Jove
Visualize
Contact Us

Related Experiment Videos

Detecting mycotoxins in agricultural commodities.

Thomas B Whitaker1

  • 1USDA/ARS, Box 7625, North Carolina State University, Raleigh, NC 27695-7625, USA.

Molecular Biotechnology
|March 4, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Use of Combined Uncertainty of Pesticide Residue Results for Testing Compliance with Maximum Residue Limits (MRLs).

Journal of agricultural and food chemistry·2015
Same author

Development of an incurred cornbread model for gluten detection by immunoassays.

Journal of agricultural and food chemistry·2013
Same author

Correlation between aflatoxin contamination and various USDA grade categories of shelled almonds.

Journal of AOAC International·2010
Same author

Effect of sample size in the evaluation of "in-field" sampling plans for aflatoxin B(1) determination in corn.

Journal of agricultural and food chemistry·2010
Same author

Sampling and analytical variability associated with the determination of aflatoxins and ochratoxin A in bulk lots of powdered ginger marketed in 1-lb bags.

Analytical and bioanalytical chemistry·2009
Same author

Sampling and analytical variability associated with the determination of total aflatoxins and ochratoxin A in powdered ginger sold as a dietary supplement in capsules.

Journal of agricultural and food chemistry·2008
Same journal

Applications of Recombinant DNA Technology in Medicine: A Comprehensive Review.

Molecular biotechnology·2026
Same journal

Optimizing miRNA Loading into Platelet Exosomes via Electroporation: A Comparative Analysis of Buffer Systems and Voltage Parameters for Enhanced Targeted Drug Delivery.

Molecular biotechnology·2026
Same journal

Regulation of Goat Milk Protein Synthesis: Genetic Architecture, Signalling Pathways, and Omics Insights.

Molecular biotechnology·2026
Same journal

Cloning and Functional Characterization of AhyAP-T65Lig, an ATP-Dependent DNA Ligase from Trabzonvirus AP-T65.

Molecular biotechnology·2026
Same journal

Overexpression of the ATP-Citrate Lyase Gene Enhances Ganoderic Acid Biosynthesis in Ganoderma lingzhi.

Molecular biotechnology·2026
Same journal

CRISPR/Cas9 Mediated Genome Editing for Enhancing Abiotic Stress Tolerance in Rice: An Omics Guided Perspective.

Molecular biotechnology·2026
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Estimating mycotoxin concentration in bulk lots is challenging due to variability in sampling and testing. Reducing variability in sampling, sample preparation, and analytical methods is crucial for accurate mycotoxin testing.

Area of Science:

  • Food Science
  • Analytical Chemistry
  • Agricultural Science

Background:

  • Accurate mycotoxin concentration estimation in bulk lots is hindered by sampling limitations.
  • Mycotoxin test procedures involve multiple steps, each introducing variability.
  • Variability in mycotoxin testing increases with higher contaminant concentrations.

Purpose of the Study:

  • To highlight the challenges in obtaining precise mycotoxin concentration estimates from bulk lots.
  • To identify sources of variability within mycotoxin test procedures.
  • To discuss methods for reducing variability in mycotoxin analysis.

Main Methods:

  • The study analyzes the inherent variability in each step of a typical mycotoxin test procedure.
  • It examines how variance statistics change with increasing mycotoxin concentration.

Related Experiment Videos

  • Methods for mitigating sampling, sample preparation, and analytical variability are discussed.
  • Main Results:

    • Sampling is identified as the primary source of variability in mycotoxin testing.
    • Variability is exacerbated by the heterogeneous distribution of mycotoxins, with some kernels showing high contamination levels.
    • The study demonstrates that variability increases as mycotoxin concentration rises.

    Conclusions:

    • Precise mycotoxin quantification from bulk lots is inherently difficult due to significant sampling variability.
    • Understanding and addressing variability in sampling, sample preparation, and analytical steps are essential for improving accuracy.
    • Further research into methods for reducing these sources of variability is warranted for reliable mycotoxin risk assessment.