Subject
- Agriculture 8
- Crop Science 8
- Soil Science 8
- Agronomy 2
Creator
- Craig S. T. Daughtry 4
- Marvin E. Bauer 3
- Mitchell R Tuinstra, 0000-0002-5322-6519 2
- Ayman F Habib, 0000-0001-6498-5951 1
- Ed Delp, 0000-0002-2909-7323 1
- Keith A Cherkauer, 0000-0002-6938-5303 1
- Larry L. Biehl, 0000-0002-2322-2445 1
- Melba M Crawford 1
- Meng-yang Lin 1
- Mitchell Tuinstra, 0000-0002-5322-6519 1
Type
- Dataset 11
Date
subject: Remote Sensing subject: Sorghum type: dataset
Total is 11 Results
Kansas Intensive Test Site 1988 (771207)
10.4231/R7XG9P2F
04/21/2015
The objective of this experiment was to provide a data set which can be used as an intermediate level of extrapolation between data collected from controlled experimental plots at field research stations and data collection by satellite scanners.
Agriculture Corn Crop Science Crops FSS LARS Remote Sensing soil Soil Science solar illumination Sorghum Soybeans spectral observations spectrometer winter wheat
Kansas Intensive Test Site 1988 (761207)
10.4231/R7251G4Z
04/21/2015
The objective of this experiment was to provide a data set which can be used as an intermediate level of extrapolation between data collected from controlled experimental plots at field research stations and data collection by satellite scanners.
Agriculture Alfalfa Corn Crop Science Crops FSS Grass LARS Remote Sensing soil Soil Science solar illumination Sorghum Soybeans spectral observations spectrometer winter wheat
Purdue Agronomy Farm Sorghum Cultural Practices (831808)
10.4231/R7SF2T4R
07/27/2015
Spectral observations of the farm sorghum cultural practices at Purdue.
Agriculture Barnes 12-1000 Crop Science Crops Exotech 100 LARS radiometer Remote Sensing Soil Science solar illumination Sorghum spectral observations
Purdue Agronomy Farm Sorghum Polarization (836401)
10.4231/R7X63JV2
07/16/2015
Purdue Agronomy Farm Sorghum Polarization Tests
Agriculture Crop Science Crops LARS Remote Sensing Soil Science solar illumination Sorghum spectral observations
Kansas Intensive Test Site 1960 (751207)
10.4231/R7P26W11
04/14/2015
The objective of this experiment was to provide a data set which can be used as an intermediate level of extrapolation between data collected from conrtolled experimental plots at field research stations and data collection by satellite scanners.
Agriculture Alfalfa Corn Crop Science Crops FSS Grass LARS Remote Sensing soil Soil Science solar illumination Sorghum Soybeans spectral observations spectrometer winter wheat
Purdue Agronomy Farm Sorghum Cultural Practices (811808)
10.4231/R7S75D8N
07/22/2015
Spectral observations of the farm sorghum cultural practices at Purdue.
Agriculture Barnes 12-1000 Crop Science Crops Exotech 100 LARS radiometer Remote Sensing Soil Science solar illumination Sorghum spectral observations
Purdue Agronomy Farm Soybean Row Direction (811810)
10.4231/R7NG4NJX
07/22/2015
Spectral observation
3M Flat Black 3M Flat White Agriculture Barnes 12-1000 Crop Science Crops LARS radiometer Remote Sensing soil Soil Science solar illumination Sorghum Soybeans spectral observations
Purdue Agronomy Farm Sorghum Cultural Practices (821808)
10.4231/R7MG7MF0
07/22/2015
Spectral observations of the farm sorghum cultural practices at Purdue.
Agriculture Barnes 12-1000 Crop Science Crops Exotech 100 LARS radiometer Remote Sensing Soil Science solar illumination Sorghum spectral observations
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
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
Display #
Results 1 - 10 of 11