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Autor: Mosisa Worku Regasa
CIMMYT Eastern Africa 2019 Regional Trial Report
MacDonald Jumbo Mosisa Worku Regasa Yoseph Beyene Dan Makumbi Prasanna Boddupalli (2021)
This dataset contains the results from three regional trials carried out in Eastern Africa in 2019. Each report focuses on a different product profile. Two reports present data for product profile EA-PP1, It focuses on includes early/intermediate-maturing white maize with multiple stress tolerance (drought, low N, MLN, MSV, TLB, GLS, ear rots) for the Eastern African rainfed mid-altitude dry/wet agro-ecologies. The third report presents data for product profile EA-PP2. It focuses on late-maturing, white maize varieties with multiple stress tolerance (drought, low N, GLS, TLB, MSV, ear rots, Striga) for the Eastern African rainfed upper mid-altitude region.
Dataset
2022 CIMMYT Maize Eastern Africa Product Profile 1A (PP1A) Product Announcement
Berhanu Tadesse Ertiro Yoseph Beyene Suresh L.M. Manje Gowda Anani Bruce Vijay Chaikam Walter Chivasa Mosisa Worku Regasa Michael Olsen Aparna Das Nicholas J. Davis Prasanna Boddupalli (2022)
New and improved maize hybrids, developed by the CIMMYT Global Maize Program, are available for uptake by public and private sector partners, especially those interested in marketing or disseminating hybrid maize seed across Eastern Africa and similar agro-ecologies in other regions. Each year, CIMMYT’s Global Maize Program conducts regional on-station and on-farm hybrid maize trials through a network of NARS and private seed companies in eastern and southern Africa under various management and environmental conditions. Promising maize hybrids developed by the CIMMYT-Africa team, along with relevant checks from private seed companies and National Agricultural Research Programs, are included in these trials. Phenotypic data collected in Stage 4 and Stage 5 trials for the selected hybrids from Product Profile 1A (PP1A) as well as information about the trial sites and management and environmental conditions are provided in this dataset.
Dataset