Determination of Fat,Moisture, and Protein in Meat and Meat Products by Using the FOSS FoodScan Near-Infrared Spectrophotometer with FOSS Artificial Neural Network Calibration Model and Associated Database: Collaborative Study
Abstract:A collaborative study was conducted to evaluate the repeatability and reproducibility of the FOSS FoodScan near-infrared spectrophotometer with artificial neural network calibration model and database for the determination of fat, moisture, and protein in meat and meat products. Representative samples were homogenized by grinding according to AOAC Official Method 983.18. Approximately 180 g ground sample was placed in a 140 mm round sample dish, and the dish was placed in the FoodScan. The operator ID was entered, the meat product profile within the software was selected, and the scanning process was initiated by pressing the start button. Results were displayed for percent (g/100 g) fat, moisture, and protein. Ten blind duplicate samples were sent to 15 collaborators in the United States. The within-laboratory (repeatability) relative standard deviation (RSDr) ranged from 0.22 to 2.67% for fat, 0.23 to 0.92% for moisture, and 0.35 to 2.13% for protein. The between-laboratories (reproducibility) relative standard deviation (RSDR) ranged from 0.52 to 6.89% for fat, 0.39 to 1.55% for moisture, and 0.54 to 5.23% for protein. The method is recommended for Official First Action.
Document Type: Research Article
Affiliations: FOSS North America, 8091 Wallace Rd, Eden Prairie, MN 55344.
Publication date: July 1, 2007
More about this publication?
- The Journal of AOAC INTERNATIONAL publishes refereed papers and reviews in the fields of chemical, biological and toxicological analytical chemistry for the purpose of showcasing the most precise, accurate and sensitive methods for analysis of foods, food additives, supplements and contaminants, cosmetics, drugs, toxins, hazardous substances, pesticides, feeds, fertilizers and the environment available at that point in time. The scope of the Journal includes unpublished original research describing new analytical methods, techniques and applications; improved approaches to sampling, both in the field and the laboratory; better methods of preparing samples for analysis; collaborative studies substantiating the performance of a given method; statistical techniques for evaluating data. The Journal will also publish other articles of general interest to its audience, e.g., technical communications; cautionary notes; comments on techniques, apparatus, and reagents.
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