Evidence map›Paper›PMID 38660316›Full record

ArticleAgronomy for sustainable development2024

APSIM-based modeling approach to understand sorghum production environments in Mali.

Madina Diancoumba, Jana Kholová, Myriam Adam, Mahamoudou Famanta, Benoît Clerget, Pierre C S Traore, Eva Weltzien, Michel Vacksmann, Greg McLean, Graeme L Hammer and 2 more

Abstract read
In one paragraph

Article in Agronomy for sustainable development, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Sustainable Management of Major Fungal Phytopathogens in Sorghum (Journal of fungi (Basel, Switzerland) · 2025
    Review
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

12 authors.

Madina DiancoumbaInternational Crops Research Institute for the Semiarid Tropics (ICRISAT), BP 320, Bamako, Mali.
Jana KholováInternational Crops Research Institute for the Semiarid Tropics (ICRISAT), Patancheru, Andhra Pradesh 502324 India.
Myriam AdamCentre de coopération internationale en recherche agronomique pour le développement (CIRAD), Avenue Agropolis, Cedex 5, 34398 Montpellier, France.
Mahamoudou FamantaInstitut Polytechnique Rural de Formation et de Recherche Appliquée (IPR/IFRA), BP 06-Katibougou, Koulikoro, Mali.
Benoît ClergetCentre de coopération internationale en recherche agronomique pour le développement (CIRAD), Avenue Agropolis, Cedex 5, 34398 Montpellier, France.
Pierre C S TraoreagCelerant-Senegal, Manobi Africa Group company, Almadies Rue 12 Lot 14, BP 25026, Dakar, Sénégal.
Eva WeltzienInternational Crops Research Institute for the Semiarid Tropics (ICRISAT), BP 320, Bamako, Mali.
Michel VacksmannCentre de coopération internationale en recherche agronomique pour le développement (CIRAD), Avenue Agropolis, Cedex 5, 34398 Montpellier, France.
Greg McLeanQueensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane, QLD 4072 Australia.
Graeme L HammerQueensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane, QLD 4072 Australia.
Erik J van OosteromQueensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane, QLD 4072 Australia.
Vincent VadezInternational Crops Research Institute for the Semiarid Tropics (ICRISAT), Patancheru, Andhra Pradesh 502324 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sorghum production system in the semi-arid region of Africa is characterized by low yields which are generally attributed to high rainfall variability, poor soil fertility, and biotic factors. Production constraints must be well understood and quantified to design effective sorghum-system improvements. This study uses the state-of-the-art in silico methods and focuses on characterizing the sorghum production regions in Mali for drought occurrence and its effects on sorghum productivity. For this purpose, we adapted the APSIM-sorghum module to reproduce two cultivated photoperiod-sensitive sorghum types across a latitude of major sorghum production regions in Western Africa. We used the simulation outputs to characterize drought stress scenarios. We identified three main drought scenarios: (i) no-stress; (ii) early pre-flowering drought stress; and (iii) drought stress onset around flowering. The frequency of drought stress scenarios experienced by the two sorghum types across rainfall zones and soil types differed. As expected, the early pre-flowering and flowering drought stress occurred more frequently in isohyets < 600 mm, for the photoperiod-sensitive, late-flowering sorghum type. In isohyets above 600 mm, the frequency of drought stress was very low for both cultivars. We quantified the consequences of these drought scenarios on grain and biomass productivity. The yields of the highly-photoperiod-sensitive sorghum type were quite stable across the higher rainfall zones > 600 mm, but was affected by the drought stress in the lower rainfall zones < 600 mm. Comparatively, the less photoperiod-sensitive cultivar had notable yield gain in the driest regions < 600 mm. The results suggest that, at least for the tested crop types, drought stress might not be the major constraint to sorghum production in isohyets > 600 mm. The findings from this study provide the entry point for further quantitative testing of the Genotype × Environment × Management options required to optimize sorghum production in Mali. Supplementary Information: The online version contains supplementary material available at 10.1007/s13593-023-00909-5.

Indexed as

Crop modelCSM335CSM63EGxE interactionPhotoperiodWater deficit scenarios

Identifiers

PMID38660316
PMCPMC11035133

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.