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Replication Data for: Discovery of Genomic Regions Associated with Grain Yield and Agronomic Traits in Bi-parental Populations of Maize (Zea mays. L) under Optimum and Low Nitrogen Conditions

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Title Replication Data for: Discovery of Genomic Regions Associated with Grain Yield and Agronomic Traits in Bi-parental Populations of Maize (Zea mays. L) under Optimum and Low Nitrogen Conditions
 
Identifier https://hdl.handle.net/11529/10548940
 
Creator Kimutai, Collins
Ndlovu, Noel
Chaikam, Vijay
Tadesse Ertiro, Berhanu
Das, Biswanath
Beyene, Yoseph
Kiplagat, Oliver
Spillane, Charles
Prasanna, B.M.
Gowda, Manje
 
Publisher CIMMYT Research Data & Software Repository Network
 
Description Low soil nitrogen stress can contribute to food insecurity, malnutrition, and rural poverty in maize-dependent smallholder communities of sub-Saharan Africa (SSA). Enhanced selection for improved varieites may result from a better understanding of the genomic regions associated with low nitrogen tolerance. Four F3 maize populations were used to study the genetic architecture of grain yield (GY) and its associated traits (anthesis-silking interval (ASI), anthesis date (AD), plant height (PH), ear position (EPO), and ear height (EH)) under different soil nitrogen regimes in Kenya and Zimbabwe. Information about the populations and the genotypic data used in the analyses are provided in this dataset. The results of the analysis are reported in the related journal article.
 
Subject Agricultural Sciences
Grain Yield
Ear Position
Ear Height
Plant Height
ASI
Days to Anthesis
Zea mays
Maize
Plant Breeding
Crop Improvement
Agricultural research
 
Language English
 
Date 2023
 
Contributor Dreher, Kate
CGIAR
CGIAR Research Program on Maize (MAIZE)
Global Maize Program (GMP)
Bill and Melinda Gates Foundation (BMGF)
Foundation for Food and Agriculture Research (FFAR)
United States Agency for International Development (USAID)
European Commission
Science Foundation Ireland (SFI)
Stress Tolerant Maize for Africa (STMA)
Improved Maize for African Soils (IMAS)
Accelerating Genetic Gains in Maize and Wheat for Improved Livelihoods (AGG)
Development Smart Innovation through Research in Agriculture (DeSIRA)
LEG4DEV
 
Type Genotypic data
Experimental data