Subject
- Crop Science 46
- Agriculture 40
- Botany 33
- Plant Pathology 33
- Soil Science 12
- Geographic Information Systems (GIS) 4
Creator
- Wad D. Crochet 12
- Darrell Schulze, 0000-0001-9278-2457 9
- J.R. Wilcox 9
- Joshua Minai 9
- Mitchell Tuinstra, 0000-0002-5322-6519 9
- Gary Nowling 7
- Sara Peel 7
- T. Scott Abney 7
- Guohong Cai 6
- Jeffrey J. Volenec, 0000-0002-5455-6157 6
Type
- Dataset 101
Date
subject: Agronomy type: dataset
Total is 101 Results
Phosphorus and Potassium Influence on Alfalfa Nutrition
10.4231/D3251FJ7S
02/22/2012
Data from several studies on the influence of phosphorus and potassium nutrition on alfalfa. It includes numeric data such as yield, plant mass, plant counts, and tissue concentration of various nutrients
Agronomy Crop Science Forage legumes Nutritive value Soil Fertility Soil Science Winter hardiness Yield components
Southeast Purdue Agricultural Center (SEPAC) drainage research data, 1984-2020
10.4231/CTM1-0Y45
Eileen J Kladivko
,
Giorgi Chighladze
,
Laura C Bowling
,
Lori Abendroth
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.
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.
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
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
,
Rachel Katrina Imel
,
To-Chia Ting
,
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
,
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.
Seedling growth and fall armyworm feeding preference influenced by dhurrin production in sorghum
10.4231/H1VR-0R08
Mitchell Tuinstra
,
Shelby M Gruss
12/22/2021
Dhurrin plays a key role in host-plant defense of sorghum. Studies of genetic mutants coupled with nondestructive phenotyping techniques revealed a significant metabolic tradeoff between dhurrin production and plant growth in sorghum seedlings.
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
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