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Record W4403703834 · doi:10.1007/s44279-024-00099-y

In vitro inhibition of Xanthomonas vasicola pv. musacearum, the causal agent of banana Xanthomonas Wilt, using medicinal plant extracts from North Kivu, Eastern Democratic Republic of Congo

2024· article· en· W4403703834 on OpenAlexfundno aff
Franchement Mukeshambala, Angele Ibanda, Ludivine Lassois, Gakuru Semacumu, Dhed’a Djailo, Léon Nabahungu, Guy Blomme, Godefroid Monde

Bibliographic record

VenueDiscover Agriculture · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogenic Bacteria Studies
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsBacterial wiltXanthomonasBiologyBotanyTraditional medicineMicrobiologyBacteriaMedicineGenetics

Abstract

fetched live from OpenAlex

Banana Wilt caused by Xanthomonas vasicola pv. musacearum ( Xvm ), has emerged as a significant threat to food security in eastern Democratic Republic of Congo (Kivu). Currently, the only means of combatting this biotic constraint is through best agricultural practices. The aim of this study was to evaluate the effectiveness of medicinal plants used in the Kivu provinces in inhibiting Xvm . Three in vitro experiments were conducted at laboratories of Uganda's National Agriculture Research Organization (NARO) and the International Institute of Tropical Agriculture (IITA) in South Kivu. The bacterial samples were collected from infected field-grown banana plants in South Kivu and isolated on Yeast Extract Peptone Agar (YPGA). Pure Xvm colonies were used for identification via i) Polymerase Chain Reaction (PCR) with specific primers and, ii) greenhouse inoculation trials. A completely randomized design was used for the three inhibition tests (1) on Mueller Hinton Agar (MHA) using disc diffusion with 10 plant extracts; (2) in liquid YPG Broth using 10 plant extracts; and (3) on MHA using disc diffusion with 19 plant extracts. The first two trials used plant extracts diluted in petroleum ether, while the third trial used 19 plant extracts diluted in methanol. After maceration, filtration, and solvent evaporation, 10 mg of extract was diluted in 80 µl of distilled water + 10 µl of Dimethylsulfoxide (DMSO). Ten µl of this solution was impregnated on perforated discs of Whatman filter paper. Zingiber officinale (ginger) and Ricinus communis (castor) were the most effective plant extracts in suppressing Xvm . Of the thirteen plant species identified as effective against the pathogen, the Myrtaceae and Euphorbiaceae families were the most represented. Based on these results, evaluating the effectiveness of the most promising plant extracts in disinfecting the metal blades of garden tools is recommended. In addition, various phytochemical groups present in plant extracts could be evaluated for their effectiveness in suppressing Xvm , especially phenols and tannins.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.222
Teacher spread0.199 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations5
Published2024
Admission routes1
Has abstractyes

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