Methods and systems for improving peak integration in mass spectrometry. A method may include accessing an ion data series; generating a set of prospective peak integrations for a target peak in the ion data series; providing, as input to a trained machine learning model, at least one peak characteristic for each prospective peak integration in the set of prospective peak integrations; processing the provided input, by the trained machine learning model, to generate an output from the trained machine learning model; based on the output, generating a ranking of one or more of the prospective peak integrations; and based on one of the prospective peak integrations, generating an ion amount represented by the target peak.

A method for estimating a state of wax in a rubber compound according to a first aspect includes the following: acquiring a chromatogram of an extracted component, by separating components thereof, in which the wax is extracted from the rubber compound including the wax; and deriving a distribution of normal hydrocarbons in the wax based on the chromatogram.

For a signal waveform to be processed, the continuous wavelet transform is performed with various scale factors, and a wavelet coefficient at each point in time is calculated. On an image showing the strength of the wavelet coefficient with respect to the scale factor and time, ridge lines are detected, and based on these ridge lines, positive and negative peak candidates are extracted, after which an error in the position and width of the peak due to the influence of a neighboring peak is corrected. Subsequently, the degree of non-symmetry of the peak shape or other features are examined to remove false negative peaks due to negative peak artifacts. Subsequently, a true peak cluster, a false peak cluster resulting from the removal of high-frequency components of a high-frequency noise or other causes, and other kinds of peaks are identified, and the obtained result is used to remove false peaks.

An analyzer configured to acquire a chromatogram or spectrum by performing a predetermined analysis of a sample and perform a qualitative or quantitative analysis of components contained in the sample. The analyzer includes: a peak detection unit configured, based on information regarding a plurality of target components that need to be checked whether contained in the sample or that need to be quantified, to detect a peak or peaks in the chromatogram or spectrum acquired by the predetermined analysis of the sample corresponding to one of the target components, configured to acquire peak information regarding each of the peak or peaks, and configured to obtain confidence information for each of the peak or peaks, the confidence information being an indicative value of certainty of detecting a peak; and a display processing unit configured to display on a display unit a list of at least a part of the target components.

A data processing system for a chromatograph including a standard sample data storage section; a standard sample sensitivity factor calculator; a post-correction standard sample chromatogram strength calculator; a specific designated retention time and specific designated wavelength setter; a measurement sample data storage section; a measurement sample sensitivity factor calculator; and a post-correction measurement sample chromatogram creator.

Peaks are detected on a mass chromatogram at multiple m/z ratios characterizing a target component, and the detected peaks are classified into groups according to their occurrence time. The measured mass spectrum is acquired for each group, the measured mass spectrum and standard mass spectrum of the target component are matched for each m/z, and the standard mass spectrum is normalized by multiplying it by the same scale factor for all the m/z ratios such that it does not exceed the peak intensities on the measured mass spectrum. The quantitation ion m/z peak intensity on the normalized standard mass spectrum is then examined, and if this intensity exceeds a preset threshold and the confirmation ion ratio determined based on the measured mass spectrum obtained for the target component is outside a reference range, then that target component is taken as a narrowed result candidate.

At least one stable isotope reagent is added to each biological sample and standard sample to prepare biological samples for analysis and standard sample for analysis. The quality of the biological samples is evaluated using data of one set of biological samples for analysis composed of a plurality of biological samples for analysis. Besides, the quality of a pretreatment and/or analysis of each set of samples for analysis is evaluated using data obtained by analyzing the standard sample for analysis before and after an analysis of one set of samples for analysis. An abnormality in a chromatograph or mass analyzer used for the analysis of one set of samples is evaluated by the data obtained by analyzing a sample for device evaluation before and after the analysis of one set of samples for analysis. Thus, the quality of data obtained by chromatographic mass spectrometry on biological samples is comprehensively evaluated.

In a quantitative determination device 10 for brominated flame-retardant compounds, a storage section 41 holds a relative response factor 411 representing a relationship of a measured intensity of a compared compound to that of a reference compound selected from target compounds. A standard-sample measurer 43 acquires the intensity of the reference compound by measuring a standard sample, using an analyzer 10, 20. A target-sample measurer 45 acquires the intensities of the reference and compared compounds by measuring a target sample, using the analyzer. A reference-compound quantity determiner 46 determines a quantitative value of the reference compound in the target sample. A compared-compound quantity determiner 47 determines a quantitative value of the compared compound based on the quantity of the reference compound in the standard sample, intensity of the reference compound acquired by the standard-sample measurer, intensity of the compared compound acquired by the target-sample measurer, and relative response factor of the compared compound.

In a quantitative determination device 100 for brominated flame-retardant compounds, a storage section 41 holds a relative response factor 411 representing a relationship of a measured intensity of a compared compound to that of a reference compound selected from target compounds. A standard-sample measurer 43 acquires the intensity of the reference compound by measuring a standard sample, using an analyzer 10, 20. A target-sample measurer 45 acquires the intensities of the reference and compared compounds by measuring a target sample, using the analyzer. A reference-compound quantity determiner 46 determines a quantitative value of the reference compound in the target sample. A compared-compound quantity determiner 47 determines a quantitative value of the compared compound based on the quantity of the reference compound in the standard sample, intensity of the reference compound acquired by the standard-sample measurer, intensity of the compared compound acquired by the target-sample measurer, and relative response factor of the compared compound.

A computer implemented method for automated quality check of chromatographic and/or mass spectral data is disclosed. The method comprises the following steps: a) (110) providing processed chromatographic and/or mass spectral data obtained by at least one mass spectrometry device (112); b) (114) classifying quality of the chromatographic and/or mass spectral data by applying at least one trained machine learning model on the chromatographic and/or mass spectral data, wherein the trained machine learning model uses at least one regression model (116), wherein the trained machine learning model is trained on at least one training dataset comprising historical and/or semi-synthetic chromatographic and/or mass spectral data, wherein the trained machine learning model is an analyte-specific trained machine learning model.