Evidence map›Paper›PMID 32461559›Full record

ArticleScientific data2020

CassavaMap, a fine-resolution disaggregation of cassava production and harvested area in Africa in 2014.

Anna Maria Szyniszewska

Abstract readDataset
In one paragraph

Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
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

18 citing papers in PubMed.

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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

1 author.

Anna Maria SzyniszewskaDepartment of Plant Sciences, University of Cambridge, Cambridge, UK. aniasz@gmail.com.ORCID http://orcid.org/0000-0002-4897-3878

Funding

Bill and Melinda Gates Foundation (Bill & Melinda Gates Foundation) OPPGD448
6 · The paper itself

Abstract

Cassava, the third main source of carbohydrates in Africa, provides daily nutrition for over 700 million people on the continent and a vital source of income for subsistence farmers. Despite its importance, our knowledge of the heterogeneity of its distribution in the landscape is limited and outdated. Information on cassava production and harvested area are typically available on aggregated administrative unit level with highly variable temporal range of records, often over a decade old, and represented on a coarse ~10 km by 10 km grid. Here, cassava production and harvested area administrative unit level data for 32 countries are standardised to 2014 FAO reported levels and disaggregated based on the distribution of the rural population in 2014. The grid obtained represents a significant improvement on the previous studies in terms of both spatial resolution (~1 km by 1 km) and temporal accuracy. Enhanced representation of cassava production and harvested area in Africa is an essential resource for policy making as well as designing strategies to manage its main pathogens.

Indexed as

AgricultureGeographic MappingAfricaCrops, AgriculturalManihot

Identifiers

PMID32461559
PMCPMC7253458

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.