Subject
- Agronomy 3
Creator
- Shelby M Gruss 2
- Keith Johnson 1
- Meng-yang Lin 1
- Seth A Tolley, 0000-0001-9664-3534 1
- Shelby M. Gruss 1
Type
- Dataset 5
Date
subject: Sorghum creator: Mitchell R Tuinstra, 0000-0002-5322-6519
Total is 5 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.
Preference of dhurrin-free sorghum by ewes
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.
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.
Row Selection in Remote Sensing for Maize and Sorghum
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
Display #
Results 1 - 5 of 5