The present invention relates to the technical field of identification on adulterated meat, and in particular, to a method for identifying raw meat and high-quality fake meat based on a gradual linear array change of a component. The present invention spatially characterizes changing rules of featured components in the meat with the utilization of sensitivities of the visible/near-infrared spectral signals to changes of the components in the meat and the advantage that spectral scanning can acquire optical signals of the samples spatially and consecutively, further constructs the identification model according to differences in components and spectra of a region of interest in the hyperspectral image by taking a derivative for characterizing rates of change of the featured components.

The present invention relates to the technical field of identification on adulterated meat, and in particular, to a method for identifying raw meat and high-quality fake meat based on a gradual linear array change of a component. The present invention spatially characterizes changing rules of featured components in the meat with the utilization of sensitivities of the visible/near-infrared spectral signals to changes of the components in the meat and the advantage that spectral scanning can acquire optical signals of the samples spatially and consecutively, further constructs the identification model according to differences in components and spectra of a region of interest in the hyperspectral image by taking a derivative for characterizing rates of change of the featured components.

A device may receive a classification model generated based on a set of spectroscopic measurements performed by a first spectrometer. The device may store the classification model in a data structure. The device may receive a spectroscopic measurement of an unknown sample from a second spectrometer. The device may obtain the classification model from the data structure. The device may classify the unknown sample into a Kosher or non-Kosher group or a Halal or non-Halal group based on the spectroscopic measurement and the classification model. The device may provide information identifying the unknown sample based on the classifying of the unknown sample.

A device may receive a classification model generated based on a set of spectroscopic measurements performed by a first spectrometer. The device may store the classification model in a data structure. The device may receive a spectroscopic measurement of an unknown sample from a second spectrometer. The device may obtain the classification model from the data structure. The device may classify the unknown sample into a Kosher or non-Kosher group or a Halal or non-Halal group based on the spectroscopic measurement and the classification model. The device may provide information identifying the unknown sample based on the classifying of the unknown sample.

Apparatus (2) for testing the degree to which meat (3) is cooked, which apparatus (2) comprises: (i) a body (4); (ii) a meat-engaging formation (6) which is fixed with respect to the body (4); (iii) a probe (8) which is movable with respect to the body (4), and which is configured such that in use it does not penetrate the meat (3); (iv) sensor means (10) for sensing the force applied by the meat (3) to the probe (8) when the meat-engaging formation (6) is placed on the meat (3); (v) processor means (12) which operates consequent upon the force sensed by the sensor means (10) to provide an indication of the degree to which the meat is cooked; and (vi) test result means (14) for giving the indication provided by the processor means (12) as a visual and/or audible test result.

Apparatus (2) for testing the degree to which meat (3) is cooked, which apparatus (2) comprises: (i) a body (4); (ii) a meat-engaging formation (6) which is fixed with respect to the body (4); (iii) a probe (8) which is movable with respect to the body (4), and which is configured such that in use it does not penetrate the meat (3); (iv) sensor means (10) for sensing the force applied by the meat (3) to the probe (8) when the meat-engaging formation (6) is placed on the meat (3); (v) processor means (12) which operates consequent upon the force sensed by the sensor means (10) to provide an indication of the degree to which the meat is cooked; and (vi) test result means (14) for giving the indication provided by the processor means (12) as a visual and/or audible test result.

The present application discloses an electrochemiluminescence immunosensor. The immunosensor includes an electrode functionalized by a nanocomposite film. The film further includes carbon nanohorns dispersed in Nafion® perfluorinated resin solution. The polymeric solution is further stabilized by magnetic nanoparticles. The immunosensor is a Point of care (POC)-based. The immunosensor is configured to work in the range from 100 ng/mL to 1 fg/mL, and has tendency to detect even traces of the tropomyosin. The immunosensor is capable to detect traces even less than 1 fg/mL, hence having high specificity for Tro-Ag detection in food products with distinguished repeatability.

The present application discloses an electrochemiluminescence immunosensor. The immunosensor includes an electrode functionalized by a nanocomposite film. The film further includes carbon nanohorns dispersed in Nafion® perfluorinated resin solution. The polymeric solution is further stabilized by magnetic nanoparticles. The immunosensor is a Point of care (POC)-based. The immunosensor is configured to work in the range from 100 ng/mL to 1 fg/mL, and has tendency to detect even traces of the tropomyosin. The immunosensor is capable to detect traces even less than 1 fg/mL, hence having high specificity for Tro-Ag detection in food products with distinguished repeatability.

An integrated rapid non-destructive detection system for multi-index of meat quality comprises a spectrometer for obtaining near-infrared spectra of a sample; an industrial tablet computer, comprising: a model embedding module for storing multiple prediction models; a model determining module connected with model embedding module and configured to call prediction model; an index prediction module connected with spectrometer and model determining module for receiving near-infrared spectra and predicting index data of the sample combining with called prediction model; wherein the number of detector elements of spectrometer is determined by an ultimate minimal resolution, and a resolution of the sample is controlled to the ultimate minimal resolution during an acquisition process; which realizes automatic black-white calibration, non-destructive detection of multi-index, improves building efficiency of model, while maintaining building stability, and optimizes detection instrument volume.

An integrated rapid non-destructive detection system for multi-index of meat quality comprises a spectrometer for obtaining near-infrared spectra of a sample; an industrial tablet computer, comprising: a model embedding module for storing multiple prediction models; a model determining module connected with model embedding module and configured to call prediction model; an index prediction module connected with spectrometer and model determining module for receiving near-infrared spectra and predicting index data of the sample combining with called prediction model; wherein the number of detector elements of spectrometer is determined by an ultimate minimal resolution, and a resolution of the sample is controlled to the ultimate minimal resolution during an acquisition process; which realizes automatic black-white calibration, non-destructive detection of multi-index, improves building efficiency of model, while maintaining building stability, and optimizes detection instrument volume.