Datasets

subject: Corn subject: Agronomy

Total is 12 Results
Southeast Purdue Agricultural Center (SEPAC) drainage research data, 1984-2020

10.4231/CTM1-0Y45

Eileen J Kladivko ORCID logo , Giorgi Chighladze ORCID logo , Laura C Bowling ORCID logo , Lori Abendroth ORCID logo

12/16/2022

This dataset contains research data obtained during a long-term subsurface drainage research project conducted at the Southeast Purdue Agricultural Center in Jennings County, Indiana, from 1984 to 2020.

Agronomy Corn Crop yield Drainage Indiana

Agronomic responses of soybean to long-term implementation of tillage and crop rotation systems in Indiana from 1975 to 2022

10.4231/2KQ5-KR50

D R Griffith , Garrett S Verhagen , J V Mannering , Terry D West , Tony J Vyn ORCID logo

02/02/2023

This dataset includes soybean population, heights, grain moisture at harvest, and grain yield measured in the Long-Term Tillage (LTT) study at the Agronomy Center for Research and Education (ACRE) in West Lafayette, IN, USA from 1975 to 2022.

Agronomy chisel-plow conservation tillage Corn crop rotation grain moisture Grain Yield Maize moldboard-plow no-till plant height plant population planting date Purdue University ridge-till Soybean strip-till

Agronomic responses of corn to long-term implementation of tillage and crop rotation systems in the US Corn Belt, from 1975 to 2022

10.4231/E031-BS21

D R Griffith , Garrett Verhagen , J V Mannering , Terry D West , Tony Vyn ORCID logo

02/02/2023

This dataset includes corn population, heights, grain moisture at harvest, and grain yield measured in the Long-Term Tillage (LTT) study at the Agronomy Center for Research and Education (ACRE) in West Lafayette, IN, USA from 1975 to 2022.

Agronomy chisel-plow conservation tillage Corn crop rotation grain moisture Grain Yield Maize moldboard-plow no-till plant height plant population planting date Purdue University ridge-till Soybean strip-till

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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