The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Breeding high-yielding drought-tolerant rice: genetic variations and conventional and molecular approaches
Open accessAbstract
The increased occurrence and severity of drought stress have led to a high yield decline in rice in recent years in drought-affected areas. Drought research at the International Rice Research Institute (IRRI) over the past decade has concentrated on direct selection for grain yield under drought. This approach has led to the successful development and release of 17 high-yielding drought-tolerant rice varieties in South Asia, Southeast Asia, and Africa. In addition to this, 14 quantitative trait loci (QTLs) showing a large effect against high-yielding drought-susceptible popular varieties were identified using grain yield as a selection criterion. Six of these (qDTY 1.1 , qDTY 2.2 , qDTY 3.1 , qDTY 3.2 , qDTY 6.1 , and qDTY 12.1 ) showed an effect against two or more high-yielding genetic backgrounds in both the lowland and upland ecosystem, indicating their usefulness in increasing the grain yield of rice under drought. The yield of popular rice varieties IR64 and Vandana has been successfully improved through a well-planned marker-assisted backcross breeding approach, and QTL introgression in several other popular varieties is in progress. The identification of large-effect QTLs for grain yield under drought and the higher yield increase under drought obtained through the use of these QTLs (which has not been reported in other cereals) indicate that rice, because of its continuous cultivation in two diverse ecosystems (upland, drought tolerant, and lowland, drought susceptible), has benefited from the existence of larger genetic variability than in other cereals. This can be successfully exploited using marker-assisted breeding.
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
Empirical threshold values for quantitative trait mapping.
Churchill, G. A., & Doerge, R. W. (1994) · Genetics · doi:10.1093/genetics/138.3.963 · Cited by 4,935
Michelmore, R. W., Paran, I., & Kesseli, R. V. (1991) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.88.21.9828 · Cited by 4,535
Map Manager QTX, cross-platform software for genetic mapping
Manly, K. F., Cudmore, & Meer, J. M. (2001) · Mammalian Genome · doi:10.1007/s00335-001-1016-3 · Cited by 1,225
Quantitative Trait Loci and Crop Performance under Abiotic Stress: Where Do We Stand?: Table I.
Collins, N. C., Tardieu, F., & Tuberosa, R. (2008) · PLANT PHYSIOLOGY · doi:10.1104/pp.108.118117 · Cited by 559
A Large‐Effect QTL for Grain Yield under Reproductive‐Stage Drought Stress in Upland Rice
Bernier, J., Kumar, A., Ramaiah, V., Spaner, D., & Atlin, G. (2007) · Crop Science · doi:10.2135/cropsci2006.07.0495 · Cited by 480
Self-citationDrought resistance in crops with emphasis on rice
Kirkham, M. B. (1984) · Field Crops Research · doi:10.1016/0378-4290(84)90066-2 · Cited by 422
Yang, J., Hu, C., Hu, H., Yu, R., Xia, Z., Ye, X., & Zhu, J. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btm494 · Cited by 412
Vikram, P., Swamy, B. M., Dixit, S., Ahmed, H. U., Teresa Sta Cruz, M., Singh, A. K., & Kumar, A. (2011) · BMC Genetics · doi:10.1186/1471-2156-12-89 · Cited by 391
Self-citationPrice, A. H., Cairns, J. E., Horton, P., Jones, H. G., & Griffiths, H. (2002) · Journal of Experimental Botany · doi:10.1093/jexbot/53.371.989 · Cited by 386
Response to Direct Selection for Grain Yield under Drought Stress in Rice
Venuprasad, R., Lafitte, H. R., & Atlin, G. N. (2007) · Crop Science · doi:10.2135/cropsci2006.03.0181 · Cited by 383
Cited by
Climate Change, Drought and Human Health in Canada
Yusa, A., Berry, P., J.Cheng, J., Ogden, N., Bonsal, B., Stewart, R., & Waldick, R. (2015) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph120708359 · Cited by 174
Dixit, S., Singh, A., Sandhu, N., Bhandari, A., Vikram, P., & Kumar, A. (2017) · Molecular Breeding · doi:10.1007/s11032-017-0737-2 · Cited by 96
Self-citation
Metadata
- Authors
- Kumar, A., Dixit, S., Ram, T., Yadaw, R. B., Mishra, K. K., & Mandal, N. P.
- Venue
- Journal of Experimental Botany
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-09-09
- Volume
- 65
- Issue
- 21
- Pages
- 6265-6278
- ISSN
- 0022-0957 (ISSN-L)
- 1460-2431
- OpenAlex
- W2127237200
- Cited by
- 423
- References
- 38
- FWCI
- 22.71
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: Breeding high-yielding drought-tolerant rice: genetic variations and conventional and molecular approaches. https://app.cochat.ai/papers/10.1093/jxb/eru363
- The paper
- Kumar, A., Dixit, S., Ram, T., Yadaw, R. B., Mishra, K. K., & Mandal, N. P. (2014). Breeding high-yielding drought-tolerant rice: genetic variations and conventional and molecular approaches. Journal of Experimental Botany. https://doi.org/10.1093/jxb/eru363
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.