PURR Registry

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

Agriculture Barnes 12-1000 Crop Science Crops LARS radiometer Remote Sensing Soil Science solar illumination spectral observations Wheat

Purdue Agronomy Farm Corn Solar Radiation Intercepted (SRI) (831805)

10.4231/R7V122QR

Craig S. T. Daughtry

07/27/2015

The overall objectives of this research are the identification and measurement of corn crop canopy variables which are related to crop growth and final yield and relationships between those variables and remotely sensed canopy spectral reflectance.

Agriculture Barnes 12-1000 Corn Crop Science Crops Exotech 100 LARS radiometer Remote Sensing solar illumination spectral observations

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

Modeling density surfaces of intraspecific classes using camera-trap distance sampling

10.4231/RF5H-C895

Rob Swihart , Zackary Delisle

02/07/2023

Density surface modelling of intraspecific classes using camera-trap-distance-sampling data and hierarchical generalized additive modelling.

abundance deer density surface modelling Forestry and Natural Resources generalized additive model precision recruitment Remote Sensing ungulate

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