The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Lights, camera, action: high-throughput plant phenotyping is ready for a close-up
Open accessAbstract
Anticipated population growth, shifting demographics, and environmental variability over the next century are expected to threaten global food security. In the face of these challenges, crop yield for food and fuel must be maintained and improved using fewer input resources. In recent years, genetic tools for profiling crop germplasm has benefited from rapid advances in DNA sequencing, and now similar advances are needed to improve the throughput of plant phenotyping. We highlight recent developments in high-throughput plant phenotyping using robotic-assisted imaging platforms and computer vision-assisted analysis tools.
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Cites
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288
Yield trends are insufficient to double global crop production by 2050
Ray, D. K., Mueller, N. D., West, P. C., & Foley, J. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066428 · Cited by 3,415
Field high-throughput phenotyping: the new crop breeding frontier
Araus, J. L., & Cairns, J. E. (2014) · Trends in Plant Science · doi:10.1016/j.tplants.2013.09.008 · Cited by 1,817 · cited 1×
“[8].”
Cited by
Plant–Pathogen Warfare under Changing Climate Conditions
Velásquez, A. C., Castroverde, C. D. M., & He, S. Y. (2018) · Current Biology · doi:10.1016/j.cub.2018.03.054 · Cited by 970
PlantCV v2: Image analysis software for high-throughput plant phenotyping
Gehan, M. A., Fahlgren, N., Abbasi, A., Berry, J. C., Callen, S. T., Chavez, L., Doust, A. N., Feldman, M. J., Gilbert, K. B., Hodge, J. G., et al. (2017) · PeerJ · doi:10.7717/peerj.4088 · Cited by 365
Self-citationEnhancing genetic gain in the era of molecular breeding
Xu, Y., Li, P., Zou, C., Lu, Y., Xie, C., Zhang, X., Prasanna, B. M., & Olsen, M. S. (2017) · Journal of Experimental Botany · doi:10.1093/jxb/erx135 · Cited by 336
Close range hyperspectral imaging of plants: A review
Mishra, P., Asaari, M. S. M., Herrero-Langreo, A., Lohumi, S., Diezma, B., & Scheunders, P. (2017) · Biosystems Engineering · doi:10.1016/j.biosystemseng.2017.09.009 · Cited by 319
From Microbiome to Traits: Designing Synthetic Microbial Communities for Improved Crop Resiliency
de Souza, R. S. C., Armanhi, J. S. L., & Arruda, P. (2020) · Frontiers in Plant Science · doi:10.3389/fpls.2020.01179 · Cited by 281
Metadata
- Authors
- Fahlgren, N., Gehan, M. A., & Baxter, I.
- Venue
- Current Opinion in Plant Biology
- Publisher
- Elsevier BV
- Published
- 2015-04
- Volume
- 24
- Pages
- 93-99
- ISSN
- 1369-5266 (ISSN-L)
- OpenAlex
- W1985870845
- Cited by
- 703
- References
- 3
- FWCI
- 8.91
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Fahlgren, N., Gehan, M. A., & Baxter, I. (2015). Lights, camera, action: high-throughput plant phenotyping is ready for a close-up. Current Opinion in Plant Biology. https://doi.org/10.1016/j.pbi.2015.02.006
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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