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4 results

  1. CORESTA Congress, Paris, 2006, PT 20

    Feature selection from near infrared spectra using genetic algorithms for tobacco blend recognition

    FIGUERES G.; DE SOUZA S.; REYNES C.; SABATIER R.; VIDAL B.
    Altadis Research Centre, Fleury-les-Aubrais, France
    Near infrared reflectance spectroscopy has proved to be very useful for predicting concentrations of chemical compounds in tobacco, classification or pattern recognition of cigarette blends. The resulting measurement of a sample is a whole reflectance ...
  2. CORESTA Congress, Paris, 2006, SS 13

    A mixture experimental design with six variables and the effects on smoke components:1 - Presentation of this experimental design and of some initial results on physical characteristics of cigarettes and blends

    VIDAL B.; FIGUERES G.; BIESSE J.P.; BREGEON B.; LOUVET F.; MUZELLEC L.
    Altadis Research Centre, Fleury-les-Aubrais, France
    The objective of this paper is to examine the effects of six tobacco components on the chemical and physical characteristics of blends and cigarettes and particularly on the mainstream smoke yields. First of all, we will develop the philosophy of this ...
  3. CORESTA Congress, Paris, 2006, SS 14

    A mixture experimental design with 6 variables and the effects on smoke components:2 - Hoffmann analytes behaviour through a mixture experimental design

    FIGUERES G.; VIDAL B.; BIESSE J.P.; BREGEON B.; LOUVET F.; MUZELLEC L.
    Altadis Research Centre, Fleury-les-Aubrais, France
    Today in the tobacco industry, one of the main scientific challenges is to understand the formation of some smoke compounds ("Hoffmann analytes"). For several years, work has been conducted in order to know the influence of cigarette design ...
  4. CORESTA Congress, Kyoto, 2004, SSPT 02

    Near-infrared spectroscopy and pattern recognition as screening methods for classification of commercial tobacco blends

    FIGUERES G.; ANDRIEU E.; BIESSE J.P.; VIDAL B.; DUMERY B.
    Altadis Research Centre, Fleury-les-Aubrais, France
    Group classification of tobacco blends is commonly performed using several different types of compositional data including tobacco compounds, additive or process components. But all of these wet chemistry methods are relatively time-consuming. A need ...