Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 243

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Role of crop physiology in predicting gene-to-phenotype relationships

Open access
Yin, Xinyou, Struik, Paul C., Kropff, Martin J.·2004·Trends in Plant Science
DOI 10.1016/j.tplants.2004.07.007
Open this paper in CoChat — free account

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 · 10.1016/j.tplants.2004.07.007

Cites

1 of 1 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 1 references

Research works printed but not linked: 42

  1. Paterson, 1988, Resolution of quantitative factors by using a complete linkage map of restriction fragment length polymorphisms, Nature, 335, 721, 10.1038/335721a0 · DOI · Paper page
  2. Lee, 1995, DNA markers and plant breeding programs, Adv. Agron., 55, 265, 10.1016/S0065-2113(08)60542-8 · DOI · Paper page
  3. Ribaut, 1998, Marker-assisted selection: new tools and strategies, Trends Plant Sci., 3, 236, 10.1016/S1360-1385(98)01240-0 · DOI · Paper page
  4. Peleman, 2003, Breeding by design, Trends Plant Sci., 8, 330, 10.1016/S1360-1385(03)00134-1 · DOI · Paper page
  5. Kearsey, 1998, QTL analysis in plants; where are we now?, Heredity, 80, 137, 10.1046/j.1365-2540.1998.00500.x · DOI · Paper page
  6. DeRisi, 1997, Exploring the metabolic and genetic control of gene expression on a genomic scale, Science, 278, 680, 10.1126/science.278.5338.680 · DOI · Paper page
  7. Brem, 2002, Genetic dissection of transcriptional regulation in budding yeast, Science, 296, 752, 10.1126/science.1069516 · DOI · Paper page
  8. Schadt, 2003, Genetics of gene expression surveyed in maize, mouse and man, Nature, 422, 297, 10.1038/nature01434 · DOI · Paper page
  9. Morandini, 2003, Plant biotechnology and breeding: allied for years to come, Trends Plant Sci., 8, 70, 10.1016/S1360-1385(02)00027-4 · DOI
  10. Knight, 2003, A dying breed, Nature, 421, 568, 10.1038/421568a · doi:10.1038/421568a
  11. Kitano, 2002, Systems biology: a brief overview, Science, 295, 1662, 10.1126/science.1069492 · DOI · Paper page
  12. Minorsky, 2003, Frontiers of plant cell biology: signals and pathways, system-based approaches 22nd symposium in plant biology (University of California-Riverside), Plant Physiol., 132, 428, 10.1104/pp.900080 · doi:10.1104/pp.900080
  13. Yin, 1999, AFLP mapping of quantitative trait loci for yield-determining physiological characters in spring barley, Theor. Appl. Genet., 99, 244, 10.1007/s001220051230 · DOI
  14. Yin, 2000, Coupling estimated effects of QTLs for physiological traits to a crop growth model: predicting yield variation among recombinant inbred lines in barley, Heredity, 85, 539, 10.1046/j.1365-2540.2000.00790.x · DOI
  15. Reymond, 2003, Combining quantitative trait loci analysis and an ecophysiological model to analyze the genetic variability of the responses of maize leaf growth to temperature and water deficit, Plant Physiol., 131, 664, 10.1104/pp.013839 · DOI · Paper page
  16. Kropff, 2002, Developments in crop ecology, NJAS-Wageningen J. Life Sci., 50, 223, 10.1016/S1573-5214(03)80008-8 · DOI
  17. Loomis, 1979, Explanatory models in crop physiology, Annu. Rev. Plant Physiol., 30, 339, 10.1146/annurev.pp.30.060179.002011 · DOI · Paper page
  18. Tardieu, 2003, Virtual plants: modelling as a tool for the genomics of tolerance to water deficit, Trends Plant Sci., 8, 9, 10.1016/S1360-1385(02)00008-0 · DOI · Paper page
  19. Chapman, 2003, Evaluating plant breeding strategies by simulating gene action and dryland environment effects, Agron. J., 95, 99, 10.2134/agronj2003.0099 · DOI · Paper page
  20. Sinclair, 2004, Crop transformation and the challenge to increase yield potential, Trends Plant Sci., 9, 70, 10.1016/j.tplants.2003.12.008 · DOI · Paper page
  21. Boote, 2001, Physiology and modelling of traits in plants: implications for genetic improvement, Agric. Syst., 70, 395, 10.1016/S0308-521X(01)00053-1 · DOI · Paper page
  22. Hammer, 2002, Future contributions of crop modeling – from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement, Eur. J. Agron., 18, 15, 10.1016/S1161-0301(02)00093-X · DOI · Paper page
  23. Slafer, 2003, Genetic basis of yield as viewed from a crop physiologist's perspective, Ann. Appl. Biol., 142, 117, 10.1111/j.1744-7348.2003.tb00237.x · DOI · Paper page
  24. De Pury, 1997, Simple scaling of photosynthesis from leaves to canopies without the errors of big-leaf models, Plant Cell Environ., 20, 537, 10.1111/j.1365-3040.1997.00094.x · DOI · Paper page
  25. Cannell, 2000, Modelling the components of plant respiration: some guiding principles, Ann Bot., 85, 45, 10.1006/anbo.1999.0996 · DOI · Paper page
  26. Yin, 2003, Some quantitative relationships between leaf area index and canopy nitrogen content and distribution, Ann Bot., 91, 893, 10.1093/aob/mcg096 · doi:10.1093/aob/mcg096
  27. Welch, 2003, Genetic neural network model of flowering time control in Arabidopsis thaliana, Agron. J., 95, 71, 10.2134/agronj2003.0071 · DOI
  28. Koornneef, 1998, Genetic control of flowering time in Arabidopsis, Annu. Rev. Plant Physiol. Plant Mol. Biol., 49, 345, 10.1146/annurev.arplant.49.1.345 · DOI · Paper page
  29. Hedden, 2003, The genes of the Green Revolution, Trends Genet., 19, 5, 10.1016/S0168-9525(02)00009-4 · DOI · Paper page
  30. Griffiths, 2003, The evolution of CONSTANS-like gene families in barley, rice and Arabidopsis, Plant Physiol., 131, 1855, 10.1104/pp.102.016188 · DOI · Paper page
  31. Zhu, 2004, Would transformation of C3 crop plants with foreign Rubisco increase productivity? A computational analysis extrapolating from kinetic properties to canopy photosynthesis, Plant Cell Environ., 27, 155, 10.1046/j.1365-3040.2004.01142.x · DOI · Paper page
  32. Hammer, 2004, On systems thinking, systems biology, and the in silico plants, Plant Physiol., 134, 909, 10.1104/pp.103.034827 · DOI
  33. Prioul, 1997, Dissecting complex physiological functions through the use of molecular quantitative genetics, J. Exp. Bot., 48, 1151, 10.1093/jxb/48.6.1151 · DOI
  34. Koornneef, 2001, Changing paradigms in plant breeding, Plant Physiol., 125, 156, 10.1104/pp.125.1.156 · DOI
  35. Yin, 2002, Use of component analysis in QTL mapping of complex crop traits: a case study on yield in barley, Plant Breed., 121, 314, 10.1046/j.1439-0523.2002.729117.x · doi:10.1046/j.1439-0523.2002.729117.x
  36. Zhou, 2001, Genetic dissection of heading time and its components in rice, Theor. Appl. Genet., 102, 1236, 10.1007/s001220100539 · doi:10.1007/s001220100539
  37. Maloof, 2003, QTL for plant growth and morphology, Curr. Opin. Plant Biol., 6, 85, 10.1016/S1369526602000080 · DOI
  38. Yan, 1998, Molecular dissection of developmental behavior of plant height in rice (Oryza sativa L.), Genetics, 150, 1257, 10.1093/genetics/150.3.1257 · DOI · Paper page
  39. Wu, 2002, Mapping of quantitative trait loci based on growth models, Theor. Appl. Genet., 105, 1043, 10.1007/s00122-002-1052-8 · doi:10.1007/s00122-002-1052-8
  40. Ma, 2002, Functional mapping of quantitative trait loci underlying the character process: a theoretical framework, Genetics, 161, 1751, 10.1093/genetics/161.4.1751 · DOI · Paper page
  41. Yin, 1999, The role of ecophysiological models in QTL analysis: the example of specific leaf area in barley, Heredity, 82, 415, 10.1038/sj.hdy.6885030 · DOI
  42. Piepho, 2000, A mixture-model approach to mapping quantitative trait loci in barley on the basis of multiple environment data, Genetics, 156, 2043, 10.1093/genetics/156.4.2043 · DOI

Cited by

See all 243

Metadata

Authors
Yin, X., Struik, P. C., & Kropff, M. J.
Venue
Trends in Plant Science
Publisher
Elsevier BV
Published
2004-09
Volume
9
Issue
9
Pages
426-432
ISSN
1360-1385 (ISSN-L)
DOI
10.1016/j.tplants.2004.07.007
OpenAlex
W2167657683
Cited by
243
References
1
FWCI
1.27
Type
journal article
Language
en
Open access
green
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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: Role of crop physiology in predicting gene-to-phenotype relationships. https://app.cochat.ai/papers/10.1016/j.tplants.2004.07.007
The paper
Yin, X., Struik, P. C., & Kropff, M. J. (2004). Role of crop physiology in predicting gene-to-phenotype relationships. Trends in Plant Science. https://doi.org/10.1016/j.tplants.2004.07.007

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.