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http://hdl.handle.net/1942/32314
Title: | Quality Control and Low-Quality Detection in Packaging using Near-Infrared Spectroscopy | Authors: | Roszel, Mary | Advisors: | AERTS, Marc STATE, Radu |
Issue Date: | 2020 | Publisher: | tUL | Abstract: | Using Near-Infrared Spectroscopy as a method of quality determination and to identify low-quality packaging in the food sector. An analysis is conducted using a portable NIR spectroscopy tool (NIRvaScan) on 244 NIR wavelengths collected from high- and low-quality packaging materials in the spectrum between 900 - 1700nm. These wavelengths are analyzed for quality distinguishing features using Linear Discriminant Analysis, Principal Component Analysis, and Partial Least Squares. The following classification algorithms are discussed: DecisionTree, XGBoost RandomForest, and Support Vector Machines. A thorough analysis of transformation and pre-treatment methods are provided, including the transformation from the Reflectance to the Absorbance scale, and the pre-filtering methods Standard Normal Variate (SNV), Multiplicative Scattering Correction (MSC), and the Savitzky-Golay (SG) filtering algorithm. | Notes: | Master of Statistics-Biostatistics | Document URI: | http://hdl.handle.net/1942/32314 | Category: | T2 | Type: | Theses and Dissertations |
Appears in Collections: | Master theses |
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013d7f8d-3292-4c12-add5-bd6342d5817d.pdf | 6.25 MB | Adobe PDF | View/Open |
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