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ARS Home Southeast Area Athens, Georgia U.S. National Poultry Research Center Quality and Safety Assessment Research Unit Research





- Bowker, Brian
- Trabelsi, Samir
- Zhuang, Hong
- Yoon, Seung-Chul
- Kong, Byungwhi
- 2023
- 2022
- 2021
- Publications
- Product Quality and New Uses (306)

Research Project: Assessment of Quality Attributes of Poultry Products, Grain, Seed, Nuts, and Feed **Location:
                            Quality and Safety Assessment Research Unit** 2023 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**
                                

Significant research progress was made to identify the mechanisms by which the physical and chemical properties of myopathic broiler muscles influence quality and processing attributes of meat products (Sub-Objective 1A). Research to determine regulatory factors that induce the spaghetti meat (SM) myopathy in broiler breast muscle was conducted using multi-omics analysis to identify differentially abundant proteins, metabolites, and lipids. As part of a collaborative project, proteomics- and bioinformatic pathway analyses were conducted with enriched mitochondria isolated from woody breast (WB) and normal (non-myopathic) breast muscle. A study was conducted to determine the effects of the WB myopathy on gene expression profiles related to muscle mitochondrial function and energy metabolism. A series of studies were conducted using low-field nuclear magnetic resonance (LF-NMR) to understand the connection between myowater properties and quality changes in broiler breast meat. Preliminary trials were conducted to determine the correct settings for the LF-NMR system. Using this technology, two experiments were then conducted to investigate changes in myowater distribution in WB fillets: one experiment covering the first 24 h postmortem and the other experiment covering extended storage (up to 7 days postmortem). Two experiments were completed (data analysis and reporting) on how different endpoint cooking temperatures and cooking times influence myowater properties as they relate to meat quality. Trials were also conducted on the effects of freezing and thawing methods on the myowater properties and quality characteristics of WB meat. Preliminary testing was conducted to determine the potential for using magnetic resonance imaging as a method for visualizing myowater distribution in broiler breast meat.

Significant research progress was made on evaluating processing and formulation strategies to the minimize the negative impact of broiler muscle myopathies on the technological, compositional, and sensory properties of meat products (Sub-Objective 1B). One experiment was completed to determine the effects of adding SM at increasing inclusion rates (up to 100%) on the technological and sensory characteristics of chicken breast meat patties. A second experiment was conducted to determine potential interacting effects of SM and food additives (phosphate/salt or tapioca flour) on the sensory quality of chicken breast patties. As part of a collaborative project, an experiment was conducted to determine the product quality and composition effects of adding SM into the formulation of chicken nuggets.

Several collaborative projects focused on the meat quality effects of various broiler production and processing practices were conducted in conjunction with university partners. Trials were conducted investigating the meat quality effects of feeding broilers a high protein diet. Commercial plant trials were conducted to determine the meat quality effects of delayed broiler carcass processing. Trials were also completed to determine the muscle protein effects of controlled atmosphere stunning of broilers and different deboning times. The research unit also invested considerable time and resources in recruiting and training 8-10 individuals to serve on the descriptive sensory panel needed to complete the research.

Research was conducted on the performance of a side-view machine vision technology (developed in-house and patented) that can sort woody breast (WB) meat at various line speeds (Sub-Objective 2A). Three different conveyor line speeds were evaluated: 10, 50, and 100 feet per minute (FPM). Additionally, a range of higher speeds from 120-260 FPM (increments of 20 FPM) were examined. This technology employed bending analysis to distinguish WB from normal breast fillets.
Research was conducted to identify sensor candidates for white striping (WS) and WB detection in poultry meat (Sub-Objective 2B). Trials were conducted to determine the feasibility of using hyperspectral imaging and color images to detect WS in chicken breast meat. Imaging focused primarily on sub-areas of breast fillets and an automated image processing technique was developed using Matlab. Research to detect WB in chicken breast meat was conducted using three sensing techniques: 3D imaging, optical coherence tomography (OCT), and compression force (CF) sensing. 3D imaging was tested as a cost-effective method using deep learning models to complement existing side-view machine vision technology. Automated image processing techniques were developed to extract relevant muscle microstructure features from OCT images, resulting in exceptional classification performance. Trials using CF sensing were conducted to analyze the spatial distribution of WB hardness in chicken fillets. Factors such as probe size and instrument type were examined. Findings from this tactile sensing research lays the groundwork for the development of a robotic tactile sensing technology capable of mimicking the WB sorting process performed by humans in poultry plants.

Research was conducted on distributed networks of microwave sensors for real-time monitoring of moisture content in grain, seed, and nut storage facilities (Sub-Objective 3A). Several wireless protocols including WLAN, Wifi, ZigBee, and Bluetooth were accessed to facilitate communication between sensors. Software was developed for the sensors to monitor moisture content. Commercial versions of microwave prototype sensors were developed, calibrated, and tested for moisture content and density determination in runner-type peanuts. Modeling of mass and heat transfer within an eighth-scale grain drying bin provided determination of moisture content, density, and shrinkage in real-time for beds of grain and seed.
Research was conducted to develop on-the-trailer multiparameter microwave sensors for non-destructive and instantaneous grading and monitoring of drying nuts (Sub-Objective 3B). Custom software was developed to facilitate measurements of dielectric properties in grain, seed, and nuts with a Keysight N5230C performance network analyzer over a broad microwave frequency range (2 GHz – 18 GHz). In addition, a custom software was developed to facilitate similar measurements with portable prototype sensors operating at a single microwave frequency, 5.8 GHz.

Research was conducted to develop microwave sensors for the simultaneous and non-destructive determination of moisture content and water activity of peanuts, almonds, and other nuts (Sub-Objective 3C). Performance of portable sensor prototypes equipped with low-cost antennas were tested for simultaneous determination of moisture content and water activity of peanuts and almonds. Two antenna configurations were tested, one pair of antennas providing a focused beam at center of the sample holder and a second configuration with four pairs of antennas beaming at four quadrants of the sample holder. AI-based algorithms were developed for moisture prediction in grains from measurement of attenuation, phase shift, and dielectric properties at microwave frequencies. An extensive database comprised of data collected in our laboratory during the last two decades was used. Working directly with a stakeholder on-site, the performance of a new small-size, portable USB vector network analyzer for measurements of dielectric properties at microwave frequencies was compared with a laboratory grade vector network analyzer and low-cost, in-house-developed prototype sensors. As part of an ARS collaborative project, a software was developed to identify individual peanut pods modified with different fillings from measurements of their dielectric properties. AI methods were used to establish classification, and resulting models were embedded in the software. **Accomplishments**
                                

1. High-resolution imaging technology for non-destructive detection of poultry meat quality defect. The woody breast (WB) condition is a chicken meat quality defect that causes great economic loss to the poultry industry due to product downgrades. Research into the underlying causes of WB has been slowed by the lack of non-destructive methods for characterizing the afflicted muscle tissue. ARS researchers in Athens, Georgia, have developed a high-resolution sub-surface imaging technology for characterizing the WB condition in poultry breast fillets. To capture high-resolution sub-surface cross-sections of the entire fillet surface area the researchers employed wide-field optical coherence tomography (OCT) imaging with a specially designed moving stage to ensure constant working distance between the sample surface and the OCT probe regardless of fillet thickness. Unlike the traditional histological technique using a light microscope, which is destructive, costly, and time-consuming, this new technology provides a non-destructive and efficient method for assessing the sub-surface physical properties of the muscle tissue affected by WB. By combining large-scale OCT imaging with appropriate image processing and machine learning techniques, the researchers demonstrated the effectiveness of this method for evaluating WB in chicken meat. Moreover, this technology holds potential for application in assessing other agricultural and horticultural products, contributing to the advancement of quality evaluation in various industries. 2. Product utilization strategies for chicken breast meat with the spaghetti meat defect. Poultry processors cannot utilize chicken breast meat exhibiting the spaghetti meat (SM) defect for high value intact breast meat products due to problems with muscle integrity and fiber separation. Through a series of studies, ARS researchers in Athens, Georgia, found that SM can be included in ground chicken patties at high levels either with or without food additives with minimal impact on objective quality measurements or consumer sensory perception. These findings demonstrate that including SM in ground meat products is an effective strategy that processors can use to recoup lost value due to SM. 3. Identification of potential pathways and markers for a poultry meat quality defect. The spaghetti meat (SM) myopathy causes inferior quality attributes in chicken breast meat. Breast fillets afflicted with SM are not used for whole muscle type products which causes significant economic losses for the industry. Unfortunately, the underlying cause for the condition is unknown. Using an advanced high-throughput multi-omics approach, ARS researchers in Athens, Georgia, identified differentially abundant proteins, metabolites, and lipids as potential inducing factors for the SM condition. Their findings greatly advanced the understanding of the overall distribution of biochemical materials in muscle with the SM condition and provide critical insights in the identification of tissue alterations that merit further in-depth research. The insights gained from this research provide researchers and poultry meat processors valuable information for designing strategies to reduce the incidence of SM. 4. Non-invasive technologies for measuring poultry meat quality. Poultry meat quality characteristics are often measured using objective but time-consuming, destructive techniques or by subjective categorical scoring techniques. Objective, rapid, and non-destructive methods for measuring poultry meat quality are needed. ARS researchers in Athens, Georgia, demonstrated that visible spectroscopy (VIS) and low-field nuclear magnetic resonance (LF-NMR) techniques can be used to screen chicken breast meat for quality defects, such as woody breast (WB) and pale-soft-exudative (PSE) meat. Findings from this research indicate that VIS can accurately distinguish normal and PSE meat, and that LF-NMR can be used to segregate WB from normal and PSE meat. The researchers showed that models built from the combined data of both technologies were able to separate normal, WB, and PSE meat. These findings show that LF-NMR and VIS technologies coupled with basic data processing can provide a simple, non-destructive, and rapid method for screening chicken meat quality defects. **Review Publications**
                            *Trabelsi, S. 2022. Use of measurement of dielectric properties at microwave frequencies for real-time monitoring of water activity of almonds. Journal of Microwave Power and Electromagnetic Energy. https://doi.org/10.1080/08327823.2022.2142755.*
                                *Guo, S., Yoon, S.C., Li, L., Wang, W., Zhuang, H., Wei, C., Liu, Y., Li, Y. 2023. Recognition and positioning of fresh tea buds using YOLOv4-lighted + ICBAM Model and RGB-D sensing. Agriculture. 13:518. https://doi.org/10.3390/agriculture13030518.*
                                *Shakeri, M., Kong, B.C., Zhuang, H., Bowker, B.C. 2023. Potential role of ribonucleotide reductase enzyme in mitochondria function and woody breast condition in broiler chickens. Animals. https://doi.org/10.3390/ani13122038.*
                                *Klein, L., Phillips, D., Kong, F., Bowker, B.C., Mohan, A. 2022. 4-oxo-2-nonenal (4-ONE) induced degradation of bovine skeletal muscle proteins. Journal of Agricultural and Food Chemistry. https://doi.org/10.1021/acs.jafc.2c05550.*
                                *Choi, J., Liu, G., Goo, D., Wang, J., Bowker, B.C., Zhuang, H., Kim, W. 2022. Effects of tannic acid supplementation on growth performance, gut health, and meat production and quality of broiler chickens raised in floor pens for 42 days. Frontiers in Physiology. https://doi.org/10.3389/fphys.2022.1082009.*
                                *Lewis, M.A., & Trabelsi, S. (2023). Use of a microwave sensor to monitor bulk density during grain drying. Applied Engineering in Agriculture, 39(3):359-366. https://doi.org/10.13031/aea.15452.*
                                *Trabelsi, S. 2023. Investigating the influence of marination and storage on microwave dielectric properties of chicken breast meat. Journal of Microwave Power and Electromagnetic Energy. https://doi.org/10.1080/08327823.2023.2207604.*
                                *Tasoniero, G., Bowker, B. 2022. Quality defects associated with poultry muscle development:  spaghetti meat. In: Petracci, M., Estevez, M., editors. Improving Poultry Meat Quality. Cambridge, UK: Burleigh Dodds Science Publishing Limited. p. 319-341.*


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