Disclosed is a method for realizing batch-based traceability for pork based on a QR code. Based on the QR code, user information is added to a web address carried by the QR code to realize the traceability for the pork. The method includes: 1) registering basic information of pigs in breeding and brokering processes; 2) printing an initial traceability QR code of a carcass in a slaughtering process; 3) adding user information to the initial traceability QR code in a selling process, and updating the user information to the traceability system; and 4) scanning the traceability QR code to recall data of the traceability system in a catering process to achieve transparent information. The pork and pork products are traced from production process to the selling process.

A system and method of inspecting a chicken piece comprising generating an image for the chicken piece, identifying a defect type, a defect location and an area of each defect on the chicken piece based on the image, and grading the chicken piece into one of a plurality of grades based on the defect type and the area.

A system and method of inspecting a chicken piece comprising generating an image for the chicken piece, identifying a defect type, a defect location and an area of each defect on the chicken piece based on the image, and grading the chicken piece into one of a plurality of grades based on the defect type and the area.

The present disclosure relates to methods and systems for assessing the quality of a meat product. In certain embodiments, the present disclosure provides a method of assessing quality of a meat product, the method comprising receiving data representative of light emitted from the meat product upon application of incident light to the meat product, analysing the data to determine one or more parameters indicative of quality of the meat product, and assessing the quality of the meat product on the basis of the one or more parameters.

The present disclosure relates to methods and systems for assessing the quality of a meat product. In certain embodiments, the present disclosure provides a method of assessing quality of a meat product, the method comprising receiving data representative of light emitted from the meat product upon application of incident light to the meat product, analysing the data to determine one or more parameters indicative of quality of the meat product, and assessing the quality of the meat product on the basis of the one or more parameters.

A shrimp processing system conveys raw peeled shrimps to an imaging chamber in which shrimp bits and shrimps with residual shell are detected and diverted from the stream of acceptable shrimps allowed to pass on to downstream processing. An ultraviolet (UV) light source in the imaging chamber is constantly on. A visual inspection system takes images of the passing stream of shrimp when a white-light source is turned on to illuminate an exposure region to detect bits, clumps of shrimps, and acceptable individual shrimps. The visual inspection system takes images of the passing stream when the white-light source is turned off and the exposure region is subjected only to ultraviolet radiation. The visual inspection system detects shrimps with residual shell in the V images. Shrimp bits and shrimps with residual shell are diverted from the stream of shrimps by air jet nozzles to corresponding reject destinations.

Devices, systems and methods for sorting and labeling food products are provided. Respective spectra of food products for a plurality of segments of a line are received at a controller from at least one line-scan dispersive spectrometer configured to acquire respective spectra of the food products for the plurality of segments of the line. The controller applies one or more machine learning algorithms to the respective spectra to classify the plurality of segments according to at least one of one or more food parameters. The controller controls one or more of a sorting device and a labeling device according to classifying the plurality of segments to cause the food products to be one or more of sorted and labeled according to the at least one of the one or more food parameters.

Devices, systems and methods for sorting and labeling food products are provided. Respective spectra of food products for a plurality of segments of a line are received at a controller from at least one line-scan dispersive spectrometer configured to acquire respective spectra of the food products for the plurality of segments of the line. The controller applies one or more machine learning algorithms to the respective spectra to classify the plurality of segments according to at least one of one or more food parameters. The controller controls one or more of a sorting device and a labeling device according to classifying the plurality of segments to cause the food products to be one or more of sorted and labeled according to the at least one of the one or more food parameters.

The invention relates to a system for detecting one or more analytes in a sample. The system comprises a probe for insertion into the sample, the probe having a first electrochemical sensor configured to detect a first analyte in the sample, and a second electrochemical sensor configured to detect a second analyte in the sample. A first potentiostat is connected to the first electrochemical sensor and configured to perform a first electrochemical measurement with the first electrochemical sensor. Additionally, a second potentiostat is connected to the second electrochemical sensor and configured to perform a second electrochemical measurement with the second electrochemical sensor. The first potentiostat and the second potentiostat are electrically isolated from one another.

The invention relates to a system for detecting one or more analytes in a sample. The system comprises a probe for insertion into the sample, the probe having a first electrochemical sensor configured to detect a first analyte in the sample, and a second electrochemical sensor configured to detect a second analyte in the sample. A first potentiostat is connected to the first electrochemical sensor and configured to perform a first electrochemical measurement with the first electrochemical sensor. Additionally, a second potentiostat is connected to the second electrochemical sensor and configured to perform a second electrochemical measurement with the second electrochemical sensor. The first potentiostat and the second potentiostat are electrically isolated from one another.