The method according to the present invention includes: a training sample measurement process (S1, S2) in which, for a food product belonging to the same kind as a determination target, a plurality of training samples individually labeled with a known state of quality are subjected to a measurement using a chromatograph mass spectrometer under the same analysis condition; a training sample data collection process (S3, S4) in which an index value related to the magnitude of a peak observed on an extracted ion chromatogram obtained by the measurement is acquired for each training sample, and the index value of the peak at each retention time common to the training samples is extracted; and a discrimination model creation process (S5-S7) in which a supervised training is performed to create a discrimination model, using, as the training data, the index value of the peak at each retention time common to the training samples acquired for each of the labeled training samples. Measurement data for an unknown sample is inputted into a discriminator based on the discrimination model, to obtain a quality discrimination result.

According to an example aspect of the present invention, there is provided an apparatus, comprising: a channel for receiving gas; thermophoretic unit configured to create a temperature gradient in the channel, and a particle detector for detecting particles in the gas on the basis of particle landing positions in the channel.

The method according to the present invention includes: a training sample measurement process (S1, S2) in which, for a food product belonging to the same kind as a determination target, a plurality of training samples individually labeled with a known state of quality are subjected to a measurement using a chromatograph mass spectrometer under the same analysis condition; a training sample data collection process (S3, S4) in which an index value related to the magnitude of a peak observed on an extracted ion chromatogram obtained by the measurement is acquired for each training sample, and the index value of the peak at each retention time common to the training samples is extracted; and a discrimination model creation process (S5-S7) in which a supervised training is performed to create a discrimination model, using, as the training data, the index value of the peak at each retention time common to the training samples acquired for each of the labeled training samples. Measurement data for an unknown sample is inputted into a discriminator based on the discrimination model, to obtain a quality discrimination result.