Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 318

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Genetic Analysis of Drought Resistance in Rice by Molecular Markers: Association between Secondary Traits and Field Performance

Babu, R. Chandra, Nguyen, Bay D., Chamarerk, Varapong, Shanmugasundaram, P., Chezhian, P., Jeyaprakash, P., Ganesh, S. K., Palchamy, A., Sadasivam, S., Sarkarung, S., Wade, L. J., Nguyen, Henry T.·2003·Crop Science

Abstract

Drought stress is the major constraint to rice (Oryza sativa L.) production and yield stability in rainfed ecosystems. Identifying genomic regions contributing to drought resistance will help develop rice cultivars suitable for rainfed regions through molecular marker assisted breeding. Quantitative trait loci (QTLs) linked to plant water stress indicators, phenology and production traits under irrigated and drought stress conditions were mapped by means of a doubled‐haploid (DH) population of 154 rice lines from the cross CT9993‐5‐10‐1‐M/IR62266‐42‐6‐2. The DH lines were subjected to water stress before anthesis in three field experiments at two locations. The DH lines showed significant variation for plant water stress indicators, phenology, plant biomass, yield and yield components under irrigated control and water stress. A total of 47 QTLs were identified for various plant water stress indicators, phenology, and production traits under control and water stress conditions in the field, which individually explained 5 to 59% of the phenotype variation. A region was identified on chromosome 4 that harbored major QTLs for plant height, grain yield, and number of grains per panicle under drought stress. By comparing the coincidence of QTLs with specific traits, we also genetically dissected the nature of association of root traits and capacity for osmotic adjustment with rice production under drought. Root traits had positive correlations with yield and yield components under drought stress. This study demonstrated that the region RG939‐RG476‐RG214 on chromosome 4 identified for root‐related drought resistance component QTLs also had pleiotropic effects on yield traits under stress. Consistent QTLs for drought resistance traits and yield under stress were detected and might be useful for marker‐assisted selection for rainfed rice improvement.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2135/cropsci2003.1457

Cites

39 of 39 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 39 references

Cited by

See all 318

Metadata

Authors
Babu, R. C., Nguyen, B. D., Chamarerk, V., Shanmugasundaram, P., Chezhian, P., Jeyaprakash, P., Ganesh, S. K., Palchamy, A., Sadasivam, S., Sarkarung, S., Wade, L. J., & Nguyen, H. T.
Venue
Crop Science
Publisher
Wiley
Published
2003-07
Volume
43
Issue
4
Pages
1457-1469
ISSN
  • 0011-183X (ISSN-L)
  • 1435-0653
OpenAlex
W1539905669
Cited by
318
References
39
FWCI
10.71
Type
journal article
Language
en
Open access
closed

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: Genetic Analysis of Drought Resistance in Rice by Molecular Markers: Association between Secondary Traits and Field Performance. https://app.cochat.ai/papers/10.2135/cropsci2003.1457
The paper
Babu, R. C., Nguyen, B. D., Chamarerk, V., Shanmugasundaram, P., Chezhian, P., Jeyaprakash, P., Ganesh, S. K., Palchamy, A., Sadasivam, S., Sarkarung, S., Wade, L. J., & Nguyen, H. T. (2003). Genetic Analysis of Drought Resistance in Rice by Molecular Markers: Association between Secondary Traits and Field Performance. Crop Science. https://doi.org/10.2135/cropsci2003.1457

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.