eng 15:21–28. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD9093&filename=YTGC1993a03002&uniplatform=NZKPT&v=UN_Bie2YiCBF4KuDgNISr4ohbQlS240Z25oQVJnk5hoXyARLbMIYdfNep3cqHBAl Accessed 6 Jun 2022

Shen ZJ (1993b) A nonlinear damage model of structured clay. Hydro-Sci Eng 21:37–45. https://doi.org/10.16198/j.cnki.1009-640x.1993.03.005

Shen ZJ (1996a) Mathematical model of soil structure the core problem of soil mechanics in the 21st century. Chin J Geotech Eng 18:95–97. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD9697&filename=YTGC601.014&uniplatform=NZKPT&v=SKTUXfIFVS0feUWjq561DKOZgb25RIbwQ-yay2HPP6Y1bvvnZdX5iTyGjSW6P2RL Accessed 6 Jun 2022

Shen ZJ (1996b) Generalized suction and unified deformation theory for unsaturated soils. Chin J Geotech Eng 18:1–9. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD9697&filename=YTGC602.000&uniplatform=NZKPT&v=i8CEtDtxqAp1Q04a6gbMYSbG4gl7_c9e_nd_4YYXa440hzuIHA8AzLMbj09SWE2V Accessed 6 Jun 2022

Shen ZJ (1998) Engineering properties of soft soils and design of soft ground. Chin J Geotech Eng 20:100–111. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD9899&filename=YTGC801.024&uniplatform=NZKPT&v=s_FIr3rL3Dx-hoHOr5yJ-40FJqBQmYH14TBRjSJDWCbBQXkihWnt30S4ntvx7bkr Accessed 6 Jun 2022

Shen ZJ (2000) A masonry model for structured clays. Rock Soil Mech 21:1–4. https://doi.org/10.3969/j.issn.1000-7598.2000.01.001

Shen ZJ (2002) Breakage mechanics and double-medium model for geological materials. Hydro-Sci Eng 30:1–6. https://doi.org/10.3969/j.issn.1009-640X.2002.04.001

Shen ZJ, Chen TL (2002) Geotechnical damage mechanics: basic concepts, objectives and tasks, Proceedings of the seventh academic conference of Chinese society of rock mechanics and engineering, pp. 22–25. https://d.wanfangdata.com.cn/conference/3407162 Accessed 6 Sep 2022

Shi B (1996) Quantitative assessment of changes of microstructure for clayey soil in the process of compaction. Chin J Geotech Eng 18:57–62. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD9697&filename=YTGC604.008&uniplatform=NZKPT&v=WmXgIDBRGHo4JV8oYP7Eald0vY168Ygx4F4gSecT8lC1-xP32AYZnYVTbYKsW5vo Accessed 6 Jun 2022

Shi S, Zhang F, Tang KW et al (2021) A nonlinear interface structural damage model between ice crystal and frozen clay soil. Sci Cold Arid Regions 13:150–166. https://doi.org/10.3724/SP.J.1226.2021.20050

Terzaghi K (1960) Theoretical soil mechanics. Geological Publishing House, pp. 469–470. https://xueshu.baidu.com/usercenter/paper/show?paperid=205a6d4a09476b9b65b0a6792915cd8f&site=xueshu_se Accessed 6 Sep 2022

Tovey NK (1973) Quantitative analysis of electron micrographs of soil microstructure. Proceedings of the International Symposium on Soil Structure, pp. 50–57. https://doi.org/10.1016/0148-9062(74)92898-8

Wang GX, Xiao SF, Huang HW et al (2004a) Study on constitutive model of structural clay based on the disturbed state concept. Chin J Solid Mech 25:191–197. https://doi.org/10.3969/j.issn.0254-7805.2004.02.013

Wang LQ, Shao SJ (2015) Quantitative relationship between structural and physical indexes of loess. Chin J Rock Mech Eng 34:4380–4386. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFDLAST2015&filename=YSLX2015S2090&uniplatform=NZKPT&v=eVJiF3ENdKFKXzggEXpjPWoyW-zT0_hs3Phz4QKtiRL4ZsgYb1rO3KpzNdikPUhg Accessed 6 Jun 2022

Wang LZ, Li LL (2006) Poisson ratio of natural structured clays in non-linear elastic model. J Hydraul Eng 51:150–159+165. https://doi.org/10.3321/j.issn:0559-9350.2006.02.004

Wang LZ, Zhao ZY, Li LL (2004b) Non-linear elastic model considering soil structural damage. J Hydraul Eng 49:83–89. https://doi.org/10.3321/j.issn:0559-9350.2004.01.016

Xie DY, Qi JL (1999) Soil structure characteristics and new approach in research on its quantitative parameter. Chin J Geotech Eng 21:651–656. https://doi.org/10.1088/0256-307X/16/9/020

Xie DY, Qi JL, Zhang ZZ (2000) A constitutive law considering soil structural properties. China Civ Eng J 47:35–41. https://doi.org/10.15951/j.tmgcxb.2000.04.008

Xu Y, Guo P, Wang Y et al (2021) Modelling the triaxial compression behavior of loess using the disturbed state concept. Adv Civ Eng Publish Online. https://doi.org/10.1155/2021/6638715

Yang Y, Qi JL, Song CX et al (2007) Experimental study on the application of sensitivity in quantitative study of soil structure. China Earthq Eng J 29:26–29. https://doi.org/10.3969/j.issn.1000-0844.2007.01.005

Yin J (2013) A modified Cam clay model for structured soft clays. Eng Mech 30:190–197. https://doi.org/10.6052/j.issn.1000-4750.2011.05.0318

Yin ZZ (2007) Geotechnical principles. China water resources and Hydropower Press, pp. 116–124. https://xueshu.baidu.com/usercenter/paper/show?paperid=6c8c06f2c53154bd246279e48f80183f&site=xueshu_se Accessed 6 Sep 2022

Yong RN, Sheeran DE (1973) Fabric unit interaction and soil behavior. Proceedings of the International Symposium on Soil Structure. 176–183. https://doi.org/10.1016/0148-9062(74)92944-1

Yuan WN, Fan W, Deng LS, Li WW, Zhou YY (2021) Particle structure characteristics of loess and their effects on shear behavior. J Eng Geol 29:871–878. https://doi.org/10.13544/j.cnki.jeg.2021-0255

Zhang C, Wang W, Zhu Z et al (2021) Mechanical behaviors and damage model of expansive soil admixed with composite materials. Arab J Geosci 14:1–12. https://doi.org/10.1007/s12517-021-07865-y

Zhang CH (1983) Geotechnical properties of two structured clays. Hydro-Sci Eng 11:68–74. https://doi.org/10.16198/j.cnki.1009-640x.1983.04.007

Zhang FG, Jiang MJ (2018) Three-dimensional constitutive model for cemented sands based on micro-mechanism of bond degradation. Chin J Geotech Eng 40:1424–1432. https://doi.org/10.11779/CJGE201808007

Zhang XD, Ying Y, Yu C, et al (2006) Development of soil’s structure study. Proceedings of the 9th National Academic Conference on Rock Mechanics And Engineering 72–78. https://d.wanfangdata.com.cn/conference/6358271 Accessed 6 Sep 2022

Zhang YW, Weng XL, Song ZP, Xie YL (2019) A modified Cam-clay model for structural and anisotropic loess. Rock Soil Mech 40:1030–1038. https://doi.org/10.16285/j.rsm.2017.1909

Zhang ZK (1964) Study on microstructure of loess in China. Acta Geologica Sinica 44:357–369. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD7984&filename=DZXE196403008&uniplatform=NZKPT&v=mH2DSIKRaDebqD3KZU6non60rdW1AV5YoBWd8MH4qiEsjTBkmsz1IVx1EXznNxTj Accessed 6 Jun 2022

Zhao LY, Zhu QZ, Xu WY et al (2016) A unified micromechanics-based damage model for instantaneous and time-dependent behaviors of brittle rocks. Int J Rock Mech Min Sci 84:187–196. https://doi.org/10.1016/j.ijrmms.2016.01.015

Zheng JY, Ge XR, Sun H (2007) Meso analysis for rationality of disturbed state concept theory on utilization of hardening model for softening response depiction. Rock Soil Mech 28:127–132. https://doi.org/10.3969/j.issn.1000-7598.2007.01.024

Zhou C, Shen ZJ, Chen SS et al (2004) A hypoplasticity disturbed state model for structured soils. Chin J Geotech Eng 26:435–435. https://doi.org/10.3321/j.issn:1000-4548.2004.04.001

Zou YJ, Wei CF, Chen HL, Zhou JZ, Wan YZ (2019) Elastic-plastic model for gas-hydrate-bearing soils using disturbed state concept. Rock Soil Mech 40:2653–2662. https://doi.org/10.16285/j.rsm.2018.0445

Download references

The research was funded and supported by the “Postgraduate Research & Practice Innovation Program of Jiangsu Province (No. KYCX19-0419)” and the “Fundamental Research Funds for the Central Universities (No. 2019B73814).”

Author information

Authors and affiliations.

Hohai University, Key Laboratory of Ministry of Education for Geomechanics and Embankment Engineering, Nanjing, 210024, China

Chuanyang Liang, Yuedong Wu, Jian Liu, Dashuo Chen & Yongyang Zhu

Geotechnical Engineering Research Center of Jiangsu Province, Nanjing, 210024, China

You can also search for this author in PubMed   Google Scholar

Contributions

The formal analysis was completed by Liang C.Y., Chen D.S., and Zhu Y.Y.; the original draft preparation was completed by Liang C.Y.; and review and editing were completed by Wu Y.D. and Liu J. All authors have read and agreed to published version of the manuscript.

Corresponding author

Correspondence to Yuedong Wu .

Ethics declarations

Conflict of interest.

The authors declare that they have no competing interests.

Institutional review board statement

Not applicable.

Informed consent statement

Additional information.

Responsible Editor: Zeynal Abiddin Erguler

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Liang, C., Wu, Y., Liu, J. et al. A critical review on soil structure: research methods, structured indexes, and constitutive models. Arab J Geosci 15 , 1509 (2022). https://doi.org/10.1007/s12517-022-10773-4

Download citation

Received : 19 March 2022

Accepted : 27 August 2022

Published : 09 September 2022

DOI : https://doi.org/10.1007/s12517-022-10773-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Soil structure
• Microstructure
• Research methods
• Structured indexes
• Constitutive model
• Find a journal
• Publish with us
• Track your research

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 27 February 2017

The influences of four types of soil on the growth, physiological and biochemical characteristics of Lycoris aurea (L’ Her.) Herb

• Miaohua Quan 1 , 2 , 3 &
• Juan Liang 1  

Scientific Reports volume  7 , Article number:  43284 ( 2017 ) Cite this article

7902 Accesses

36 Citations

Metrics details

• Agroecology

Based on the characteristics of Lycoris aurea (L. aurea ) natural distribution and local soil types, we selected four representative types of soil, including humus soil, sandy soil, garden soil and yellow-brown soil, for conducting the cultivation experiments to investigate key soil factors influencing its growth and development and to select the soil types suitable for cultivating it. We found that there existed significant differences in the contents of mineral elements and the activities of soil enzymes (urease, phosphatase, sucrase and catalase) etc. Among which, the contents of organic matters, alkali-hydrolysable nitrogen, Ca and Mg as well as the activities of soil enzymes in humus soil were the highest ones. In yellow-brown soil, except for Fe, the values of all the other items were the lowest ones. Net photosynthetic rate ( P n ), biomass and lycorine content in humus soil were all the highest ones, which were increased by 31.02, 69.39 and 55.79%, respectively, as compared to those of yellow-brown soil. Stepwise multiple regression analysis and path analysis indicated that alkali-hydrolysable nitrogen, and Ca etc. were key soil factors influencing P n , biomass and lycorine content of L. aurea . Thus, humus soil can be used as medium suitable for artificial cultivation of L. aurea .

Similar content being viewed by others

Maize smart-canopy architecture enhances yield at high densities

Conceptualizing soil fauna effects on labile and stabilized soil organic matter

Microbial competition for phosphorus limits the CO2 response of a mature forest

Introduction.

Lycoris aurea (L’ Her.) Herb ( L. aurea ), also known as Golen Magic Lily , is a perennial herbaceous plant belonging to the genus Lycoris . It is a traditional Chinese medicinal herb plant 1 . Its bulb is rich in more than 10 types of alkaloids, including lycorine, galanthamine and lycoramine etc. and can be used to treat several important diseases such as poliomyelitis sequel, Alzheimer’s disease, and myasthenia Gravis etc. It also possesses certain anti-cancer effects and has been used in treating cancer. Thus, it has important medicinal value 2 . Lycorine belongs to pyrrolo-phenanthridine alkaloid within the class of isoquinoline alkaloids and is one of the major components of the anti-cancer alkaloids present in the plants in the family Amaryllidaceae 3 , 4 . Moreover, L. aurea is also a good groundcover and ornamental flower plant. Its bulb is also rich in starch and galanthus nivalis agglutinin. Thus, it is valuable to be widely applied in many fields, including landscape garden, industry and agriculture 5 . Its bulb contains many types of abundant components such as alkaloids and has relatively higher ornamental value. Thus, there is increasing market demand on L. aurea . However, in the recent years, the deterioration of the ecological environment and the over-artificial digging had led to the shortage of the resources of wild L. aurea . Thus, to initiate the artificial cultivation of L. aurea is of theoretical importance and practical significance for protection and proper utilization of the rare resource of wild L. aurea .

The quality of herb medicines is the comprehensive indicator reflecting certain cultivation technologies and ecological conditions under which the medicinal plants grow. Among which, soil serves as an essential medium for supporting plant growth and development, and thus, it has important influences on the growth, development and the medicinal quality of herb plants 6 . The nutritional elements (e.g. N, P, K, Ca, and Mg etc.) of soil are required for the growth of medicinal plants. These elements are not only the important sources of materials for building up the structures of plant tissues, but also are actively involved in the metabolic activities within plants 7 . For instance, Barlóg 8 reported that magnesium and nitrogenous fertilizers were favorable for the growth, the biosynthesis and accumulation of alkaloids in Lupinus angustifolius . Ca 2+ plays important roles in sequestration and signaling in regulating the activities of chloroplasts 9 , 10 . Plants require K + for important intracellular physiological functions, including photosynthesis and nutrient transport 11 . Soil enzymes are one type of the most important biological components of the soil ecosystem. They play an important role in organic matter decomposition and nutrient cycling 12 . For instance, the hydroxylases (e.g. urease and sucrase etc.) can hydrolyze the macromolecules, such as proteins and polysaccharides, to form the simpler and smaller molecules that are easily absorbed by plants and to accelerate the nitrogen cycle and carbon cycle within the soil ecosystem. The activities of soil enzymes are closely related to soil physicochemical properties, soil types, and fertilizer application, cultivation and other agricultural measures 13 , 14 . Alkaloids are an important class of plant secondary metabolites and the result of the interactions between plants and their environments (both biotic and abiotic) during the long-term evolution process 15 , 16 . Different types of soil possess different textures and physiochemical properties while the demands of different types of medicinal herb plants for suitable soil conditions are quite different. Thus, the types of soil for cultivation of medicinal herb plants should be selected according to the particular physiological requirements of the particular plants 6 , 17 . Currently, most of the studies on L. aurea have mainly focused on the such aspects as biological evolution 18 , 19 , chemical compositions 20 , 21 , 22 , physiology and biochemistry 23 , 24 , 25 , pharmacology and pharmacodynamics 2 , 26 , 27 . In term of cultivation, Zeng et al . 28 reported that L. aurea preferred the environments of shading, humidity, pleasantly cool, ventilation and penetrating light and had no strict requirement for soil type, but it grew better in sandy loam and calcific soil etc. that were fertile, porous, and rich in organic matter. However, the studies on the effects of soil conditions on the growth and development of L. aurea and the accumulation of the medicinal components have been barely available. Thus, it is necessary to select suitable soil conditions for artificial cultivation of L. aurea . In this study, based on the characteristics of its natural distribution patterns, we selected four representative types of soil with different textures and physiochemical properties for conducting the controlled experiments on the cultivation of L. aurea, aiming to study the correlations of the key soil factors with its growth, development and accumulation of medicinal component for providing the experimental basis for artificial cultivation of L. aurea.

Comparison in physicochemical properties among different types of cultivation soil

As shown in Table 1 , there were significant differences in pH value, the contents of soil moisture, organic matter, alkali-hydrolysable nitrogen, rapidly available phosphorus, rapidly available kalium, Ca and Mg etc. in different types of soil. Among which, the contents of organic matter, alkali-hydrolysable nitrogen, Ca and Mg were the richest ones in humus soil, which were 22.64, 7.99, 11.66 and 5.88 times those of yellow-brown soil, the poorest ones. The Fe content in yellow-brown soil was the highest one. The contents of soil moisture, rapidly available phosphorus, rapidly available kalium, Zn, Mn and Cu in garden soil were higher but its Mo content was extremely low. The Mo content in sandy soil was the highest one while the contents of the remaining compositions were between the other types of soil. The humus soil, sandy soil and garden soil were all alkalescent while yellow-brown soil was acidic.

Comparison and analysis on major agronomic trials of L. aurea among different types of cultivation soil

Different types of cultivation soil had different impacts on the major agronomic trials of L. aurea ( Table 2 ). The biomass performances, the bulb diameter, floral axis height, leaf length and leaf width were all the highest ones in humus soil, which were increased by 69.39, 14.50, 11.74, 15.72 and 8.06%, respectively, as compared to those in yellow-brown soil in which their performances were poorest. The differences in these parameters between two types of soil were statistically significant (P < 0.05). Their performances in sandy soil and garden soil were between those of the humus soil and yellow-brown soil.

Comparison and analysis on photosynthetic parameters of L. aurea among different types of cultivation soil

Different types of cultivation soil had different effects on photosynthetic parameters of L. aurea ( Table 3 ). Among which, the net photosynthetic rate ( P n ), chlorophyll content, transpiration rate ( T r ), intercellular CO 2 concentration ( C i ) and stomatal conductance ( G s ) were all the highest ones in humus soil. Except for the lowest T r value in sandy soil, the performances of all the remaining parameters in yellow-brown soil were the poorest ones. Compared to those in yellow-brown soil, P n and chlorophyll content were significantly increased by 31.02 and 25.32%, respectively (P < 0.01).

Comparison and analysis on the activities of soil enzymes among different types of cultivation soil

As shown in Table 4 , there existed differences, to certain extend, in the activities of soil enzymes of L. aurea among four types of cultivation soil. Among which, the activities of soil enzymes in humus soil were the highest ones whereas those in yellow-brown soil were the lowest ones. Compared to those in yellow-brown soil, the activities of urease, sucrase, phosphatase and catalase were significantly increased by 9.63, 1.64, 4.03 and 1.95 times, respectively (P < 0.01). Among the soil enzymes tested, the activities of both urease and sucrase in four types of soil were also higher whereas the activity of catalase was the lowest one.

Comparison and analysis on the lycorine content of L. aurea among different types of cultivation soil

The chromatogram of the bulb sample of L. aurea in cultivation soil were shown in Fig. 1b . The lycorine content of L. aurea in four types of cultivation soil was in the order from high to low as follows: humus soil (1.48 mg g −1 DW) >sandy soil (1.35 mg g −1 DW) >garden soil (1.27 mg g −1 DW) >yellow-brown soil (0.95 mg g −1 DW). Among which, the lycorine content of L. aurea in humus soil was significantly increased by 55.79%, as compared to that in yellow-brown soil (P < 0.01).

*The objective peak of lycorine.

Analysis on key soil factors significantly influencing the medicinal quality of L. aurea

Stepwide multiple regression analysis on soil factors significantly influencing the medicinal quality of l. aurea.

The measured values of the soil nutrients and mineral elements were taken as the soil factor group while the measured values of P n , biomass and lycorine content were taken as the L. aurea medicinal quality group. The soil factors, including pH ( X 1 ), soil moisture ( X 2 ), organic matter ( X 3 ), alkali-hydrolysable nitrogen ( X 4 ), rapidly available phosphorus ( X 5 ), rapidly available kalium ( X 6 ), Ca ( X 7 ), Mn ( X 8 ), Fe ( X 9 ), Na ( X 10 ), Zn ( X 11 ), Cu ( X 12 ), Mn ( X 13 ), and Mo ( X 14 ), were taken as the independent variables, i.e. soil factor group while the leaf P n ( Y 1 ), biomass ( Y 2 ) and lycorine content ( Y 3 ) of L. aurea were taken as the dependent variables, i.e. medicinal quality group. The soil factors were selected with stepwide multiple regression method. The stepwide multiple regression equations between the L. aurea medicinal quality and significant soil factors were formulated ( Table 5 ). As shown in Table 5 , the significant soil factors influencing leaf P n were alkali-hydrolysable nitrogen ( X 4 ) and Mo( X 14 ) while the significant soil factor influencing the biomass was alkali-hydrolysable nitrogen ( X 4 ); the significant soil factors influencing the lycorine content were alkali-hydrolysable nitrogen ( X 4 ), Ca ( X 7 ) and soil moisture ( X 2 ). Thus, the significant soil factors influencing the medicinal quality of L. aurea are alkali-hydrolysable nitrogen, Ca, Mo and soil moisture.

Path analysis on the key soil factors significantly influencing P n , biomass and lycorine content of L. aurea

In order to further confirm the key soil factors significantly influencing P n , biomass and lycorine content of L. aurea, SPSS statistics analysis was conducted on the significant soil factors and the results were presented in Table 6 . As shown in Table 6 , the effects of alkali-hydrolysable nitrogen on P n , biomass and lycorine content of L. aurea were the greatest ones with determination coefficients of 0.927, 0.976 and 0.833, respectively, indicating that among these factors, alkali-hydrolysable nitrogen is the most significant one; The determination coefficient for the effect of Ca on lycorine content of L. aurea was 0.666, which was ranked the second place among the factors tested, indicating that Ca has important effect on the accumulation of lycorine in L. aurea . Mo had little direct effect on leaf P n of L. aurea (R 2  = 0.015); Soil moisture had negative effect on the lycorine content as its determination coefficient was negative, indicating that soil moisture is a limiting factor. Thus, the key soil factors significantly influencing P n , biomass and lycorine content of L. aurea were alkaline-hydrolysable nitrogen and Ca etc.

L. aurea has been used as a traditional Chinese medicinal herb plant to treat several important diseases. However, the increasing demand on L. aurea is contradictory to the limited supply source of wild L. aurea due to the deterioration of its inhabitant environment and over-artificial digging. One of the effective ways to resolve this contradiction is to artificially cultivate it in large-scale. Selection of appropriate types of soil for artificial cultivation of L. aurea is an essential step toward this solution. In the present study, we selected four representative types of soil, i.e. humus soil, sandy soil, garden soil and yellow-brown soil, to investigate their effects on the growth, development and accumulation of alkaloids of L. aurea . We determined that humus soil could be the suitable soil type for artificial cultivation of L. aurea, as supported by several lines of evidence as follows: (a) Humus soil contained the most abundant organic matter, alkali-hydrolysable nitrogen, Ca and Mg; (b) Humus soil displayed the best performances in several important agronomic trials, including biomass, the bulb diameter, floral axis height, leaf length and leaf width; (c) Humus soil contained the highest activities of soil enzymes including urease, sucrase, phosphatase and catalase; and (d) L. aurea grown in humus soil contained the highest content of lycorine, an important alkaloid. Furthermore, we also found that the key soil factors significantly influencing P n , biomass and lycorine content of L. aurea were alkali-hydrolysable nitrogen and Ca etc.

Different types of soil have quite different physicochemical and biological properties, which have substantial effects on the growth, development and the active constituents of medicinal plants 29 . Thus, different plants have different demands for appropriate type(s) of soil. For instance, Liu et al . 6 reported that the types and texture of soil were closely related to the growth and development of medicinal plants and that loam soil was the relatively ideal type of soil for the cultivation of root/stem-types of medicinal plants. The results obtained from this study have indicated that the humus soil displays the best comprehensive performances in both agronomic trials and physiological and biochemical characteristics including P n , biomass and lycorine content of L. aurea grown among four different types of soil tested, followed by those of sandy soil, garden soil, and yellow-brown soil in the order from high to low. The differences in comprehensive performances are partially due to the significant differences in texture, pH value and organic matter etc. among the types of soil tested. In this study, measurement of the general physicochemical properties of cultivation soils revealed that humus soil was rich in organic matter content with its looser texture and better permeability. Humus soil, sandy soil and garden soil were all alkalescent while yellow-brown soil was acidic. The correlation analysis revealed that the soil pH value displayed a positive correlation with the lycorine content of L. aurea ( Supplementary Information ), indicating that the alkalescent soil is favorable for the accumulation of lycorine of L. aurea . This result was consistent with that obtained by Chao et al . 30 , who reported that the alkaline soil in North China was favorable for the accumulation of alkaloids while the acidic soil and yellow-brown soil in South China were unfavorable for the accumulation of alkaloids. Furthermore, path analysis indicated that value for the direct effect of soil moisture on the lycorine content was negative, implying that high soil moisture content may be unfavorable for the accumulation of alkaloids such as lycorine in L. aurea . This result was consistent with those obtained by El-Shazly et al . 16 and Bustamante et al . 31 , who reported that drought environment could enhance the biosynthesis of plant alkaloids. The rich organic matter that was constantly decomposed in humus soil can provide the stable supply of nitrogen nutrients etc. for the growth of plants. The physicochemical properties of humus soil, i.e. rich organic matter, alkalescent pH value, the looser texture and thus, lower soil moisture, are favorable for the growth, biosynthesis and accumulation of alkaloids such as lycorine of L. aurea .

Deficiency or shortage of any of the nutritional elements (e.g. N, P, K, Ca, and Mg etc.) will certainly affect the normal growth and development as well as the internal and external qualities of plants 7 . Nitrogen is the most important element among all the nutritional elements required by plants 32 . For instance, the biosynthetic processes of alkaloids require nitrogen involvement. The increased, adequate or surplus nitrogen source was found to be favorable for the biosynthesis of alkaloids in Larkspur 33 . The present study indicated that the contents of alkaline-hydrolysable nitrogen and Ca in humus soil were higher than those in the poorest yellow-brown soil. Its biomass and the lycorine content were increased substantially. Stepwide multiple regression analysis and path analysis indicated that alkaline-hydrolysable nitrogen was the most important soil factor, and Ca is the secondary factor, implying that the higher contents of alkaline-hydrolysable nitrogen and Ca in humus soil are favorable not only for the growth and development of L. aurea but also for the accumulation of alkaloids including lycorine. These results also further confirm that nitrogen nutrient and Ca are the important environment factors stimulating plant growth and the biosynthesis of alkaloids. NO 3 -N and NH 4 -N are two major forms of nitrogen nutrients that are absorbed and utilized by plants. The effectiveness of these two forms of nitrogen element on the growth and development of plants are dependent on the types of plants, the concentrations of NO 3 -N and NH 4 -N and their ratio. The absorption, transport and assimilation during the metabolism processes and the effects on the growth, development and physiological processes are significantly different 34 . During the cultivation of crops, nitrogen nutrient and water supply are two very important controlling factors. Thus, how to maximize the effects of nitrogen nutrients, water and Ca 2+ on stimulation of the growth, development, and the accumulation of alkaloids such as lycorine of L. aurea and the underlying regulatory mechanisms remain to be further investigated.

The microorganisms inhabiting in soil (e.g. bacteria and fungi etc.) play extremely important roles in the formation of soil fertility and the inter-conversion of plant nutrients and also affect the permeability of root cells and root metabolism. They can modify the root secretion and change the rhizosphere nutrients 35 , 36 . In the present study, we found that among four types of soil tested, there existed significant differences in the activities of soil enzymes, including urease and sucrase. Among four types of soil, the humus soil was rich in nutrients, such as organic matter, The activities of its soil enzymes were also higher. But in the poorest yellow-brown soil, the mean activities of soil enzymes were lower. The higher activities of these soil enzymes in the humus soil may be mainly attributed to the higher abundance and activities of soil microorganisms, likely due to the favorable soil conditions for their growth. The high activities of these soil enzymes and active soil microorganisms can continuously drive the degradation and mineralization of soil organic matter and provide the stable supply of nitrogen nutrients etc. for the growth of plants and thus, they are favorable for the growth, development and formation and accumulation of alkaloids, including lycorine of medicinal plants.

In this study, we found that among four representative types of soil tested, the humus soil displayed the best comprehensive performances in terms of the agronomic, physiological and biochemical characteristics including P n , biomass and lycorine content of L. aurea , followed by those of sandy soil, garden soil, and yellow-brown soil in the order from high to low. This humus soil contained higher levels of organic matter, the activities of soil enzymes and mineral elements such as alkali-hydrolysable nitrogen, rapidly available phosphorus, and Ca etc. Its texture was looser and its permeability was quite good. Thus, this type of humus soil was suitable for artificial cultivation of L. aurea . Stepwise multiple regression analysis and path analysis indicated that the key soil factors significantly influencing P n , biomass and lycorine content of L. aurea were alkaline-hydrolysable nitrogen and Ca etc. Soil moisture was a limiting factor, implying that high soil moisture content may be unfavorable for the accumulation of lycorine of L. aurea . Our findings provide not only the guidance for conducting artificial cultivation of L.aurea, but also the methods for accumulation of alkaloids including lycorine of medicinal plants.

Materials and Methods

Materials and cultivation plots.

The material of Lycoris aurea (L’Her.) Herb is an acclimated cultivar original from Huaihau, Hunan Province, China. Given that different medicinal plants have different requirements for soil types suitable for their growth and development, in this study, based on the characteristics of the natural distribution of L. aurea , we selected four representative soil types with quite different textures and physicochemical properties, i.e. humus soil (looser texture and rich in nutrition), sandy soil (loose texture), garden soil (moderate texture) and yellow-brown soil (dense texture). These four types of soil were collected from the original ecological environment in August 2012 and placed on the same experimental field under the same climate conditions for artificial cultivation of L. aurea . This experiment was conducted in Botanical Garden of Huaihua University, Hunan, China. The coordinates of geographical location are 110°01’ E, 27°35’ N, and the level above sea is 267 m. The climate in this location belongs to subtropical humid monsoon. The mean annual atmosphere temperature was 16.9 °C and the mean annual rainfall was 1358.6 mm. A number of bulbs with uniform size were selected and cultivated in the spacing (20 × 20 cm) in the experimental plots. The area of the plot was 1 m 2 . Each experiment was repeated three times. All the other conditions, such as water and light, were the same. The plots were managed with conventional management. The experimental period was from August 2012 to December 2015. This study aimed to investigate the effects of different soil types on the growth, development and accumulation of alkaloids of L. aurea for finding out the appropriate soil type(s) and for providing the reference basis for artificial culture of L. aurea.

Experimental Methods

Measurement of the general physicochemical properties of cultivation soil, soil sampling and measurement of the contents of elements.

The soil samples (0–20 cm depth) were collected from the experimental plots in December 2014. The samples were air-dried at room temperature. After passed through a 2 mm sieve, the soil samples were used for analysis. The contents of elements such as Ca, Mg, Fe and Mn etc. in the samples were determined with Inductively Coupled Plasma-Mass Spectrometry (Agilent7700, USA) in Hunan Food Test and Analysis Center, according to Agricultural Industry Standards or National Quality Standards NY/T 87–1988 and NY/T 296–1995 etc 37 .

Measurement of other factors of the soil samples

The contents of alkali-hydrolysable nitrogen, rapidly available phosphorus, rapidly available kalium were determined with diffusion method, NaHCO 3 extraction-Mo-Sb colorimetric method, and NH 4 OAc extraction-flame spectrophotometry, respectively. The organic matters were determined with potassium dichromate oxidation heating method. The soil water content was measured with oven-drying methd 38 . The pH value was determined by using of PHS-3C precision acidity meter.

Measurement of major agronomic trails

Because L. aurea has the following characteristics: its flowers and leaves do not appear at the same time and it has summer dormancy. Its flowers blossom out in August, its leaf development starts in September and its vigorous growth stage is in December. Thus, the measurements of its agronomic trails in different types of cultivation soil were conducted in two stages. Its floral axis height was measured in August 2014 while its morphological parameters, including leaf length, leaf width and the bulb size were measured in December of the same year. The entire plants, including roots, leaves and bulb, were collected and dried by baking in oven to the constant weight and its biomass was weighted. The bulb samples were ground into powder with grinder (60 meshes) and stored under dry condition for subsequent analysis. Five healthy and strong plants were randomly selected from each sampling site and used as the measured subjects. Three repeat experiments were set.

Measurement of photosynthetic characteristics

Photosynthetic parameters, such as leaf P n , T r , G s , and C i, and other physiological factors were measured by using of Li- 6400 portable photosynthesis measurement system with a red-blue light source ( Li-cor , USA) under saturating light of 1 000 μmol m −2 s −1 . The net photosynthetic rates were measured at least 30 min after the attainment of the temperature 39 . Given that an “afternoon relaxation of photosynthesis” phenomenon exists in L. aurea , measurement of photosynthesis was conducted in morning time. The same positions of the leaves of five randomly selected L. aurea were used to measure P n during 9:00–11:00 am in December 2014 when the plant was in nutrition period 24 . Immediately after that, the corresponding leaves were collected and extracted in 95% ethanol and measured by spectrophotometric method (DU-800 spectrophotometer, Beckman Coulter, Inc.) at the wavelengths 665 and 649 nm. Contents of chlorophyll a and b were calculated by using the method of Lichtenthaler 40 .

Assays of activities of soil enzymes

In the middle 10 days of each month from January to December 2013, the soil samples at 2 cm below the surface soil nearby the root system of L.aurea were collected from various sampling sites. The enzymatic activities in these soil samples were assayed with the method reported by Guan et al . 41 as follows: Urease activity was assayed with indophenol blue colorimetric method and expressed as the amount (in mg) of NH 3 -N/g of dried soil produced within 24 h incubation at 37 °C. Sucrase activity was assayed with 3,5-dinitrosalicylic acid colorimetry and expressed as amount (in mg) of glucose produced within 24 h incubation at 37 °C. Phosphotase activity was assayed with alkaline phosphatase colorimetric method and expressed as the amount (in mg) of phenol produced/g of dried soil within 24 h incubation at 37 °C. Catalase activity was assayed with potassium permanganate titration method and expressed as the volume (in mL) of consumption of 0.1 N KMnO 4 /g of dried soil within 20 min incubation at 37 °C. The mean annual activity of each of these enzymes was calculated.

Measurement of lycorine content

Conditions used in assays with high-performance liquid chromatography (hplc).

HPLC was used to measure of lycorine content. The chromatographic conditions used were set as following: 20 μL of samples or standards were injected into the Agilent Eclipse XDB-C18 column at 25 °C and eluted with mobile phase of 0.1% phosphoric acid:methanol of 65:35 at flow rate of 1.0 mL/min. The detection wavelength was at 288 nm 24 .

Linear regression

Lycorine content was measured with a LC-20AT HPLC (Shimadzu, Japan). 20 μL of lycorine standard (HPLC ≥ 98%, National Institutes for Food and Drug Control) solutions at concentrations of 20.0, 40.0, 60.0, 80.0 and 100.0 μg·mL −1 were injected into the column and separated under the above conditions. The equation of linear regression was as follows: y  = 20648x + 11934, R 2  = 0.9996. The chromatogram of the lycorine reference substance was shown in Fig. 1a . Its retention time of the objective peak was 5.833 min.

Sample preparation and measurement of lycorine content

The sieved samples of the bulbs were dried at 65 °C to constant weight. The sample was extracted with Soxhlet method 24 . The sample solution was separated as described above and lycorine content was calculated using the peak area according to the linear regression equation.

Data analysis

Data analysis was performed with Statistical Product and Service Solutions(SPSS). The correlation analysis was conducted with Pearson correlation coefficient method. The key soil factors influencing P n , biomass and lycorine content of L. aurea were determined with multiple regression analysis 42 and path analysis 43 , 44 . The multiple regression analysis was performed with a stepwide method to sequentially include variables in the model, using the following pre-established criteria: inclusion of a variable when its level of significance was <0.05 (p in <0.05), exclusion of a variable when its level of significance was >0.10. This method selects significant variables one by one, and every time a new variable is included, the rest of those previously selected are examined to check if any of them may be removed from the model. The significance of coefficients was evaluated by a t-test. A p-value < 0.05 was considered significant.

Additional Information

How to cite this article : Quan, M.H. and Liang, J. The influences of four types of soil on the growth, physiological and biochemical characteristics of Lycoris aurea (L’ Her.) Herb. Sci. Rep. 7 , 43284; doi: 10.1038/srep43284 (2017).

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Hsu, Y., Hu, Z. B., Huang, X. L. & Fan G. J. Lycoris in Flora Reipublicae Popularis Sinicae 1st edn, Vol. 16 (eds Pei, C. et al.), 16–27 (Science press, 1985).

Google Scholar  

Ji, Y. B., Xin, G. S., Qu, Z. Y., Zou, X. & Yu, M. Research progress on chemical constituents and pharmacological effects of alkaloids from plants of Lycoris Herb. Chinese Traditional and Herbal Drugs 47 , 157–164 (2016).

CAS   Google Scholar  

Qin, K. M., Li, X., Xu, Z. & Cai, B. C. A survey of the studies on pharmacological effects of lycorine and its derivatives. Journal of Beijing Union University (Natural Sciences) 23 , 6–10 (2009).

Mcnulty, J., Nair, J. J., Little, J. R. L., Brennan, J. D. & Bastida, J. Structure–activity studies on acetylcholinesterase inhibition in the lycorine series of amaryllidaceae alkaloids. Bioorganic & Medicinal Chemistry Letters 20 , 5290–5294 (2010).

Yang, Z. L. & Tan, Z. F. Utilization of Lycoris resource and suggestion on propagation-studying. Economic Forest Researches 21 , 97–99 (2003).

Liu, Y., Zhang, Z. S., He, Y. L., Zhang, B. G. & Li, X. E. Quality of crude traditional Chinese drugs and ecological environment. Modernization of Traditional Chinese Medicine and Materia Materia-World Science and Technology 9 , 65–69 (2007).

Al-Humaid, A. I. Effects of compound fertilization on growth and alkaloids of datura (Daturainnoxia Mill.) plants. Journal of Plant Nutrition 27 , 2203–2219 (2005).

Barlóg, P. K. Effect of magnesium and nitrogenous fertilisers on the growth and alkaloid content in Lupinus Aangustifolius L. Australian Journal of Agricultural Research 53 , 671–676 (2002).

Brand, J. J. & Becker, D. W. Evidence for direct roles of calcium in photosynthesis. Journal of Bioenergetics & Biomembranes 16 , 239–249 (1984).

Rocha, A. G. & Vothknecht, U. C. The role of calcium in chloroplasts – an intriguing and unresolved puzzle. Protoplasma 249 , 957–966 (2012).

CAS   PubMed   Google Scholar  

Jin, S. H. et al. Effects of potassium supply on limitations of photosynthesis by mesophyll diffusion conductance in Carya cathayensis . Tree Physiology 31 , 1142–1151 (2011).

Wang, L. D. et al. Review: Progress of soil enzymology. Soils 48 , 12–21 (2016).

Han, F. G. et al. Analysis of relationship between soil enzymes activities and fertilities in the field of grain for green in downstream of the Shiyang River. Chinese Journal of Soil Science 45 , 1396–1401 (2014).

Tamura, K., Dudley, J., Nei, M. & Kumar, S. MEGA4: Molecular evolutionary genetics analysis (MEGA) software version 4.0. Molecular Biology and Evolution 24 , 1596–1599 (2007).

Ainouche, A., Greinwald, R., Witte, L. & Huon, A. Seed alkaloid composition of Lupinus tassilicus Maire (Fabaceae: Genisteae) and comparison with its related rough seeded lupin species . Biochemical Systematics & Ecology 24 , 405–414 (1996).

El-Shazly, A. M., Dora, G. & Wink, M. Alkaloids of Haloxylon salicornicum (Moq.) Bunge ex Boiss (Chenopodiaceae). Pharmazie 60 , 949–952 (2005).

Xia, G. J. et al. Influence of different soil types on reed growth and photosynthesis characteristics. Acta Botanica Boreali-Occidentalia Sinica 34 , 1252–1258 (2014).

Chang, Y. C., Choutou, S. & Meichu, C. Variations in ribosomal RNA gene Loci in Spider Lily (Lycoris spp.). Journal of the American Society for Horticultural Science 134 , 567–573 (2009).

Quan, M. H., Ou, L. J., She, C. W., Chen, D. M. & Ye, W. Analysis of interspecific relationships in Lycoris Herb based on trn H- psb A sequence. Acta Horticulturae Sinica 38 ,1589–1594 (2011).

Yagi, F., Noguchi, S., Suzuki, S., Tadera, K. & Goldstein, I. J. Purification and characterization of isolectins from Lycoris aurea . Plant & Cell Physiology 34 , 1267–1274 (1993).

Liu, X. D. et al. Galantamine content determination of different organs of the artificial cultivation Lycoris aurea from different places. Journal of Hunan Univ. of CM 35 , 31–33 (2015).

CAS   ADS   Google Scholar  

Zhao, Y. N., Song, K., Peng, S. & Xiao, Z. B. Purification of lycorine from Lycoris aurea using zeolite molecular sieve. Natural product research and development 28 , 289–292, 299 (2016).

Meng, P. et al. Growth and photosynthetic responses of three Lycoris species to levels of irradiance. Hortscience 43 , 134–137 (2008).

Quan, M. H. et al. Photosynthetic characteristics of Lycoris aurea and monthly dynamics of alkaloid contents in its bulbs. African Journal of Biotechnology 11 , 3686–3691 (2012).

Xu, S. et al. Physiological and antioxidant parameters in Two Lycoris species as influenced by water deficit stress. Hortscience 50 , 1702–1708 (2015).

Evidente, A. et al. Biological evaluation of structurally diverse amaryllidaceae alkaloids and their synthetic derivatives: discovery of novel leads for anticancer drug design. Planta Medica 75 , 501–507 (2009).

CAS   PubMed   PubMed Central   Google Scholar  

Liu, R. F. et al. Lycorine hydrochloride inhibits metastatic melanoma cell-dominant vasculogenic mimicry. Pigment Cell & Melanoma Research 25 , 630–638 (2012).

Zeng, F. Z., Yang, Y. K., Xiang, J. Q. & Yin, H. Q. Artificial cultivation technology of Lycoris aurea . Modern Chinese Medicine 16 , 631–632 (2014).

Li Q. L. & Xiao, H. L. The interactions of soil properties and biochemical factors with plant allelopathy. Ecology and Environmental Sciences 21 , 2031–2036 (2012).

Chao, Z., Wang, E. Z. & Zhou, X. J. Relationship between alkaloid contents and growth environment of motherwort (Herba Leonuri ). Journal of Southern Medical University 20 , 504–506 (2000).

Bustamante, R. O., Chacon, P. & Ninmeyer, H. M. Patterns of chemical defences in plants: an analysis of the vascular flora of Chile. Chemoecology 16 , 145–151 (2006).

Chen, B. et al. Effect of N fertilization rate on soil alkali-hydrolyzable N, subtending leaf N concentration, fiber yield, and quality of cotton. Crop Journal 4 , 323–330 (2016).

Ralphs, M. H. & Gardner, D. R. Distribution of norditerpene alkaloid in tall Larkspur plant parts through the growing season. Journal of Chemical Ecology 29 , 2013–2021 (2003).

Rosen, C. J., Allan, D. L. & Luby, J. J. Nitrogen form and solution pH influence growth and nutrition of two Vaccinium clones. Journal of the American Society for Horticultural Science 115 , 83–89 (1990).

Whipps, J. M. Microbial interactions and biocontrol in the rhizosphere . Journal of Experimental Botany 52 ,487–511 (2001).

Compant, S., Duffy, B., Nowak, J., Clément, C. & Barka, E. A. Use of plant growth-promoting bacteria for biocontrol of plant diseases: principles, mechanisms of action, and future prospects. Applied & Environmental Microbiology 71 , 4951–4959 (2005).

Xu, J. et al. Study on the major and trace elements in soil of Yunnan farmland. Agricultural Science & Technology 15 , 2141–2144 (2014).

Bao, S. D. Analysis of Soil Agrochemistry , 22–108 (China Agriculture Press, 2000).

Hanba, Y. T., Kogami, H. & Terashima, I. The effect of growth irradiance on leaf anatomy and photosynthesis in Acer species differing in light adaptation. Plant Cell & Environment 25 , 1021–1030 (2002).

Lichtenthaler, H. K. Chlorophylls and carotenoids: Pigments of photosynthetic biomembranes. Methods in Enzymology 148 , 350–382 (1987).

Guan, S. Y., Zhang, D. & Zhang, Z. Soil Enzyme and its Research Methods , 274–323 (China Agriculture Press, 1986).

Menéndez, R., Nauffal, D. & Cremades, M. J. Prognostic factors in restoration of pulmonary flow after submassive pulmonary embolism: a multiple regression analysis. European Respiratory Journal 11 , 560–564 (1998).

PubMed   Google Scholar  

Xu, C. H., Zhang, H., Zhang, L. & Kang, Y. R. Factors influencing photosynthesis of three typical plant species in Beishan Mountain of Lanzhou based on path analysis. Chinese Journal of Ecology 34 , 1289–1294 (2015).

Moghaddam, M., Ehdaie, B. & Waines, J. Genetic variation and interrelationships of agronomic characters in landraces of bread wheat from southeastern Iran. Euphytica 95 , 361–369 (1997).

Download references

Acknowledgements

This work was supported by National Natural Science Foundation of China (No. 31470403), Innovation Platform Open Fund in Higher Education Institutions of Hunan Province (No. 11K051) and the Foundation of Hunan Key Discipline Construction Projects. We sincerely thank Dr. L.J. Ou, A.P.A.N. He and A.P.S.H. Li for their helps in the experiments, Prof. X.J. Wu and Prof. C.W. She for the helpful discussions and constructive suggestions.

Author information

Authors and affiliations.

College of Biological and Food Engineering, Huaihua University, Huaihua, 418008, Hunan, P. R. China

Miaohua Quan & Juan Liang

Key Laboratory of Hunan Province for Study and Utilization of Ethnic Medicinal Plant Resources, Huaihua, 418008, Hunan, P. R. China

Miaohua Quan

Key Laboratory of Hunan Higher Education for Hunan-western Medicinal Plant and Ethnobotany, Huaihua, 418008, Hunan, P. R. China

You can also search for this author in PubMed   Google Scholar

Contributions

M.H.Q. designed the study, analyzed data and wrote the paper; J.L. performed experiments and analyzed the data. All the authors reviewed and approved the manuscript.

Corresponding author

Correspondence to Miaohua Quan .

Ethics declarations

Competing interests.

The authors declare no competing financial interests.

Supplementary information

Supplementary information (doc 53 kb), rights and permissions.

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Reprints and permissions

About this article

Cite this article.

Quan, M., Liang, J. The influences of four types of soil on the growth, physiological and biochemical characteristics of Lycoris aurea (L’ Her.) Herb. Sci Rep 7 , 43284 (2017). https://doi.org/10.1038/srep43284

Download citation

Received : 19 May 2016

Accepted : 24 January 2017

Published : 27 February 2017

DOI : https://doi.org/10.1038/srep43284

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Potato tillage method is associated with soil microbial communities, soil chemical properties, and potato yield.

Journal of Microbiology (2022)

Effects of Vermicompost and Vermicompost Leachate on the Biochemical and Physiological Response of Withania somnifera (L.) Dunal

• Amandeep Kaur
• Pratap Kumar Pati
• Arvinder Kaur

Journal of Soil Science and Plant Nutrition (2022)

Structural and functional changes in soil bacterial communities by drifting spray application of a commercial red seaweed extract as revealed by metagenomics

• Khanjan Trivedi
• Ranjeet Kumar

Archives of Microbiology (2022)

Protists as main indicators and determinants of plant performance

• Stefan Geisen

Microbiome (2021)

Mixed evidence for plant–soil feedbacks in forest invasions

Oecologia (2020)

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List

Pesticides: Behavior in Agricultural Soil and Plants

Associated data.

The data presented in this study are not available.

This review considers potential approaches to solve an important problem concerning the impact of applied pesticides of various classes on living organisms, mainly agricultural crops used as food. We used the method of multi-residual determination of several pesticides in agricultural food products with its practical application for estimating pesticides in real products and in model experiments. The distribution of the pesticide between the components of the soil-plant system was studied with a pesticide of the sulfonylureas class, i.e., rimsulfuron. Autoradiography showed that rimsulfuron inhibits the development of plants considered as weeds. Cereals are less susceptible to the effects of pesticides such as acetamiprid, flumetsulam and florasulam, while the development of legume shoots was inhibited with subsequent plant death.

1. Introduction

On the global scale, the damage of agricultural crops is caused by approximately 50,000 species of plant pathogens, 9000 species of insects and mites and 8000 species of pest plants [ 1 , 2 , 3 ]. This damage to crops in the form of crop loss includes an estimated −13% due to plant pathogens, −14% due to pest insects and −13% due to pest plants [ 4 ]. Furthermore, pesticides are indispensable for growing plants, especially for growing economically important crops. According to predictive research, pesticides protect about a third of the world agricultural production. [ 5 ]. As is shown in the recent data, about 2 million tons of pesticides are used, including herbicides −47.5%, insecticides −29.5%, fungicides −17.5% and other pesticides −5.5% [ 6 , 7 ].

Pesticides are chemical substances intended for fighting insects, pests, fungi, rodents and microbes. A lot of pesticides are found to be harmful to the health of humans and animals or dangerous for the environment.

The Food and Agriculture Organization of the United Nations (FAO) gives the following definition of pesticides: “Pesticide means any substance or mixture of substances or biological ingredients intended for repelling, destroying or controlling any pest or regulating plant growth” [ 8 , 9 ].

The term pesticide implies more than just a Plant Protection Product (PPP) [ 10 ]. Plant Protection Products are “pesticides”, which protect crops or desirable and useful plants. They contain at least one active substance and have one of the following functions:

• To protect plants or plant products from pests/diseases before or after the harvest (e.g., fungicides, insecticides, molluscicides, nematocides, rodenticides);
• To influence processes of plant life (e.g., substances affecting their growth, with the exception of nutrients);
• To preserve plant products (e.g., fumigants);
• To destroy undesirable plants and their parts or to prevent their growth (e.g., defoliants);
• To prevent undesirable growth of plants (e.g., herbicides).

The problem of food contamination and food ingredients by residual amounts of pesticides has been urgent for several decades. At present, most agricultural products are being produced according to technologies which rely on the wide application of pesticides. In spite of the efforts of scientists and farmers, “ecological agriculture” cannot provide a necessary amount of food for the world population.

Taking into account the fact that about 80–85% of residual amounts of pesticides (RAP) enter the human organism with food, special attention is paid to this branch of industry aimed at providing high-quality food for the population [ 1 , 2 , 11 ].

Since not all countries in the world can supply their population with sufficient agricultural raw materials, as well as with the products of their processing, of special significance are the issues concerning the quality of imported food, including imports from developing countries.

To minimize the risk to human health caused by the residual amounts of pesticides in agricultural products, it is necessary to have vast and reliable information about the level of pollution which could allow one to develop measures to guarantee food safety for the population.

There is a large list of pesticides used in the exporting country; this list also includes combinations of two, three or more active substances in various compositions. Various chemical substances for plant protection are applied several times during the crop growing period. All these above-mentioned factors—as well as the geographical location of the main importing countries, soil and climatic conditions (high temperature, humidity, precipitation, intensive solar radiation), which greatly correlate with the pesticide detoxification rate—influence the RAP level in plant products [ 11 , 12 , 13 ].

The regulations and science of pesticide residues permeate every facet of the food industry, from the farm to the consumer. Comprehensive understanding of the regulatory climate, both domestically and internationally, ensures that the proper precautions are taken to mitigate regulatory and safety risks associated with pesticide use. Furthermore, evaluating pesticide testing screens and capabilities offered by laboratories encourages meaningful results that represent ingredients used for food products at home and abroad. [ 14 ].

The implementation of enforcement measures on providing the hygiene safety of pesticides in the consumer market is closely connected with the creation and validation of identification methods and quantitative estimation of their residual amounts.

The aim of the present review is to study the impact of pesticides on the system of soil and agricultural plants in order to reveal possible negative factors for the resilience of plants used as food for the population.

2. Multi-Residual Methods to Determine Pesticides in Agricultural Products

Taking into account the fact that in agriculture, a big list of chemicals is used for plant protection from insects, pests and fungi diseases, as well as for growth stimulation, the control of the composition of these chemicals is a task of major importance. Moreover, if there is a possibility to determine the chemicals used in one sample, this can be a reference in terms of the composition control with the subsequent estimation of their individual and combined impact on living organisms.

Various sample preparation procedures have been suggested due to a great variety of the pesticides used and inherent matrix complexity. Here, a rather high content of lipids in certain grain samples is said to negatively interfere with the analysis [ 11 , 12 , 13 , 15 ].

In recent years, the QuEChERS method (quick, easy, cheap, reliable and safe) has been developed which deserves attention for allowing the determination of residual amounts of pesticides in various matrices. The QuEChERS method was suggested in 2003 [ 16 ] for estimating residual amounts of pesticides in foods which do not contain fat, particularly fruit and vegetables. The method based on the initial extraction with acetonitrile and a subsequent stage of purification using the dispersive solid-state extraction (DSPE) decreases the volume of samples and solvents as compared to the traditional techniques based on the redistribution with a liquid. This method is simple, fast and less expensive.

Forty active substances in pesticides were selected for the research (including a number of metabolites), with the substances belonging to different chemical groups (neonicotinoids, tryasols, imidazoles, pyrethroids, organophosphorus compounds, strobilurins, etc.) [ 17 , 18 ].

The identification was performed taking into account the retention time, presence of characteristic ions in the mass spectra (GC-MS method) and product ions (LC-MS/MS) and the area ratio of the chromatographic peaks, which are related to the characteristic ions.

To choose the conditions for detection (the LC-MS/MS method), optimization was implemented for 23 active substances ( Figure 1 ), i.e., scanning in the positive and negative ionization mode using a source of electrostatic spraying. For each analyte, several product ions were obtained, formed after the destruction of the parent ion; the compounds were identified by the multiple reaction monitoring (mass-transfer).

Chromatogram of the model solution of 23 pesticides with the concentration of 0.1 µg·ml −1 , the electrospray ionization source (ESI) in the positive ion mode (TIC—total ion current): 1—omethoate, 2—thiamethoxam, 3—imidacloprid, 4—clothianidine, 5—flumetsulam, 6—dimethoate, 7—acetamiprid, 8—rimsulfuron, 9—thiacloprid, 10—florasulam, 11—thiabendazole, 12—carboxim, 13—spiroxamine, 14—fluxapiroxade, 15—fluopyram, 16—epoxiconazole, 17—iprodione, 18—kresoxym-methil, 19—penconazole, 20—pyraclostrobin, 21—prochloraz, 22—trifloxystrobin, 23—ipconazole. On the X axis is the time (min), on the Y axis is the peak intensity.

The method of gas chromatography-mass spectrometry was used to estimate the residual amounts of 18 compounds ( Figure 2 ). In the first research stage, in order to identify the whole list of substances, with all of them being present, use was made of the full scanning mode (by full ion current) in the range from 50 to 500 atomic mass units with the automatic library search “NIST”.

Chromatogram of the model solution of 18 pesticides with the concentration of 0.1 µg·ml −1 . The Selected Ion Mode (SIM): 1—diazinon, 2—chlorothalonil, 3—mefenoxam, 4—malathion, 5—cyprodinin, 6—fipronil, 7—fludioxanil, 8—flutriafol, 9—prothioconazole-desthio, 10—fipronil sulfone, 11—cyproconazole, 12—propiconazole, 13—tebuconazole, 14—epoxiconazole, 15—bifentrin, 16—lambda-cyhalothrin, 17—alpha-cyperomenthrin, 18—esfenvalerate. On the X axis is the time (min), on the Y axis is the peak intensity.

The application of the sample preparation method for QuEChERS excluded a number of active substances from the analysis; these substances, according to their structure, physical and chemical properties and ability for metabolic degradation with the formation of numerous metabolites, cannot be analyzed by the given technique.

It is worth noting that the original method QuEChERS [ 15 , 16 ] is only slightly different from the main procedure being applied at present to matrices with the low (2–20%) or high (>20%) fat content. The main difference is in the purification stage since even a small amount of fat is also co-extracted from the matrix and can affect the subsequent chromatographic analysis [ 17 , 18 ].

The method for preparing QuEChERS samples is very widely developed both for analyzing new media (of different origin, composition, physical and chemical properties) and for studying numerous combinations of pesticides, followed by GC-MS and LC-MS/MS detection [ 19 , 20 , 21 ].

For example, the developed methods of multi-residual determination of pesticides were also tested in estimating the contamination of grain crops by residual amounts of pesticides. The attention was focused on wheat, maize and rice, the grain crops which amount to 88% of the world grain production [ 22 ]; these methods were also successfully applied to determine pesticides in a number of tropical and dried fruit.

3. Herbicide-Absorption and Translocation in the Soil-Plants Systems

Pesticides can be characterized by various degrees of toxicity for target and non-target organisms [ 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. Due to their cumulative properties, many pesticides [ 32 , 33 , 34 , 35 ] circulate in ecosystems, can be accumulated by many living organisms and even migrate through them along food chains. For recognizing the impact of a pesticide, certain biological specimens, individuals, species and communities are predominantly used as models for estimating harmful effects. Pesticides can penetrate into an organism (1) depending on the species and peculiarities of metabolism, and also, (2) depending on the level of susceptibility to toxins [ 36 , 37 ]. However, if a chemical substance has already penetrated into an organism, it must be able to fight it in order to neutralize or minimize its harmful impact by means of biotransformation, conjugation, isolation and/or release into the environment or by means of a combination of the above mechanisms. All these efforts are directed towards preventing or minimizing the harm for the organism [ 38 , 39 ].

Many agricultural areas with humic-sandy and loamy-sandy soils are also used for the extraction of water for drinking water supply. The pesticide concentrations per depth in soil are highly variable due to local differences in transport, adsorption and transformation. Measurements both in the subsoil and in the upper groundwater are scarce, also due to sampling problems. The methods of pesticide analysis in soil samples are often not sensitive enough to measure micro concentrations of the substances [ 40 ].

A literature review of tests of four simulation models for pesticides in the soil-plant system was presented by Van den Bosch and Boesten [ 41 ]. The frequently occurring shortcomings in the experimental data sets used for the tests are the following:

• Poor characterization of soil profiles and compositions of the layers.
• Weather conditions not quantified (rainfall/irrigation pattern).
• No information on the crop growth during the experiment (soil cover/leaf area index, root development).
• Few soil-sampling field experiments, low number of samples and too shallow soil sampling (only the top layer).
• Too short duration of the experiments to study deeper movement.
• Too low sensitivity of the concentration measurements in soil (high determination limit).
• No site-specific measurements on adsorption and rate of transformation in soil as model inputs (e.g., data taken from handbooks and databases).
• Pesticide uptake by the plant roots set to zero (because of the lack of data) [ 42 , 43 ].

The research was carried out directly with rimsulfuron and with a labeled 14 C preparation [ 44 ].

Two species of plants were used in the experiments: two-week old shoots of Sinapis arvensis L. as weed plants, and two-week old seedlings of Zeamays  L., 1753 as crop plants.

Soil was taken from the secondary forest of the Moscow Region. It was classified as sod-podzolic with sandy-clay texture. After the litter removal, the soil was collected from the upper 20 cm layer, dried at room temperature and sieved through a 2 mm mesh. The soil was fertilized with 30 g NPK 4-14-8 in each microcosm and limed to pH 5 to 5.5.

Table 1 presents the parameters of the plants before and after the introduction of the herbicide.

Dynamics of changes in the plant parameters [ 44 ].

n: number of measurements.

Table 2 presents the estimation data on the proportion of the radioactivity distribution over the components of the model systems.

Distribution of the radioactivity over the components of the soil-plants systems [ 44 ].

The presented results show that a larger portion of radioactivity is found in the soil both in the systems with and without plants (from 55.0% to 99.5%). The root part of the soil, rhizosphere, was analyzed separately. The amount of radioactivity in this part is approximately the same for the systems with plants, including weeds, given the degradation of the above-ground part (from 20.5% to 22.5%).

It is interesting to know whether the calculated concentration profiles of the substances are sensitive to the way of the soil layer simulation.

Figure 3 a,b shows the distribution results for rimsulfuron and 14 C over the studied layers of the system.

Distribution of 14 C isotope, kBq·kg −1 ( a ) and pesticide ( b ) over the soil profile of the experimental system [ 44 ].

To analyze the soil in the model experiments, we used the method of multi-residual determination of pesticides, described above. Matrix effects (MEs) are one of the main aspects that must be addressed when evaluating a multi-residue method for pesticide analysis. The procedure also was based on the quick, easy, cheap, effective, rugged and safe (QuEChERS) sample preparation method. The choice of the buffer, type of extract solvent, shaking time and dispersive solid-phase extraction (d-SPE) clean-up were optimized. The study showed that the content of pesticides analyzed by our method was lower than the detection limit, with the exception of rimsulfuron, which we had introduced.

The results show the distribution of the pesticide and radiocarbon 14 days after the application of the labeled preparation to the experimental system enclosed in a microcosm.

The highest pesticide and radiocarbon content was found in the uppermost soil layer, ~54% of the amount applied. With the distance from the soil surface, the labelled pesticide content apparently decreased. The resulting distribution was not unusual due to the main downward transport of fluid flows between the soil particles.

Insignificant amounts of rimsulfuron and radiocarbon were also detected in drainage waters, which were collected in a tray installed beneath a cylinder in which the test soil was placed: ~0.5% of 14 C and rimsulfuron.

The half-life of rimsulfuron was determined as being 22 days in laboratory conditions. The linear adsorption coefficient was K d = 18 mg·L −1 . The calculated value of Gibbs free energy was <50 kJ·mol −1 , which indicates mainly physical preparation adsorption with soil particles under exothermic conditions. The results have been statistically processed [ 44 ].

To assess the contribution of the pesticide loss as a result of metabolism, studies were conducted to identify the degradation rate for the initial pesticide [ 45 , 46 , 47 , 48 , 49 , 50 ].

A research team in [ 51 ] studied adsorption, degradation and leaching migration characteristics of chlorothalonil in different soils. The results show that the adsorption of chlorothalonil in clay and sandy soils can be characterized by the Freundlich equation. The adsorption coefficient (K) was found to be 6.7158 and 1.2568, respectively. The residual degradation kinetics of chlorothalonil in both soils corresponds to the first-order kinetics degradation equation. As the concentration of chlorothalonil increased, the higher the residual amount of chlorothalonil in the soil, the slower was the degradation rate and the longer the half-life. In the soil column, chlorothalonil could not easily move and migrate in the two soil columns. The highest residual residues were in the range from 0 to 10 cm (the topmost), with the following decrease. The correlation analysis showed that the adsorption and leaching of chlorothalonil in the two soils may be affected by a combination of factors such as soil organic matter content, clay content, cation exchange capacity and soil pH value. This leads to a great risk of the groundwater contamination, and thus, it should be paid serious attention [ 51 ].

The adsorption, desorption and leaching potential of glyphosate and aminomethylphosphonic acid [ 52 ], adsorption of dieldrin by parent and processed montmorillonite clays [ 53 ] and other pesticides were studied including the biodegradation of pesticides by soil bacteria [ 54 , 55 , 56 ].

The content of 14 C in the leaves varied from 9.3 to 11.4, with this amount being higher in the weed leaves. With the simultaneous presence of two plant species, the amount of 14 C in the leaves was comparable with the amount of the radioisotope in the leaves of Sinapis arvensis L ., despite the fact that there was intense necrosis of the entire leaf surface. In this case, the radioactive isotope appeared to be incorporated into the leaf structure, intensely affecting the cells.

The physiology of the maize leaves did not undergo any noticeable changes, and the detected content of 14 C was likely to be present only on the surface, or in the uppermost layer of the epidermis of the leaf blade.

The stem in the studied systems can be assigned solely the role of a conductor of the preparation between the leaves treated at the very beginning of the experiment and the soil in which the plants grew.

The herbicides applied to the plants can undergo the following [ 47 , 48 , 49 , 50 , 51 ]: (1) volatilize off the leaf surface before absorption, (2) be washed off the leaf surface before absorption, (3) photodegrade before absorption, (4) remain on the leaf surface, without being absorbed, (5) penetrate the cuticle, and remain tied up in the cuticle, (6) penetrate the cuticle, and enter the apoplast or symplast and (7) be subject to translocation and metabolism. This may be caused by intensive photosynthesis and transpiration processes in plant edible parts and by their growing conditions: located close to the soil surface, they are attacked by insects more frequently, and hence, larger amounts of pesticides are applied to protect them.

Whole-body autoradiography is widely used to trace the routes of molecules in metabolism. First, a radioactive tracer ( 14 C-rimsulfuron) is administered to an organism by ingestion or injection. After a period of time, individual samples of tissue are removed and pressed directly against an X-ray film for several days, to expose the film wherever the radioactivity has become concentrated.

The film is then developed and examined, mostly using a microscope. This process is used to trace the uptake of nutrients by the plants leaves or buds from the soil.

Figure 4 presents the autoradiography results for the maize leaves: the left panel shows transverse cross-section, while the right panel is the view from the top.

Distribution of the labelled rimsulfuron over the leaf of Zea mays  L., 1753 [ 44 ].

As can be seen from the presented results, a larger amount of radiocarbon is found in the leaf part which is closer to the stem (the lighter part of the image), with some inclusions in the rest of the leaf. When examining the image obtained for the leaf cross section using a scanning microscope ( Figure 4 A,B), the part of the leaf facing the surface was found to contain more 14 C than the inner part of the leaf.

This is likely to be due to the fact that rimsulfuron, when sprayed, first covers the outer parts of the plant leaves. This is where the primary effect of the preparation is exerted on the physiological functions of the plants, including the impact associated with the absorption and transformation of the introduced herbicide.

Figure 5 presents the accumulation of 14 C by the intracellular space of the maize leaf.

Distribution of 14 C in the intracellular space of the leaf of Zea mays  L., 1753 [ 44 ].

Figure 6 shows the autoradiography results for the weed plant Sinapis arvensis L. in the system with the 14 C-labelled rimsulfuron treatment, the exposure time being 32 h.

Autoradiography of the shoots Sinapis arvensis L., 32 h after the treatment [ 44 ].

The accumulation of radiocarbon in the plant tissues is dark colored in Figure 5 and Figure 6 . One can see in Figure 5 that 14 C is present in almost all the organelles of the intracellular space of the maize leaf Zea mays  L., 1753. The image presented in Figure 6 shows that radiocarbon is detected in the root, stem and remaining leaf of the shoot of the Sinapis arvensis L. After additional 12 h following the treatment, all the shoots of Sinapis arvensis L. died and shed onto the soil surface, to be removed for the purity of the experiment.

The question arises as to what is the origin of these processes?

When considering the toxic effects of pesticides on living organisms, it is necessary to take into account the stability of the preparations in the environment when exposed to humidity, UV radiation, changes in temperature, etc., since the more stable the pesticide, the greater the level of its accumulation in an organism. Pesticides such as chlordane, dieldrin, hexachlorobenzene thiobencarb and endrin are reported to be resistant to degradation (persistent organic pollutants) and they remain in the environment for a long time. In addition, persistent pesticide residues can accumulate in the organism and reach the bioconcentration more than 70,000 times higher than the initial concentrations [ 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 ].

Earlier, we conducted research on samples of honey and other honey products. Studies were carried out to reveal the presence of residues of a number of pesticides, including neonicotinoids. The possible concentration of residues depends on the amount of the pesticide used (excessive or moderate use), which reflects the accumulation and toxic effects of such residues on pollinators (bees) and other insects [ 64 , 65 , 66 , 67 ].

The main way is the mechanistic route of the pesticide uptake, starting from the moment of the pesticide application, followed by photodegradation, and absorption by plant parts (stem, leaves or fruit) or sorption at the soil level. This means that pesticides enter the soil, where they undergo biodegradation, chemical decomposition (pH, humidity and temperature) and biodegradation (enzymes of bombardment).

The pesticide residues and decomposition by-products penetrate through the roots into the entire plant parts, causing some detrimental effects on soil and plants. These effects include overproduction of ROS, oxidative stress, DNA damage, photosynthetic blockade, necrosis, chlorosis, leaf curl and ultimately, plant death. An example of this process is the research described in the section above.

Generalized hazardous effects of pesticides and the most common toxic effects of the main types of pesticides (insecticides, herbicides and fungicides) on the soil and plants are listed in Table 3 [ 68 ].

Toxic effects of pesticides on agricultural soils and plants.

During the study aimed at assessing the toxicity, with some agricultural crops from the bean and cereal families subjected to a number of pesticides, ambiguous results were obtained, which are presented in Table 4 .

Changes in the morphological parameters for agricultural crops: rye, oats, bean and clover upon the application of pesticides ( n = 15, p = 0.95).

When bean and cereals were treated with pesticides, more stable morphological parameters were observed in experiments with Secále and Avéna ( Table 4 ). The development of bean shoots ceased; the plants began to wither, and their development almost stopped ( Figure 7 ). In the case of cereals, the shoot development visually deteriorated ( Figure 8 ), mainly due to some dried leaf tips.

Comparison of the physical appearance of the bean shoots ( Vícia fába ): ( a ) control, ( b ) after treatment with the pesticide (acetamiprid).

Comparison of the physical appearance of the rye shoots ( Secále ): ( a ) control, ( b ) after treatment with the pesticide (acetamiprid).

To assess the efficiency of the photosynthetic apparatus of plants and its resistance to various external influences, methods were developed for considering the intensity of the delayed fluorescence (DF) [ 69 , 70 , 71 , 72 , 73 , 74 ].

DF of photosynthetic organisms, discovered in 1951 by B. Strehler and W. Arnold (USA), is now widely used to study the mechanisms of photosynthetic reactions and their relationship with the physiological state of plants [ 70 ].

DF is a biophysical method which provides information about the functioning of the primary reactions of photosynthesis in intact objects or the afterglow of photosynthetic organisms.

Briefly, the origin and mechanism of the DF in photosynthetic organisms can be represented as follows.

A comparative study of the emission spectra of fast (10 −9 s) and delayed (in ms) fluorescence showed their similarity. On this basis, it was concluded that DF occurred during the radiative deactivation of the first singlet excited state of chlorophyll [ 70 , 73 , 74 ].

At the same time, in contrast to the rapid fluorescence of plant chlorophyll, which decays in a time of the order of 10 −8 –10 −9 s, the duration of the DF significantly exceeds the intrinsic time of the singlet excited state of chlorophyll. This shows that DF is due to the secondary excitation of chlorophyll during reverse reactions formed in the light of photoproducts [ 69 , 73 , 74 ].

The kinetics of the DF are very complex and multicomponent. This is due to the fact that the stages of stabilization of the stored light energy are reversible and can generate an excited state of chlorophyll [ 71 ].

It has been established that DF of green plants occurs mainly in the reaction centers of photosystem II and a very weak DF can be observed in the photosystem.

During the recombination of the excited molecules of the reaction center, a part of the resulting energy is transferred to the molecules of light-harvesting chlorophyll, which emits it in the form of quanta of DF.

The DF method is characterized by high sensitivity, reliability, rapidity and ability to automate the information obtained from intact objects in the field [ 71 , 74 ].

Using delayed fluorescence to detect the effect of the applied pesticides on the studied plants of the bean and cereal families, a decrease in the intensity of the DF was observed ( Figure 9 ).

Dependence of the dynamics of changes in the relative index of delayed fluorescence (RIDF) on the pesticide concentration.

Based on the results of the entire experiment and intensity of the DF, one can conclude that the cereal plants are more resistant to treatment with the studied pesticides than the bean plants. The indices of DF are decreased by a factor of 2 or less for the cereals, while for the beans, a complete suppression of the indices is observed. In the system with rye, the intensity of DF hardly changed when acetamiprid, flumetsulam and florasulam were added to the system.

The above presented studies and discussions highlight that pesticide residues cause direct and indirect damage to fauna, flora, physicochemical and biological properties of agricultural soils. In addition, they can reduce enzymatic activity and suppress microbial communities in the soil. Pesticides can cause chlorosis, leaf curl/necrosis and photosynthetic impairment, including oxidative stress [ 74 , 75 , 76 , 77 ]. Different classes of pesticides lead to a suppression of nitrogen metabolism by increasing or decreasing the activity of certain enzymes. In addition, the pigmentation of the leaves may change, and grains may stop developing. The validation of the method for multi-residual determination of pesticides belonging to different classes in terms of the chemical structure and properties, and having different types of effects, makes it possible to simultaneously detect the presence of certain substances in the environments of different types.

4. Conclusions

The implementation of enforcement measures on providing the hygiene safety of pesticides to the consumer market is closely connected with the creation and validation of identification methods and quantitative estimation of their residual amounts.

The aim of the present review was to study the impact of pesticides on the “soil-agricultural plants system” in order to reveal possible negative factors for the resilience of plants used as food for the population.

(1) The method of multi-residual determination of pesticides in agricultural crops was considered. Forty active substances in pesticides were selected for the research (including a number of metabolites), with the substances belonging to different chemical groups (neonicotinoids, tryasols, imidazoles, pyrethroids, organophosphorus compounds, strobilurins, etc.). The identification was performed taking into account the retention time, presence of characteristic ions in the mass spectra (GC-MS method) and product ions (LC-MS/MS) and area ratio of the chromatographic peaks which are related to the characteristic ions. The method QuEChERS was used to prepare the samples of agricultural products. This methodological approach is very promising in the research of pesticides that have different physical and chemical properties and ways of their intake by the organism, as well as various types of behavior in the soil-water-plant system.

(2) In the model experiments to study the migration and translocation in the soil-plant system (the agricultural crop Zeamays L., 1753 and the weed Sinapisarvensis L.), using rimsulfuron and labelled 14 C-rimsulfuron, a larger portion of radioactivity was found in the soil both in the systems with the plants and without them (from 55.0% to 99.5%); in all the systems, the radioactive content in the root zone of the soil, i.e., in rhizosphere, was from 20.5% to 22.5%; the content of 14 C in the leaves varied from 9.3% to 11.4%. The degradation of the weed Sinapisarvensis L. followed by its decomposition was revealed by the method of autoradiography. However, in the leaves of maize ( Zeamays L., 1753), these processes spread both on the leaf surface and in its intracellular compartment, with no visible changes in the vital functions of the plants found.

(3) Based on our results and on the data from the information sources, the adsorption of pesticides in soil was found to follow the regularity described by the Freundlich equation.

(4) During the study of the toxic impact of acetamiprid, flumetsulam and florasulam on some crops of the bean family and cereal family, ambiguous results were obtained: the bean family was affected by the considered pesticides to the highest extent (including the complete inhibition of the plant shoots), while the cereal plants were hardly affected.

Acknowledgments

This review was prepared with the partial financial support of the Program of the Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing (Russian Federation) 2020–2025.

Author Contributions

Conceptualization, L.B. and N.F.; methodology, L.B. and N.F.; validation, L.B.; formal analysis, N.F.; investigation, L.B.; resources, L.B. and N.F.; data curation, N.F.; writing—original draft preparation, L.B.; writing—review and editing, N.F.; visualization, L.B. and N.F.; supervision, N.F.; project administration, L.B.; funding acquisition, L.B. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Soil Basics

Why is soil important for plant growth and health?

Soils provide  water , air,  nutrients ,  and   mechanical support   for plants. Soils also tie up, filter, and break down natural and man-made toxins.   Soils sustain all life on Earth and might be the most important, neglected, and least understood resource in the landscape. 

Soil problems such as compaction, low fertility, poor drainage, and thin topsoil, can cause stress, poor growth, and decline in our garden and landscape plants.

The native topsoil has been removed from many urban and suburban soils. These soils are often compacted and low in organic matter. Poor soil management and misuse of fertilizers contribute to surface and groundwater pollution.

It’s our job to protect and improve our soils so they can nourish future generations of plants and animals - including humans!

What you should know about soil

• Soil is a natural resource and a living ecosystem (the "living skin of the earth").
• Soils sustain all life on earth and filter and break down natural and man-made toxins.
• Soils provide water, nutrients, and support, along with oxygen for the plant's root growth.
• Soils have four main components: mineral particles (sand, silt, and clay), organic matter, water, and air.
• There are many different types of soil in Maryland. You may have several types even in a small yard!
• Healthy soils grow healthy plants that keep people healthy.
• Information found on this page.

Soil texture

• Nearly all soils in Maryland contain a combination of sand, silt, and clay particles. Soil texture is determined by the relative amounts of these three types of particles and doesn't change over time. Soil texture is determined by the parent material (rocks from which the soil formed), climate, slope, and other factors.
• Texture determines, in large part, how the soil feels and behaves. Sand particles are the largest (0.05-2 mm) and can be seen without a magnifier. Silt particles (0.002-0.05 mm) are next in size, followed by clay particles that are 1,000 times smaller than sand particles (< 0.002 mm) and can only be seen with an electron microscope.
• Too much clay in the soil can make it difficult to manage. But clay plays a positive role in holding and protecting organic matter particles. Also, clay's enormous surface area carries negative charges that hold positively charged nutrients (e.g., calcium, magnesium, potassium, ammonium) used by plants and soil microbes.
• You can roughly determine your soil's texture by the " feel method " or the " jar test ." Some soil testing labs will conduct a "mechanical analysis" (for an additional fee) to identify soil texture.
• You can determine your specific soil type through the U.S.D.A.'s  Web Soil Survey .

The soil triangle shows the 12 textural classes of soils. In the example below, the soil has 25% sand, 10% clay, and 65% silt, giving it a silt loam texture.

• One half of the volume of most soils is composed of solids (sand, silt, clay, and organic matter) and the other one half is composed of pores--spaces between solid particles, that are filled with air, water, roots, microorganisms, earthworms, and other soil animals.
• Healthy soils have a large number of pore spaces of varying sizes that allow for the free movement of water, air, and growth of plant roots, soil microbes, and animals.

In the diagram below we can imagine that rain fell two or three days ago. Most of the pore spaces would have been filled with water. Gravity carries excess water down through the soil profile. The water in the diagram is held on, and between, soil and organic matter particles and is available for uptake by plant roots.

• You may have seen soils with a high percentage of clay draining very slowly after a thunderstorm. The tiny clay particles are packed closely together which slows the movement of water. Soils with a lot of clay are also more susceptible to compaction from foot traffic, vehicles, and machinery, further slowing the movement of water and air into (infiltration) and through (percolation) the soil.
• Soils with a high percentage of sand drain quickly after a thunderstorm, carrying nutrients from fertilizers and organic matter down through the soil and out of the root zone of plants. As a result, plants growing in sandy soils often require more frequent watering and fertilizing.

This chart shows how soil texture affects water, air, and nutrients in the soil

Credit: Melissa L. Wilson, Ph.D., and Patricia Steinhilber, Ph.D. 

Soil structure

• Soil structure describes the way that particles fit together and form small clumps, called aggregates.
• Roots, fungal hyphae (thread-like growths), and sticky substances produced by soil microbes and plant roots hold and "glue" clay and silt particles into aggregates. Very small microaggregates combine to form macroaggregates.
• Earthworms and small soil animals also contribute to aggregation by burrowing and producing fecal pellets.
• The topsoil of a healthy soil should have a crumb-like structure with ½ of the volume made up of different size pores.
• Soil structure can be improved over time by increasing the amount of organic matter in the soil.

Organic matter

• Soil organic matter is made up of living, dead, and decomposing organisms within and on top of the soil. These include plants (leaves, stems, roots), earthworms and other soil animals, and microorganisms. Organic matter accounts for a relatively small part of soil (1%-5% by weight) but is critically important to soil health because it supports the soil food web that drives the biochemical action in the soil.
• Organic matter exists on a continuum from living organisms to "protected organic matter" (formerly described as humus) which is made up primarily of dead microbial cells found inside small soil crumbs (microaggregates) or attached to clay particles. The "protected organic matter" in the graphic accounts for about 75% of total soil organic matter. It's made up mostly of dead soil microbes that are protected from further decomposition because of their location and attachment to clay particles.
• Once plants and animals die, their tissues ("residues and by-products" in the graphic above) are shredded, chewed, and digested by huge populations of soil animals and microbes (fungi and bacteria). This leads to the release of nutrients, like potassium and nitrogen, that plants can use. In the process nutrients, once part of organic compounds in the living organisms are converted through biochemical processes into inorganic forms used by plants and microbes.
• Organic Matter and Soil Amendments  

 The soil food web

• On first glance, soil may appear dense, dead, and deserted. But it's actually teeming with life. Soils are home to thousands of different species of soil -animals, including tiny mites, nematodes, springtails, and earthworms, as well as bacteria and fungi. A teaspoon of soil can contain several billion microorganisms!
• All of these life forms occupy particular positions (trophic levels) in the soil ecosystem. Organic matter feeds the soil food web with larger animals consuming smaller ones.
• Living plant roots leak sugars and other compounds that support huge populations of bacteria and fungi in the root zone.
• Roots and microbes release sticky substances that help form stable aggregates, giving the soil a crumb-like structure.

Additional resources

Soil texture "feel method".

Washington State University video -  Determining Soil Texture by Hand University of California-Davis video -  Soil Texture by Feel University of Kentucky -  (PDF) Determining Soil Texture by Feel

Soil Texture "Jar Test" Method

Clemson University -  Soil Texture Analysis "The Jar Test" University of California -  (PDF) Sedimentation Test of Soil Texture  

Author, Jon Traunfeld, HGIC Director, and Extension Specialist, Fruits and Vegetables.

Still have a question? Contact us at Ask Extension .

Stabilization of soft soil with rice husk and coconut fibre

• Zulkafli, M. H.
• Noorasyikin, M. N.
• Roslan, L. F.

This study focuses on the stabilization of soft soil, which has a low bearing capacity and is prone to significant deformations and high moisture content. Soft soil is one type of soil with a poor bearing capacity, and when loaded, it significantly reduces the likelihood of a nonuniform decline. The aim of this study is to determine the physical properties of soft soil and to determine the mechanical properties of soft soil mixture with rice husk and coconut fibre with curing days of 14, and 21 days. The significance of this study lies in its contribution to establish a strong foundation and stabilizing soil, which plays a crucial role in constructing solid and durable structures, ensuring their stability and longevity. By utilizing rice husk and coconut fiber as soil stabilizers, the study also addresses environmental concerns by substituting natural resources with unwanted or discarded materials. Furthermore, this approach offers an economically viable solution for soft soil stabilization. The study involved two types of soil samples. The first type served as a control sample without any rice husk or coconut fiber, while the second type included rice husk and coconut fiber. The second type of sample was further divided into two ratios, with curing durations of 14 days and 21 days. A soil sample was collected from a paddy field in Sg Balang, Muar, Johor. The rice husk was burned at temperatures below 800 °C, resulting in silica-rich ash. The physical and mechanical properties of the soft soil mixture with rice husk and coconut fiber were determined through various tests. The preliminary tests were conducted to assess the physical qualities of the soil, including the Atterberg Limit Method, Compaction Test, and Direct Shear Test. The results showed that the Liquid Limit (LL) was 20.1%, with moisture content ranging from 15.56% to 27.38%. The compaction test indicated that a ratio of 2 with a 21-day curing duration achieved a maximum dry density of 0.56 and an optimum moisture content of 47.8%. The Direct Shear Test demonstrated that a ratio of 1 with a 21-day curing period exhibited the highest shear strength and shear stress at 3.25 kg and 10.45 kPa, respectively. Moreover, the cohesive and friction angle increased with longer curing days, with the mixture of ratio 1 and 21 days showing the highest values at 4.7 kPa and 35.03°, respectively. In summary, the presence of rice hush and coconut fibre significantly improve the soft soil stabilization. The study suggests that further research should explore longer curing periods of 30 days and 60 days to enhance shear strength.