The DOI matches its Crossref record; 186 of the 186 references it cites were found in a registry or an index.
Rhizosphere microbiome: Engineering bacterial competitiveness for enhancing crop production
Open accessAbstract
Plants in nature are constantly exposed to a variety of abiotic and biotic stresses which limits their growth and production. Enhancing crop yield and production to feed exponentially growing global population in a sustainable manner by reduced chemical fertilization and agrochemicals will be a big challenge. Recently, the targeted application of beneficial plant microbiome and their cocktails to counteract abiotic and biotic stress is gaining momentum and becomes an exciting frontier of research. Advances in next generation sequencing (NGS) platform, gene editing technologies, metagenomics and bioinformatics approaches allows us to unravel the entangled webs of interactions of holobionts and core microbiomes for efficiently deploying the microbiome to increase crops nutrient acquisition and resistance to abiotic and biotic stress. In this review, we focused on shaping rhizosphere microbiome of susceptible host plant from resistant plant which comprises of specific type of microbial community with multiple potential benefits and targeted CRISPR/Cas9 based strategies for the manipulation of susceptibility genes in crop plants for improving plant health. This review is significant in providing first-hand information to improve fundamental understanding of the process which helps in shaping rhizosphere microbiome.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., Lesniewski, R. A., Oakley, B. B., Parks, D. H., Robinson, C. J., et al. (2009) · Applied and Environmental Microbiology · doi:10.1128/aem.01541-09 · Cited by 19,549
Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences
Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., Clemente, J. C., Burkepile, D. E., Vega Thurber, R. L., Knight, R., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2676 · Cited by 9,116
THE ROLE OF ROOT EXUDATES IN RHIZOSPHERE INTERACTIONS WITH PLANTS AND OTHER ORGANISMS
Bais, H. P., Weir, T. L., Perry, L. G., Gilroy, S., & Vivanco, J. M. (2006) · Annual Review of Plant Biology · doi:10.1146/annurev.arplant.57.032905.105159 · Cited by 4,682
Kanehisa, M., Sato, Y., & Morishima, K. (2016) · Journal of Molecular Biology · doi:10.1016/j.jmb.2015.11.006 · Cited by 4,055
Going back to the roots: the microbial ecology of the rhizosphere
Philippot, L., Raaijmakers, J. M., Lemanceau, P., & van der Putten, W. H. (2013) · Nature Reviews Microbiology · doi:10.1038/nrmicro3109 · Cited by 3,883
Meyer, F., Paarmann, D., D'Souza, M., Olson, R., Glass, E., Kubal, M., Paczian, T., Rodriguez, A., Stevens, R., Wilke, A., et al. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-386 · Cited by 3,565
Goecks, J., Nekrutenko, A., Taylor, J., & The Galaxy Team (2010) · Genome Biology · doi:10.1186/gb-2010-11-8-r86 · Cited by 3,453
MEGAN analysis of metagenomic data
Huson, D. H., Auch, A. F., Qi, J., & Schuster, S. C. (2007) · Genome Research · doi:10.1101/gr.5969107 · Cited by 3,312
Structure and functions of the bacterial microbiota of plants
Bulgarelli, D., Schlaeppi, K., Spaepen, S., van Themaat, E. V. L., & Schulze-Lefert, P. (2013) · Annual Review of Plant Biology · doi:10.1146/annurev-arplant-050312-120106 · Cited by 3,308
Cited by
Hakim, S., Naqqash, T., Nawaz, M. S., Laraib, I., Siddique, M. J., Zia, R., Mirza, M. S., & Imran, A. (2021) · Frontiers in Sustainable Food Systems · doi:10.3389/fsufs.2021.617157 · Cited by 507
Metadata
- Authors
- Kumar, A., & Dubey, A.
- Venue
- Journal of Advanced Research
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 24
- Pages
- 337-352
- ISSN
- 2090-1224 (ISSN-L)
- 2090-1232
- OpenAlex
- W3022610004
- Cited by
- 328
- References
- 186
- FWCI
- 23.11
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Rhizosphere microbiome: Engineering bacterial competitiveness for enhancing crop production. https://app.cochat.ai/papers/10.1016/j.jare.2020.04.014
- The paper
- Kumar, A., & Dubey, A. (2020). Rhizosphere microbiome: Engineering bacterial competitiveness for enhancing crop production. Journal of Advanced Research. https://doi.org/10.1016/j.jare.2020.04.014
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.