Related Experiment Video
Updated: Feb 8, 2026
03:53
Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
2.0K
Development and Application of a TaqMan Probe-Based qPCR Detection Assay for Detecting Fusarium pseudograminearum
Li Yan1, Zhiwei Mao1, Meixin Yang1
1State Key Laboratory for Biology of Plant Disease and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China.
Phytopathology
|February 6, 2026
Summary
A new TaqMan qPCR assay effectively detects Fusarium pseudograminearum, the cause of Fusarium crown rot (FCR) in wheat. Cyclobutrifluram seed treatment suppressed pathogen biomass, unlike tebuconazole, providing insights for FCR management.
Area of Science:
- Plant Pathology
- Molecular Biology
- Agricultural Science
Background:
- Fusarium crown rot (FCR) is a growing threat in China's Huanghuai wheat region.
- Fusarium pseudograminearum is the primary pathogen responsible for FCR.
Purpose of the Study:
- Develop a specific and sensitive TaqMan qPCR assay for F. pseudograminearum detection.
- Investigate the seasonal dynamics of F. pseudograminearum in wheat and soil.
- Evaluate the efficacy of seed treatments against FCR.
Main Methods:
- Developed a TaqMan qPCR assay targeting the FpAH1 gene.
- Validated assay specificity against multiple fungal species.
- Monitored pathogen dynamics over two growing seasons with untreated, tebuconazole, and cyclobutrifluram seed treatments.
Main Results:
- The qPCR assay demonstrated high efficiency (105.3%) and a low LOD (1 × 10² copies/μL).
- Cyclobutrifluram significantly reduced F. pseudograminearum biomass in wheat plants.
- Tebuconazole showed no significant effect; pathogen biomass peaked late in the season across treatments.
Conclusions:
- A reliable qPCR assay for F. pseudograminearum detection was established.
- Pathogen dynamics in wheat and soil were characterized, informing FCR control strategies.
- Cyclobutrifluram shows promise for managing FCR in wheat cultivation.
Related Concept Videos
01:00Detection of Gross Error: The Q Test
7.0K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
7.0K
01:10Detection of Black Holes
2.6K
Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
Not until the 1960s, when the first neutron...
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
Not until the 1960s, when the first neutron...
2.6K
01:05Difference from Background: Limit of Detection
8.4K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
The LOD indicates the presence or absence...
8.4K
01:18Effects of EDTA on End-Point Detection Methods
667
Different methods, such as visual observance of metal-ion indicators, spectroscopic techniques, and potentiometric methods, can determine the endpoint of an EDTA titration.
In the visual method, metal-ion indicators (metallochromic dyes), which have distinct colors in their free and complex forms, are added to the mixture to signal the titration's end point. They form stable complexes with metal ions, but these complexes are weaker than the corresponding metal–EDTA complexes. As a...
In the visual method, metal-ion indicators (metallochromic dyes), which have distinct colors in their free and complex forms, are added to the mixture to signal the titration's end point. They form stable complexes with metal ions, but these complexes are weaker than the corresponding metal–EDTA complexes. As a...
667
01:12Types of Errors: Detection and Minimization
11.4K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
11.4K
01:19Precipitation Titration: Endpoint Detection Methods
6.0K
In argentometric precipitation titrations, endpoints can be detected visually by the Mohr, Volhard, and Fajans methods. In the Mohr method, adding a soluble chromate indicator gives an initial yellow color to the analyte solution. As the titrant is added, the first excess of silver ions forms a red silver chromate precipitate, marking the endpoint. The solution pH should be maintained at about 8 by adding solid CaCO3.
In the Volhard method, a standard excess of AgNO3 is first added to the...
In the Volhard method, a standard excess of AgNO3 is first added to the...
6.0K