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MATERIALS AND METHODS
Four agricultural production areas of the Western Cape Province, as indicated in Figures 1 & 2, were included in this study, namely Malmesbury- Moorreesburg (Swartland) – area A, Worcester Robertson (Breede River Valley) – area B, Stellenbosch-Paarl (Winelands) – area C, and Caledon- Swellendam (Overberg) – area D. These areas were used for Lolium spp sampling in 2008 from August until October at 10 localities in each area. Two additional localities with known resistant and susceptible populations of rye grass were also sampled and designated F (Fairview Farm, multiple resistant) and G (Glencairn, susceptible).
Collection points
A simple random sampling strategy, using geographic coordinate points, was followed to ensure representative sample collection. To achieve this, the Random Geographic Coordinate Sampling function of the software program Survey Toolbox© was used to determine 40 randomly selected geographic coordinate points in the main agricultural production areas for grain, fruit, vineyards and mixed agricultural production in the Western Cape. ArcView 8.3 software was used for GIS manipulation of these collection points for easy reference during collection. A Magellan® SporTrak GPS system (with 3 meter accuracy) was utilised in the location of these randomly selected collection points.
Genetic analyses
The first specimen taken at each collection point was used for genetic analyses. Total DNA was extracted from leaves according to the modified CTAB protocol (Senda et al., 2004). DNA was prepared twice for experimental replication in each analysis. The SSR technique is a high-resolution genetic marker analysis used to assess genetic relationships in many species. The polymerase chain reaction (PCR) enables the development of powerful genetic markers for the measurement of genotype variation. By measuring genotype, rather than phenotype, genetic markers avoid complicating environmental effects and provide ideal tools for assessing genetic variation, identifying species and other locally adapted forms, as well as the definition of genetic relationships.
SSRs were analysed using an appropriate selection of the published primer pairs for Lolium, distributed across the genetic map to ensure a random selection of genetic markers. The SSRs were chosen from those, which were known to work across species, and to have the largest number of alleles.
Primers were synthesised with fluorescent labels for subsequent analysis (Madhou et al., 2005). Primer optimisation was undertaken to obtain conditions of selective PCR giving unique products for each primer set. Where appropriate, multiple reactions containing several sets of primers were used (Madhou et al., 2005). When this was completed the analysis of a range of Lolium isolates was undertaken. Alleles were scored by analysis using the ABI Genetic Analyser, and scored using the GenoTyperTM software.
SSR similarities between isolates were calculated by the simple matching coefficient, m/n, where m is the number of alleles matched and n is the total number of alleles. Cluster analysis was performed using the un-weighted pairgroup method with arithmetic averages (UPGMA) (Senda et al., 2005). For each dendrogram, the correlation coefficient between the matrix of genetic similarities and the matrix of co-phenetic values was computed, and data produced by AFLP were compared using the Mantel test (Senda et al., 2005).
Morphological analyses
A second specimen of each sample was collected and morphologically analysed at the Compton Herbarium, Kirstenbosch Botanical Gardens, Cape Town, in order to identify the different species or hybrids.
Pathogenic analyses
A third specimen of each sample was collected and analysed for the soilborne pathogen crown rot at the Agricultural Research Council – Plant Protection Research Institute’s laboratory at Stellenbosch. The number of plants collected from each area for isolation of the fungus varied from three and five for areas F and G, respectively, to 50 each for areas A, B, C and D. The protocol described by Lamprecht et al. (2006) was used for the isolation and identification of crown rot.
Soil analyses
A soil sample was taken at each rye grass collection point and analysed at the Soil Science Laboratory at Elsenburg.
RESULTS AND DISCUSSION
Genetic analyses
SSRs use an appropriate selection of the published primer pairs for Lolium, but as these were only published for Italian -, perennial – and rigid rye grass, all specimens were categorised as one of these species. Therefore, no SSRs have been characterised and published for hybrids among rye grass species, creating contrasts in results between genetic and morphological analyses. However, evaluation of these two methods for identification of Italian rye grass revealed that 90% of specimens occurring as weeds were morphologically
classified as a hybrid.
Huge genetic variation was detected between Italian rye grass weed populations with no identifiable alleles associated with herbicide resistance. This finding was complicated by the number of alleles per locus for grass species which is 8n as opposed to 2n for humans, and the occurrence of
quantitative trait loci (http://wikipedia.org) which occurs in organisms displaying chemical resistance. Rigid rye grass showed similarity in genetic make-up in the eastern part of area D and perennial rye grass to a lesser extent in area B from samples collected at Robertson and Montagu, but there was no consistent correlation between geographical and genetic distance of specimen pairs. Overall, SSRs indicated 47.6% of specimens as rigid rye grass, 42.9% as Italian rye grass and 9.5% as perennial rye grass (Figure 1 & Appendix A, Tables A2-A5). Genetic variation analyses indicated 38% of specimens as rigid rye grass from the areas A and D (Swartland-Overberg), while 9.5% classified as rigid rye grass was sampled in areas B and C (Breede River Valley-Winelands). Only four specimens (9.5%) were classified as perennial rye grass, of which three occurred in areas B and C and a single specimen in area D.
CHAPTER 1 Literature review
-Introduction
-Field assessment of crop residues for allelopathic potential on both crops and weeds.
-Greenhouse and laboratory assessment of rotational crops for allelopathic potential that affects both crops and weeds
-Geographical differentiation and genetic variation of Lolium spp in the Western Cape: identification of the hybrid Lolium multiflorum x perenne and isolation of the pathogen Fusarium pseudograminearum.
-Allelopathic root exudates of the weed Lolium multiflorum x perenne and crops influence plant growth and changes in the soil microbial community
CHAPTER 2 Field assessment of crop residues for allelopathic potential on both crops and weeds.
-Introduction
-Materials and Methods
-Results
-Discussion
-Conclusion
CHAPTER 3 Greenhouse and laboratory assessment of rotational crops for allelopathic potential that affects both crops and weeds
-Introduction
-Materials and Methods
-Results
-Discussion
-Conclusion
CHAPTER 4 Geographical differentiation and genetic variation of Lolium spp in the Western Cape: identification of the hybrid Lolium multiflorum x perenne and isolation of the pathogen Fusarium pseudograminearum
-Introduction
-Materials and Methods
-Results and Discussion
-Conclusion
CHAPTER 5 Allelopathic root exudates of the weed Lolium multiflorum x perenne and crops influence plant growth and changes in the soil microbial community
-Introduction
-Materials and Methods
-Results
-Discussion
-Conclusion
CHAPTER 6 General Discussion and Conclusion
-Crop residues
-Plant leachates
-Geographic variation of rye grass weed type
-Effects of root leachates on micro-organisms
SUMMARY
Acknowledgements
References
Appendix A
