Datasets

subject: Remote Sensing subject: Sorghum

Total is 11 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

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

Geospatial Image Data for Sorghum Phenotyping

10.4231/MY7W-FH43

Ayman F Habib ORCID logo , Ed Delp ORCID logo , Keith A Cherkauer ORCID logo , Larry L. Biehl ORCID logo , Melba M Crawford , Mitchell Tuinstra ORCID logo

05/27/2021

This publication includes sample rgb and hyperspectral image data collected in 2018 by unmanned aerial systems for a Sorghum Phenotying and Trait Analysis project being conducted at Purdue's Agronomy Center for Research and Education (ACRE).

Agronomy hyperspectral Phenotyping Remote Sensing Sorghum UAS

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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