Location: Quality and Safety Assessment Research Unit
Project Number: 6040-41440-003-000-D
Project Type: In-House Appropriated
Start Date: Sep 14, 2020
End Date: Sep 13, 2025
Objective:
1. Assess the intrinsic properties of myopathic chicken that alter quality and processing attributes in meat and enable commercially-viable processing strategies to limit myopathy impact.
1.A. Identify the mechanisms by which the physical and chemical properties of myopathic broiler muscles influence quality and processing attributes of meat products.
1.B. Evaluate processing and formulation strategies to minimize the negative impact of broiler muscle myopathies on the technological, compositional, and sensory properties of meat products.
2. Develop nondestructive, rapid imaging technologies to enable commercial measurement of quality characteristics and defects in poultry meat and eggs.
2.A. Develop a high-speed imaging technology for detecting and sorting poultry muscle myopathies and meat quality defects.
2.B. Utilize sensor fusion to enhance the ability of imaging technology to simultaneously assess multiple quality attributes and defects in poultry meat.
2.C. Develop imaging technology for rapid assessment of egg quality and defects.
3. Develop rapid, nondestructive microwave sensors to enable commercial measurement of quality parameters in grain, seed, nuts, and feed.
3.A. Enable distributed networks of microwave sensors for real-time monitoring of moisture content in grain, seed, and nut storage facilities.
3.B. Enable on-the-trailer multiparameter microwave sensors for nondestructive and instantaneous grading and monitoring of drying nuts.
3.C. Enable microwave sensors for simultaneous and nondestructive determination of moisture content and water activity of peanuts, almonds, and other nuts.
Approach:
Poultry meat, egg, grain, seed, nut and feed commodity values depend upon quality. Research on poultry meat quality defects will focus on underlying mechanisms, utilization methods and rapid detection/sorting systems for quality defects. To determine how woody breast (WB) affects postmortem changes in breast muscle, trials will measure WB muscle deboning response, rigor mortis development and postmortem energy metabolism. Low field time-domain nuclear magnetic resonance techniques will be used to assess how muscle water properties influence WB meat quality during aging, cooking, freezing and marination. Impact of spaghetti meat (SM) on breast meat quality, composition, and functionality will be measured. Effects of SM on processing and quality in further-processed products (ground meat patties, fresh sausages and hotdogs) will be measured. A machine vision WB detection technology will be expanded to integrate the side-view imaging component into a system for both detection and sorting. Image acquisition and processing will be enhanced to match commercial processing line speeds and system will be tested on breast meat from a range of broiler varieties and sizes. To simultaneously assess multiple quality traits associated with WB and white striping, sensor fusion techniques will be evaluated. Multiple sensors measuring 2D and 3D shape morphology, spatial texture, muscle rigidity, color, and spectral data will be evaluated via independent trials. Once best sensing modalities are determined, sensor fusion algorithms will be developed and tested. For measuring egg quality, a modified-pressure imaging system to detect hairline cracks will be modified to grade table eggs for air-cell depth and yolk shadow using new machine vision algorithms. System will be redesigned for online operation and applied to detect cracked eggs in hatcheries. Microwave sensors for quality assessment of grains, seeds, nuts, and feeds will be developed. Microwave sensors in a distributed network will be developed for real-time nondestructive monitoring of moisture content in storage facilities for peanuts, almonds, wheat, corn, soybean and corn-soybean meal. Following laboratory testing in an eighth-scale drying bin equipped with multiple sensors, sensor networks will be tested in commercial grain and nut facilities. Microwave sensors will be developed to assess multiple attributes (moisture, bulk density, meat content and foreign material) before and during drying of peanuts, almonds, pecans and pistachios. After calibration with static samples, sensors will be tested in a quarter-scale nut drying system. Microwave sensors will be developed to simultaneously measure moisture content and water activity of in-shell peanuts, almonds and other nuts. A dielectric database will be collected with lab grade instrumentation. Following selection of optimal frequencies, prototype sensors will be assembled, calibrated and tested. By seeking to understand quality attributes, investigating utilization methods and developing rapid assessment tools, this project takes a multifaceted approach to provide information and technologies for producing and marketing high quality commodities.
