Subject
- Agronomy 2
Creator
- Mitchell R Tuinstra, 0000-0002-5322-6519 3
- Beichen Lyu 1
- Katy Rainey, 0000-0001-8541-5851 1
- Keith Cherkauer, 0000-0002-6938-5303 1
- Meng-yang Lin 1
- Seth A Tolley, 0000-0001-9664-3534 1
- Shelby M Gruss 1
- Stuart D Smith 1
Type
- Dataset 4
Date
subject: High-throughput Phenotyping type: dataset
Total is 4 Results
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
HTP-Soy: An Aerial Image Set of Multi-category Soybean for High-Throughput Phenotyping (HTP)
10.4231/ZAD3-MG98
Beichen Lyu
,
Katy Rainey
,
Keith Cherkauer
,
Stuart D Smith
01/06/2020
The publication “HTP-Soy” contains 1,728 aerial images of soybean plots in the field and each image is categorized based on spatial, temporal, and genetic variations. Data is made available to encourage development of HTP applications.
Agricultural and Biological Engineering Computer Vision High-throughput Phenotyping Image Dataset Indiana Plant Breeding Remote Sensing Soybean Unmanned Aerial Systems
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
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 - 4 of 4