Abstract: A method for evaluating and controlling roasting and degree (level) of roast in food items including but not limited to: coffee, cocoa, beans, nuts, grains and seeds, involves collecting spectra of the gases (including water vapor) emitted during roasting in the mid-infrared region using either mid-infrared source or visible light to include Raman scattering. The changes in the spectra, due to absorption by molecular vibrations in the gases emitted during roasting are evaluated in real time during roasting. These data may be processed in frequency or time domain. The spectra and change in spectra are correlated with a roasting profile to mark the inception of roasting, progress of roasting and maturity/achievement of degree of a roast. The information can be transmitted to the roaster or controller to monitor the roasting progress and can be used to adjust parameters as desired during roasting.

Abstract: A method for evaluating and controlling roasting and degree (level) of roast in food items including but not limited to: coffee, cocoa, beans, nuts, grains and seeds, involves collecting spectra of the gases (including water vapor) emitted during roasting in the mid-infrared region using either mid-infrared source or visible light to include Raman scattering. The changes in the spectra, due to absorption by molecular vibrations in the gases emitted during roasting are evaluated in real time during roasting. These data may be processed in frequency or time domain. The spectra and change in spectra are correlated with a roasting profile to mark the inception of roasting, progress of roasting and maturity/achievement of degree of a roast. The information can be transmitted to the roaster or controller to monitor the roasting progress and can be used to adjust parameters as desired during roasting.

Abstract: A motion-based method and system for rapidly identifying the presence of spatially dispersed or interwoven patterns in data and their deviation from a test model for the pattern includes transforming dispersed patterns into one concentrated moving objects, for which there is a characteristic, identifiable motion signature. The method may be used with data sets containing sharp peaks, such as frequency spectra, and other data sets. A roadmap of basic motion signatures is provided for reference, including multiple harmonic series, separation of odd and even harmonics, missing modes, sidebands and inharmonic patterns. The system and method may also be used with data stored in arrays and volumes. It remaps such data to show both high-resolution information and long range trends simultaneously for applications in nanoscale imaging.

Abstract: A motion-based method and system for rapidly identifying the presence of spatially dispersed or interwoven patterns in data and their deviation from a test model for the pattern includes transforming dispersed patterns into one concentrated moving objects, for which there is a characteristic, identifiable motion signature. The method may be used with data sets containing sharp peaks, such as frequency spectra, and other data sets. A roadmap of basic motion signatures is provided for reference, including multiple harmonic series, separation of odd and even harmonics, missing modes, sidebands and inharmonic patterns. The system and method may also be used with data stored in arrays and volumes. It remaps such data to show both high-resolution information and long range trends simultaneously for applications in nanoscale imaging.