Evidence map›Paper›PMID 40216941›Full record

ArticleScientific reports2025

Additive modeling of zonal level crop production in Ethiopia.

Yidnekachew Mare, Temesgen Zewotir, Denekew Bitew Belay

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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

3 authors.

Yidnekachew MareDepartment of Statistics, College of Science, Bahir Dar University, P.O. Box 79, Bahir Dar, Ethiopia. yidnekachew.mare08@gmail.com.
Temesgen ZewotirSchool of Mathematics, Statistics and Computer Science, College of Agriculture Engineering and Science, University of KwaZulu-Natal, Durban, South Africa.
Denekew Bitew BelayDepartment of Statistics, College of Science, Bahir Dar University, P.O. Box 79, Bahir Dar, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Crop production is the main source of food security and income for smallholder private farmers in Sub-Saharan countries. To have a sustainable source of food security and economy, it is important to identify covariates that affect crop production linearly and nonlinearly. Annual agricultural sample survey data of eight Meher seasons, from 2012/13 to 2019/20, is used in this study with the main objective of identifying the set of covariates that have linear and nonlinear effects on crop production and estimating their effects using an additive mixed effects model. The minimum, mean, and maximum crop production across the country for the study period were 1.616, 8.693, and 147.843 quintals, respectively, and 50% of the farmers produced less than 6.95 quintals. The histogram, kernel density, and P-P plots suggested that log-transformed crop production is approximately normally distributed. From the competing models' summary statistics, information criteria values, and analysis of variance tests, relaxing the linearity assumption and including a random effect in the model has improved model performance, suggesting the additive mixed effects model best fits the data on hand. Gambella, SNNP, and Oromia regions have significantly different overall mean crop production than the reference in Dire Dawa town. Covariates like year, proportion of female farmers, household age, and UREA fertilizer used have a significant nonlinear effect, while covariates like proportion of educated farmers, area used, and proportion of farmers who received credit service have a significant linear effect on log crop production. The basic model assumptions are not violated, so the final additive mixed effects model can be used for prediction and inference purposes. We recommend farmers use more croplands, indigenous seeds, and UREA fertilizer; practice pure agriculture; and participate in local farmers associations. Policies regarding the participation of female and educated farmers, the implementation and effectiveness of credit services and extension programs, private investors to participate in crop production, and the provision of farm inputs to the elderly farmers should be revised.

Indexed as

AgricultureCrop ProductionCrops, AgriculturalEthiopiaFarmersFemaleHumansMaleAdditive mixed modelsCrop productionNonlinear effectRandom effectSmooth terms

Identifiers

PMID40216941
PMCPMC11992157

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LicenceCC BY-NC-ND
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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.