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Integrating spatial variations in the vineyard to enhance quantitative trait locus (QTL) detection

French vineyards are often located on the least fertile lands, generally more heterogeneous than lands devoted to food crops. The detection of quantitative trait loci (QTLs) is all the more precise, as the number of genotypes studied is high, but increasing the size of experimental plots means taking the risk of exploring more spatial heterogeneity. Designing randomized blocks experiments is a classical way to overcome this difficulty. However, when several hundred genotypes are studied, this not only requires more land but is also time consuming. Another approach is to take into account the spatial heterogeneity when searching for QTLs. We performed QTL detection for variables corrected for spatial heterogeneity in the progeny of a 'Riesling' (RI) × 'Gewurztraminer' (GW) cross to evaluate the potential of such an approach. We show that “mapping” methods can improve QTL detection for grapevine water status (δ13C) and pruning weight. QTLs for vegetative indices measured with the portable fluorimeter Multiplex® were, however, not better detected after taking into account the spatial heterogeneity. This study shows that QTL detection can be improved when correcting raw data for spatial heterogeneity.