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Variability of virulence of Cercospora zea maydis
There is little evidence that the virulence of Cercospora zea maydis is changing (Thompson, 1987; Wang et al., 1998; Dunkle and Levy, 2000) or that races of the pathogen exist. However, Latterell and Rossi (1974) described variation in certain structural, cultural and metabolic characteristic among the isolates of Cercospora zea maydis and concluded that such variation also may be expressed in pathogenecity or aggressiveness. However, Bair and Ayers (1986) reported variation in components of parasitic fitness (disease deficiency and virulence measured as lesion length). Dunkle and Levy (2000) reported that isolates within both groups I and II of the USA exhibit a range of aggressiveness when inoculated on maize hybrids but disease symptoms were identical and no significant differences were noted in the severity of the disease incited by both groups. They concluded that the substantial genetic difference between the two groups in the USA was not expressed as differential virulence. While Wang et al. (1998) showed that the relative disease severity ratings of hybrids with a range of phenotypes did not change significantly from location to location. They also observed neither of the siblings of Cercospora species had selected maize genotypes which are more susceptible to one than.
Also note that in field trials, significant G x E (hybrid x location) interaction is frequently observed (Bair and Ayers, 1986; Bubeck et al., 1993; Carson, 1997; Huff et al., 1988 and Thompson, 1987). Such variation may be due to differential sensitivities of maize genotypes to environmental factors and thus are predisposed to more severe infection by GLS development. Such sensitivities usually have an impact on disease severity, since the QTL effects associated with resistance to GLS are inconsistent over environment (Bubeck et al., 1993; Wang et al., 1998) resulting from genotype x environmental interaction, random variation within environment or in some cases false positives (Bubeck et al., 1993). Although numerous instances of G x E interactions have been detected by classical quantitative genetics analysis, recent results from RFLP mapping tentatively suggest very little environment by QTLS interaction (Tanksley, 1993).
Variability of Cercospora zea maydis in East Africa
Phyllogenetic analysis using AFLP on the East African population structure of Cercospora zea maydis (Okori et al., 2003) revealed two major clusters. One large cluster comprised 75 % African and USA group II isolates and the second cluster had four USA group I. Similar grouping was observed with RFLP data. Analysis of molecular variation (AMOVA) based on AFLP data revealed a significant population structure between American and African populations (фFst = 0.07). No population structure was detected among African isolates (фFst = 0.01). But a strong and significant structure was obtained between the two pathotypes (фFst = 0.19). The AMOVA using RFLP data showed absence of population structure among African populations (фFst = 0.01). The Okori et al. (2003) study reported that gene flow among African populations was high 0.45. These findings suggest that group II pathotype is predominant in East Africa and gene flow appears to be fundamental evolutionary force accounting for the current genetic structure.
Disease epidemiology and development
GLS disease development is favoured by extended periods of overcast days, warm temperatures and high relative humidity (Beckman and Payne, 1982; Rupe et al., 1982).
High relative humidity, suitable air temperatures, host susceptibility and the presence of a source of inoculum are the conditions necessary to cause a GLS epiphytotic. The absolute rate of change of GLS with respect to time is often best described by the logistic model in which the absolute rate of disease increase dy/dt is a function of ry (1- y) (Jenco 1995; Nutter and Jenco, 1992; Nutter et al., 1994; Ward et al., 1999). Logits = log e (p/1-p) i.e. the natural logarithm of the odds corresponding to the probability p of a specified outcome given the existence of a stated attribute (international dictionary of medicine and biology volume 3 in John Willey and sons 1986) and is conveniently expressed as the difference of the two logits. Thus, the rate of disease development of GLS epidemics is driven by three factors that interact in time and space: (1) the initial amount of inoculum (y); (2) the rate of within season pathogen reproduction (r); and (3) the proportion of healthy tissue remaining to be infected (1-y). It follows that the higher the initial level of inoculum the faster the GLS development will occur with respect to time.
Several studies have shown that environmental factors have tremendous impact on the rate of within season gray leaf spot disease development. In Ohio, deNazareno et al. (1992) reported that the rate of GLS progress (r) ranged from 0.13 to 0.17 logits per day (favourable) for disease development and 0.02 to 0.06 logits per day (less favourable) for disease development. In Iowa, Nutter and Stromberg (1999) obtained some what higher estimates of disease increase with rates of disease development ranging from 0.07 in 1991 (moderate favourable) to 0.28 logits per day in 1992 (extremely favourable). In South Africa, Ward et al. (1999) reported apparent infection rates of up to 0.16 logits per day during 1991/92-rain season (highly favourable) and up to 0.10 logits per day (moderately favourable). It was suggested that higher apparent infection rates in moderately favourable seasons coupled with longer growing seasons help to explain as to why disease severities are generally higher by the end of the growing season in Africa as compared with the United States (Ward et al., 1999; Nutter and Stromberg, 1999).
CHAPTER 1
GENERAL INTRODUCTION
REFERENCES
CHAPTER 2
LITERATURE REVIEW
2.1 The genus Cercospora
2.2 The African population structure of Cercospora zea maydis
2.3 Variability of virulence of Cercospora zea maydis
2.4 Variability of Cercospora zea maydis in East Africa
2.5 Disease epidemiology and development
2.6 Symptoms of GLS on maize plants
2.7 Effects of GLS on maize crop
2.8 Control of the disease
2.9 Early genetic studies for GLS resistance
2.10 QTLs identification for GLS resistance studies
2.11 Linkages between GLS resistance QTL and other disease resistance genes
2.12 Molecular markers
2.13 Types of DNA markers
2.14 Application of molecular marker technology
2.15 The success of MAS
2.16 Limitations in utilizing marker loci-QTLs associations
2.17 Marker loci-QTLs associations for GLS resistance in maize
2.18 Correlations between mean GLS scores over environments
REFERENCES.
CHAPTER 3
THE PREDICTION OF BEST LINE COMBINERS AND HETEROSIS IN TANZANIAN MAIZE BREEDING LINES THROUGH USE OF AMPLIFIED FRAGMENT LENGTH POLYMORPHISM (AFLPs)
Abstract
Introduction
Materials and Methods
Results
Discussion
Conclusions
Acknowledgement
REFERENCES.
CHAPTER 4
ASSOCIATION BETWEEN AFLP BASED GENETIC DISTANCE OF INBREDS AND HYBRID PERFORMANCE IN THE 21 TANZANIAN MAIZE LINES USED IN THIS STUDY.
Abstract
Introduction
Materials and Methods
Plant material and field design
Results
Discussion
Conclusion
Acknowledgement
REFERENCES.
CHAPTER 5
EVALUATION OF HYBRIDS FOR GLS RESISTANCE IN MULTIENVIRONMENTS
Abstract
Introduction
Materials and Methods
Results
Discussion
Conclusions
Acknowledgement
REFERENCES.
CHAPTER 6
PRELIMINARY STUDY ON THE DEVELOPMENT OF CAPS MARKERS FOR FUTURE APPLICATION IN MAS STRATEGIES IN THE SOUTHERN HIGHLAND TANZANIAN MAIZE HYBRID BREEDING PROGRAM
Introduction
Materials and Methods
Results
REFERENCES
CHAPTER 7
CONCLUSION
ANNEXURE
