2013 Annual Report
1a.Objectives (from AD-416):
To assist in the application of analysis of variance-principal components analysis (ANOVA-PCA) to food and botanical data acquired at ARS and to develop an algorithm for aligning chromatograms obtained with ultra-violet (UV) and mass spectrometric (MS) detection. The purpose of this cooperative agreement is to develop spectral fingerprinting and chromatographic profiling methods for the rapid detection and categorization of foods and botanical materials.
1b.Approach (from AD-416):
The Food Composition and Methods Development Laboratory (FCMDL) is responsible for developing analytical methods for chemical components in foods and dietary supplements. New methods are being developed for spectral fingerprinting and chromatographic profiling of plant materials using UV and MS detection. Fingerprints are acquired by direct analysis with no chromatographic separation. Both types of data are analyzed using pattern recognition programs like ANOVA-PCA. Proper interpretation of the data requires considerable skill in the area of chemometrics, the area of expertise of the cooperator. A particularly troublesome problem is that the application of ANOVA-PCA to chromatographic profiles requires the alignment of the chromatograms prior to processing. The cooperator will assist in the application of ANOVA-PCA to data obtained at USDA and in the analysis of variable interaction. In addition, the cooperator will develop software for aligning chromatograms so that ANOVA-PCA can be applied to chromatographic profiles.
Ohio University assisted FCMDL in the development of SIMCA (soft independent modeling of class analogy) and PLS-DA (partial least squares-discriminant analysis) methods for the detection of adulteration of skim milk powder and non-fat dry milk with protein and small molecules. They have also assisted in the development of methods for the determination levels of adulteration of American ginseng (Panax quinquefolius) with Asian ginseng (P. ginseng). The Cooperator has developed 2 new approaches to classification, FuRES (Fuzzy rule building expert system) and FOAM (fuzzy optimal associative memories) and applied them to the identification of adulterated ginseng.