Method for classifying wine and coffee

A method for classifying beverages of natural origin, comprising the following steps:

• a) providing a plurality of beverage classes, with a plurality of known beverage samples per class, each beverage class having a plurality of known class properties;
• b) irradiating the known beverage samples with irradiated light from a predetermined wavelength range
• c) measuring detected light over a range of wavelengths, the detected light being of at least one of the following types:
• light passed through the known beverage samples, light reflected from the known beverage samples, light re-emitted from the known beverage samples, or light dispersed by the known beverage samples;
• d) determining a ratio of the irradiated light to the detected light at one or more wavelengths for each known beverage samples of each class, to obtain spectral data;
• e) performing numerical-mathematical conditioning of the spectral data of the individual known beverage samples, to obtain conditioned spectral data;
• f) correlating the conditioned spectral data of a plurality of known beverage samples of each beverage class to one another, to determine a class correlation;
• g) compiling a database from the conditioned spectral data with different beverage classes based on the measured known beverage samples of the individual classes for calibration of a class correlation;
• h) providing at least one unknown beverage sample, said unknown beverage sample having at least partially unknown properties;
• i) irradiating the unknown beverage sample with irradited light from a predetermined wavelength range;
• j) measuring detected light over a range of wavelengths, the detected light being of at least one of the following types:
• light passed through the unknown beverage samples, light reflected from the unknown beverage samples, light re-emitted from the unknown beverage samples, or light dispersed by the unknown beverage samples;
• k) determining a ratio of the irradiated light to the detected light at one or more wavelengths for each unknown beverage sample of each class, to obtain spectral data;
• l) performing numerical-mathematical conditioning of the spectral data of the individual unknown beverage samples, to obtain conditioned spectral data;
• m) determining the beverage classes to which the unknown beverage sample is to be associated, with the aid of a class correlation of the measured spectra, by using the compiled calibration database of step g), to arrive at a classification result;
• n) at least one of representing the classification result to a user, and recording the classification result;
• o) repeating steps h-n as necessary to classify additional unknown beverage samples;
• wherein correlation of the numerically-mathematically conditioned spectral data is performed by cluster formation.