The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Synergy of Empirical Breeding, Marker‐Assisted Selection, and Genomics to Increase Crop Yield Potential
Abstract
This paper was presented as part of the symposium entitled “Post‐Green Revolution Trends in Crop Yield Potential: Increasing, Stagnant or Greater Resistance to Stress.” In this presentation, we have focused on (i) uses of marker technology in determining the genetic basis of phenotypic expression and the manipulation of phenotypic variation in plants. This included the use of markers in understanding heterosis, in attempts to improve hybrid predictions, in quantitative trait locus (QTL) identification and mapping, in marker‐assisted selection (MAS), and in enhancing breeding success in the development of improved lines and hybrids; (ii) the role of genomics in developing a precise understanding of the genetic basis of phenotypic expression which will then provide more precision in the manipulation of phenotypic variation; and (iii) some attempts to integrate marker technology and genomics into empirical breeding strategies. In addition, we have focused on what has been successful as well as what has fallen short of expectations, and have suggested some of the possible reasons for the lack of success. Because of page limitations, we could not include an exhaustive review of the plant literature and have limited many of our examples to investigations in maize (Zea mays L).
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Citations
Cites
Prediction of Maize Single‐Cross Performance Using RFLPs and Information from Related Hybrids
Bernardo, R. (1994) · Crop Science · doi:10.2135/cropsci1994.0011183x003400010003x · Cited by 379
Cited by
Structure of linkage disequilibrium and phenotypic associations in the maize genome
Remington, D. L., Thornsberry, J. M., Matsuoka, Y., Wilson, L. M., Whitt, S. R., Doebley, J., Kresovich, S., Goodman, M. M., & Buckler, E. S. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.201394398 · Cited by 1,256
Hasan, N., Choudhary, S., Naaz, N., Sharma, N., & Laskar, R. A. (2021) · Journal of Genetic Engineering and Biotechnology · doi:10.1186/s43141-021-00231-1 · Cited by 513
TUBEROSA, R. (2002) · Annals of Botany · doi:10.1093/aob/mcf134 · Cited by 397
Molecular Markers and Marker-Assisted Breeding in Plants
Jiang, G.-L. (2013) · Plant Breeding from Laboratories to Fields · doi:10.5772/52583 · Cited by 278
A gene-based model to simulate soybean development and yield responses to environment
Messina, C. D., Jones, J. W., Boote, K. J., & Vallejos, C. E. (2006) · Crop Science · doi:10.2135/cropsci2005.04-0372 · Cited by 145
Metadata
- Authors
- Stuber, C. W., Polacco, M., & Lynn, M.
- Venue
- Crop Science
- Publisher
- Wiley
- Published
- 1999-11
- Volume
- 39
- Issue
- 6
- Pages
- 1571-1583
- ISSN
- 0011-183X (ISSN-L)
- 1435-0653
- OpenAlex
- W2071193504
- Cited by
- 227
- References
- 1
- FWCI
- 3.55
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Synergy of Empirical Breeding, Marker‐Assisted Selection, and Genomics to Increase Crop Yield Potential. https://app.cochat.ai/papers/10.2135/cropsci1999.3961571x
- The paper
- Stuber, C. W., Polacco, M., & Lynn, M. (1999). Synergy of Empirical Breeding, Marker‐Assisted Selection, and Genomics to Increase Crop Yield Potential. Crop Science. https://doi.org/10.2135/cropsci1999.3961571x
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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.