Research Project: Assessment of Quality Attributes of Poultry Products, Grain, Seed, Nuts, and Feed

Location: Quality and Safety Assessment Research Unit

2022 Annual Report

Objectives
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.

Progress Report
During Fiscal Year (FY) 2022, research to identify the mechanisms by which the physical and chemical properties of myopathic broiler muscles influence quality and processing attributes of meat products was conducted (Sub-Objective 1A). Research to determine the effects of the spaghetti meat (SM) myopathy on muscle protein degradation and the myowater properties of broiler breast meat during refrigerated storage was completed. Trials to measure the effects of the SM myopathy on the oxidative status of the muscle and protein functionality were conducted. Studies were completed on the myowater properties of woody breast meat during storage and marinade uptake using low-field nuclear magnetic resonance relaxation measurements. As part of a collaborative project, trials were conducted to determine the effects of including various antioxidant plant additives in broiler rations on breast myopathy development and meat quality. Additionally, data analysis was completed on a collaborative project to determine the effects of on-farm broiler slaughter and delayed processing on carcass characteristics and fresh and marinated breast meat quality. During FY 2022, research to evaluate processing and formulation strategies to minimize the negative impact of broiler muscle myopathies on the technological, compositional, and sensory properties of meat products was conducted (Sub-Objective 1B). As part of a collaborative project, a study was conducted to measure the impact of including different percentages of SM into the formulations of frankfurters on final product quality, composition, and yield. A study was completed to evaluate sous vide cooking of woody breast meat to explore a potential new way to utilize broiler breast meat exhibiting the myopathy. Through the use of a commercially available service, sensory descriptive analysis was completed on product from a study utilizing woody breast meat in frankfurters. A two-step plan for rebuilding the trained sensory panel capabilities of the research unit was developed that will utilize the difference test method as an alternative research technique as the trained panel is being re-established following the pandemic-induced hiatus. During FY 2022 further research was conducted to develop a high-speed imaging technology for detecting and sorting poultry muscle myopathies and meat quality defects (Sub-Objective 2A). A machine vision system to detect poultry breast fillets with the woody breast condition was integrated with a commercial-grade reject machine. A software program written in C++ was developed for real-time imaging and operation of the reject machine to discard breast fillets with the woody breast condition. During FY 2022 the research to utilize sensor fusion to enhance the ability of imaging technology to simultaneously assess multiple quality attributes and defects in poultry meat was advanced (Sub-Objective 2B). A 3-D imaging technique has been studied for the detection of woody breast fillets using 3-D point cloud processing and deep learning artificial intelligence. The woody breast condition is characterized by abnormal hardness upon palpation and a ridge-like bulge on the caudal (tail) end of the breast fillet. This bulginess was modeled by rounded convexity, for which curvature features were extracted from 3-D point clouds. The modeled curvature features were analyzed by deep learning to determine the presence of the woody breast condition. In order to develop a force-sensing technology to characterize breast meat defects research was conducted to assess the ability of force-sensing resistors for measuring hardness and rigidity palpation of chicken breast fillets with the woody breast condition. Silicone molds were made and used to standardize the compression force measurement of force-sensing resistors. Responses of chicken breast fillets to the compression forces were measured with force-sensing resistors and analyzed. During FY2022 significant progress was made on research to enable distributed networks of microwave sensors for real-time monitoring of moisture content in grain, seed, and nut storage facilities (Sub-Objective 3A). Dielectric properties data collected with a vector network analyzer over a broad microwave frequency range (2 GHz – 18 GHz) for grain, seed, peanuts, and almonds were analyzed by using graphical and statistical methods to identify correlations with physical properties including moisture content and bulk density. For each material, moisture and density calibration equations in terms of the dielectric properties were established at each frequency. To evaluate performance of each calibration equation, the standard errors of calibration (SEC) were calculated for each material. Overall, these calibration equations allowed moisture prediction from measurement of the dielectric properties with an SEC of less than 1%. For bulk density, the SEC was less than 0.02 grams per cubic centimeters. In addition, these calibration equations were successfully tested on prototype sensors operating at 5.8 Gigahertz and 9.6 Gigahertz. Additionally, improved mass and heat transfer models for monitoring grains, seeds, and nuts drying in a laboratory-scale drying bin were developed. During FY2022 progress was made on research to enable on-the-trailer multiparameter microwave sensors for nondestructive and instantaneous grading and monitoring of drying nuts (Sub-Objective 3B). Dielectric properties data collected with a vector network analyzer over a broad microwave frequency range (2 GHz – 18 GHz) for uncleaned shelled peanuts and cleaned shelled peanuts were analyzed graphically and statistically to identify calibration equations for determining peanut pods bulk density and peanut kernels moisture content. For foreign material percentage determination, a Neural Network-based technique was used. The standard error of performance was about 1.4% for foreign material in uncleaned peanut pods. During FY 2022, progress was made on research to enable microwave sensors for simultaneous and nondestructive determination of moisture content and water activity of peanuts, almonds, and other nuts (Sub-Objective 3C). In collaborative work with a stakeholder, the performance of a USB vector network analyzer for measurement of the dielectric properties of grain, seed, and nuts at microwave frequencies was compared to those obtained with a classical vector network analyzer (HP 8510C) and low-cost prototype sensors. Overall, the accuracy of the USB was as good as the classical vector network analyzer and low-cost prototype sensors. As part of an ARS collaborative project, software was developed to automate measurement of dielectric properties of single peanut pod with a resonant cavity and a vector network analyzer. About 1260 peanut pods of different varieties (Runner, Spanish, Valencia, and Virginia) and different fillings were measured. An AI-based algorithms was developed to identify individual pods from measurement of their dielectric properties.

Accomplishments
1. Development of a woody breast detection imaging system with a reject machine for sorting poultry meat. The woody breast condition in poultry breasts is characterized by abnormal hardness upon human palpation, which can lead to reduced consumer acceptance and decreased meat value. The current method of woody breast detection in the industry is subjective and manual. ARS researchers in Athens, Georgia, have developed a machine vision system for real-time inspection and sorting of boneless chicken breast fillets with the woody breast condition. The ARS researchers developed a machine vision technology and a prototype system for online detection and sorting of woody breast fillets by objectively measuring physical features such as fillet rigidity, bending, and shape. This technology can provide the industry an objective method for accurately sorting product based on the woody breast condition at commercial processing line speeds.

2. Factors controlling poultry meat quality attributes with the woody breast defect. A growth-related poultry meat quality defect known as woody breast causes significant economic losses for the industry due to product downgrades and discards. The woody breast condition causes objectionable meat texture making the breast fillet unsuitable for usage as a high dollar intact boneless breast meat product. Through a series of studies, ARS researchers in Athens, Georgia, have utilized low-field nuclear magnetic resonance (NMR) methods to decipher for the first time underlying mechanisms that influence water-binding properties in woody breast meat. Their findings greatly advanced the understanding of how the woody breast condition influences meat moisture loss during refrigerated and frozen storage, during cooking, and how it impacts moisture uptake and retention during marination. The insights gained from this research provide researchers and poultry meat processors valuable information for designing new processing and product utilization strategies for more effectively handling woody breast meat.

Review Publications
Yoon, S.C., Bowker, B.C., Zhuang, H., Lawrence, K.C. 2022. Development of imaging system for online detection of chicken meat with wooden breast condition. Sensors. 22(3):1036. https://doi.org/10.3390/s22031036.
Julrat, S., Trabelsi, S. 2021. Determination of foreign material content in uncleaned peanuts by microwave measurements and machine learning techniques. Journal of Microwave Power and Electromagnetic Energy. https://doi.org/10.1080/08327823.2021.1993047.
Zhang, J., Bowker, B.C., Yang, Y., Pang, B., Yu, X., Tasoniero, G., Zhuang, H. 2022. Water properties and marinade uptake in broiler pectoralis major with the woody breast condition. Food Chemistry. Volume 391:133230. https://doi.org/10.1016/j.foodchem.2022.133230.
Gao, Y., Yeh, H., Bowker, B.C., Zhuang, H. 2021. Effects of different antioxidants on quality of meat patties treated with in-package cold plasma. Innovative Food Science and Emerging Technologies. https://doi.org/10.1016/j.ifset.2021.102690.
Zhang, J., Zhuang, H., Bowker, B.C., Stelzleni, A.M., Yang, Y., Pang, B., Gao, Y., Thippareddi, H. 2021. Evaluation of Multi Blade Shear (MBS) for determining texture of raw and cooked broiler breast fillets with the woody breast myopathy. Poultry Science. https://doi.org/10.1016/j.psj.2021.101123.
Tasoniero, G., Zhuang, H., Bowker, B.C. 2022. Biochemical and physicochemical changes in spaghetti meat during refrigerated storage of chicken breast. Frontiers in Physiology. https://doi.org/10.3389/fphys.2022.894544.
Welter, A.A., Wu, W., Maurer, R., O'Quinn, T.G., Chao, M.D., Boyle, D.L., Geisbrecht, E.R., Hartson, S.D., Bowker, B.C., Zhuang, H. 2022. An investigation of the altered textural property in woody breast myopathy using an integrative omics approach. Frontiers in Physiology. https://doi.org/10.3389/fphys.2022.860868.
Lewis, M.A., Trabelsi, S. 2022. Investigating the influence of grain drying with ambient air versus heated air within an eighth-scale grain drying bin. Applied Engineering in Agriculture. 38(3):523-533. https://doi.org/10.13031/aea.14890.
Trabelsi, S. 2021. Microwave nondestructive sensing of moisture content and water activity of almonds. Transactions of the ASABE. https://doi.org/10.13031/trans.14338.
Julrat, S., Trabelsi, S. 2022. Influence of peanut orientation on microwave sensing of moisture content in cleaned unshelled peanuts. IEEE Sensors Journal. https://doi.org/10.1109/JSEN.2022.3168664.
Ma, T., Schimleck, L., Dahlen, J., Yoon, S.C., Inagaki, T., Tsuchikawa, S., Sandak, J., Sandak, A. 2022. Comparative performance of NIR-Hyperspectral imaging systems. Foundations. https://doi.org/10.3390/foundations2030035.
Zhang, J., Zhuang, H., Cao, J., Geng, A., Wang, H., Chu, Q., Yan, Z., Zhang, X., Zhang, Y., Liu, H. 2022. Breast meat fatty acid profiling and proteomic analysis of Beijing-You chicken during the laying period. Frontiers in Veterinary Science. https://doi.org/10.3389/fvets.2022.908862.
Zhao, J., Qian, J., Zhuang, H., Luo, J., Huang, M., Yan, W., Zhang, J. 2021. Effect of plasma-activated solution treatment on cell biology of Staphylococcus aureus and quality of fresh lettuces. Foods. 10(12):2976. https://doi.org/10.3390/foods1012297610.3390/foods10122976.
Luo, J., Nasiru, M.M., Zhuang, H., Zhou, G., Zhang, J. 2020. Effects of partial NaCl substitution with high-temperature ripening on proteolysis and volatile compounds during process of Chinese dry-cured lamb ham. Food Research International. https://doi.org/10.1016/j.foodres.2020.110001.