Datasets

Subject
Creator
Type
Date

subject: Remote Sensing subject: Corn

Total is 30 Results
Purdue Agronomy Farm Corn Cultural Practices (791803)

10.4231/R72B8VZN

Craig S. T. Daughtry

04/06/2015

The objectives of this experiment are to determine (1) the threshold of early season spectral detection of corn, (2) the spectral response of corn as a function of growth and amount of vegetation, and (3) the effect of soil background differences.

Agriculture Corn Crop Science Crops Exotech 100 LARS radiometer Remote Sensing soil Soil Science solar illumination spectral observations

Purdue Agronomy Farm Corn Moisture Stress (791801)

10.4231/R7DF6P5N

Craig S. T. Daughtry

04/22/2015

This experiment was a limited study of the effects of deficits in plant available moisture on the spectral characteristics of corn canopies.

Agriculture Corn Crop Science Crops Exotech 20C-SW LARS Remote Sensing Soil Science spectral observations spectrometer

Purdue Agronomy Farm Corn Nitrogen (791802)

10.4231/R7NZ85MC

Craig S. T. Daughtry

04/22/2015

The specific objectives of the experiment were to determine the threshold of spectral detection of nitrogen deficiency and to determine kind and magnitude of changes in reflectance and thermal response as a function of level of nitrogen nutrition.

Agriculture Corn Crop Science Crops Exotech 20C-SW LARS Remote Sensing Soil Science solar illumination spectral observations spectrometer

Iowa Intensive Test Site 0893 (791237)

10.4231/R7ST7MR1

Marvin E. Bauer

04/06/2015

The purpose of the experiment is to study the spectral characteristics and separability of corn, soybeans, oats, and pasture as a function of growth stage and cultural practices.

Agriculture Corn Crop Science Crops FSS Grass LARS oats Remote Sensing soil Soil Science solar illumination Soybeans spectral observations spectrometer

South Dakota Intensive Test Site 1687 (791227)

10.4231/R7HD7SK7

Marvin E. Bauer

04/15/2015

The purpose of the experiment is to study the spectral characteristics and separability of corn, soybeans, oats, and pasture as a function of growth stage and cultural practices.

Agriculture Alfalfa barley Corn Crop Science FSS Grass LARS oats Remote Sensing soil Soil Science spectral observations spring wheat Sunflower winter wheat

Iowa Intensive Test Site 0893 (801237)

10.4231/R7FJ2DQB

Marvin E. Bauer

04/01/2015

The purpose of the experiment is to study the spectral characteristics and separability of corn, soybeans, oats, and pasture as a function of growth stage and cultural practices.

Agriculture Corn Crop Science Crops FSS Grass helicopter mounted Field Spectrometer System Laboratory for Applications of Remote Sensing LARS Remote Sensing soil Soil Science solar illumination Soybeans spectral observations

Purdue Agronomy Farm Corn Hybrid (811801)

10.4231/R76H4FCH

Craig S. T. Daughtry

07/22/2015

Purdue Agronomy Farm Corn Hybrid test

Agriculture Corn Crop Science Crops Exotech 100 LARS radiometer Remote Sensing Soil Science solar illumination spectral observations

Iowa Intensive Test Site 0893 (811237)

10.4231/R7T72FD1

Marvin E. Bauer

07/22/2015

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 Grass LARS Remote Sensing soil Soil Science solar illumination Soybeans spectral observations spectrometer

North Dakota Intensive Test Site 0817 (811247)

10.4231/R7PG1PP9

Marvin E. Bauer

07/22/2015

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 barley Corn Crop Science Crops durum wheat FSS LARS oats Remote Sensing Soil Science solar illumination Soybeans spectral observations spring wheat sugar beets Sunflower

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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