Datasets

subject: Sorghum

Total is 20 Results
Kansas Intensive Test Site 1988 (771207)

10.4231/R7XG9P2F

Marvin E. Bauer

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

Marvin E. Bauer

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 Polarization (846401)

10.4231/R7PC309T

Vern C. Vanderbilt

07/28/2015

The purpose of this experiment is to characterize the polarization of a sorghum field at various view and illumination angles and by its physical and agronomic attributes.

Agriculture Barnes 12-1000 Crop Science Crops LARS radiometer Soil Science solar illumination Sorghum

Kansas Intensive Test Site 1960 (751207)

10.4231/R7P26W11

Marvin E. Bauer

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

Multi-Species Prediction of Physiological Traits with Hyper-Spectral Modeling

10.4231/FPHP-0153

Meng-yang Lin , Mitchell R Tuinstra ORCID logo

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

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