Recipient Organization
COMPASS TECHNOLOGY GROUP, LLC
1005 ALDERMAN DR STE 203
ALPHARETTA,GA 30005
Performing Department
(N/A)
Non Technical Summary
Recently, several conditions have appeared in chickens that affect the quality of their meat. Currently, these conditions can only be detected after the meat has been fully processed, and the detection requires a person to manually inspect each piece of meat for defects. The poultry industry would benefit from a device that could automatically screen for any abnormalities without human intervention. In this project, a microwave sensor is proposed as a potential technology that could enable this automated screening.As a part of this effort, the interaction of chicken breast to electrical signals (ranging from high frequency radio to microwave) will be tested to determine how these waves behave in healthy or abnormal chicken meat. Following this, a machine learning based classification method will be applied to the data collected, which will sort chicken into a score of meat quality. This algorithm will be evaluated for accuracy compared to the manual screening method that is commonly used. At the end of the project, a prototype system will be built to test the feasibility of the whole method in a practical (i.e. non-laboratory) setting.
Animal Health Component
30%
Research Effort Categories
Basic
5%
Applied
30%
Developmental
65%
Goals / Objectives
The goal of this effort will be the creation and testing of a microwave NDE system that is capable of detecting several chicken breast myopathies, including woody breast. The objectives supporting this goal are as follows:1. Development of a physical model of microwave interactions with chicken breast (healthy and otherwise). Success in this objective will result in an analytical model that can be used to generate s-parameters for an idealchicken breast.2. Development of a classification algorithm to translate measured s-parameters into a classification related to chicken breast quality. Success in the objective will be determined by the overall accuracy/reliability of the method compared to standard methods.3. Deployment of the microwave system in a prototype form. Success in this objective will result in the integration of microwave sensors into an in-line conveyor belt (or similar) system.
Project Methods
Methods:Chicken breast meat will be procured from local suppliers with an attempt to capture both low and high quality meat specimens. These meat specimens will be classified based on their visual appearance and through manual palpation in a manner consistent with literature methods. The specimens will be characterized using a variety of in-house electrical characterization tools using standard methods to obtain S-parameters and permittivity values. As needed, the specimens may be processed down into different shapes and sizes to aid electrical characterization. The development of physical models will be aided by both analytical tools (i.e. transmission line network method) and computational tools (i.e. computational electromagnetics codes). A classification algorithm will be constructed using a variety of tools (e.g. multiple linear regressions, singular value decomposition, neural network) with the ultimate selection of algorithm based on the accuracy/reliability of the scoring output. A prototype device will be constructed in accordance with general design needs that arise during the course of the project.Evaluation:The primary evaluation criteria for the work in this project will be the accuracy/reliability of the screening method (i.e. the total effect of physical models, classification algorithm, and device performance). Further evaluations will focus on the practicality and commercialization protentional of the device.Efforts:Reports will be generated and data shared with USDA partners. Equipment demonstrations will be performed with interested parties.?