1. ¹Laboratory of Theoretical Production Ecology, P.O. 430, 6700 AK Wageningen, The Netherlands
2. ²Laboratory of Plant Breeding, Agricultural University, P.O. 430, 6700 AK Wageningen, The Netherlands

Correspondence: Xinyou Yin, E-mail: x.yin@ab.dlo.nl

³Present address: DLO-Research Institute for Agrobiology and Soil Fertility, PO Box 14, 6700 AA Wageningen, The Netherlands.

Received 16 September 1998; Accepted 1 December 1998.

Abstract

Crop modelling has so far contributed little to the genetic analysis of a quantitative trait. This study illustrates how a simple model for crop phenological development, which assumes that crop development rate is affected by daily effective temperature, can assist the identification of Quantitative Trait Loci (QTLs), using specific leaf area (SLA) in barley as an example. The SLA was measured in a field experiment six times during the growing season of 94 recombinant inbred lines (RILs) derived from a cross between cultivars Prisma and Apex. Of the six measurements, one was conducted at the same physiological age for all RILs (at flowering), four were undertaken at specific chronological days prior to flowering, and the last one was taken at 14 days after flowering. When the measured SLA was directly used as the quantitative trait, one to three QTLs were detected for SLA at each measurement time. The major dwarfing gene denso segregating in the population was found to affect SLA strongly at all measurement times except at flowering. If SLA of the different RILs was corrected for differences in physiological age at the time of measurement, by the use of the crop development model, QTLs were detected for SLA at only three stages. Furthermore, the effect of the denso gene was no longer significant during the preflowering stages. The effect of the denso gene detected in the first instance was therefore the consequence of its direct effect on the duration of the preflowering period. This demonstrates the important role that crop development models can play in QTL analysis of a trait that varies with developmental stage. Potential uses of ecophysiological crop growth models in QTL analysis are briefly discussed.