Jove
Visualize
Contact Us
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

Related Experiment Videos

Data verification in the residue laboratory

J A Ault1, P S Cassidy, C J Crawford

  • 1Ricerca, Inc., Painesville, Ohio 44077, USA.

Quality Assurance (San Diego, Calif.)
|December 1, 1994
PubMed
Summary

Quality assurance (QA) in residue analysis is streamlined by a new data verification program. This system ensures data integrity and efficient review, benefiting both scientists and QA auditors.

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

Correction: Sulfated mannan of diatoms selects host-specific microbiota in the sunlit ocean.

Microbiome·2026
Same author

Sulfated mannan of diatoms selects host-specific microbiota in the sunlit ocean.

Microbiome·2026
Same author

Stability of picrotoxin during yogurt manufacture and storage.

Journal of food science·2008
Same author

Application of neural networks to the analysis of pyrolysis mass spectra.

Zentralblatt fur Bakteriologie : international journal of medical microbiology·1997
Same author

Immunoelectrochemical assays for bacteria: use of epifluorescence microscopy and rapid-scan electrochemical techniques in development of an assay for Salmonella.

Analytical chemistry·1996
Same author

Growth profiles and articular cartilage characterization in a goat model of Legg-Calve-Perthes disease.

Journal of investigative surgery : the official journal of the Academy of Surgical Research·1995

Area of Science:

  • Analytical Chemistry
  • Quality Assurance
  • Data Management

Background:

  • Residue analysis generates large data volumes, challenging quality assurance (QA) auditors.
  • A defined process is crucial to ensure data quality and integrity for scientists and QA auditors.

Purpose of the Study:

  • To present a program that ensures complete and appropriate data verification before submission to the Quality Assurance Unit (QAU).
  • To introduce the "Guidelines for Peer Review of Data" to optimize review time and clarify acceptable data standards.

Main Methods:

  • Implementation of a structured data verification program.
  • Incorporation of five core elements: study initiation meetings, calculations, verification, approval, and a verification checklist.

Related Experiment Videos

Main Results:

  • The program provides a systematic approach to data auditing.
  • Enhances confidence in the quality and integrity of residue analysis data.

Conclusions:

  • The "Guidelines for Peer Review of Data" program effectively addresses challenges in residue analysis QA.
  • This systematic approach ensures reliable data for scientific and auditing purposes.