Probability of Identification: A Statistical Model for the Validation of Qualitative Botanical Identification Methods

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

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

The increased utilization of metrology resources and expanded application of its’ approaches in the development of internationally agreed upon measurements can lay the basis for regulatory harmonization, support reproducible research, and advance scientific understanding, especially of dietary supplements and herbal medicines. Yet, metrology is often underappreciated and underutilized in dealing with the many challenges presented by these chemically complex preparations. This article discusses the utility of applying rigorous analytical techniques and adopting metrological principles more widely in studying dietary supplement products and ingredients, particularly medicinal plants and other botanicals. An assessment of current and emerging dietary supplement characterization methods is provided, including targeted and non-targeted techniques, as well as data analysis and evaluation approaches, with a focus on chemometrics, toxicity, dosage form performance, and data management. Quality assessment, statistical methods, and optimized methods for data management are also discussed. Case studies provide examples of applying metrological principles in thorough analytical characterization of supplement composition to clarify their health effects. A new frontier for metrology in dietary supplement science is described, including opportunities to improve methods for analysis and data management, development of relevant standards and good practices, and communication of these developments to researchers and analysts, as well as to regulatory and policy decision makers in the public and private sectors. The promotion of closer interactions between analytical, clinical, and pharmaceutical scientists who are involved in research and product development with metrologists who develop standards and methodological guidelines is critical to advance research on dietary supplement characterization and health effects

The First Step—Monitoring What We Eat

Nestled in the Maryland suburbs outside northeast Washington, D.C., is arguably the world’s largest and most diversified agricultural research complex—the Henry A. Wallace Beltsville Agricultural Research Center (BARC). Among its 7,000 acres of fields, farmland, and science buildings is the Beltsville Human Nutrition Research Center (BHNRC)—the oldest and most comprehensive of six human nutrition research centers within the Agricultural Research Service. Two new buildings— totaling more than 100,000 square feet of research space—were added to BHNRC in 2003. “The first human nutrition research conducted by the U.S. Department of Agriculture dates back to the late 1890s,” says Allison Yates, the nutrition center’s former director, “and USDA nutrition research first moved to the Beltsville area in 1941.” Yates is now BARC’s associate director. Nutrition center researchers oversee the national food and nutrient databases and national dietary-intake survey. These products are the tools used by scientists to examine the influence of dietary interventions on human health. Besides nutrition monitoring, the nutrition center’s research program also includes investigating the role of food nutrients at the cellular level as well as in animal models and in human studies

Digital Detectives Deciper Ingredients

Television shows featuring crime scene investigators have been keeping viewers intrigued for years. But the Agricultural Research Service’s intriguing “food composition investigators” are just as innovative at deciphering truth from fiction relating to ingredients of plant-based foods and dietary supplements. The researchers are at the ARS Food Composition and Methods Development Laboratory, which is headed by research leader James Harnly. The laboratory is part of the Beltsville [Maryland] Human Nutrition Research Center (BHNRC). They’re using new equipment and a metabolomics approach to discover compounds and to accurately identify ingredients in foods and supplements. They are also looking at chemical composition patterns to find differences between cultivars, growing years, and locations—knowledge important for consumers, farmers, and marketers

Exploring Authentic Skim and Nonfat Dry Milk Powder Variance for the Development of Nontargeted Adulterant Detection Methods Using NIR Spectroscopy and Chemometrics

This document provided is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Agricultural and Food Chemistry, copyright © American Chemical Society, after peer review and technical editing by the publisher. To access the final edited and published work see http://pubs.acs.org/doi/abs/10.1021/jf4023433peer-reviewedA multinational collaborative team led by the U.S. Pharmacopeial Convention is currently investigating the potential of near-infrared (NIR) spectroscopy for nontargeted detection of adulterants in skim and nonfat dry milk powder. The development of a compendial method is challenged by the range of authentic or nonadulterated milk powders available worldwide. This paper investigates the sources of variance in 41 authentic bovine skim and nonfat milk powders as detected by NIR diffuse reflectance spectroscopy and chemometrics. Exploratory analysis by principal component analysis and varimax factor rotation revealed significant variance in authentic samples and highlighted outliers from a single manufacturer. Spectral preprocessing and outlier removal methods reduced ambient and measurement sources of variance, most likely linked to changes in moisture together with sampling, preparation, and presentation factors. Results indicate that significant chemical variance exists in different skim and nonfat milk powders that will likely affect the performance of adulterant detection methods by NIR spectroscopy