Crop modeling, QTL mapping, and their complementary role in plant breeding

ABSTRACT massive amounts of information for plant breeding (Stuber et al., 1999; Miflin, 2000), an option of improvingCrop modelers and geneticists have developed a vision of their roles breeding efficiency is to develop and utilize a thoroughin plant breeding from their own perspective. However, to improve breeding efficiency, interdisciplinary collaboration becomes increas- understanding of morphophysiological factors that de-ingly important. The objective of this paper is to explore opportunities termine yield (Bindraban, 1997). However, only in a for collaboration between modelers and geneticists in ideotype breed- limited number of instances has plant physiology led to ing for high crop yield. The advent of molecular markers enables vari- crop improvement; rather, its role in breeding so far ation of a complex trait to be dissected into the effects of quantitative has been to provide possible explanations for the im-trait loci (QTL) and assists the transfer of these QTL into desired provements that have been achieved. Miflin (2000) sug-cultivars or lines. A recent study in which QTL information was linked gested that this situation may change in the future ifto crop modeling has shown that QTL analysis removes part of random the links between physiology and genetics are established.errors of measured model input parameters and that QTL information This suggestion agrees with a main conclusion from ancan successfully be coupled with crop models to replace measured extensive survey (Jackson et al., 1996) that there is aparameters. The QTL-based modeling overcomes the limitations in de-signing ideotypes by using models that ignore the inheritance of model general agreement among plant breeders and physiolo