Related Experiment Video
Updated: Jan 28, 2026

10:05
Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation
Published on: July 4, 2014
14.8K
Soil Variables Associated with Sudden Death Syndrome in Soybean Fields in Iowa
H Scherm1, X B Yang2, P Lundeen2
1Department of Plant Pathology, University of Georgia, Athens 30602.
Plant Disease
|March 13, 2019
Summary
Sudden death syndrome in soybeans is primarily caused by Fusarium solani f. sp. glycines. Soil nutrient manipulation shows limited potential for disease reduction, emphasizing pathogen control instead.
Area of Science:
- Plant Pathology
- Agronomy
- Soil Science
Background:
- Sudden death syndrome (SDS) prevalence is increasing in U.S. soybean production.
- Factors influencing SDS severity in the Fusarium solani f. sp. glycines pathosystem are poorly understood.
- Research is needed to identify soil and environmental correlates of SDS.
Purpose of the Study:
- To investigate associations between soil variables and SDS foliar symptom severity.
- To determine the influence of soil biological, chemical, and physical properties on SDS.
- To assess the impact of Fusarium solani f. sp. glycines and Heterodera glycines on SDS.
Main Methods:
- Field study across nine commercial soybean fields in Iowa (1995-1996).
- Soil sampling along transects from symptomless to diseased areas (25 stops/transect).
- Assays for F. solani f. sp. glycines, Heterodera glycines cysts, and soil chemical properties (pH, nutrients, etc.).
- Measurement of soil strength, moisture, and foliar disease severity.
Main Results:
- SDS severity strongly associated with F. solani f. sp. glycines populations.
- Soybean cyst nematode (Heterodera glycines) presence showed a minor association with SDS.
- Available potassium (K) showed a context-dependent association with disease severity.
- No consistent associations found for other soil variables (e.g., pH, organic matter, other nutrients).
Conclusions:
- Localized distribution of F. solani f. sp. glycines is the primary driver of SDS patchiness.
- Soil nutrient manipulation has limited potential for SDS management in high-yield Iowa soybean systems.
- Focus should be on preventing establishment and reducing populations of F. solani f. sp. glycines and H. glycines.
Keywords:
risk assessmentRelated Concept Videos
The Soil Ecosystem
24.7K
Plants obtain inorganic minerals and water from the soil, which acts as a natural medium for land plants. The composition and quality of soil depend not only on the chemical constituents but also on the presence of living organisms. In general, soils contain three major components:
24.7K
Variables Affecting Phosphorescence and Fluorescence
1.5K
Fluorescence and phosphorescence are essential phenomena in fields like analytical chemistry, biological imaging, and materials science, where they detect molecular properties and visualize cellular structures. Understanding the variables that influence these luminescent behaviors is crucial for maximizing accuracy and efficiency in their applications. These variables can broadly be grouped into chemical structure, solvent properties, and external conditions, each playing a distinct role in...
1.5K
Variability: Analysis
500
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
The range is a simple measure of variability, indicating the difference between the highest and...
500
Random Variables
17.8K
A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
17.8K
Work and Energy for Variable Forces
5.8K
When an object is acted upon by a variable force, the amount of work done and the change in energy of the object can be more complex to calculate compared to when a constant force is applied. Work is the product of force and displacement, while energy is the capacity of a system to do work. When a constant force is applied to an object, the work done can be calculated as the product of the force and the distance moved in the direction of the force. However, when a variable force is applied, the...
5.8K
Overview of Cell Death
9.8K
Cell death is an essential process where the body gets rid of old or damaged cells. Cell proliferation and death need to be balanced, as an imbalance between the two may lead to cancer or autoimmune diseases.
Cell death was observed in the early 19th century, but there was no experimental evidence to prove it. In 1842, Carl Vogt first discovered cell death in a metamorphic toad; however, it was not termed ‘cell death.’ Scientists discovered different cell death pathways only in the...
Cell death was observed in the early 19th century, but there was no experimental evidence to prove it. In 1842, Carl Vogt first discovered cell death in a metamorphic toad; however, it was not termed ‘cell death.’ Scientists discovered different cell death pathways only in the...
9.8K

