Free, open access repository of research studies developed by CIMMYT scientists.
Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

11 to 20 of 10,526 Results
Mar 31, 2026
Kamaluddin Tijani ALIYU; Joao Vasco SILVA; Bisrat Haile GEBREKIDAN; Tesfaye Shiferaw SIDA; Samuel GAMEDA; Deo-Gratias HOUGNI; Frederic BAUDRON; Nicholaus KUBOJA; Zampela PITTAKI; Elvis WEULLOW; Dickens ATEKU; Valentine KARARI; Jordan CHAMBERLIN, 2026, "Agronomic data of on-farm trials on yield response to lime rates in Tanzania", https://doi.org/10.71682/10549400, CIMMYT Research Data & Software Repository Network, V1
This dataset was generated as part of the Guiding Acid Soil Management Investments in Africa (GAIA) project, which aims to support evidence-based investments in acid soil management across sub-Saharan Africa. Within this project, researcher-managed on-farm trials were established...
Comma Separated Values - 175.0 KB - MD5: 7cbc9e7c95c95366c8b143ad639f7956
Mar 31, 2026
Kamaluddin Tijani ALIYU; Joao Vasco SILVA; Bisrat Haile GEBREKIDAN; Tesfaye Shiferaw SIDA; Samuel GAMEDA; Deo-Gratias HOUGNI; Frederic BAUDRON; Richard KAUNDA; Zampela PITTAKI; Elvis WEULLOW; Dickens ATEKU; Valentine KARARI; Jordan CHAMBERLIN, 2026, "Soil properties predicted from mid-infrared spectral (MIRS) analysis of 366 soil samples collected in 2024 before and/or after establishing on-farm trials on yield response to lime rates in Zambia", https://doi.org/10.71682/10549395, CIMMYT Research Data & Software Repository Network, V1
Selected soil properties were predicted from 366 topsoil samples subjected to spectral analysis (MIRS). A subset of samples were also subjected to wet chemistry analysis (see link in the PDF report), and results were used to calibrate a machine-learning algorithm developed by the...
Feb 23, 2026
Sida,Tesfaye Shiferaw; Gebrekidan, Bisrat Haile; Silva, Joao Vasco; Gameda, Samuel; Hougni,Deo-Gratias; Baudron, Frederic; Desalegn, Temesgen; Pittaki, Zampela; Weullow, Elvis; Ateku, Dickens; Karari, Valentine; Chamberlin, Jordan, 2025, "Soil properties predicted from mid-infrared spectral (MIRS) analysis of soil samples collected in 2023 (second year) before and/or after establishing on-farm trials on yield response to lime rates in Ethiopia", https://doi.org/10.71682/10549328, CIMMYT Research Data & Software Repository Network, V2
Selected soil properties were predicted from 232 topsoil samples subjected to spectral analysis (MIRS). A subset of samples were also subjected to wet chemistry analysis, and results were used to calibrate a machine-learning algorithm developed by the International Centre for Res...
Feb 10, 2026
Vitale, Paolo; Crossa, Jose; Montesinos-López, Abelardo; Ammar, Karim; Dreisigacker, Susanne; Govindan, Velu; Montesinos-López, Osval A; Thompson, Gilberto; Gardner, Keith; Reynolds, Matthew; Gerard, Guillermo, 2026, "Replication Data for: Multi-Omics Prediction for Yellow Rust in Bread and Durum Wheat Through Conventional and AI-based Frameworks", https://doi.org/10.71682/10549375, CIMMYT Research Data & Software Repository Network, V1
Yellow rust (YR) is a major threat to both bread and durum wheat production. In this study, we evaluated alternatives to visual scoring. We tested the predictability (PA) using genomic and phenomic data for YR severity under multiple prediction scenarios in one biparental bread w...
Add Data

Sign up or log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.