首页|Reports from University of Cadiz Add New Data to Research in Machine Learning (D evelopment of a Novel HS-GC/MS Method Using the Total Ion Spectra Combined with Machine Learning for the Intelligent and Automatic Evaluation of Food-Grade Para ffin ...)
Reports from University of Cadiz Add New Data to Research in Machine Learning (D evelopment of a Novel HS-GC/MS Method Using the Total Ion Spectra Combined with Machine Learning for the Intelligent and Automatic Evaluation of Food-Grade Para ffin ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Current study results on artificial in telligence have been published. According to news originating from Puerto Real, Spain, by NewsRx correspondents, research stated, “The intensity of the odor in food-grade paraffin waxes is a pivotal quality characteristic, with odor panel r atings currently serving as the primary criterion for its assessment.” Our news journalists obtained a quote from the research from University of Cadiz : “This study presents an innovative method for assessing odor intensity in food -grade paraffin waxes, employing headspace gas chromatography with mass spectrom etry (HS/GC-MS) and integrating total ion spectra with advanced machine learning (ML) algorithms for enhanced detection and quantification. Optimization was con ducted using Box-Behnken design and response surface methodology, ensuring preci sion with coefficients of variance below 9%. Analytical techniques, including hierarchical cluster analysis (HCA) and principal component analysis (PCA), efficiently categorized samples by odor intensity. The Gaussian support v ector machine (SVM), random forest, partial least squares regression, and suppor t vector regression (SVR) algorithms were evaluated for their efficacy in odor g rade classification and quantification.”
University of CadizPuerto RealSpainEuropeCyborgsEmerging TechnologiesHydrocarbonsMachine LearningParaffin
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