Cassava brown streak disease (CBSD) is a major constraint to cassava production in Uganda. The disease is caused by two ipomovirus species: Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), both transmitted by the whitefly vector (Bemisia tabaci). Since the outbreak of the CBSD epidemic in Uganda in 2004, knowledge of its spread in the field is still limited. In this study, five cassava genotypes with varying levels of resistance to CBSD: TME 204 (susceptible), I92/0067, MH 97/2961, MH 96/0686 (moderately tolerant) and NASE 3 (tolerant) were used to evaluate the effect of genotype and prevailing disease pressure on CBSD spread in Uganda. The experiment was established in a randomized Complete Block Design (RCBD) in three sites of varying CBSD disease pressure: high (Wakiso), moderate (Kamuli) and low (Lira) in

A total of 99 cassava genotypes whose field reaction to cassava brown streak disease (CBSD) was known, were assayed with 30 simple sequence repeat (SSR) markers to establish their genetic parallels. Two categories of CBSD reaction were considered: CBSD-susceptible genotypes (characterized by > 60% root and foliar CBSD incidence), and CBSD-tolerant genotypes (characterized by < 15% root and foliar CBSD incidence). DNA was extracted from leaf samples using the miniprep method and genotyped using ABI 3730 DNA sequencer. The test genotypes at 0.02 similarity coefficient, CBSD-tolerant and CBSD-susceptible genotypes clustered into 5 main sub-clusters. When data were subjected to principle component analysis (PCA) irrespective of the CBSD reaction grade, the first three principal components accounted for 68% of the total genetic variation. Despite having different number of individuals, the observed heterozygosity (H_o) for CBSD-susceptible (H_o = 0.58) and CBSD-tolerant (Ho = 0.66) were comparable and provide scope for long-term CBSD breeding and/or gene tapping

High populations of species in the whitefly complex Bemisia tabaci Gennadius (Hemiptera: Aleyrodidae) were reported to cause severe damage to cassava in East and Central Africa. However, reasons for B. tabaci population increases are not well understood. We investigated the effect of cassava morphological traits, temperature, rainfall and relative humidity (RH) on the abundance of B. tabaci. Five cassava genotypes with varying levels of resistance to cassava mosaic disease, cassava brown streak disease, and B. tabaci infestation were planted in three Ugandan agro-ecological zones. The experiment was conducted in 2016 and 2017 in a randomized complete block design. Across all locations, the tallest genotype Alado alado supported the lowest number of B. tabaci adults. In areas with high B. tabaci prevalence, leaf area, leaf lobe width, and leaf lobe number exhibited significant positive effects (p < 0.001) on B. tabaci adult count. Positive effects of relative humidity and negative effects of temperature and rainfall on B. tabaci adult and nymph counts were observed in 2016 and 2017, resulting in low populations in Lira. Evidently, temperatures of 28–30 °C, rainfall of 30–150 mm and RH of 55–70%, and deployment of cassava genotypes of low plant height, large leaf area, and lobe width significantly enhanced B. tabaci population growth.

http://www.eje.cz cassava and also intensify its role as a vector of two damaging viral diseases of cassava: Cassava Mosaic Disease (CMD) and Cassava Brown Streak Disease (CBSD) (Legg et al., 2014b; Maruthi et al., 2017), thus undermining food security and livelihood benefi ts of cassava production. In Sub-Saharan Africa, cassava is considered a staple crop that is highly resilient to climate change (Nweke et al., 2002; Jarvis et al., 2012; Maruthi et al., 2017).Though many mortality factors are known to impact B. tabaci fi eld populations (Gerling et al., 2001; Naranjo & Ellsworth, 2005), there is limited information on the rates of mortality associated with specifi c causes of death, especially in light of the different B. tabaci species currently described. Age-specifi c life tables for insects under fi eld conditions provide critical information for a given cohort of individuals thus helps to identify mortality factors responsible for population regulation (Choudhury et al., 2013). Life tables have previously been used to study the