Location: Quality Safety and Assessment Research2021 Annual Report
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.
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.
Progress was made on assessing the intrinsic properties of myopathic chicken that alter quality and processing attributes in meat and on developing commercially-viable processing strategies to limit myopathy impact (Objective 1). Research was completed and reported on the effects of deboning broiler carcasses at different postmortem times on the texture characteristics of breast meat with the woody breast (WB) myopathy. Trials to determine the influence of the spaghetti meat (SM) myopathy on broiler breast muscle protein degradation and structure during postmortem storage were completed. Methods for measuring protein and lipid oxidation in chicken meat were developed in preparation for future trials to assess the impact of SM myopathy on breast meat functionality and quality. Research was conducted to establish measurement parameters and data analysis protocols for using time domain nuclear magnetic resonance (TD-NMR) to assess water-holding capacity (WHC) and moisture characteristics in poultry. The effects of sample size and temperature on TD-NMR measurements and WHC attributes (cook loss, drip loss thaw loss, marinade uptake, and salt-induced water gain) in WB fillets were investigated. New TD-NMR software was evaluated for enhancing data analysis capacity. The relationships between TD-NMR measurements collected at different raw and cooked breast meat temperatures were evaluated. Data was analyzed to assess the ability of a multi-blade shear force apparatus to distinguish the texture characteristics of WB meat. As part of a collaborative grant project, a study was conducted to measure the composition and water characteristics of WB meat that was treated with a combination of blade tenderization and marination to improve the negative cooked meat texture characteristics. Collaborative research trials were also conducted to determine the effects of on-farm broiler slaughter and delayed processing on carcass characteristics and fresh and marinated breast meat quality. Progress was made on developing nondestructive, rapid imaging technologies to enable commercial measurement of quality characteristics and defects in poultry meat (Objective 2). For the woody breast detection system previously developed in the research unit, a software program written in C++ program was developed for real-time image acquisition and processing at the frame rate of 200 frames/s. A real-time image processing algorithm for woody breast condition detection was developed and tested to enable real-time processing within 5 ms per frame. With regards to sensor fusion to increase woody breast detection accuracy, research suggested that 3D imaging and sideview imaging modalities can be combined to characterize important shape features of fillets with woody breast. A technique for normalization of an image shape feature characterizing the bending property was developed to improve the detection accuracy over 95% by measuring sideview thickness. A 3D imaging study also confirmed that average thickness was an important shape feature. Optical coherence tomography and hyperspectral imaging were also identified as sensor fusion candidates. In other research, a software system for phenotyping biological materials with artificial intelligence (AI) and big data analytics was developed. Data models and schemas for a prototype database system were developed. An artificial intelligence (AI) technique for natural language processing, via an open source chatbot, was studied to make the schemas designed for the database system change on the fly by interpreting the contents and intention of the user input through an AI agent. Progress was made on developing rapid, nondestructive microwave sensors to enable commercial measurement of quality parameters on various agricultural commodities (Objective 3). Dielectric properties of wheat, corn, soybeans, peanuts, and almonds were measured with a pair of horn-lens antennas connected to a vector network analyzer between 2 and 18 GHz for varying bulk density, moisture content and temperature. For each material, variations of the dielectric properties with each variable were analyzed and several dielectric-based calibration algorithms were used to determine moisture content. Statistical analysis and computation of the standard error of calibration and the standard error of performance identified the best performing frequencies. Dielectric properties of in-shell peanuts and in-shell almonds were measured in free space with a transmission technique between 2 and 18 GHz with a vector network analyzer and at 5.8 GHz with a microwave sensor prototype. For both peanuts and almonds, the measurements were carried out for samples of varying moisture content and water activity. The data collected were used in the development of a novel dielectric-based algorithm for simultaneous determination of moisture content and water activity from measurement of the dielectric properties. With this additional development, it is possible to predict four different quality attributes of the nuts, namely, bulk density, moisture content, water activity, and foreign material content from measurement of their dielectric properties at a single microwave frequency. A method for measurements on a single unshelled peanut pod was developed. A resonant cavity operating at 4 GHz was used to measure the quality factor (Q-factor) and phase shift of unshelled peanut pods of four different types of peanuts (Runner, Spanish, Valencia, and Virginia). From measurement of the Q-factor and phase shift, the dielectric properties were determined. Measurements were performed on intact unshelled peanuts, empty unshelled peanuts, and unshelled peanut filled with a low-loss powder to simulate diseased peanuts. The database collected will be instrumental in developing algorithms for identifying healthy and contaminated/diseased unshelled peanut pods.
1. Database of dielectric properties of agricultural commodities. Dielectric properties can be used as indicators of various quality characteristics in agricultural commodities. An extensive database of dielectric properties of grains, seeds, and nuts (peanuts and almonds) measured by ARS researchers in Athens, Georgia, over a broad microwave frequency range during the last ten years was compiled, organized, and analyzed. The data included in the database correspond to samples of different moisture content, bulk density, and temperature. This database will be beneficial to scientists and engineers working in the fields of agriculture, the food industry, and instrumentation manufacturers.
2. Chicken carcass processing influences meat quality in myopathic breast muscle. In fast growing broiler chickens, a breast muscle myopathy known as woody breast can occur and cause abnormal meat texture characteristics which are objectionable to consumers. Although it is known that afflicted muscle has an altered composition, the impact on the postmortem changes that occur in the muscle as it relates to the increased hardness and rigidity observed in the tissue are not well understood. ARS researchers in Athens, Georgia, found that deboning broiler breast meat exhibiting the woody breast myopathy at different times postmortem affects the texture characteristics of the raw and cooked meat. These researchers identified 6 h postmortem as a potentially critical postmortem time that influences meat texture quality in woody breast meat. This information is not only important to understand better the underlying mechanisms by which this myopathy negatively impacts meat eating quality but also provides information for processors to consider in evaluating potential procedures for carcass processing and handling to optimize product quality.
3. Novel method for measuring texture in poultry meat. The woody breast (WB) myopathy in chicken breast meat has abnormal texture characteristics that are difficult to assess with standard meat shear force techniques. A novel multi-blade shear device was evaluated by ARS researchers and collaborators in Athens, Georgia. The multi-blade shear device was found to be quicker, easier to use, and more reliable for measuring texture characteristics in raw and cooked breast meat with the WB myopathy compared to the standard shear technique used in poultry. This new technique provides a useful tool for both researchers and industry personnel for assessing and understanding texture characteristics in chicken breast meat.
4. Emerging chicken breast meat defect influences meat functionality. An emerging chicken meat quality defect, known as spaghetti meat (SM), impairs the integrity of the muscle structure and negatively impacts the usefulness of breast meat for intact, whole muscle products. Little is known about the potential use of SM in processed meat products. ARS researchers in Athens, Georgia, demonstrated that the SM myopathy influences breast meat composition and impairs the functionality traits of the meat. Researchers found that a reduction in muscle protein content in SM is likely the cause of reduced meat functionality. These findings provide critical information needed by researchers and meat processors seeking to optimize the utilization of SM in processed meat products.
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