Evidence map›Paper›PMID 40530281›Full record

ArticleFrontiers in plant science2025

More bang for your buck: potential gains through optimizing maize breeding schemes in sub-Saharan Africa.

Davison Chaingeni, Ronica Mukaro, Clay Sneller, Jill E Cairns, Lennin Musundire, Biswanath Das, Olivia Odiyo, Sammy Madahana, Purity Mazibuko, Washington Mubvereki and 2 more

Abstract read
In one paragraph

Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

12 authors.

Davison ChaingeniCrop Breeding Institute, Agricultural Research, Innovation and Specialist Services Directorate, Harare, Zimbabwe.
Ronica MukaroCrop Breeding Institute, Agricultural Research, Innovation and Specialist Services Directorate, Harare, Zimbabwe.
Clay SnellerDepartment of Horticulture and Crop Science, The Ohio State University College of Food, Agriculture and Environmental Science, Columbus, OH, United States.
Jill E CairnsGlobal Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Harare, Zimbabwe.
Lennin MusundireAccelerated Breeding Initiative (ABI)-Transform, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya.
Biswanath DasAccelerated Breeding Initiative (ABI)-Transform, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya.
Olivia OdiyoAccelerated Breeding Initiative (ABI)-Transform, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya.
Sammy MadahanaAccelerated Breeding Initiative (ABI)-Transform, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya.
Purity MazibukoCrop Breeding Institute, Agricultural Research, Innovation and Specialist Services Directorate, Harare, Zimbabwe.
Washington MubverekiCrop Breeding Institute, Agricultural Research, Innovation and Specialist Services Directorate, Harare, Zimbabwe.
Boddupali M PrasannaGlobal Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya.
Dumisani KutywayoCrop Breeding Institute, Agricultural Research, Innovation and Specialist Services Directorate, Harare, Zimbabwe.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing the rate of genetic gain in breeding programs is a critical component of crop genetic improvement strategies to increase yields in smallholder farmers' fields. While a growing array of technologies and tools are being deployed within breeding programs, optimizing resource allocation could provide a simple yet effective way to increase genetic gain, particularly within resource-constrained breeding programs. The objective of this study was to demonstrate that an easy-to-use deterministic model and a breeding costing tool could identify key modifications to improve the efficiency of breeding within the Zimbabwean national maize breeding program. The current program uses pedigree inbreeding, with a 4-1-1 tester scheme, and relatively low selection intensity. The method of inbreeding, test-crossing schemes, and selection intensity were modified within the current program budget. A combination of using doubled haploid lines, a 2-2-1 tester plan, and increased selection intensity improved gain per cycle by 42.8%, gain per year by 161.8%, gain per dollar by 43.1%, and decreased cost of one unit of genetic gain by 28.5% without a change in budget. Our results highlight how a simple deterministic model can identify steps to greatly improve breeding efficiency within resource-constrained breeding programs.

Indexed as

breeding efficiencybreeding optimizationcontinuous improvementdeterministic modelgenetic gain

Identifiers

PMID40530281
PMCPMC12170565

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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.