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Record W3005572225 · doi:10.5539/jas.v12n3p105

Cassava Root Necrosis Disease (CRND): A New Crop Disease Spreading in Western Democratic Republic of Congo and in Some Central African Countries

2020· article· en· W3005572225 on OpenAlexvenueno aff
Bakelana Zeyimo, Justin S. Pita, Godefroid Monde, Mahungu Nzola, Lema ki Munseki, Tshilenge Kanana, Kalonji Mbuyi

Bibliographic record

VenueJournal of Agricultural Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
FundersBill and Melinda Gates Foundation
KeywordsBiologyCropPopulationDNA sequencingVeterinary medicineHorticultureAgronomyMedicineGeneticsGene

Abstract

fetched live from OpenAlex

Cassava is consumed in the Democratic Republic of Congo (DRC) as a staple food for the majority of the Congolese population. This crop is used in several forms: as fufu, chikwangue and pondu; cassava leaves are the most consumed vegetable in the country. In 2002, cassava root symptoms similar to cassava brown streak disease (CBSD) were reported for the first time in western DRC. PCR assays, using primers specific to Cassava brown streak virus (CBSV), failed to detect or identify any viral pathogens in diseased cassava samples from western DRC. Therefore, next generation sequencing (NGS) techniques were used as they are able to sequence full organism genomes and are widely used for the identification of pathogens responsible for new diseases. The main objective of this study was to identify the pathogens causing root necrosis in western DRC. Whatman®FTA™ cards were used to collect 12 cassava leaf samples from plants with symptoms indicative of very severe root necrosis, as well as two asymptomatic samples. These 12 samples were sent to Australia at the University of Western Australia in Perth for next generation sequencing (NGS) using the Illumina HiSeq platform. Additional bioinformatics tools included Geneious, CLC workbench, ParaKraken and Kaijou software for short DNA sequences. No viruses (including CBSV) were found in any of the DRC samples. These preliminary results confirm all the previous negative results obtained using PCR and CBSV primers. However, NGS analyses did reveal the presence of a number of bacterial and fungal taxa. These will require further investigation and tests such as the Koch Postulates, to establish their specific pathogenic role in cassava. This is the first scientific evidence that no currently known virus is responsible for the disease which had been referred to previously as ‘CBSD-like disease’. Consequently, the disease found in DRC cassava samples has been designated ‘Cassava Root Necrosis Disease’ or CRND.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.256
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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