A systematic map of cassava farming practices and their agricultural and environmental impacts using new ontologies: agri-ontologies 1.0
Author(s)
Type
Journal Article
Abstract
1. Cassava is consumed by 800 million people and is a staple crop in Africa. Its production may increase under climate change due to its high drought tolerance. We produced a systematic map of scientific studies about cassava farming practices, with the aim of identifying knowledge gaps and clusters. Our secondary aim was to develop a classification system for [1] farming interventions and [2] agricultural, economic and environmental outcomes. Standardised classification systems facilitate data reuse, including for evidence synthesis, and promote research efficiency.
2. Following our published protocol, we searched eight publication databases using the search string ‘cassava OR mandioca OR manihot OR manioc OR yuca’ in December 2017. We screened 36,580 records and included publications that measured the impact of cassava farming practices on agricultural, economic or environmental outcomes, including yield, soil, water, wildlife and labour. We classified the resultant 1599 publications by interventions, outcomes, location, study year and study design. We assessed coding consistency using Kappa scores.
3. We found regional knowledge clusters (Nigeria, Columbia and Brazil accounted for 45.5% of country occurrences) and gaps (e.g. the Democratic Republic of Congo). There were knowledge clusters for interventions testing cultivar type, fertiliser use and diversifying crop rotations and outcomes related to crop production (e.g. yield/biomass). We found knowledge gaps for environmental interventions and outcomes (e.g. 5% of studies measured pollutants or wildlife). In terms of study design, reporting standards were poor (e.g. 24% of studies did not report start dates), average study duration was 2 years, and average publication delays were 4 years. The Kappa scores indicated that we successfully developed consistent ontologies (named Agri-ontologies 1.0). The map and ontologies are available online: https://www.metadataset.com/.
4. This systematic map of cassava farming practices can direct researchers and funders to knowledge gaps that need addressing, and reviewers to knowledge clusters for synthesis. Better research practices should be promoted within cassava research, as poor reporting standards, short study durations and long publication delays result in an ineffective research environment. This systematic map provides an evidence base for cassava production and the ontologies (Agri-ontologies 1.0) can be applied to other systems to facilitate more efficient and effective synthesis.
2. Following our published protocol, we searched eight publication databases using the search string ‘cassava OR mandioca OR manihot OR manioc OR yuca’ in December 2017. We screened 36,580 records and included publications that measured the impact of cassava farming practices on agricultural, economic or environmental outcomes, including yield, soil, water, wildlife and labour. We classified the resultant 1599 publications by interventions, outcomes, location, study year and study design. We assessed coding consistency using Kappa scores.
3. We found regional knowledge clusters (Nigeria, Columbia and Brazil accounted for 45.5% of country occurrences) and gaps (e.g. the Democratic Republic of Congo). There were knowledge clusters for interventions testing cultivar type, fertiliser use and diversifying crop rotations and outcomes related to crop production (e.g. yield/biomass). We found knowledge gaps for environmental interventions and outcomes (e.g. 5% of studies measured pollutants or wildlife). In terms of study design, reporting standards were poor (e.g. 24% of studies did not report start dates), average study duration was 2 years, and average publication delays were 4 years. The Kappa scores indicated that we successfully developed consistent ontologies (named Agri-ontologies 1.0). The map and ontologies are available online: https://www.metadataset.com/.
4. This systematic map of cassava farming practices can direct researchers and funders to knowledge gaps that need addressing, and reviewers to knowledge clusters for synthesis. Better research practices should be promoted within cassava research, as poor reporting standards, short study durations and long publication delays result in an ineffective research environment. This systematic map provides an evidence base for cassava production and the ontologies (Agri-ontologies 1.0) can be applied to other systems to facilitate more efficient and effective synthesis.
Date Issued
2023-04-01
Date Acceptance
2023-04-18
Citation
Ecological Solutions and Evidence, 2023, 4 (2)
ISSN
2688-8319
Publisher
Wiley
Journal / Book Title
Ecological Solutions and Evidence
Volume
4
Issue
2
Copyright Statement
© 2023 The Authors. Ecological Solutions and Evidence published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:001007574100001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Subjects
agricultural taxonomy
cassava Manihot esculenta
CLIMATE-CHANGE
Ecology
Environmental Sciences & Ecology
evidence-based management
interactive evidence map
Life Sciences & Biomedicine
RANDOMIZED CONTROLLED-TRIALS
reporting standards
Science & Technology
standardised classification system
subject-wide evidence synthesis
sustainable agriculture
systematic map
terminological ontology agriculture
Publication Status
Published
Article Number
e12249
Date Publish Online
2023-06-13