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Record W4214898999 · doi:10.3390/su14052954

Insight on Fruit Fly IPM Technology Uptake and Barriers to Scaling in Africa

2022· article· en· W4214898999 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSustainability · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect behavior and control techniques
Canadian institutionsnot available
FundersFP7 International CooperationAustralian Centre for International Agricultural ResearchForeign Agricultural ServiceAnimal and Plant Health Inspection ServiceInternational Fund for Agricultural DevelopmentBiovision Foundation for Ecological DevelopmentAfrican UnionForeign, Commonwealth and Development OfficeEuropean CommissionInternational Atomic Energy AgencyBelgisch OntwikkelingsagentschapDepartment for International DevelopmentInternational Development Research CentreUnited States Agency for International DevelopmentDeutsche Gesellschaft für Internationale ZusammenarbeitBelgian Federal Science Policy OfficeBundesministerium für Wirtschaftliche Zusammenarbeit und EntwicklungU.S. Department of Agriculture
KeywordsTephritidaeDacusIntegrated pest managementCeratitis capitataBactrocera dorsalisGeographyAgroforestryBiopesticideBactroceraBiologyPEST analysisSocioeconomicsHorticultureAgronomyPesticide

Abstract

fetched live from OpenAlex

Tephritid fruit flies are considered one of the world’s most notorious pests of horticultural crops, causing extensive direct and indirect damage. Over the past two decades, a comprehensive, integrated pest management (IPM) package for the management of a plethora of fruit fly pests, including Bactrocera dorsalis, B. latifrons, B. zonata, Ceratitis cosyra, C. rosa, C. fasciventris, C. quilici, C. capitata, Dacus spp. and Zeugodacus cucurbitae, has been developed, disseminated and promoted among horticultural growers in Africa. To estimate the numbers of beneficiaries reached by the fruit fly IPM technology and the barriers to technology uptake, we interviewed 290 experts in 30 African countries covering five regions of the continent, and the responses collected were represented as follows: Southern Africa (39.1%), Eastern Africa (31.6%), Western Africa (18.0%), Central Africa (9.0%) and Northern Africa (2.0%). Our results revealed that the use of fruit fly IPM technologies varied across the regions, with Eastern Africa and Western Africa the leading regions, with the highest IPM technology penetration. Field sanitation remains the most common practice for managing fruit flies, followed by protein bait spray, use of biopesticides, male annihilation technique and parasitoid releases. According to the survey, over 101 million people have benefited from the fruit fly IPM interventions in the countries surveyed representing only 19.1% of the estimated beneficiaries. The region that benefitted the most was Eastern Africa (50.2 million), followed by Central and Western Africa (11.7 to 17.7 million), and Southern and Northern Africa had the fewest beneficiaries (10.4 to 11.0 million). The limitations to the IPM technologies uptake varied among the regions, but the common ones include a lack of awareness of the IPM technologies, a lack of access to the IPM products, insufficient training, a low involvement of private sectors and a lack of policies for the regulation of IPM technologies. Although significant strides have been made in promoting the fruit fly IPM technologies over the past two decades, our study reveals that the demand surpasses the current supply. Our study recommends a comprehensive strategy for the dissemination and promotion of the technologies through a multi-institutional alliance that enhances public and private partnerships, digital platforms and youth engagement to consolidate previous gains at the regional and continental levels.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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