Evidence map›Paper›PMID 42647429›Full record

ArticlePloS one2026

Modeling the role of fertilizers and improved seeds on rice productivity in Tanzania using a stochastic simulation approach.

Ibrahim L Kadigi, Lazaro Kagata, Stefan Sieber

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Ibrahim L KadigiDepartment of Business Management, College of Humanities and Business Studies, Mbeya University of Science and Technology (MUST), Mbeya, Tanzania.ORCID https://orcid.org/0000-0002-9915-280X
Lazaro KagataDepartment of Business Management, College of Humanities and Business Studies, Mbeya University of Science and Technology (MUST), Mbeya, Tanzania.
Stefan SieberLeibniz-Zentrum fur Agrarlandschaftsforschung (ZALF e. V.), Müncheberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate change poses a significant threat to food production in Tanzania, particularly for smallholder farmers who rely on rain-fed agriculture. This study examines the role of improved seeds and fertilizers as climate adaptation strategies to boost rice productivity and food security. Using data from the 2019/20 National Sample Census of Agriculture (NSCA), the study analyzed 6,025 rice farms from Mainland Tanzania and Zanzibar. A Stochastic Simulation model was used to account for yield variability and uncertainty. Farms were classified by seed type (local or improved) and fertilizer use (organic, inorganic, or none). Findings show that using improved seeds with inorganic fertilizers significantly enhances productivity, with a 16% chance of achieving yields above 4.5 t/ha. This combination also reduced the risk of falling below food security thresholds. In contrast, farms using local seeds, even with fertilizers, had only a 10% chance of reaching that yield level. The impact was more notable in Mainland Tanzania (25%) than in Zanzibar (6%). While organic fertilizers improve soil health, they offer limited short-term yield gains. The study concludes that promoting access to improved seeds and inorganic fertilizers is crucial for enhancing rice productivity and achieving the SDG 2 goal of Zero Hunger in Tanzania.

Indexed as

AgricultureFertilizersOryzaSeedsClimate ChangeComputer SimulationFood SecuritySoilStochastic ProcessesTanzaniaFertilizersSoil

Identifiers

PMID42647429
PMCPMC13514031

What OpenQuestion holds

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Registered trials

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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.