Datasets

subject: Agronomy

Total is 104 Results
MEIGS Soil Ecology Project - Turco Lab 2014-2015

10.4231/R79W0CG7

Andrea Clavijo , Jacob D Widner , Lori A Hoagland , Marianne Bischoff Gray , Ronald F. Turco Jr. ORCID logo

12/12/2016

The purpose of this project was to study the effects of organic and conventional farming methods on soil microbial ecosystems by monitoring greenhouse gas (GHG) emissions from the soil during the planting season.

Agronomy Conventional Farming Crop Science Greenhouse Gas Emissions Organic Farming Soil Ecology Soil Emissions Soil Science

Uniform Soybean Tests Northern Region 2020

10.4231/ZWFR-8Y15

Adam Nicholas Brock , Guohong Cai

05/09/2022

This dataset contains tables prepared for the 2020 Uniform Soybean Tests Northern Region Report.

Agriculture Agronomy Botany Botany and Plant Pathology Crop Science Plant Pathology Soybeans USDA-ARS

Uniform Soybean Tests Northern Region 2021

10.4231/8FTE-B575

Adam Nicholas Brock , Guohong Cai

05/09/2022

This dataset contains tables prepared for the 2021 Uniform Soybean Tests Northern Region Report.

Agriculture Agronomy Botany Crop Science Plant Pathology Soybeans USDA-ARS

Surface boundary layer turbulence on an 11% slope.

10.4231/3PT4-GD65

Richard H Grant ORCID logo

05/31/2022

Surface Boundary Layer Turbulence measurements in presence of mesoscale slope flow of 11% slope.

Agronomy Mesoscale Meteorology planetary boundary layer Slope Position wind

Quantifying physiological trait variation with automated hyperspectral imaging in rice

10.4231/SY0A-W347

Augusto Souza , Carmela R. Guadagno , Chris Hoagland , Diane Ran Wang ORCID logo , Rachel Katrina Imel , To-Chia Ting ORCID logo , Yang Yang

12/08/2022

To predict rice physiological traits from automated hyperspectral data, 14 physiological traits were collected when the rice plants were six to 13 weeks old. Concurrently, side-view hyperspectral imaging events took place two to three times per week.

Agronomy Genetic Diversity growth traits Hyperspectral imaging Nitrogen Oryza sativa

Evaluation of water-deficit responses in wild-by-cultivated rice introgression lines

10.4231/0JP3-WK59

Diane Ran Wang ORCID logo , Rachel Katrina Imel

10/04/2022

Rice introgression lines were analyzed for their response to water-deficit conditions under controlled environments at Purdue University as well as a field setting in Stuttgart, Arkansas.

Agronomy Crop Science Drought Rice

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