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Impact of Soil Microbial Amendments on Tomato Rhizosphere Microbiome and Plant Growth in Field Soil

  • Plant Microbe Interactions
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Abstract

There is increased interest by the agricultural industry in microbial amendments that leverage natural beneficial interactions between plants and soil microbes to improve crop production. However, translating fundamental knowledge from laboratory experiments into efficient field application often has mixed results, and there is less clarity about the interaction between added microbes and the native microbial community, where microorganisms belonging to the same phylogenic clades often reside. In this study, four commercially available microbial amendments were examined in two greenhouse experiments using field soil to assess their impact on tomato plant growth and the native soil microbial communities. The amendments contained different formulations of plant growth-promoting bacteria (Lactobacilli, Rhizobia, etc.), yeasts, and mycorrhizal fungi. The application of the tested amendments in greenhouse conditions resulted in no significant impact on plant growth. A deeper statistical analysis detected variations in the microbial communities that accounted only for 0.25% of the total species, particularly in native taxa not related to the inoculated species and represented less than 1% of the total variance. This suggests that under commercial field conditions, additional confounding variables may play a role in the efficacy of soil microbial amendments. This study confirms the necessity of more in-depth validation requirements for the formulations of soil microbial amendments before delivery to the agricultural market in order to leverage their benefits for the producers, the consumers, and the environment.

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References

  1. Berendsen RL, Pieterse CMJ, Bakker PAHM (2012) The rhizosphere microbiome and plant health. Trends Plant Sci. 17:478–486. https://doi.org/10.1016/j.tplants.2012.04.001

    Article  PubMed  CAS  Google Scholar 

  2. Schlaeppi K, Bulgarelli D (2015) The plant microbiome at work. Mol. Plant-Microbe Interact. 28:212–217. https://doi.org/10.1094/MPMI-10-14-0334-FI

    Article  PubMed  CAS  Google Scholar 

  3. Bulgarelli D, Schlaeppi K, Spaepen S et al (2013) Structure and functions of the bacterial microbiota of plants. Annu. Rev. Plant Biol. 64:807–838. https://doi.org/10.1146/annurev-arplant-050312-120106

    Article  PubMed  CAS  Google Scholar 

  4. Lugtenberg B, Kamilova F (2009) Plant-growth-promoting rhizobacteria. Annu. Rev. Microbiol. 63:541–556. https://doi.org/10.1146/annurev.micro.62.081307.162918

    Article  PubMed  CAS  Google Scholar 

  5. Backer R, Rokem JS, Ilangumaran G et al (2018) Plant growth-promoting rhizobacteria: context, mechanisms of action, and roadmap to commercialization of biostimulants for sustainable agriculture. Front. Plant Sci. 9:1–17. https://doi.org/10.3389/fpls.2018.01473

    Article  Google Scholar 

  6. Hacquard S, Garrido-Oter R, González A et al (2015) Microbiota and host nutrition across plant and animal kingdoms. Cell Host Microbe 17:603–616. https://doi.org/10.1016/j.chom.2015.04.009

    Article  PubMed  CAS  Google Scholar 

  7. Schulz-Bohm K, Zweers H, de Boer W, Garbeva P (2015) A fragrant neighborhood: volatile mediated bacterial interactions in soil. Front. Microbiol. 6:1–11. https://doi.org/10.3389/fmicb.2015.01212

    Article  Google Scholar 

  8. Chaparro JM, Sheflin AM, Manter DK, Vivanco JM (2012) Manipulating the soil microbiome to increase soil health and plant fertility. Biol. Fertil. Soils 48:489–499. https://doi.org/10.1007/s00374-012-0691-4

    Article  Google Scholar 

  9. Ersek B, Lange S.: Organic soil amendments and method for enhancing plant health. US Patent 8790436B2, July 2014

  10. Pardey PG, Beddow JM, Hurley TM et al (2014) A bounds analysis of world food futures: global agriculture through to 2050. Aust. J. Agric. Resour. Econ. 58:571–589. https://doi.org/10.1111/1467-8489.12072

    Article  Google Scholar 

  11. Calvo P, Nelson L, Kloepper JW (2014) Agricultural uses of plant biostimulants. Plant Soil 383:3–41. https://doi.org/10.1007/s11104-014-2131-8

    Article  CAS  Google Scholar 

  12. Parnell JJ, Berka R, Young HA et al (2016) From the lab to the farm: an industrial perspective of plant beneficial microorganisms. Front. Plant Sci. 7:1401–1409. https://doi.org/10.3389/fpls.2016.01110

    Article  Google Scholar 

  13. Sessitsch A, Brader G, Pfaffenbichler N et al (2018) The contribution of plant microbiota to economy growth. Microb. Biotechnol. https://doi.org/10.1111/1751-7915.13290

  14. Kloepper JW, Lifshitz R, Zablotowicz RM (1989) Free-living bacterial inocula for enhancing crop productivity. Trends Biotechnol. 7:39–44. https://doi.org/10.1016/0167-7799(89)90057-7

    Article  Google Scholar 

  15. Lamont JR, Wilkins O, Bywater-Ekegärd M, Smith DL (2017) From yogurt to yield: potential applications of lactic acid bacteria in plant production. Soil Biol. Biochem. 111:1–9. https://doi.org/10.1016/j.soilbio.2017.03.015

    Article  CAS  Google Scholar 

  16. Giassi V, Kiritani C, Kupper KC (2016) Bacteria as growth-promoting agents for citrus rootstocks. Microbiol. Res. 190:46–54. https://doi.org/10.1016/j.micres.2015.12.006

    Article  PubMed  Google Scholar 

  17. Sundaramoorthy S, Raguchander T, Ragupathi N, Samiyappan R (2011) Combinatorial effect of endophytic and plant growth promoting rhizobacteria against wilt disease of Capsicum annum L. caused by Fusarium solani. Biol. Control 50:155–174. https://doi.org/10.1016/j.biocontrol.2011.10.002

    Article  Google Scholar 

  18. Rudresh DL, Shivaprakash MK, Prasad RD (2005) Effect of combined application of rhizobium, phosphate solubilizing bacterium and Trichoderma spp. on growth, nutrient uptake and yield of chickpea (Cicer aritenium L.). Appl. Soil Ecol. 28:139–146. https://doi.org/10.1016/j.apsoil.2004.07.005

    Article  Google Scholar 

  19. Ghorchiani M, Etesami H, Alikhani HA (2018) Improvement of growth and yield of maize under water stress by co-inoculating an arbuscular mycorrhizal fungus and a plant growth promoting rhizobacterium together with phosphate fertilizers. Agric. Ecosyst. Environ. 258:59–70. https://doi.org/10.1016/j.agee.2018.02.016

    Article  CAS  Google Scholar 

  20. Wintermute EH, Silver PA (2010) Dynamics in the mixed microbial concourse. Genes Dev. 24:2603–2614

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Xia Y, Sun J (2017) Hypothesis testing and statistical analysis of microbiome. Genes Dis 4:138–148. https://doi.org/10.1016/j.gendis.2017.06.001

    Article  PubMed  PubMed Central  Google Scholar 

  22. Stegen JC, Bottos EM, Jansson JK (2018) A unified conceptual framework for prediction and control of microbiomes. Curr. Opin. Microbiol. 44:20–27. https://doi.org/10.1016/j.mib.2018.06.002

    Article  PubMed  Google Scholar 

  23. Ruzzi M, Aroca R (2015) Plant growth-promoting rhizobacteria act as biostimulants in horticulture. Sci Hortic (Amsterdam) 196:124–134. https://doi.org/10.1016/j.scienta.2015.08.042

    Article  CAS  Google Scholar 

  24. Owen D, Williams AP, Griffith GW, Withers PJA (2015) Use of commercial bio-inoculants to increase agricultural production through improved phosphorus acquisition. Appl. Soil Ecol. 86:41–54. https://doi.org/10.1016/j.apsoil.2014.09.012

    Article  Google Scholar 

  25. Nicot PC, Bardin M, Alabouvette C, et al (2011) Potential of biological control based on published research. 1. Protection against plant pathogens of selected crops. In: Nicot PC (ed) Classical and augmentative biological control against diseases and pests: critical status analysis and review of factors influencing their success. IOBC/WPRS Publications, Montfavet cedex, FR, pp 1–11

  26. Schneider S, Tajrin T, Lundström JO, Hendriksen NB, Melin P, Sundh I (2017) Do multi-year applications of Bacillus thuringiensis subsp. israelensis for control of mosquito larvae affect the abundance of B. cereus group populations in riparian wetland soils? Microb. Ecol. 74:901–909. https://doi.org/10.1007/s00248-017-1004-0

    Article  PubMed  Google Scholar 

  27. Díaz S, Fargione J, Chapin FS, Tilman D (2006) Biodiversity loss threatens human well-being. PLoS Biol. 4:e277. https://doi.org/10.1371/journal.pbio.0040277

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Schneider CA, Rasband WS, Eliceiri KW (2012) NIH image to ImageJ: 25 years of image analysis. Nat. Methods 9:671–675

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Apprill A, McNally S, Parsons R, Weber L (2015) Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat. Microb. Ecol. 75:129–137. https://doi.org/10.3354/ame01753

    Article  Google Scholar 

  30. Gardes M, Bruns TD (1993) ITS primers with enhanced specificity for basidiomycetes--application to the identification of mycorrhizae and rusts. Mol. Ecol. 2:113–118

    Article  CAS  PubMed  Google Scholar 

  31. Bolyen E, Rideout JR, Dillon MR et al (2018) QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science. PeerJ:9–10. https://doi.org/10.7287/peerj.preprints.27295v1

  32. Zhang J, Kobert K, Flouri T, Stamatakis A (2014) PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30:614–620. https://doi.org/10.1093/bioinformatics/btt593

    Article  PubMed  CAS  Google Scholar 

  33. Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17:10. https://doi.org/10.14806/ej.17.1.200

    Article  Google Scholar 

  34. Callahan BJ, McMurdie PJ, Rosen MJ et al (2016) DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13:581

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2012) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41:D590–D596. https://doi.org/10.1093/nar/gks1219

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Tedersoo L, Sánchez-Ramírez S, Kõljalg U et al (2018) High-level classification of the Fungi and a tool for evolutionary ecological analyses. Fungal Divers. 90:135–159. https://doi.org/10.1007/s13225-018-0401-0

    Article  Google Scholar 

  37. Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, Huttley GA, Gregory Caporaso J (2018) Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6:90. https://doi.org/10.1186/s40168-018-0470-z

    Article  PubMed  PubMed Central  Google Scholar 

  38. Price MN, Dehal PS, Arkin AP (2010) FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS One 5:e9490. https://doi.org/10.1371/journal.pone.0009490

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Core Team R (2016) R: a language and environment for statistical computing. R Found Stat Comput 1:409. https://doi.org/10.1007/978-3-540-74686-7

    Article  Google Scholar 

  40. Venables WN, Ripley BD (2002) Modern Applied Statistics with S, Springer, New York https://doi.org/10.1007/978-0-387-21706-2

  41. Mendiburu F, Simon R (2015) Agricolae-ten years of an open source statistical tool for experiments in breeding, agriculture and biology. PeerJ Prepr 3:1–17. https://doi.org/10.7287/peerj.preprints.1404v1

    Article  Google Scholar 

  42. McMurdie PJ, Holmes S (2014) Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput Biol. https://doi.org/10.1371/journal.pcbi.1003531

  43. Oksanen AJ, Blanchet FG, Friendly M, et al (2016) Vegan: community ecology package. https://github.com/vegandevs/vegan

  44. Wei T and Simko V (2017). R package ‘‘corrplot’’: Visualization of a Correlation Matrix (Version 0.84). Available from https://github.com/taiyun/corrplot

  45. Bokulich N, Dillon M, Bolyen E et al (2018) q2-sample-classifier: machine-learning tools for microbiome classification and regression. bioRxiv. https://doi.org/10.1101/306167

  46. Mendes R, Kruijt M, de Bruijn I et al (2011) Deciphering the Rhizosphere microbiome for disease-suppressive bacteria. Science (80- ) 332:1097–1100. https://doi.org/10.1126/science.1203980

    Article  CAS  Google Scholar 

  47. Povero G, Mejia JF, Di Tommaso D et al (2016) A systematic approach to discover and characterize natural plant biostimulants. Front. Plant Sci. 7:1–9. https://doi.org/10.3389/fpls.2016.00435

    Article  Google Scholar 

  48. Kaminsky LM, Trexler RV, Malik RJ, Hockett KL, Bell TH (2019) The inherent conflicts in developing soil microbial inoculants. Trends Biotechnol. 37:140–151. https://doi.org/10.1016/j.tibtech.2018.11.011

    Article  PubMed  CAS  Google Scholar 

  49. Stewart EJ (2012) Growing unculturable bacteria. J. Bacteriol. 194:4151–4160. https://doi.org/10.1128/JB.00345-12

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Großkopf T, Soyer OS (2014) Synthetic microbial communities. Curr. Opin. Microbiol. 18:72–77. https://doi.org/10.1016/j.mib.2014.02.002

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Singh DP, Singh HB, Prabha R (2016) Microbial inoculants in sustainable agricultural productivity: vol. 2: functional applications. Microb Inoculants Sustain Agric Product 2 Funct Appl:1–308. https://doi.org/10.1007/978-81-322-2644-4

    Article  Google Scholar 

  52. Welc M, Ravnskov S, Kieliszewska-Rokicka B, Larsen J (2010) Suppression of other soil microorganisms by mycelium of arbuscular mycorrhizal fungi in root-free soil. Soil Biol. Biochem. 42:1534–1540. https://doi.org/10.1016/j.soilbio.2010.05.024

    Article  CAS  Google Scholar 

  53. Smith SE, Smith FA (2011) Roles of arbuscular mycorrhizas in plant nutrition and growth: new paradigms from cellular to ecosystem scales. Annu. Rev. Plant Biol. 62:227–250. https://doi.org/10.1146/annurev-arplant-042110-103846

    Article  PubMed  CAS  Google Scholar 

  54. González-Guerrero M, Escudero V, Saéz Á, Tejada-Jiménez M (2016) Transition metal transport in plants and associated endosymbionts: arbuscular mycorrhizal fungi and rhizobia. Front. Plant Sci. 7:1–21. https://doi.org/10.3389/fpls.2016.01088

    Article  Google Scholar 

  55. Cameron DD, Neal AL, van Wees SCM, Ton J (2013) Mycorrhiza-induced resistance: more than the sum of its parts? Trends Plant Sci. 18:539–545. https://doi.org/10.1016/j.tplants.2013.06.004

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Gajbhiye MH, Kapadnis BP (2016) Antifungal-activity-producing lactic acid bacteria as biocontrol agents in plants. Biocontrol Sci. Tech. 26:1451–1470. https://doi.org/10.1080/09583157.2016.1213793

    Article  Google Scholar 

  57. Ashour SM, Kheiralla ZMH, Badawy FMI, Zaki SS (2015) Killer toxins of the yeasts; Candida utilis 22 and Kluyveromyces marxianus and their potential applications as biocontrol agents. Egypt J Biol Pest Control 25:317–325

  58. Pii Y, Mimmo T, Tomasi N et al (2015) Microbial interactions in the rhizosphere: beneficial influences of plant growth-promoting rhizobacteria on nutrient acquisition process. A review. Biol. Fertil. Soils 51:403–415. https://doi.org/10.1007/s00374-015-0996-1

    Article  CAS  Google Scholar 

  59. Berg G (2009) Plant-microbe interactions promoting plant growth and health: perspectives for controlled use of microorganisms in agriculture. Appl. Microbiol. Biotechnol. 84:11–18. https://doi.org/10.1007/s00253-009-2092-7

    Article  PubMed  CAS  Google Scholar 

  60. Jangir M, Pathak R, Sharma S, Sharma S (2018) Biocontrol mechanisms of Bacillus sp., isolated from tomato rhizosphere, against Fusarium oxysporum f. sp. lycopersici. Biol. Control 123:60–70. https://doi.org/10.1016/j.biocontrol.2018.04.018

    Article  CAS  Google Scholar 

  61. Harman GE, Howell CR, Viterbo A, Chet I, Lorito M (2004) Trichoderma species-opportunistic, avirulent plant symbionts. Nat Rev Microbiol 2:43–56. https://doi.org/10.1038/nrmicro797

    Article  PubMed  CAS  Google Scholar 

  62. Bates ST, Garcia-Pichel F (2009) A culture-independent study of free-living fungi in biological soil crusts of the Colorado Plateau: their diversity and relative contribution to microbial biomass. Environ. Microbiol. 11:56–67. https://doi.org/10.1111/j.1462-2920.2008.01738.x

    Article  PubMed  CAS  Google Scholar 

  63. Yu L, Nicolaisen M, Larsen J, Ravnskov S (2013) Organic fertilization alters the community composition of root associated fungi in Pisum sativum. Soil Biol. Biochem. 58:36–41. https://doi.org/10.1016/j.soilbio.2012.11.004

    Article  CAS  Google Scholar 

  64. Prado IGD, da Silva MDS, Prado DGD, Kemmelmeier K et al (2019) Revegetation processes increases the diversity of total and arbuscular mycorrhizal fungi in areas affected by the Fundao dam failure in Mariana, Brazil. Appl. Soil Ecol 141:84–95. https://doi.org/10.1016/j.apsoil.2019.05.008

    Article  Google Scholar 

  65. Stockinger H, Krüger M, Schüßler A (2010) DNA barcoding of arbuscular mycorrhizal fungi. New Phytol. 187:461–474. https://doi.org/10.1111/j.1469-8137.2010.03262.x

    Article  PubMed  CAS  Google Scholar 

  66. Ryan MH, Graham JH (2018) Little evidence that farmers should consider abundance or diversity of arbuscular mycorrhizal fungi when managing crops. New Phytol. 220:1092–1107. https://doi.org/10.1111/nph.15308

    Article  PubMed  Google Scholar 

  67. Tarbell TJ, Koske RE (2007) Evaluation of commercial arbuscular mycorrhizal inocula in a sand/peat medium. Mycorrhiza 18:51–56. https://doi.org/10.1007/s00572-007-0152-3

    Article  PubMed  CAS  Google Scholar 

  68. Nowrouzian FL, Stadler LS, Adlerberth I, Wold AE (2017) The 16S rRNA gene-based PCR method used for the detection of segmented filamentous bacteria in the intestinal microbiota generates false-positive results. Apmis 125:940–942. https://doi.org/10.1111/apm.12743

    Article  PubMed  CAS  Google Scholar 

  69. Almeida A, Mitchell AL, Tarkowska A, Finn RD (2018) Benchmarking taxonomic assignments based on 16S rRNA gene profiling of the microbiota from commonly sampled environments. Gigascience 7:1–10. https://doi.org/10.1093/gigascience/giy054

    Article  Google Scholar 

  70. Baffoni L, Gaggia F, Dalanaj N, Prodi A, Nipoti P, Pisi A, Biavati B, di Gioia D (2015) Microbial inoculants for the biocontrol of Fusarium spp. in durum wheat. BMC Microbiol. 15:8–10. https://doi.org/10.1186/s12866-015-0573-7

    Article  CAS  Google Scholar 

  71. Gaggìa F, Baffoni L, Di Gioia D et al (2013) Inoculation with microorganisms of Lolium perenne L.: evaluation of plant growth parameters and endophytic colonization of roots. New Biotechnol. 30:695–704. https://doi.org/10.1016/j.nbt.2013.04.006

    Article  CAS  Google Scholar 

  72. Jilani G, Akram A, Ali RM et al (2007) Enhancing crop growth, nutrients availability, economics and beneficial rhizosphere microflora through organic and biofertilizers. Ann Microbiol 57:177–184. https://doi.org/10.1007/BF03175204

    Article  CAS  Google Scholar 

  73. Agler MT, Ruhe J, Kroll S et al (2016) Microbial hub taxa link host and abiotic factors to plant microbiome variation. PLoS Biol. 14:1–31. https://doi.org/10.1371/journal.pbio.1002352

    Article  CAS  Google Scholar 

  74. Jones DL, Oburger E (2011) Solubilization of phosphorus by soil microorganisms. In: Bünemann E, Oberson A, Frossard E (eds) Phosphorus in action: biological processes in soil phosphorus cycling. Springer Berlin Heidelberg, Berlin, pp 169–198

    Chapter  Google Scholar 

  75. Verbruggen E (2017) Mycorrhizal fungal establishment in agricultural soils: factors determining inoculation success. Minireview. 1104–1109. https://doi.org/10.1111/j.1469-8137.2012.04348.x

  76. Jackson MA, Dunlap CA, Jaronski ST (2010) Ecological considerations in producing and formulating fungal entomopathogens for use in insect biocontrol. Ecol Fungal Entomopathog:129–145. https://doi.org/10.1007/978-90-481-3966-8_10

  77. Dorrestein PC, Mazmanian SK, Knight R (2014) Finding the missing links among metabolites, microbes, and the host. Immunity 40:824–832. https://doi.org/10.1016/j.immuni.2014.05.015

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. Gloor GB, Wu JR, Pawlowsky-Glahn V, Egozcue JJ (2016) It’s all relative: analyzing microbiome data as compositions. Ann. Epidemiol. 26:322–329. https://doi.org/10.1016/j.annepidem.2016.03.003

    Article  PubMed  Google Scholar 

  79. Tsilimigras MCB, Fodor AA (2016) Compositional data analysis of the microbiome: fundamentals, tools, and challenges. Ann. Epidemiol. 26:330–335. https://doi.org/10.1016/j.annepidem.2016.03.002

    Article  PubMed  Google Scholar 

  80. Wang J, Jia H (2016) Metagenome-wide association studies: fine-mining the microbiome. Nat Rev Microbiol 14:508–522. https://doi.org/10.1038/nrmicro.2016.83

    Article  PubMed  CAS  Google Scholar 

  81. Chang H-X, Haudenshield JS, Bowen CR, Hartman GL (2017) Metagenome-wide association study and machine learning prediction of bulk soil microbiome and crop productivity. Front. Microbiol. 8:1–11. https://doi.org/10.3389/fmicb.2017.00519

    Article  Google Scholar 

  82. Soueidan H, Nikolski M (2017) Machine learning for metagenomics: methods and tools. Metagenomics 1:1–19. https://doi.org/10.1515/metgen-2016-0001

    Article  Google Scholar 

  83. Callahan BJ, Sankaran K, Fukuyama JA et al (2016) Bioconductor workflow for microbiome data analysis: from raw reads to community analyses. F1000Research 5:1492. https://doi.org/10.12688/f1000research.8986.2

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

The authors would like to acknowledge Rachel Berner and Bryce Meyering at UF/IFAS Southwest Florida Research and Education Center for the help and support during the design of the greenhouse setup, sampling of the tomato plants, and soil DNA extractions.

Funding

This work was supported by the USDA National Institute of Food and Agriculture Hatch project 1011186.

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Correspondence to Sarah L Strauss.

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Nuzzo, A., Satpute, A., Albrecht, U. et al. Impact of Soil Microbial Amendments on Tomato Rhizosphere Microbiome and Plant Growth in Field Soil. Microb Ecol 80, 398–409 (2020). https://doi.org/10.1007/s00248-020-01497-7

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