Cassava brown streak virus disease: Past, present and future.

Cassava has been an important success story in Africa's developing agriculture over the past decade. The crop's inherei'lt capacity to cope with marginal growing conditions and unpredictable rainfall, coupled with determined efforts of a number of countries to move away from over-reliance on maize, have helped establish it as the continent's number one crop in terms of total fresh production. The hope provided by these gains is now threatened, however, by the devastating impact of the virus diseases, cassava mosaic and cassava brown streak. Both have been known for many years, but seem to be becoming increasingly damaging, and pose an ever greater threat to the livelihoods of the millions of Africans who depend on cassava as a food staple. Substantial effort has been directed towards understanding and managing cassava mosaic. By contrast, cassava brown streak disease (CBSD), which has a more limited distribution, and causes most severe damage in the coastal lowlands of Eastern and Southern Africa, has received little attention. In order to address this deficiency, an international workshop was convened at Mombasa, Kenya. This meeting brought together a diverse range of cassava stakeholders with the twin aims of reviewing current research into cassava brown streak and developing a plan to guide future research for development initiatives. The IS papers presented in these proceedings provide a useful and informative summary of the history and current status of CBSD, recent research initiatives and management options for the worst affected countries - Malawi, Tanzania, Kenya and Mozambique. Outputs of the research and on-farm working group sessions are also included. lt is anticipated that this information will serve both as a useful technical resource as well as an essential planning tool for scientists, development workers and others with an interest in the management of CBSD and the development of cassava in Africa

Unravelling the genetic diversity among cassava Bemisia tabaci whiteflies using NextRAD Sequencing

Article purchased; Published online: 31 Oct 2017Bemisia tabaci threatens production of cassava in Africa through vectoring viruses that cause cassava mosaic disease (CMD) and cassava brown streak disease (CBSD). B. tabaci sampled from cassava in eight countries in Africa were genotyped using NextRAD sequencing, and their phylogeny and population genetics were investigated using the resultant single nucleotide polymorphism (SNP) markers. SNP marker data and short sequences of mitochondrial DNA cytochrome oxidase I (mtCOI) obtained from the same insect were compared. Eight genetically distinct groups were identified based on mtCOI, whereas phylogenetic analysis using SNPs identified six major groups, which were further confirmed by PCA and multidimensional analyses. STRUCTURE analysis identified four ancestral B. tabaci populations that have contributed alleles to the six SNP-based groups. Significant gene flows were detected between several of the six SNP-based groups. Evidence of gene flow was strongest for SNP-based groups occurring in central Africa. Comparison of the mtCOI and SNP identities of sampled insects provided a strong indication that hybrid populations are emerging in parts of Africa recently affected by the severe CMD pandemic. This study reveals that mtCOI is not an effective marker at distinguishing cassava-colonizing B. tabaci haplogroups, and that more robust SNP-based multilocus markers should be developed. Significant gene flows between populations could lead to the emergence of haplogroups that might alter the dynamics of cassava virus spread and disease severity in Africa. Continuous monitoring of genetic compositions of whitefly populations should be an essential component in efforts to combat cassava viruses in Africa

Application of FTA technology for sampling, recovery and molecular characterization of viral pathogens and virus-derived transgenes from plant tissues

BACKGROUND: Plant viral diseases present major constraints to crop production. Effective sampling of the viruses infecting plants is required to facilitate their molecular study and is essential for the development of crop protection and improvement programs. Retaining integrity of viral pathogens within sampled plant tissues is often a limiting factor in this process, most especially when sample sizes are large and when operating in developing counties and regions remote from laboratory facilities. FTA is a paper-based system designed to fix and store nucleic acids directly from fresh tissues pressed into the treated paper. We report here the use of FTA as an effective technology for sampling and retrieval of DNA and RNA viruses from plant tissues and their subsequent molecular analysis. RESULTS: DNA and RNA viruses were successfully recovered from leaf tissues of maize, cassava, tomato and tobacco pressed into FTA(® )Classic Cards. Viral nucleic acids eluted from FTA cards were found to be suitable for diagnostic molecular analysis by PCR-based techniques and restriction analysis, and for cloning and nucleotide sequencing in a manner equivalent to that offered by tradition isolation methods. Efficacy of the technology was demonstrated both from sampled greenhouse-grown plants and from leaf presses taken from crop plants growing in farmer's fields in East Africa. In addition, FTA technology was shown to be suitable for recovery of viral-derived transgene sequences integrated into the plant genome. CONCLUSION: Results demonstrate that FTA is a practical, economical and sensitive method for sampling, storage and retrieval of viral pathogens and plant genomic sequences, when working under controlled conditions and in the field. Application of this technology has the potential to significantly increase ability to bring modern analytical techniques to bear on the viral pathogens infecting crop plants

Automated registration of multimodal optic disc images: clinical assessment of alignment accuracy

Purpose: To determine the accuracy of automated alignment algorithms for the registration of optic disc images obtained by 2 different modalities: fundus photography and scanning laser tomography. Materials and Methods: Images obtained with the Heidelberg Retina Tomograph II and paired photographic optic disc images of 135 eyes were analyzed. Three state-of-the-art automated registration techniques Regional Mutual Information, rigid Feature Neighbourhood Mutual Information (FNMI), and nonrigid FNMI (NRFNMI) were used to align these image pairs. Alignment of each composite picture was assessed on a 5-point grading scale: “Fail” (no alignment of vessels with no vessel contact), “Weak” (vessels have slight contact), “Good” (vessels with 50% contact), and “Excellent” (complete alignment). Custom software generated an image mosaic in which the modalities were interleaved as a series of alternate 5×5-pixel blocks. These were graded independently by 3 clinically experienced observers. Results: A total of 810 image pairs were assessed. All 3 registration techniques achieved a score of “Good” or better in >95% of the image sets. NRFNMI had the highest percentage of “Excellent” (mean: 99.6%; range, 95.2% to 99.6%), followed by Regional Mutual Information (mean: 81.6%; range, 86.3% to 78.5%) and FNMI (mean: 73.1%; range, 85.2% to 54.4%). Conclusions: Automated registration of optic disc images by different modalities is a feasible option for clinical application. All 3 methods provided useful levels of alignment, but the NRFNMI technique consistently outperformed the others and is recommended as a practical approach to the automated registration of multimodal disc images

Genetic diversity of Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) colonizing sweet potato and cassava in South Sudan

Open Access Journal; Published online: 17 Jan 2020Bemisia tabaci (Gennadius) is a polyphagous, highly destructive pest that is capable of vectoring viruses in most agricultural crops. Currently, information regarding the distribution and genetic diversity of B. tabaci in South Sudan is not available. The objectives of this study were to investigate the genetic variability of B. tabaci infesting sweet potato and cassava in South Sudan. Field surveys were conducted between August 2017 and July and August 2018 in 10 locations in Juba County, Central Equatoria State, South Sudan. The sequences of mitochondrial DNA cytochrome oxidase I (mtCOI) were used to determine the phylogenetic relationships between sampled B. tabaci. Six distinct genetic groups of B. tabaci were identified, including three non-cassava haplotypes (Mediterranean (MED), Indian Ocean (IO), and Uganda) and three cassava haplotypes (Sub-Saharan Africa 1 sub-group 1 (SSA1-SG1), SSA1-SG3, and SSA2). MED predominated on sweet potato and SSA2 on cassava in all of the sampled locations. The Uganda haplotype was also widespread, occurring in five of the sampled locations. This study provides important information on the diversity of B. tabaci species in South Sudan. A comprehensive assessment of the genetic diversity, geographical distribution, population dynamics, and host range of B. tabaci species in South Sudan is vital for its effective management

Efficacy of selected botanical oils against the cassava whitefly ( Bemisia tabaci ) and their effects on its feeding behaviour

The control of the whitefly Bemisia tabaci relies heavily on the use of synthetic insecticides. There is a need to develop alternative control strategies due to concerns about impact of these insecticides on the environmental and human health, and the threat of insecticide resistance. Botanical oil extracts could potentially be used for the management of whiteflies and other pests. The study reported here therefore aimed to evaluate the efficacy of selected botanical oils against the cassava whitefly, B. tabaci and test their effect on its feeding behaviour. Patchouli oil treatment was the most effective at repelling whiteflies in no choice and choice experiments with up to 85% of whiteflies being repelled. Oviposition was also reduced 50–89% in patchouli. Neem was found to be effective at reducing oviposition, nymph and adult emergence by 50%, 70% and 80%, respectively, in a screenhouse no choice experiment. Patchouli significantly reduced the phloem ingestion phase (E2) by 40% and potential drops (pd) by 46% compared to control plants. Neem significantly increased the non‐probing duration by 48% and reduced pd by 50% compared to the control. Patchouli and neem were found to be the most effective among the selected botanical oils. These two oils should be further evaluated for efficacy under field conditions to determine suitability for recommendation as biopesticides against the cassava B. tabaci whitefly

A Mobile-Based Deep Learning Model for Cassava Disease Diagnosis

Convolutional neural network (CNN) models have the potential to improve plant disease phenotyping where the standard approach is visual diagnostics requiring specialized training. In scenarios where a CNN is deployed on mobile devices, models are presented with new challenges due to lighting and orientation. It is essential for model assessment to be conducted in real world conditions if such models are to be reliably integrated with computer vision products for plant disease phenotyping. We train a CNN object detection model to identify foliar symptoms of diseases in cassava (Manihot esculenta Crantz). We then deploy the model in a mobile app and test its performance on mobile images and video of 720 diseased leaflets in an agricultural field in Tanzania. Within each disease category we test two levels of severity of symptoms-mild and pronounced, to assess the model performance for early detection of symptoms. In both severities we see a decrease in performance for real world images and video as measured with the F-1 score. The F-1 score dropped by 32% for pronounced symptoms in real world images (the closest data to the training data) due to a decrease in model recall. If the potential of mobile CNN models are to be realized our data suggest it is crucial to consider tuning recall in order to achieve the desired performance in real world settings. In addition, the varied performance related to different input data (image or video) is an important consideration for design in real world applications

Plant pest surveillance: from satellites to molecules

Plant pests and diseases impact both food security and natural ecosystems, and the impact has been accelerated in recent years due to several confounding factors. The globalisation of trade has moved pests out of natural ranges, creating damaging epidemics in new regions. Climate change has extended the range of pests and the pathogens they vector. Resistance to agrochemicals has made pathogens, pests, and weeds more difficult to control. Early detection is critical to achieve effective control, both from a biosecurity as well as an endemic pest perspective. Molecular diagnostics has revolutionised our ability to identify pests and diseases over the past two decades, but more recent technological innovations are enabling us to achieve better pest surveillance. In this review, we will explore the different technologies that are enabling this advancing capability and discuss the drivers that will shape its future deployment