ArticleScientific reports2026
Evaluating iSAT climate-informed agro-advisories for farm decisions and system performance in Senegal's drylands.
Article in Scientific reports, 2026. 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
10 authors.
Funding
Abstract
Smallholder farmers in Africa’s drylands face increasing climate risks, compounded by limited access to inputs, credit, and climate information. Climate Information Service(CIS) can support adaptation, yet adoption remains low due to insufficient localized data and limited availability of tailored advisories. This study evaluates the effectiveness of the Intelligent Agricultural Systems Advisory Tool (iSAT), a climate-informed advisory system adapted for Senegal and delivered through Interactive Voice Response (IVR) in local languages. Deployed in 18 villages, the tool reached over 2,700 farmers during the 2022 and 2023 seasons. Its impact was assessed through pre- and post-season household surveys and focus group discussions. Propensity Score Matching(PSM) was used to identify comparable treatment and control villages, and statistical analyses examined differences in yields, input and labor costs, and adoption of climate-smart practices. Farmers who received iSAT advisories recorded significantly higher yields for key crops, with millet yields increasing by 41% and groundnut yields by 21% (p < 0.05) compared with matched control farmers. Input and labor costs were 24% lower among advisory users, indicating improved cost-effectiveness. Cowpea exhibited no significant yield differences, reflecting its low-management requirements and the smaller number of users who cultivated it. Nevertheless, farmer feedback consistently highlighted the usefulness of the advisories for planning and managing climate risks. These findings demonstrate the potential of localized advisory systems to strengthen climate-smart agriculture in resource-limited environments. Scaling such tools will require investment in meteorological infrastructure, digital delivery platforms, and partnerships that enhance climate and digital literacy while supporting long-term adoption among vulnerable smallholders.
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.