Near-infrared spectroscopy detects woody breast syndrome in chicken fillets by the markers protein content and degree of water binding

Cardiac implications of chicken wooden breast myopathy

Introduction

Wooden breast disease is a myopathy of the skeletal muscle in chickens of commercial breeding. Although the underlying pathophysiology remains unknown, we and others have previously shown that affected broilers display varying degrees of fibrosis, extracellular matrix (ECM) remodeling, inflammation, and alterations in various molecular signaling pathways. Other myopathy conditions, such as Duchenne muscular dystrophy, also affect the cardiac muscle and are associated with fibrosis and reduced cardiac function. To determine potential cardiac implications of wooden breast disease and identify whether molecular and fibrotic changes were similar to what we have previously found in the breast, we have investigated the hearts of commercial Ross 308 broilers.

Methods

Hearts from male Ross 308 broiler chickens from mildly and severely wooden breast-affected chickens categorized in previous studies were analyzed. Ventricles from the hearts were analyzed by immunoblotting, real-time qPCR, near-infrared spectroscopy, Raman spectroscopy, and Masson`s trichrome histology. RNA sequencing was also conducted to identify the molecular footprint of the mildly and severely wooden breast-affected chickens.

Results

Compared to mildly affected chickens, the severely wooden breast-affected chickens did not show an increase in heart weight, water-binding capacity, or macronutrient composition. The hearts did also not display any differences in fibrosis development, extracellular matrix gene expression, or typical cardiac and inflammatory markers. The severely affected chickens did, however, show a reduction in protein levels of biglycan and fibromodulin, as well as alterations in matrix metalloproteinase 2, Wnt ligands, mTOR signaling, heat shock protein 70, and muscle LIM protein. Functional enrichment analysis of RNA sequencing also suggested a different molecular footprint of biological processes and pathways between the two groups.

Conclusion

Hearts from wooden breast-affected chickens did not display the same fibrotic alterations as those previously found in the breast. Despite few alterations detected in the markers and signaling molecules tested, RNA sequencing indicated a different molecular footprint in the hearts of severely compared to mildly wooden breast-affected chickens.

Breast myopathy co-occurrence and its impact on carcass and meat quality attributes in broiler chickens

Wooden breast (WB), spaghetti meat (SM) and white striping (WS) are significant research focuses due to their impact on meat quality. This study examines the relationship between different myopathies in chickens from a commercial slaughterhouse and compares physicochemical traits between breasts with single and multiple myopathies and control (CO-no apparent myopathy). A total of 240 breasts were evaluated for myopathy presence, severity and location, and physicochemical parameters (i.e. carcass weight and color; breast color, pH, electrical conductivity, drip, thaw and cooking loss, Warner-Brazler texture, moisture, protein, fat and collagen content). A 54.8 % of the affected breasts presented multiple myopathies, and within them, a correlation between WB and WS was found (Kendall's tau = 0.24; P < 0.01). Additionally, myopathies were more prevalent in the breast cranial region (P < 0.05). Most physicochemical parameters varied significantly across myopathy classes. Breasts presenting WB, alone or in combination, were the most altered, showing: heavier carcasses with higher breast yield and redder and yellower skin; breasts with higher L*, b* and Hue, higher moisture, fat and collagen and lower protein content, and with higher cooking loss and lower resistance to shear (P < 0.05). SM, WS and their combination often had intermediate values between CO and WB breasts, with a few exceptions in carcass color and breast fat content. The principal component discriminant analysis revealed a proximity of CO to WS, SM, and their combinations, and a clear separation to WB and WB-SM. Breast yield, pH, cooking and thaw loss, and protein and fat content were the most discriminative parameters between categories. The partial least squares discriminant analysis could not differentiate between single, multiple myopathies and CO (accuracy = 42.6 %), but showed 80.63 % balanced accuracy for WB-SM, 74.26 % for SM and 74.61 % for CO. These findings confirm most previously reported data on meat quality, and provide a thorough analysis that can help industries to improve breast myopathies postmortem classification and identification.

Rapid detection of poultry meat quality using S-band to KU-band radio-frequency waves combined with machine learning-A proof of concept

Rapid changes in consumer preferences for high-quality animal-based protein have driven the poultry industry to identify non-invasive, in-line processing technologies for rapid detection of muscle meat quality defects. At production plants, technologies like radio-frequency waves (RF waves) can identify and separate myopathy-conditioned meat, reducing misclassification errors due to human fatigue and inexperience. Previous studies have shown that advanced diagnostic tools combined with complex data analytics, such as support vector machines (SVMs) and backpropagation neural networks (BPNNs), can classify chicken breast myopathies post-deboning. This study demonstrates RF wave use for myopathy detection at four processing stages. Using 107 (48-day old) broilers, RF wave data in amplitude and phase were collected from live birds, pre-chilled without giblets (WOGs), post-chilled WOGs, and freshly deboned fillets (3-3.5 h post-slaughter) and examined by hand-palpation for woody breast categories (1-normal; 2-moderate; 3-severe). Data preprocessing involved false discovery rate and predictor analysis to identify specific signature frequencies and develop classification models using supervised machine learning (ML) algorithms. Variable clustering analysis identified seven to eight different frequencies at various processing stages. Preprocessed data with identified signature frequencies were used to develop classification models using BPNN and SVM. BPNN demonstrated superior classification accuracy compared to SVM, with accuracy ranges from 90.0% to 96.1% for live birds, 78.9% to 97.1% for pre-chilled WOGs, 82.1% to 95.9% for post-chilled WOGs, and 94.2% to 98.2% for deboned fillets. Integrating specific RF range devices or sensors with supervised ML algorithms like SVM and BPNN in poultry processing can effectively detect muscle myopathies at different processing steps during in-line processing.

Review: Myopathies in broilers: supply chain approach to provide solutions to challenges related to raising fast growing birds

This review is a summary of a Poultry Science Association symposium addressing myopathies in broilers' breast meat, focusing on the interactions between genetics, nutrition, husbandry, and meat processing. The Pectoralis major myopathies (woody breast [WB]; white striping [WS]; spaghetti meat [SM]) and Pectoralis minor ("feathering") are described, followed by discussing their prevalence, potential causes, current and future ways to mitigate, as well as detection methods (in live birds and meat) as well as ways to utilize affected meat. Overall, breast myopathies remain an important focus across the poultry industry and whilst a lot of data and knowledge has been gathered, it is clear that there is still a lot to understand. As there are multiple factors impacting the occurrence of breast myopathies, their reduction relies on a holistic approach. Ongoing balanced breeding strategies by poultry breeders is targeting the longer-term genetic component but comprehending the significant influence from nongenetic factors (short-term solutions such as nutrition) remains a key area of opportunity. Consequently, understanding the physiology and biological needs of the muscle through the life of the bird is critical to reduce the myopathies (e.g., minimizing oxidative stress) and gain more insight into their etiology.

Combined Relaxation Spectra for the Prediction of Meat Quality: A Case Study on Broiler Breast Fillets with the Wooden Breast Condition

This study evaluated the potential of using combined relaxation (CRelax) spectra within time-domain nuclear magnetic resonance (TD-NMR) measurements to predict meat quality. Broiler fillets affected by different severities of the wooden breast (WB) conditions were used as case-study samples because of the broader ranges of meat-quality variations. Partial least squares regression (PLSR) models were established to predict water-holding capacity (WHC) and meat texture, demonstrating superior CRelax capabilities for predicting meat quality. Additionally, a partial least squares discriminant analysis (PLS-DA) model was developed to predict WB severity based on CRelax spectra. The models exhibited high accuracy in distinguishing normal fillets from those affected by the WB condition and demonstrated competitive performance in classifying WB severity. This research contributes innovative insights into advanced spectroscopic techniques for comprehensive meat-quality evaluation, with implications for enhancing precision in meat applications.

Beyond the Spectrum: Unleashing the Potential of Infrared Radiation in Poultry Industry Advancements

The poultry industry is dynamically advancing production by focusing on nutrition, management practices, and technology to enhance productivity by improving feed conversion ratios, disease control, lighting management, and exploring antibiotic alternatives. Infrared (IR) radiation is utilized to improve the well-being of humans, animals, and poultry through various operations. IR radiation occurs via electromagnetic waves with wavelengths ranging from 760 to 10,000 nm. The biological applications of IR radiation are gaining significant attention and its utilization is expanding rapidly across multiple sectors. Various IR applications, such as IR heating, IR spectroscopy, IR thermography, IR beak trimming, and IR in computer vision, have proven to be beneficial in enhancing the well-being of humans, animals, and birds within mechanical systems. IR radiation offers a wide array of health benefits, including improved skin health, therapeutic effects, anticancer properties, wound healing capabilities, enhanced digestive and endothelial function, and improved mitochondrial function and gene expression. In the realm of poultry production, IR radiation has demonstrated numerous positive impacts, including enhanced growth performance, gut health, blood profiles, immunological response, food safety measures, economic advantages, the mitigation of hazardous gases, and improved heating systems. Despite the exceptional benefits of IR radiation, its applications in poultry production are still limited. This comprehensive review provides compelling evidence supporting the advantages of IR radiation and advocates for its wider adoption in poultry production practices.

Explorative study for the rapid detection of adulterated surimi using gas chromatography-ion mobility spectrometry

Driven by economic interests, surimi adulteration has become a high-frequency issue. This study aims to assess the feasibility of gas chromatography-ion mobility spectrometry (GC-IMS) in detecting surimi adulteration. In this work, three common adulterated surimi models were established by mixing with different fish species and ratios. The fingerprints enabled a clear discrimination among different tuna surimi, and other two surimi models with different mixing ratios also showed VOCs (volatile organic compounds) differences. Results of unsupervised principal component analysis (PCA) and supervised partial least-squares discrimination analysis (PLS-DA) revealed that different types of adulterated surimi models can be well separated from each other. A total of 12, 16, and 9 VOCs were selected as the potential markers in three simulated models by PLS-DA method, respectively. Therefore, GC-IMS coupled with certain chemometrics is expected to serve as an alternative analytical tool to directly and visually detect adulterated surimi.

Water properties in intact wooden breast fillets during refrigerated storage

The wooden breast (WB) condition notably alters moisture content and water holding capacity (WHC) in broiler breast fillets. The purpose of this study was to investigate water properties during refrigerated storage from 4 h to 168 h postmortem using time domain nuclear magnetic resonance (TD-NMR). Water properties measured included mobility (T), proportion (P), and abundance per 100 g of meat (A). Changes in meat quality indicators including compression force, color, pH, cumulative purge loss, and proximate composition were also measured. Compression force and energy of the WB fillets were higher than normal fillets (P < 0.05). Slopes of changes in lightness of the WB and normal fillets were different in skin and bone side (P < 0.05). The slope of the purge loss from the WB fillets was higher than the normal fillets (P < 0.05). Time domain nuclear magnetic resonance analysis showed 4 water populations in intact broiler fillets with transverse relaxation time (T2) constants at approximately 4 to 5 milliseconds (ms) (designated as 2b, corresponding to hydration water or bound water), 40 to 60 ms (designated as 21, corresponding to intra-myofibrillar water or immobilized water), 80 to 210 ms (designated as 22a, corresponding to extra-myofibrillar water or free water with lower mobility) and 210 to 500 ms (designated as 22b, corresponding to extra-myofibrillar water or free water with higher mobility) during early postmortem storage (between 4 h and 72 h postmortem) and only 3 populations (2b, 21, and 22a) after 72 h postmortem. There were interaction effects (P < 0.05) between storage time and WB condition for all water properties except T2b, A2b/100 g, and T22b. The linear change of T21, P21, A21/100 g, T22a, A22a/100 g, P22b, and A22b/100 g in stored WB samples were different from the normal fillets (P < 0.05). During storage, P21 and A21/100 g of the WB fillets exhibited faster linear increases than those of the normal fillets, whereas T21 and T22a of the normal fillets and A22a/100 g, P22b, and A22b/100 g of the WB fillets showed faster linear decreases (P < 0.05). Our data demonstrate that the WB condition affects changes in water properties in broiler fillets during postmortem refrigerated storage.

Characterization of wooden breast myopathy: a focus on syndecans and ECM remodeling

Introduction: The skeletal muscle deformity of commercial chickens (Gallus gallus), known as the wooden breast (WB), is associated with fibrotic myopathy of unknown etiology. For future breeding strategies and genetic improvements, it is essential to identify the molecular mechanisms underlying the phenotype. The pathophysiological hallmarks of WB include severe skeletal muscle fibrosis, inflammation, myofiber necrosis, and multifocal degeneration of muscle tissue. The transmembrane proteoglycans syndecans have a wide spectrum of biological functions and are master regulators of tissue homeostasis. They are upregulated and shed (cleaved) as a regulatory mechanism during tissue repair and regeneration. During the last decades, it has become clear that the syndecan family also has critical functions in skeletal muscle growth, however, their potential involvement in WB pathogenesis is unknown. Methods: In this study, we have categorized four groups of WB myopathy in broiler chickens and performed a comprehensive characterization of the molecular and histological profiles of two of them, with a special focus on the role of the syndecans and remodeling of the extracellular matrix (ECM). Results and discussion: Our findings reveal differential expression and shedding of the four syndecan family members and increased matrix metalloproteinase activity. Additionally, we identified alterations in key signaling pathways such as MAPK, AKT, and Wnt. Our work provides novel insights into a deeper understanding of WB pathogenesis and suggests potential therapeutic targets for this condition.

Use of image analysis to evaluate morphometric measurements of broiler breast fillets affected by the woody breast condition

The objective of this study was to investigate the relationships between morphometric measurements and woody breast (WB) severity in breast fillets using image processing as an objective detection method for WB. Breast fillets were collected and categorized as normal (NORM), mild (MILD), moderate (MOD), and severe (SEV). Compression force and energy increased as WB severity increased alongside a decrease in severity through fillet regions (P < 0.05). Length and caudal thickness were highest in SEV and MOD groups (P < 0.05), and cranial thickness increased as WB severity increased (P < 0.05). The aerial area was the smallest in NORM fillets, while the planar area increased from NORM to MOD (P < 0.05). Fillet curvatures were highest in SEV and MOD fillets (P < 0.05). All measured parameters expressed strong correlation to WB scores (P < 0.05) except width. The results from this study may provide a basis for further assessment of the potential incorporation of these measurements into vision grading systems that may allow processors to sort fillets by WB severity in commercial plants.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-022-05525-x.

Classification and Feature Extraction Using Supervised and Unsupervised Machine Learning Approach for Broiler Woody Breast Myopathy Detection

Bioelectrical impedance analysis (BIA) was established to quantify diverse cellular characteristics. This technique has been widely used in various species, such as fish, poultry, and humans for compositional analysis. This technology was limited to offline quality assurance/detection of woody breast (WB); however, inline technology that can be retrofitted on the conveyor belt would be more helpful to processors. Freshly deboned (n = 80) chicken breast fillets were collected from a local processor and analyzed by hand-palpation for different WB severity levels. Data collected from both BIA setups were subjected to supervised and unsupervised learning algorithms. The modified BIA showed better detection ability for regular fillets than the probe BIA setup. In the plate BIA setup, fillets were 80.00% for normal, 66.67% for moderate (data for mild and moderate merged), and 85.00% for severe WB. However, hand-held BIA showed 77.78, 85.71, and 88.89% for normal, moderate, and severe WB, respectively. Plate BIA setup is more effective in detecting WB myopathies and could be installed without slowing the processing line. Breast fillet detection on the processing line can be significantly improved using a modified automated plate BIA.

Feasibility of In-Line Raman Spectroscopy for Quality Assessment in Food Industry: How Fast Can We Go?

Raman spectroscopy is a viable tool within process analytical technologies due to recent technological advances. In this article, we evaluate the feasibility of Raman spectroscopy for in-line applications in the food industry by estimating the concentration of the fatty acids EPA + DHA in ground salmon samples (n = 63) and residual bone concentration in samples of mechanically recovered ground chicken (n = 66). The samples were measured under industry like conditions: They moved on a conveyor belt through a dark cabinet where they were scanned with a wide area illumination standoff Raman probe. Such a setup should be able to handle relevant industrial conveyor belt speeds, and it was studied how different speeds (i.e., exposure times) influenced the signal-to-noise ratio (SNR) of the Raman spectra as well as the corresponding model performance. For all samples we applied speeds that resulted in 1 s, 2 s, 4 s, and 10 s exposure times. Samples were scanned in both heterogenous and homogenous state. The slowest speed (10 s exposure) yielded prediction errors (RMSECV) of 0.41%EPA + DHA and 0.59% ash for the salmon and chicken data sets, respectively. The more in-line relevant exposure time of 1 s resulted in increased RMSECV values, 0.84% EPA + DHA and 0.84% ash, respectively. The increase in prediction error correlated closely with the decrease in SNR. Further improvements of model performance were possible through different noise reduction strategies. Model performance for homogenous and heterogenous samples was similar, suggesting that the presented Raman scanning approach has the potential to work well also on intact heterogenous foods. The estimation errors obtained at these high speeds are likely acceptable for industrial use, but successful strategies to increase SNR will be key for widespread in-line use in the food industry.

Development of Imaging System for Online Detection of Chicken Meat with Wooden Breast Condition

In recent years, the wooden breast condition has emerged as a major meat quality defect in the poultry industry worldwide. Broiler pectoralis major muscle with the wooden breast condition is characterized by hardness upon human palpation, which can lead to decrease in meat value or even reduced consumer acceptance. The current method of wooden breast detection involves a visual and/or tactile evaluation. In this paper, we present a sideview imaging system for online detection of chicken breast fillets affected by the wooden breast condition. The system can measure a physical deformation (bending) of an individual chicken-breast fillet through high-speed imaging at about 200 frames per second and custom image processing techniques. The developed image processing algorithm shows the over 95% classification performance in detecting wooden breast fillets.

Characteristics of Broiler Chicken Breast Myopathies (Spaghetti Meat, Woody Breast, White Striping) in Ontario, Canada

Spaghetti meat (SM), woody breast (WB), and white striping (WS) are myopathies affecting breast muscle of broiler chickens, and are characterized by a loss of myofibers and an increase in fibrous tissue. The conditions develop in intensive broiler chicken production systems, and cause poor meat process-ability and negative customer perception leading to monetary losses. The objectives of the present study were to describe the physical and histological characteristics of breast myopathies from commercial broiler chicken flocks in Ontario, Canada, and to assess the associations between the severity of myopathies with the physical and histological characteristics of the affected breast muscle fillets. Chicken breast fillets (n = 179) were collected over 3 visits from a processing plant and scored macroscopically to assess the severity of myopathies, following an established scoring scheme. For each fillet, the surface area, length, width, thickness, weight, and hardness (compression force) were measured. A subset of 60 fillets was evaluated microscopically. Multinomial logistic regression models were built to evaluate associations between physical parameters and macroscopic scores. The odds of SM co-occurring with severe WB (SM1WB2) were significantly associated with increased fillet thickness (OR = 1.59, 95% CI 1.31–1.94) and weight (OR = 1.06, 95% CI 1.03–1.09). Histologically, myopathies had overlapping lesions consisting of polyphasic myodegeneration, perivascular inflammatory cuffing and accumulation of fibrous tissue and fat. The pairwise correlation between macroscopic and microscopic scores was moderate (rho 0.45, P < 0.001). This is the first study to characterize breast myopathies in Canadian broiler flocks. Results show that the morphologic and microscopic changes of fillets from this cohort are similar to data from other countries, and provide database to benchmark these parameters in future studies. Our standardized categorization can be applied to broiler breast fillets in other regions of the world.

Acceptability of Artificial Intelligence in Poultry Processing and Classification Efficiencies of Different Classification Models in the Categorisation of Breast Fillet Myopathies

Breast meat from modern fast-growing big birds is affected with myopathies such as woody breast (WB), white striping, and spaghetti meat (SM). The detection and separation of the myopathy-affected meat can be carried out at processing plants using technologies such as bioelectrical impedance analysis (BIA). However, BIA raw data from myopathy-affected breast meat are extremely complicated, especially because of the overlap of these myopathies in individual breast fillets and the human error associated with the assignment of fillet categories. Previous research has shown that traditional statistical techniques such as ANOVA and regression, among others, are insufficient in categorising fillets affected with myopathies by BIA. Therefore, more complex data analysis tools can be used, such as support vector machines (SVMs) and backpropagation neural networks (BPNNs), to classify raw poultry breast myopathies using their BIA patterns, such that the technology can be beneficial for the poultry industry in detecting myopathies. Freshly deboned (3–3.5 h post slaughter) breast fillets (n = 100 × 3 flocks) were analysed by hand palpation for WB (0-normal; 1-mild; 2-moderate; 3-Severe) and SM (presence and absence) categorisation. BIA data (resistance and reactance) were collected on each breast fillet; the algorithm of the equipment calculated protein and fat index. The data were analysed by linear discriminant analysis (LDA), and with SVM and BPNN with 70::30: training::test data set. Compared with the LDA analysis, SVM separated WB with a higher accuracy of 71.04% for normal (data for normal and mild merged), 59.99% for moderate, and 81.48% for severe WB. Compared with SVM, the BPNN training model accurately (100%) separated normal WB fillets with and without SM, demonstrating the ability of BIA to detect SM. Supervised learning algorithms, such as SVM and BPNN, can be combined with BIA and successfully implemented in poultry processing to detect breast fillet myopathies.

Characterization of Collagen Structure in Normal, Wooden Breast and Spaghetti Meat Chicken Fillets by FTIR Microspectroscopy and Histology

Recently, two chicken breast fillet abnormalities, termed Wooden Breast (WB) and Spaghetti Meat (SM), have become a challenge for the chicken meat industry. The two abnormalities share some overlapping morphological features, including myofiber necrosis, intramuscular fat deposition, and collagen fibrosis, but display very different textural properties. WB has a hard, rigid surface, while the SM has a soft and stringy surface. Connective tissue is affected in both WB and SM, and accordingly, this study's objective was to investigate the major component of connective tissue, collagen. The collagen structure was compared with normal (NO) fillets using histological methods and Fourier transform infrared (FTIR) microspectroscopy and imaging. The histology analysis demonstrated an increase in the amount of connective tissue in the chicken abnormalities, particularly in the perimysium. The WB displayed a mixture of thin and thick collagen fibers, whereas the collagen fibers in SM were thinner, fewer, and shorter. For both, the collagen fibers were oriented in multiple directions. The FTIR data showed that WB contained more β-sheets than the NO and the SM fillets, whereas SM fillets expressed the lowest mature collagen fibers. This insight into the molecular changes can help to explain the underlying causes of the abnormalities.

Diffuse reflectance spectroscopy reveals heat stress-induced changes in hemoglobin concentration in chicken breast

Heat stress (HS) is devastating to the poultry industry due to its adverse effects on animal well-being and performance. The effects of heat stress are typically measured using a portable i-STAT blood analyzer that quantifies circulatory hemoglobin concentration and other blood chemistry parameters. Here, we used diffuse reflectance spectroscopy (DRS) as a novel non-invasive method to directly determine changes in hematological parameters in the breast tissues of live heat-stressed broilers. Three-week-old male broilers were randomly subjected to two environmental conditions (thermoneutral, TN, 24 °C vs. cyclic heat stress, HS, 35 °C, 12 h/day). Optical spectra were acquired using DRS to monitor breast hemoglobin (Hb) concentration and vascular oxygen saturation (sO₂) at three time points: at baseline prior to heat stress, 2 days, and 21 days after initiation of HS. While i-STAT did not demonstrate a discernible change due to HS in circulatory hemoglobin, DRS found a significant decrease in breast Hb and sO₂ after exposure to chronic HS. The decrease in sO₂ was found to be due to a decrease in oxygenated hemoglobin concentration, indicating a large increase in oxygen consumption in heat-stressed broilers. Our results demonstrate that DRS could potentially be used to study the effects of HS directly in specific organs of interest, such as the breast and thigh, to improve meat quality.

Detection of woody breast condition in commercial broiler carcasses using image analysis

Image analysis could be an objective and rapid method to identify woody breast (WB) myopathy and benefit the global poultry industry. The objective of this study was to determine if there are conformational changes that can be used to detect WB characteristics in commercial broiler carcasses across strains, gender, and ages using image analysis. A total of 900 images of male and female broiler carcasses from commercial standard and high breast-yielding strains and 5 ages (6 through 10 wk) were captured before evisceration. These images were processed and analyzed using ImageJ software. Conformational measurements were M0: breast length; M1: breast width in the cranial region; M2: vertical line from the tip of keel to 1/5th of breast length; M3: breast width at the end of M2; M4: angle formed at the tip of keel and extending to outer points of M3; M5: area of the triangle formed by M3 and lines generated by M4; M6: area of the breast above M3; M7: M6 minus M5. Ratios of these measurements were also considered. Intact breast fillets were scored for WB severity based on tactile evaluation. Regardless of strain, sex, and age, M11 (M1/M0), M9 (M3/M2), and M4 had the highest correlation to WB score (r_s ≥ 0.65; P < 0.01). Overall, the best validated model (Gen. R² = 0.61) to predict WB included M1, M2, and M3. Using this model, 91% of broiler carcasses were properly classified as normal or WB along with a sensitivity of 71% to detect affected carcasses. Although the predictive performance of models for detecting the WB condition using these measurements was associated with the broiler strain, sex, and age or live weight, these data also support the feasibility of using image analysis to predict WB defect in broiler carcasses. The possible integration of these image measurements into commercial noncontact, nondestructive, and fast in-line vision grading systems would allow processors to identify broilers with WB and potentially sort, provide large-scale information downstream to further processing operations and upstream to live production.

Effect of Woody Breast Condition on Instrumental Texture Characteristics of Poultry Deli Loaves

The use of broiler breast fillets affected by the woody breast (WB) condition in processed poultry products couldbe a feasible solution to this meat quality problem. This study assessed the impact of utilizing broiler breast fillets at differ-ent degrees of WB severity and percentages on instrumental texture characteristics of deli loaves. Breast fillets (n = 270) were collected from broiler carcasses and sorted based on palpation assessment in 3 WB categories (normal [NOR], mild [MIL], and severe [SEV]). Nine treatments of deli loaves were prepared from cubed portions in each of 3 replications: 100% NOR (T1), 67% NOR + 33% MIL (T2), 67% NOR + 33% SEV (T3), 33% NOR + 67% MIL (T4), 33% NOR + 67% SEV (T5), 100% MIL (T6), 67% MIL + 33% SEV (T7), 33% MIL + 67% SEV (T8), and 100% SEV (T9). Cooked deli loaves were subjected to texture profile analysis, cook loss, instrumental color, and dimensional modifications. Hardness of deli loaves increased (P &lt; 0.05), whereas cohesiveness values decreased (P &lt; 0.05), as WB severity increased in the meat added into the product formulation when compared with NOR samples and excluding treatments T2 through T4. The use of SEV fillets at 100% (T9) or mixtures of MIL and SEV fillets (T7 and T8) yielded nonuniform deli loaves with different color parameters and higher levels of cook loss (&gt;13%), coupled with reductions in diameter (&gt;8%) and length (&gt;5%), comparedto NOR samples (P &lt; 0.05). These results suggest that the negative effects of WB on quality and yield characteristics are not minimized by the preparation of this formed product when using high proportions of WB meat. Thus, broiler breast fillets affected by the WB condition may be used at relatively low percentages combined with NOR fillets as an option in commercial chicken deli loaf formulations.

Characterization of chicken muscle disorders through metabolomics, pathway analysis, and water relaxometry: a pilot study

Metabolite profiles of chicken breast extracts and water mobility in breasts were studied using proton nuclear magnetic resonance (1H-NMR) spectroscopy and time-domain NMR (TD-NMR) relaxometry, respectively, using normal breast (NB), and wooden breast (WB) and white striping (WS) myopathies in broilers. One thousand eight hundred sixty broilers were raised to commercial standards, receiving the same diets that were formulated as per the different growth stages. At 49 D of age, 200 animals were slaughtered following routine commercial procedures, and at 4 h postmortem, the whole breast (pectoralis major muscle) was removed and visually inspected by an experienced meat inspector who selected NB (without myopathies) and samples with the presence of WS and WB myopathies. Fifteen breasts (5 each of NB, WS, and WB) were analyzed through TD-NMR relaxometry, and samples of approximately 20 g were taken from each breast and frozen at -80°C for metabolite profiling through 1H-NMR spectroscopy. Multivariate statistical analysis was used to evaluate the effect on water relaxometry and metabolite profile in accordance with the presence and type of myopathy in the breast. 1H-NMR data showed that the metabolite profiles in WS and WB breasts were different from each other and from NB. This pilot study shows that myopathies appear to be related to hypoxia, connective tissue deposition, lower mitochondrial function, and greater oxidative stress compared with NB. The longitudinal and transverse relaxation time of the breasts determined by TD-NMR relaxometry was shorter for NB than that for WS and WB, indicating greater water mobility in breasts affected by myopathies. 1H-NMR spectroscopy can be used to differentiate the metabolism of WS, WB, and NB, and TD-NMR has the potential to be a fast, simple, and noninvasive method to distinguish NB from WB and WS. As a practical application, the metabolomic profile as per the occurrence of breast myopathies may be used for a better understanding of these issues, which opens a gap to mitigate the incidence and severity of WS and WB. In addition, the present study brings an opportunity for the development of a new and objective tool to classify the incidence of breast myopathies through TD-NMR relaxometry.

Occurrence of wooden breast and white striping in Brazilian slaughtering plants and use of near-infrared spectroscopy and multivariate analysis to identify affected chicken breasts

White Striping (WS) and Wooden Breast (WB) are emerging poultry myopathies that occur worldwide, affecting the quality of meat. The aim of this study was to evaluate the occurrence of N, WS, WB, and WS/WB (myopathies combined) in chicken breast from Brazilian commercial plant, comparing (1) inspection based on visual aspect and palpation of Pectoralis major muscle, and (2) identification of these myopathies by near-infrared Spectroscopy (NIRS). Chickens slaughtered at Brazilian commercial plant at four age ranges (4 to 5, 6 to 7, 8 to 9, and 65 weeks) were inspected. Spectral information was acquired using a portable NIR spectrometer, and classification models were performed using and Successive Projection Algorithm-Linear Discriminant Analysis (SPA-LDA) and Soft Independent Modeling of Class Analogy (SIMCA) to distinguish normal and affected muscles. Results showed that occurrence of myopathies was aggravated by age of slaughter, as chicken slaughtered at 4 to 5 and 65 weeks exhibited 13.6 and 95% of myopathies, respectively. Birds slaughtered at 65 weeks showed no occurrence of WB, isolated or combined with WS. It was not possible to differentiate the WB and WS/WB classes; therefore, those samples were grouped (WB+WS/WB). SPA-LDA model showed greater accuracy (92 to 93%) in identifying Normal (N), WS, and WB+WS/WB groups, compared to SIMCA (89 to 91%). It can be concluded that the level of occurrence of myopathies in meat is directly related to the age of slaughter. This study demonstrated that NIRS combined with SPA-LDA model could be used as a tool to detect myopathies in chicken breast. This technique has potential for application in industrial processing lines as an alternative to the traditional methods of identification. PRACTICAL APPLICATION: This study shows that NIRS combined with chemometric techniques can be used to identify chicken breast myopathies in a wide range of ages at slaughter. In addition to being able to discriminate chicken muscles into subclasses, namely, Normal, WS, and WB/WB+WS, this technique has potential for application in industrial processing lines as it is a portable and nondestructive method. This procedure is emphasized as an alternative to the conventional method of identification based on palpation and visual assessment of muscle.

A review on the woody breast condition, detection methods, and product utilization in the contemporary poultry industry

In recent years, the global poultry industry has been facing increasing and challenging myopathies such as the woody breast (WB) condition that has caused significant economic losses. Even though the etiological causes of WB myopathy are still unknown or partially understood, the intensive genetic selection for rapid-growth rates and high yields in broilers may be the main factor associated with the development of this abnormality. The severity of this anomaly and its incidence rates are associated with fast-growing and heavier broilers, especially with those from high breast yielding strains. Such WB myopathy is primarily characterized by a notorious hardness in broiler breast muscles, which exhibit morphometric and histopathological alterations coupled with physicochemical abnormalities that result in undesired sensory, nutritional, and technological properties. In this negative context, although scientists are trying to solve or reduce the prevalence of this meat quality problem, the poultry industry needs noncontact and rapid in-line methods for WB detection at the fillet and/or carcass level that could help to establish automated objective grading or sorting systems according to its severity. Another need is the development and selection of profitable alternatives for the utilization of WB meat once poultry carcasses or deboned fillets affected by this abnormality are objectively detected and sorted. Indeed, there is a need for studies to expand the industrial applications of WB meat in further processed products, optimizing the incorporation of this affected chicken meat based on sensorial, technological, and nutritional profile evaluations. Even though a better understanding of the contribution of genetic and nongenetic factors to the development of growth-related myopathies can be the main strategy to mitigate their negative effects, the poultry industry could benefit from meeting the aforementioned needs.

NIR Spectroscopic Techniques for Quality and Process Control in the Meat Industry

Near-infrared spectroscopy (NIRS) is widely used for quality and process control in the food industry. In the meat industry, the method is still used mainly for determination of fat, water, and protein content, while new applications are emerging. In this paper, we report on how in-line NIRS can be used to detect and sort chicken breast fillets with the myopathies wooden breast and spaghetti meat from normal fillets. A total of 270 fillets were measured with 2 different near-infrared systems. The near-infrared spectra contained information about protein content and water-binding properties that showed systematic differences between the 3 quality classes. Wooden breast could be well separated fro m normal fillets (96% correct classification), while spaghetti meat was slightly more difficult to separate from both normal and wooden breast because properties measured by NIRS were overlapping between the 3 groups. Two quite similar NIRS instruments had quite different classification performance, which emphasizes the importance of optimizing spectroscopic instrumentation for different applications.

Differentiation between Normal and White Striped Turkey Breasts by Visible/Near Infrared Spectroscopy and Multivariate Data Analysis

The appearance of white striations over breast meat is an emerging and growing problem. The main purpose of this study was to employ the reflectance of visible-near infrared (VIS/NIR) spectroscopy to differentiate between normal and white striped turkey breasts. Accordingly, 34 turkey breast fillets were selected representing a different level of white striping (WS) defects (normal, moderate and severe). The findings of VIS/NIR were analyzed by principal component (PC1) analysis (PCA). It was found that the first PC1 for VIS, NIR and VIS/NIR region explained 98%, 97%, and 96% of the total variation, respectively. PCA showed high performance to differentiate normal meat from abnormal meat (moderate and severe WS). In conclusion, the results of this research showed that VIS/NIR spectroscopy was satisfactory to differentiate normal from severe WS turkey fillets by using several quality traits.