subject: Agronomy subject: Maize creator: Mitchell R Tuinstra, 0000-0002-5322-6519
Total is 2 Results
Investigating the Genomic Background and Predictive Ability of Genotype-by-environment Interactions in Maize Grain Yield Based on Reaction Norm Models
10.4231/0C1Q-2G44
Mitchell R Tuinstra
,
Seth A Tolley
05/12/2023
Genotype-by-environment interaction (GEI) is among the greatest challenges for maize breeding programs. The main objectives of this study were to evaluate genetic parameters and perform genomic prediction using a reaction norm model.
Agronomy G2F Genome-Wide Association Study Genomes 2 Fields Genomic Prediction Genotype-by-environment Interaction Grain Yield GxE Maize Multi-environment Trial Reaction Norm Model
Best linear unbiased predictions (BLUPs) for ear photometry traits of 831 testcross maize hybrids. This dataset was used in ANOVA and tukey testing to differentiate maize heterotic groups.
10.4231/D2JJ-Y263
Mitchell R Tuinstra
,
Seth A Tolley
10/12/2020
Ear photometry was used to characterize 298 ex-PVP inbred lines and 274 Drought Tolerant Maize for Africa (DTMA) inbred lines when crossed to Iodent (PHP02) and/or Stiff Stalk (2FACC) testers for 25 yield-related traits in 2017 and 2018.
Agronomy Ear photometry in maize testcrosses heat-tolerant maize Maize
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