| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
a Crop and Weed Ecol. Group, Wageningen Univ., P.O. Box 430, 6700 AK Wageningen, the Netherlands
b Lab. of Plant Breeding, Wageningen Univ., P.O. Box 386, 6700 AJ Wageningen, the Netherlands
c Plant Dynamics, Englaan 8, 6703 EW Wageningen, the Netherlands
* Corresponding author (xinyou.yin{at}wur.nl)
Received for publication May 1, 2001. Crop modelers and geneticists have developed a vision of their roles in plant breeding from their own perspective. However, to improve breeding efficiency, interdisciplinary collaboration becomes increasingly important. The objective of this paper is to explore opportunities for collaboration between modelers and geneticists in ideotype breeding for high crop yield. The advent of molecular markers enables variation of a complex trait to be dissected into the effects of quantitative trait loci (QTL) and assists the transfer of these QTL into desired cultivars or lines. A recent study in which QTL information was linked to crop modeling has shown that QTL analysis removes part of random errors of measured model input parameters and that QTL information can successfully be coupled with crop models to replace measured parameters. The QTL-based modeling overcomes the limitations in designing ideotypes by using models that ignore the inheritance of model input traits. On the other hand, crop modeling can potentially be a powerful tool to resolve genotype x environment interactions and to dissect yield into characters that might be under simpler genetic control. Based on the complementary aspects of crop modeling and QTL mapping, we propose an approach that integrates marker-assisted selection into model-based ideotype framework to support breeding for high crop yield. For this approach to be effective, there is a need to develop crop models that are capable of predicting yield differences among genotypes in a population under various environmental conditions.
Abbreviations: AFLP, amplification fragment length polymorphism • G x E, genotype x environment interaction • h2, heritability • MAB, marker-assisted breeding • QTL, quantitative trait locus or loci • QTL x E, quantitative trait loci x environment interaction • RFLP, restriction fragment length polymorphism • RIL, recombinant inbred line • SLA, specific leaf area
This article has been cited by other articles:
|
|
 |
|
  V. Letort, P. Mahe, P.-H. Cournede, P. de Reffye, and B. Courtois Quantitative Genetics and Functional-Structural Plant Growth Models: Simulation of Quantitative Trait Loci Detection for Model Parameters and Application to Potential Yield Optimization Ann. Bot., May 1, 2008; 101(8): 1243 - 1254. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
Q. Dong, G. Louarn, Y. Wang, J.-F. Barczi, and P. de Reffye Does the Structure-Function Model GREENLAB Deal with Crop Phenotypic Plasticity Induced by Plant Spacing? A Case Study on Tomato Ann. Bot., May 1, 2008; 101(8): 1195 - 1206. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Y. Xu and J. H. Crouch Marker-Assisted Selection in Plant Breeding: From Publications to Practice Crop Sci., March 19, 2008; 48(2): 391 - 407. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. Tuberosa, S. Salvi, S. Giuliani, M. C. Sanguineti, M. Bellotti, S. Conti, and P. Landi Genome-wide Approaches to Investigate and Improve Maize Response to Drought Crop Sci., December 18, 2007; 47(Supplement_3): S-120 - S-141. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
Y. Ma, B. Li, Z. Zhan, Y. Guo, D. Luquet, P. de Reffye, and M. Dingkuhn Parameter Stability of the Functional-Structural Plant Model GREENLAB as Affected by Variation within Populations, among Seasons and among Growth Stages Ann. Bot., January 1, 2007; 99(1): 61 - 73. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. D. Messina, J. W. Jones, K. J. Boote, and C. E. Vallejos A Gene-Based Model to Simulate Soybean Development and Yield Responses to Environment Crop Sci., January 24, 2006; 46(1): 456 - 466. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 B. Quilot, J. Kervella, M. Genard, and F. Lescourret Analysing the genetic control of peach fruit quality through an ecophysiological model combined with a QTL approach J. Exp. Bot., December 1, 2005; 56(422): 3083 - 3092. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. Takai, Y. Fukuta, T. Shiraiwa, and T. Horie Time-related mapping of quantitative trait loci controlling grain-filling in rice (Oryza sativa L.) J. Exp. Bot., August 1, 2005; 56(418): 2107 - 2118. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
X. Yin, P. C. Struik, J. Tang, C. Qi, and T. Liu Model analysis of flowering phenology in recombinant inbred lines of barley J. Exp. Bot., March 1, 2005; 56(413): 959 - 965. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
X. Yin, P. C. Struik, F. A. van Eeuwijk, P. Stam, and J. Tang QTL analysis and QTL-based prediction of flowering phenology in recombinant inbred lines of barley J. Exp. Bot., March 1, 2005; 56(413): 967 - 976. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Chapman, M. Cooper, D. Podlich, and G. Hammer Evaluating Plant Breeding Strategies by Simulating Gene Action and Dryland Environment Effects Agron. J., January 1, 2003; 95(1): 99 - 113. [Abstract] [Full Text] [PDF]
|
|
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| The SCI Journals | Crop Science | Vadose Zone Journal | |||
| Journal of Natural Resources and Life Sciences Education |
Soil Science Society of America Journal | ||||
| Journal of Plant Registrations | Journal of Environmental Quality |
The Plant Genome | |||
