subject: Agronomy creator: Mitchell R Tuinstra, 0000-0002-5322-6519
Total is 6 Results
Multi-Species Prediction of Physiological Traits with Hyper-Spectral Modeling
10.4231/FPHP-0153
Meng-yang Lin
,
Mitchell R Tuinstra
02/11/2022
High-throughput hyperspectral imaging in corn and sorghum can be used in multi-species models to predict water and nitrogen status of plants within and across these crop species.
Abiotic stress Agronomy Corn Ecophysiology High-throughput Phenotyping Machine Learning nitrogen content partial least square regression relative water content Remote Sensing Sorghum
Expression of Stay-Green in Dhurrin-Free Sorghum
10.4231/4ABA-TW22
Mitchell R Tuinstra
,
Shelby M Gruss
07/15/2022
This data examines the effects dhurrin production has on the stay-green trait by utilizing near isogenic lines, near isogenic backcrosses, and near isogenic hybrids varying in dhurrin production.
Seedling growth and fall armyworm feeding preference influenced by dhurrin production in sorghum
10.4231/3PQE-NP07
Mitchell R Tuinstra
,
Shelby M Gruss
06/15/2021
Dhurrin plays a key role in host-plant defense of sorghum. Studies of genetic mutants coupled with nondestructive phenotyping techniques revealed a significant metabolic tradeoff between dhurrin production and plant growth in sorghum seedlings.
Agronomy dhurrin High-throughput Phenotyping Spodoptera frugiperda
Stability of dhurrin and HCN release in dried sorghum samples
10.4231/SDJ6-9C84
Keith Johnson
,
Mitchell R Tuinstra
,
Shelby M Gruss
05/31/2022
Dhurrin is a cyanogenic glucoside of sorghum. Dhurrin content is thought to decline when making sorghum hay. Contrary to expectations, this study demonstrated that dhurrin was stable in sorghum tissues during the hay drying and curing process.
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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