Parasitic¯owering weeds of the genus Striga (Scrophulariaceae) cause substantial losses in sorghum [Sorghum bicolor (L.) Moench] production in sub-Saharan Africa. Striga-resistant sorghum cultivars could be a major component of integrated striga management, if resistance was available in adapted, productive germplasm. In this paper we review methodologies for breeding striga-resistant sorghums. The agar-gel assay is an excellent tool to screen host genotypes in the laboratory for low production of the striga seed germination stimulant. Further laboratory assays are needed which allow the non-destructive, rapid and inexpensive evaluation of individual plants for additional resistance mechanisms. Field screening for striga resistance is hampered by high microvariability in African soils, heterogeneity of natural infestations, and concomitant large environmental effects on striga emergence. An improved ®eld testing methodology should include one or several of the following practices: ®eld inoculation with striga seeds; appropriate experimental design including elevated replication number; speci®c plot layout; use of appropriate susceptible and resistant checks; evaluation in adjacent infested and uninfested plots; and the use of selection indices derived from emerged striga counts, striga vigor, and grain yield or a host plant damage score. Due to the extreme variability of the parasite and signi®cant genotypeÂenvironment interaction effects, multi-locational screening is recommended to obtain materials with stable performance. Additional strategies include: careful de®nition of the target environments; determination of the most important selection traits in each target environment; characterization of crop germplasm and improvement of available sources of resistance for better agronomic performance; transfer and pyramiding of resistance genes into adapted, farmer-selected cultivars; development of striga-resistant parent lines for hybrid or synthetic cultivars; and development of random-mating populations with multiple sources of resistance. The development of markerassisted selection techniques for broad-based, polygenic striga resistance is underway. This approach is particularly promising because striga resistance tests are dif®cult, expensive, and sometimes unreliable; the parasite is quarantined; and some resistance genes are recessive. Transgenic, herbicide-tolerant sorghums could contribute to an immediate, cost-effective control of striga by herbicides, but such cultivars are not yet available. The selection of sorghum cultivars with speci®c adaptation to integrated striga management approaches could contribute to sustainable sorghum production in striga-infested areas of sub-Saharan Africa. #

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Molecular markers for resistance of sorghum to the hemi-parasitic weed Striga hermonthica were mapped in two recombinant inbred populations (RIP-1, and -2) of F(3:5) lines developed from the crosses IS9830 x E36-1 (1) and N13 x E36-1 (2). The resistant parental lines were IS9830 and N13; the former is characterized by a low stimulation of striga seed germination, the latter by "mechanical" resistance. The genetic maps of RIP-1 and RIP-2 spanned 1,498 cM and 1,599 cM, respectively, with 137 and 157 markers distributed over 11 linkage groups. To evaluate striga resistance, we divided each RIP into set 1 (116 lines tested in 1997) and set 2 (110 lines evaluated in 1998). Field trials were conducted in five environments per year in Mali and Kenya. Heritability estimates for area under the striga number progress curve (ASNPC) in sets 1 and 2 were respectively 0.66 and 0.74 in RIP-1 0.81 and 0.82 in RIP-2. Across sites, composite interval mapping detected 11 QTL (quantitative trait loci) and nine QTL in sets 1 and 2 of RIP-1, explaining 77% and 80% of the genetic variance for ASNPC, respectively. The most significant RIP-1 QTL corresponded to the major-gene locus lgs (low stimulation of striga seed germination) in linkage group I. In RIP-2, 11 QTL and nine QTL explained 79% and 82% of the genetic variance for ASNPC in sets 1 and 2, respectively. Five QTL were common to both sets of each RIP, wtih the resistance alleles deriving from IS9830 or N13. Since their effects were validated across environments, years and independent RIP samples, these QTL are excellent candidates for marker-assisted selection.

Breeding for high yielding Sorghum bicolor varieties with effective resistance and tolerance against the hemi-parasitic weed Striga hermonthica requires suitable selection measures for both characteristics. The objective of this research was to constitute a set of practical selection measures that contain independent, reliable and discriminative criteria for resistance and tolerance. Ten sorghum genotypes were grown in the field with and without Striga infestation in a split-plot design in 3 successive years (2001-2003) using different Striga infestation levels (low, high and intermediate). Resistance against Striga in the below-ground stages was determined separately in an agar-gel assay and a pot trial. The addition of Striga-free control plots facilitated the calculation of the relative yield loss, which represents the result of resistance and tolerance combined. Correlation analysis indirectly demonstrated that both resistance and tolerance are important yield determining traits under Striga infestation. Tolerance was relatively more important under low Striga infestation levels, whereas resistance was relatively more important at high infestation levels. With respect to resistance, both the area under the Striga number progress curve (ASNPC) and maximum above-ground Striga number (NS max) turned out to be discriminative and consistent selection measures. Both measures also corresponded well with the expression of resistance during below-ground stages of the parasite. It proved more difficult to arrive at a satisfactory measure for tolerance. Inclusion of Striga-free plots is an essential step for the determination of tolerance, but in itself not sufficient. It provides a basis for the determination of the relative yield loss, which then needs to be corrected for differences in infection level resulting from genotypic differences in resistance. A linear correction for infection level disregards the density dependency of the relative yield loss function. It is expected that clarification of the relation between Striga infection level and yield loss, provides a solid basis for the development of unambiguous tolerance measures in the field. This will enable the breeder to select for resistance and tolerance separately, which is likely to result in the optimum combination of both defence mechanisms.