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Importance of cassava as a staple food in sub–Sahara Africa, with focus on East Africa
Cassava is a woody shrub, considered as an important staple food crop in many countries of tropical and subtropical areas (Legg et al. 2006). Cassava originates from South America, it was introduced in Africa by the Portuguese during the 16th century on the west coast of Africa (Jones 1959) and later was introduced in East Africa via Madagascar and Zanzibar (Fauquet and Fargette
1990). This crop is produced in 102 countries with a majority of them found in Asia and Africa (FAOstat 2017). Its adaptation to marginal land makes it affordable for most subsistence farmers in Africa, because of the low cost of production. Cassava’s ability to tolerate drought makes it a food security crop (Jarvis et al. 2012, Reincke et al. 2018) and feeds more than 800 million people, majoriy of them are from sub–Sahara Africa (FAOstat 2017).
Cassava is valued for its different usages (Fig. 1.1): the roots are used as a source of carbohydrate, leaves as a leaf vegetable nutritionally important in fibre, vitamin A and B, protein and essential amino acids, while the stem as a source of fuel as well as planting material for the next season (Zhu et al. 2015). The roots can be harvested in piecemeal manner which provides food throughout the year as fresh meal, or it can be dried and processed into flour. The cassava flour can be sold in local markets or processed into value added food products such as in bakery (Hillocks et al. 2002).
Nigeria, Democratic Republic of Congo, Thailand, Indonesia, Brazil, Ghana, Angola, Cambodia, Viet Nam and Mozambique are among the 10 largest cassava producers in the world. Majority of these countries are from Southeast Asia and West Africa (FAOstat 2017). In Asia, cassava is mainly used for starch production or to feed animals, while in Africa cassava is used for human consumption (Howeler et al. 2013, Parmar et al. 2017). Africa produces 57% of the global cassava production with more than 20% coming from Nigeria alone (Bennett 2015, FAOstat 2017).
In East Africa, Tanzania is the leading producer. The crop is grown in different agroecological zones, but the main production areas include the Lake Zone (Mwanza Mara and Shinyanga), Coast regions (Lindi, Mtwara, Tanga, Zanzibar), Kigoma and Ruvuma areas. Being the third most important crop in the country, it contributes to 7.8% of the total calories in Tanzanian diet after maize and rice (Cochrane and D’Souza 2015).
Uganda is the second largest cassava producer in East Africa, and the crop also ranks second in importance after plantain (Haggblade and Dewina 2010). Per capita consumption the crop accounts for about 11% of calories intake (Haggblade and Dewina 2010). Cassava is grown in all regions of Uganda normally in mixed farming systems and about 9% of farmers grow the crop as a cash crop (Otim-Nape and Zziwa 1990).
Malawi is the largest cassava producer in Southern African zone. The crop ranks second after maize and as being drought resistance, it gained popularity following drought intervention in late and mid 1990s when maize was reduced by half of its normal production (Kambewa 2010, Minot 2010). The crop feeds 30 to 40% of Malawian population (Chipeta and Bokosi 2013) and also contributes to 7% of calories intake per capita consumption (Minot 2010).
Despite increases in cultivated land, significant reductions in cassava yields have been reported (FAOstat 2017). Cassava yield has the potential to reach up to 80.0 tonnes per ha under optimal conditions, however, the World average yield is only 12.2 tonnes, with much of the low productivity coming from sub–Saharan Africa (Howeler et al. 2013). Several factors attribute to this loss among them are poor soil fertility, early water stress, altitude, poor agriculture practices, inadequate extension services, poor processing as well as pests and diseases (Legg 1999, Moyo et al. 2004, Fermont et al. 2009, Patil et al. 2015, Reincke et al. 2018). Among the diseases, CMD and CBSD are the most prominent together with the insect pest whiteflies.
Whiteflies
Whiteflies are sap sucking insects. The name whitefly is derived from their white appearance due to the deposition of fine white powdery wax over their four wings and body (Fig.1.2). Whiteflies are not true flies, they are in the same order of insect as scales, aphids and mealy bugs of the order Hemiptera.
They belong to the Aleyrodidae family which is further divided into two sub families: Aleurodicinae which include, Aspidiotus destructor (Mackie) and Aleurodicus dispersus (Russell) and Aleyrodinae. More than 1550 species of whiteflies have been classified (Ko 2001, Martin 2003). Aleyrodinae ranks the largest sub family with around 140 genera, among them one of economic importance pest and vector known as B. tabaci.
Bemisia tabaci classification
The first B. tabaci specimen was found in Greece (1897), it was collected on tobacco and was described as a new genus, Bemisia inconspicua as a « type » species (Quaintance and Baker 1914, Gill 1990). It’s only in 1957 that this species, along with a dozen other species of whiteflies, were put synonimized (grouping of species) in the same taxon: Bemisia tabaci (Russell 1957).
The classification of whiteflies is based on the morphology of the last larval stage or pupa than on adults, which differ very little morphologically (Gill 1990). The observation of a large morphological variability of the last larval stage, related to the physical characteristics of the host plant, led the taxonomists to synonymize numerous species. Nevertheless, the subsequent variations reported in pupal morphology depended on host plant (Russell 1948), leaf surface character (Mound 1963), atmosphere (temperature) as well as surrounding environment (Sundararaj and David 1992).
Due to that discrepancy some populations were not differentiated. Other factors were considered in classifying populations which were based on life history (Costa and Brown 1991, Viscarret et al. 2003), induction of physiological disorders (Costa and Brown 1991, Cohen et al. 1992), mating behaviour (Bethke et al. 1991), or insecticide resistance (Dittrich et al. 1990, Costa and Brown 1991). This is the period where the concept of biotypes or races was introduced (Brown et al. 1995a). As a result, several studies considered B. tabaci as a species complex (Perring et al. 1993, Bellows Jr et al. 1994, Oliveira et al. 2001, De Barro et al. 2011, De Barro 2012, Lee et al. 2013).
Different approaches have been used to study population diversity and differentiation within each of the species complex, but the first true taxonomic differentiation between B. tabaci species was performed with the help of molecular tools. Those tools included several molecular markers such as polymerase chain reaction (PCR) amplified fragment length polymorphism (AFLP), or AFLP-PCR, the technique of PCR–restriction fragment length polymorphism (PCR-RFLP), microsatellite markers, Rad-seq, or sequencing of mitochondrial markers (Cytochrome oxidase 1, mtCOI) (Costa and Brown 1991, Wool et al. 1991, De Barro et al. 2003, De Barro et al. 2005, Sseruwagi et al. 2005, Delatte et al. 2006, Ma et al. 2007, Hadjistylli et al. 2016, Wosula et al. 2017).
Using mtCOI, 11 major B. tabaci genetic groups with 24 potential species were described with 3.5% of nucleotides of divergence between the morpho-species (Boykin et al. 2007, Dinsdale et al. 2010). The number of cryptic species increased from 24 to 28 (De Barro et al (2011), to 31 (Lee et al., 2013) and currently believed to be over 40 (Mugerwa et al., 2018). Lee et al., (2013) observed that the 31 species revealed an average of intraspecific genetic divergence of 1.2% (0.2 to 3.9%) and an average of interspecific genetic divergence of 15.7% (4.2 to 24.1%). These authors therefore proposed to raise the « threshold bar » samples of 3.5% of the species within the complex to 4% (Fig. 1.3).
Several species have been identified in SSA (see section 1.9) (Fig. 1.4). Although some B. tabaci species such as MEAM1 and Med live in sympatry, biologically, they cannot reproduce (De Barro et al. 2000, Saleh et al. 2012). Lack of hybridization between other B. tabaci species were also reported previously (Maruthi et al. 2004, Omondi et al. 2005b, Liu et al. 2007, Wang et al. 2010, Xu et al. 2010, Tsueda and Tsuchida 2011, Saleh et al. 2012).
Molecular tools used for molecular taxonomic issues
(a) Amplified fragment length polymorphism (AFLP)
This method relies on the presence or absence of polymorphism within restriction enzyme sites. For example, the procedure was used to differentiate fall army worms strains collected from corn and forage grasses at Louisiana State (McMichael and Prowell 1999). Variation of Med and MEAM1 species was accessed using AFLP from populations in Brazil and China Cervera (2000). The AFLP technique was also used to study genetic relationship among B. tabaci species, as well as differentiating MEAM I and Med in China (Guo et al. 2012).
(b) Restriction fragment length polymorphism (RFLP)
In this technique polymorphism is determined by variation on the length of DNA fragment produced by restriction enzymes (Fig. 1.5). For instance, the method used to identify molecular phylogeny and evolutionary relationships among four mosquito (Diptera: Culicidae) species from India (Sharma et al. 2013). Similar approach was used to understand the genetic diversity of B. tabaci collected from DRC, Malawi, Tanzania and Uganda (Ghosh 2015). The RFLP technique was used in other studies to understand genetic diversity of different B. tabaci species (Bosco et al. 2006, Shoorcheh et al. 2008, Rocha et al. 2011, Queiroz et al. 2016).
(c) Random amplified of polymorphic DNA (RAPD)
The RAPD technique uses a single primer for amplification. The technique was applied in molecular ecology for studying taxonomic identity, kinship relationships, analyse mixed genome samples or create specific probes (Hadrys et al. 1992). In insects, RAPDs have widely been used for example to study aphid polymorphism (Black et al. 1992) and many other species. Studies using this marker were also, conducted on whiteflies, revealing first distinction between “biotype B” (former name of MEAM1) and non-B biotypes within the Brazilian B. tabaci populations (Lima et al. 2000, Lima et al. 2002). RAPD was also used to differentiate the cassava B. tabaci species from non–cassava species from B. tabaci collected in the major cassava growing area in Africa (Abdullahi et al. 2003). Other studies also, reported the genetic variation within B. tabaci by using similar procedures (De Barro and Driver 1997, Guirao et al. 1997, Horowitz et al. 2003, Delatte et al. 2005).
Table of contents :
Chapter 1: literature review
1.1. Importance of cassava as a staple food in sub–Sahara Africa, with focus on East Africa
1.2. Whiteflies
1.3. Bemisia tabaci classification
1.5. Molecular tools used for molecular taxonomic issues
(a) Amplified fragment length polymorphism (AFLP)
(b) Restriction fragment length polymorphism (RFLP)
(c) Random amplified of polymorphic DNA (RAPD)
(d) Sequence characterized amplified regions (SCAR)
1.6. Other nuclear markers for population studies
(a) Microsatellite markers
(b) Restriction site associated DNA markers (RADseq)
1.7. Biology of B. tabaci
1.7.1. B. tabaci developmental stages
1.7.2. B. tabaci host plants utilization
1.8. Whitefly impact on agriculture
1.9. Bemisia tabaci distribution
1.9.1 Worldwide distribution of B. tabaci invasive species
1.9.2. B. tabaci distribution in sub–Sahara Africa
1.9.2.1. The cassava colonizing group
1.9.2.2. Non–cassava colonizing group
1.10.1. History of the CMD pandemic from the initial outbreak in 1920s
1.10.2. Factors driving the whitefly upsurges in East Africa, partly responsible of the spread of CMD
1.10.21. Biological factors
1.10.22. Abiotic factors (temperature and rainfall)
1.11. Study area: East Africa countries geography, demography, land use and agroecological zones
1.12. Study objectives
References used in the general introduction and literature review sections
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Chapter 2: What has changed in the outbreaking populations of the severe crop pest whitefly species in cassava in two decades?
Introduction
Material and methods
Results
Discussion
Acknowledgements
Supplementary information:
References
Chapter 3: B. tabaci species distribution in Tanzania and Uganda: their genetic diversity and structuring according to agroecological zones, host plant utilization and population dynamic
status
Introduction
Material and methods
Results
Discussion
Conclusion
Acknowledgements
Supplementary information
References
Chapter 4: The whitefly, Bemisia tabaci, species distribution and genetic diversity in Malawi
Introduction
Materials and methods
Results
Discussion and conclusion
Acknowledgements
Supplementary information accompanied this chapter
Chapter 5: General discussion
Conclusion and perspective
References
