Evidence map›Paper›PMID 34313932›Full record

ReviewPlant molecular biology2022

Modelling cassava production and pest management under biotic and abiotic constraints.

Vasthi Alonso Chavez, Alice E Milne, Frank van den Bosch, Justin Pita, C Finn McQuaid

Open access · hybridAbstract readReview
In one paragraph

Review in Plant molecular biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.7field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 20 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 3 countries.

Vasthi Alonso ChavezDepartment of Biointeractions and Crop Protection, Rothamsted Research, Harpenden, AL5 2JQ, UK. vasthi.alonso-chavez@rothamsted.ac.uk.ORCID http://orcid.org/0000-0003-3506-7603
Alice E MilneDepartment of Biointeractions and Crop Protection, Rothamsted Research, Harpenden, AL5 2JQ, UK.
Frank van den BoschSchool of Molecular and Life Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia.
Justin PitaLaboratory of Plant Physiology, Université Félix Houphouët-Boigny, Abidjan, Côte d'Ivoire.
C Finn McQuaidDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Rothamsted Research · GBCurtin University · AULondon School of Hygiene & Tropical Medicine · GBUniversité Félix Houphouët-Boigny · CI

Funding

Biotechnology and Biological Sciences Research Council BB/P022480/1
6 · The paper itself

Abstract

key messageWe summarise modelling studies of the most economically important cassava diseases and arthropods, highlighting research gaps where modelling can contribute to the better management of these in the areas of surveillance, control, and host-pest dynamics understanding the effects of climate change and future challenges in modelling. For over 30 years, experimental and theoretical studies have sought to better understand the epidemiology of cassava diseases and arthropods that affect production and lead to considerable yield loss, to detect and control them more effectively. In this review, we consider the contribution of modelling studies to that understanding. We summarise studies of the most economically important cassava pests, including cassava mosaic disease, cassava brown streak disease, the cassava mealybug, and the cassava green mite. We focus on conceptual models of system dynamics rather than statistical methods. Through our analysis we identified areas where modelling has contributed and areas where modelling can improve and further contribute. Firstly, we identify research challenges in the modelling developed for the surveillance, detection and control of cassava pests, and propose approaches to overcome these. We then look at the contributions that modelling has accomplished in the understanding of the interaction and dynamics of cassava and its' pests, highlighting success stories and areas where improvement is needed. Thirdly, we look at the possibility that novel modelling applications can achieve to provide insights into the impacts and uncertainties of climate change. Finally, we identify research gaps, challenges, and opportunities where modelling can develop and contribute for the management of cassava pests, highlighting the recent advances in understanding molecular mechanisms of plant defence.

Indexed as

ManihotPest ControlPlant DiseasesCassavaDynamicsModellingPestsSurveillanceSystem

Identifiers

PMID34313932
PMCPMC9163018
OpenAlexW3184200922

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.