creator: Mitchell R Tuinstra, 0000-0002-5322-6519 date: 2023
10.4231/PF9S-4G38
Mitchell R Tuinstra , Seth A Tolley
07/26/2023
Remote sensing data evaluates all row segments of a plot, but the repeatability of traits from different row segments has not been evaluated. We evaluated which row segments provide the best repeatability and yield prediction of remote sensing traits.
Border effect High-throughput Phenotyping hyperspectral LiDAR Maize Plot trimming Predictive modelling Remote Sensing RGB Sorghum UAV
10.4231/A2WW-EF74
Mitchell R Tuinstra , Shelby M. Gruss
10/16/2023
The preference of dhurrin-free sorghum was evaluated using ewes in a free choice grazing trial comparing a dhurrin-free hybrid to commercial hyrbids, and a set of near isogenic lines varying in dhurrin production.
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
10.4231/PQFT-7G59
Mitchell R Tuinstra , Seth A Tolley
05/02/2023
The objective of this study was to assess genetic parameters and perform single- and multi-trait genomic prediction of grain yield and yield components assessed through ear photometry in three testcross populations of either temperate or tropical descent.
Ear Photometry Ear photometry in maize testcrosses Genomic Prediction Grain Yield Maize Multi-Trait Genomic Prediction Single-Trait Genomic Prediction Temperate Germplasm Tropical Germplasm Yield components
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