Cassava mosaic disease and its whitefly vector in Cameroon: Incidence, severity and whitefly numbers from field surveys

Doungous, Oumar; Masky, Boutou; Levai, Lewis Dopgima; Bahoya, Joseph A.L.; Minyaka, Emile; Mavoungou, Jacques François; Mutuku, J. Musembi; Pita, Justin S.

doi:10.1016/j.cropro.2022.106017

Cited by 8 publications

(6 citation statements)

References 40 publications

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“…Geo-Wiki 32 data quality checks involved using control locations to produce quality scores for participants labelling drivers of forest loss and the technical validation involved a comparison with the Curtis et al 45 drivers of forest loss layer in South America. Doungous et al 34 data are individual field surveys. BIOPAMA data 36 was validated with more than 10,000 randomly distributed reference points 35 and existing oil palm maps [46][47][48][49] .…”

Section: Technical Validationmentioning

confidence: 99%

“…• A CSV file from Geo-Wiki identifying the coordinates of wildfires, infrastructure and other small-scale plantations (cassava) in 2020 32,33 (https://pure.iiasa.ac.at/id/eprint/17539/). • A CSV file from Doungous et al identifying the coordinates of other small-scale plantations (maize) in 2020 34 (https://view.officeapps.live.com/op/view.aspx?src=https%3A%2F%2Fars.els-cdn.com%2Fcontent%2Fimage %2F1-s2.0-S0261219422001132-mmc1.xlsx&wdOrigin=BROWSELINK). • A TIF file from BIOPAMA identifying small-scale oil palm plantation in 2019 35,36 , with the relevant layer extracted and converted to a shapefile on QGIS (https://zenodo.org/records/4473715).…”

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confidence: 99%

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A labelled dataset to classify direct deforestation drivers from Earth Observation imagery in Cameroon

Debus,

Beauchamp,

Acworth

et al. 2024

Sci Data

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Understanding direct deforestation drivers at a fine spatial and temporal scale is needed to design appropriate measures for forest management and monitoring. To achieve this, reference datasets with which to design Artificial Intelligence (AI) approaches to classify direct deforestation drivers within areas experiencing forest loss in a detailed, comprehensive and locally-adapted way are needed. This is the case for Cameroon, in the Congo Basin, which has known increasing deforestation rates in recent years. Here, we created an Earth Observation dataset with associated labels to classify detailed direct deforestation drivers in Cameroon, which includes satellite imagery (Landsat and PlanetScope) and auxiliary data on infrastructure and biophysical properties. The dataset provides the following fifteen labels: oil palm, timber, fruit, rubber and other-large scale plantations; grassland/shrubland; small-scale oil palm or maize plantations and other small-scale agriculture; mining; selective logging; infrastructure; wildfires; hunting; and other.

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Section: Technical Validationmentioning

confidence: 99%

mentioning

confidence: 99%

A labelled dataset to classify direct deforestation drivers from Earth Observation imagery in Cameroon

Debus,

Beauchamp,

Acworth

et al. 2024

Sci Data

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“…There is often limited Information about the range of pathogens and pests that are a concern for plant health, and their potential spread through planting materials and other means, even when studies have addressed specific species in specific locations. For example, in Cameroon there have been targeted studies of diseases and pests of RTB crops, such as weevils, nematodes, sigatoka, and banana bunchy top disease on banana (Fogain et al, 1998; Ngatat et al, 2022; Okolle et al, 2009), cassava viruses, cassava whitefly, cassava root rot, cassava green mite, cassava root mealybug, cassava anthracnose, and cassava bacterial blight on cassava (Doungous et al, 2022; Poubom et al, 2005; Tize et al, 2021), and potato tuber moth, aphids, potato viruses, leaf miners, bacterial wilt, and late blight on potato (Deloko et al, 2021; Konje et al, 2019). In Ethiopia, studies have also been conducted on the incidence and spread of some important diseases and pests of potato and sweetpotato, such as potato bacterial wilt (Tessema & Seid, 2023), viral diseases of sweetpotato (Buko et al, 2020; Tesfaye et al, 2011) and sweetpotato weevil (Beyene, 2015).…”

Section: Introductionmentioning

confidence: 99%

Pathogen and pest risks to vegetatively propagated crops in humanitarian contexts: geographic priorities for Cameroon and Ethiopia

Mouafo-Tchinda,

Etherton,

Sulá

et al. 2024

Preprint

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Cameroon and Ethiopia face complex humanitarian crises that disrupt the production of key food security crops like banana and plantain, cassava, potato, and sweetpotato. These vegetatively propagated crops are prone to the buildup of pests and diseases causing seed degeneration. In this study, we address seed degeneration in the context of natural and human-driven crises, to provide insights that can guide the decisions of humanitarian groups to reduce seed degeneration. We identified locations in Cameroon and Ethiopia that are likely to be particularly important for pathogen and pest spread in cropland network analyses. We analyzed cropland networks in each country to develop a map of locations that are candidate priorities for disease and pest management and surveillance. For example, locations in central and western Oromia, Ethiopia, are likely important for potato pathogen and pest spread given the locations' roles in the cropland network. Next, we used expert knowledge elicitation to characterize crop health risk in these systems. For example, experts reported with high consensus that there are formal and informal imports of cassava from Gabon to Cameroon, which pose a risk to cassava production in Cameroon through seedborne pathogens. These results can inform regional and national surveillance and management strategies and provide a baseline for more in-depth studies in Cameroon and Ethiopia. The results can also inform decision-making in the humanitarian sector, for designing on-the-ground actions to avoid unintentional spread of pathogens and pests during agricultural recovery interventions.

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“…Cassava mosaic disease (CMD) is caused by at least ten species in the genus Begomovirus ( Geminiviridae) that are endemic to Africa and Asia [ 5 , 6 ]. Begomoviruses are transmitted by the whitefly Bemisia tabaci (Gennadius) (Aleyrodidae: Hemiptera) cryptic species complex [ 7 , 8 , 9 , 10 , 11 ]. Cassava cultivars grown in Asia lack tolerance or resistance to cassava mosaic begomovirus infection [ 5 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava

Ashraf

Ali

Brown

et al. 2023

Viruses

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Cassava mosaic disease (CMD) is caused by several divergent species belonging to the genus Begomovirus (Geminiviridae) transmitted by the whitefly Bemisia tabaci cryptic species group. In India and other parts of Asia, the Indian cassava mosaic virus-Kerala (ICMV-Ker) is an emergent begomovirus of cassava causing damage that results in reduced yield loss and tuber quality. Double-stranded RNA-mediated interference (RNAi) is an evolutionary conserved mechanism in eukaryotes and highly effective, innate defense system to inhibit plant viral replication and/or translation. The objective of this study was to identify and characterize cassava genome-encoded microRNAs (mes-miRNA) that are predicted to target ICMV-Ker ssDNA-encoded mRNAs, based on four in silico algorithms: miRanda, RNA22, Tapirhybrid, and psRNA. The goal is to deploy the predicted miRNAs to trigger RNAi and develop cassava plants with resistance to ICMV-Ker. Experimentally validated mature cassava miRNA sequences (n = 175) were downloaded from the miRBase biological database and aligned with the ICMV-Ker genome. The miRNAs were evaluated for base-pairing with the cassava miRNA seed regions and to complementary binding sites within target viral mRNAs. Among the 175 locus-derived mes-miRNAs evaluated, one cassava miRNA homolog, mes-miR1446a, was identified to have a predicted miRNA target binding site, at position 2053 of the ICMV-Ker genome. To predict whether the cassava miRNA might bind predicted ICMV-Ker mRNA target(s) that could disrupt viral infection of cassava plants, a cassava locus-derived miRNA–mRNA regulatory network was constructed using Circos software. The in silico-predicted cassava locus-derived mes-miRNA-mRNA network corroborated interactions between cassava mature miRNAs and the ICMV-Ker genome that warrant in vivo analysis, which could lead to the development of ICMV-Ker resistant cassava plants.

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Cassava mosaic disease and its whitefly vector in Cameroon: Incidence, severity and whitefly numbers from field surveys

Cited by 8 publications

References 40 publications

A labelled dataset to classify direct deforestation drivers from Earth Observation imagery in Cameroon

A labelled dataset to classify direct deforestation drivers from Earth Observation imagery in Cameroon

Pathogen and pest risks to vegetatively propagated crops in humanitarian contexts: geographic priorities for Cameroon and Ethiopia

In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava

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