ArticlePloS one2025
Assessing yield stability of pearl millet and rice cropping systems across West Africa using long-term experiments and a modeling approach.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Long-term field experiments (LTEs) provide invaluable insights into temporal yield patterns of agronomic interventions. However, the number of LTEs and agronomic management options tested withing these experiments remain limited compared to the diversity of farming systems in West Africa. Well-tested crop models may be used to identify crop management strategies with high temporal yield stability. This study examines the yield stability of pearl millet and rice under various management options in West Africa, utilizing both experimental and modeling approaches. The Agricultural Production Systems Simulator (APSIM) for pearl millet and rice were calibrated and tested for locally-recommended varieties using LTE data from Niger (pearl millet) and Senegal (rice). Yield stability was evaluated with multiple metrics, including the adjusted coefficient of variation, the sustainable yield index, and the Finlay-Wilkinson regression coefficient. Both APSIM models exhibited a strong performance for grain yield, with Willmott's indices of agreement at 0.74 for pearl millet and 0.90 for rice, and absolute root mean square errors of 0.19 and 1.20 Mg ha-1, respectively. The models effectively reproduced yield stability patterns across a variety of management options including planting date, planting density, fertilizer treatments, and residue retention. Combining fertilizer applications with crop residue retention enhanced yield stability in pearl millet, while season-specific nitrogen management strategies reduced yield variability in rice. Our study underscores the potential of well-tested crop models to complement LTEs in investigating pearl millet and rice yield stability, offering actionable insights for agronomic intensification strategies to enhance productivity and sustainability.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.