Literature DB >> 22468371

Probability of identification: a statistical model for the validation of qualitative botanical identification methods.

Robert A LaBudde1, James M Harnly.   

Abstract

A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.

Entities:  

Mesh:

Year:  2012        PMID: 22468371      PMCID: PMC3620024          DOI: 10.5740/jaoacint.11-266

Source DB:  PubMed          Journal:  J AOAC Int        ISSN: 1060-3271            Impact factor:   1.913


  1 in total

1.  Probability of Detection (POD) as a statistical model for the validation of qualitative methods.

Authors:  Paul Wehling; Robert A LaBudde; Sharon L Brunelle; Maria T Nelson
Journal:  J AOAC Int       Date:  2011 Jan-Feb       Impact factor: 1.913

  1 in total
  8 in total

Review 1.  The Importance of Method Selection in Determining Product Integrity for Nutrition Research.

Authors:  Elizabeth M Mudge; Joseph M Betz; Paula N Brown
Journal:  Adv Nutr       Date:  2016-03-15       Impact factor: 8.701

Review 2.  The Challenge of Reproducibility and Accuracy in Nutrition Research: Resources and Pitfalls.

Authors:  Barbara C Sorkin; Adam J Kuszak; John S Williamson; D Craig Hopp; Joseph M Betz
Journal:  Adv Nutr       Date:  2016-03-15       Impact factor: 8.701

3.  Comparison of Flow Injection MS, NMR, and DNA Sequencing: Methods for Identification and Authentication of Black Cohosh (Actaea racemosa).

Authors:  James Harnly; Pei Chen; Jianghao Sun; Huilian Huang; Kimberly L Colson; Jimmy Yuk; Joe-Ann H McCoy; Danica T Harbaugh Reynaud; Peter B Harrington; Edward J Fletcher
Journal:  Planta Med       Date:  2015-12-21       Impact factor: 3.352

Review 4.  Selection and characterization of botanical natural products for research studies: a NaPDI center recommended approach.

Authors:  Joshua J Kellogg; Mary F Paine; Jeannine S McCune; Nicholas H Oberlies; Nadja B Cech
Journal:  Nat Prod Rep       Date:  2019-08-14       Impact factor: 13.423

Review 5.  Dietary Supplements: Regulatory Challenges and Research Resources.

Authors:  Johanna T Dwyer; Paul M Coates; Michael J Smith
Journal:  Nutrients       Date:  2018-01-04       Impact factor: 5.717

Review 6.  The Importance of Reference Materials and Method Validation for Advancing Research on the Health Effects of Dietary Supplements and Other Natural Products.

Authors:  Sanem Hosbas Coskun; Stephen A Wise; Adam J Kuszak
Journal:  Front Nutr       Date:  2021-12-14

Review 7.  Analytical Challenges and Metrological Approaches to Ensuring Dietary Supplement Quality: International Perspectives.

Authors:  Alessandra Durazzo; Barbara C Sorkin; Massimo Lucarini; Pavel A Gusev; Adam J Kuszak; Cindy Crawford; Courtney Boyd; Patricia A Deuster; Leila G Saldanha; Bill J Gurley; Pamela R Pehrsson; James M Harnly; Aida Turrini; Karen W Andrews; Andrea T Lindsey; Michael Heinrich; Johanna T Dwyer
Journal:  Front Pharmacol       Date:  2022-01-11       Impact factor: 5.810

8.  Detection of adulterated Ginkgo biloba supplements using chromatographic and spectral fingerprints.

Authors:  James M Harnly; Devanand Luthria; Pei Chen
Journal:  J AOAC Int       Date:  2012 Nov-Dec       Impact factor: 1.913

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.