New microbial performance standards for chicken parts necessitate postchill antimicrobial interventions to make poultry parts safer for consumers. This research was conducted to determine the effectiveness of antimicrobials (0.003% chlorine; 0.07% acidified sodium chlorite [ASC], 0.07 or 0.1% peracetic acid [PAA], and 0.35 or 0.60% cetylpyridinium chloride [CPC]) when used in a postchill decontamination tank to reduce Salmonella and Campylobacter on broiler chicken parts (including breasts, thighs, wings, and drumsticks) and to determine the sensory attributes of the treated samples. Samples ( n = 90, 9 treatments × 5 samples × 2 replications) were inoculated with Salmonella Typhimurium (10 CFU/mL) and Campylobacter jejuni (10 CFU/mL). After a 30-min attachment time, chicken parts were rinsed with various antimicrobials in a decontamination tank for 23 s. Salmonella and Campylobacter reduction was determined by sampling parts after the treatments were applied. Sensory evaluation of skin-on (drumettes) and skin-off (breast meat) parts were conducted by untrained panelists by using an 8-point hedonic scale. CPC (0.35 or 0.60%), provided a reduction of 2.5 or 3.5 log CFU/mL on Salmonella and a reduction of 4 or 5 log CFU/mL on Campylobacter, respectively. Both concentrations of PAA (0.07 or 0.1%) provided a 1.5-log reduction on Salmonella and Campylobacter. Chlorine at 0.003% and ASC at 0.07% were the least effective antimicrobials, providing <1-log reduction for both pathogens, which did not differ from the reduction provided by a water rinse alone. Sensory attributes were unaffected in drumettes, and skinless breast fillets received the most acceptable scores ( P ≤ 0.05) for texture, juiciness, and overall acceptability when treated with 0.07% PAA and 0.35% CPC. Results from this study indicated that using PAA and CPC in a postchill decontamination tank are effective treatments for reducing Salmonella and Campylobacter on chicken parts, with minimal effects on product quality.

Woody breast (WB) myopathy in modern broilers is causing major meat quality issues and consumer complaints. The poultry industry is sorting out WB filets through the inconsistent manual hand-palpation method. Bioelectrical impedance analysis (BIA) method was evaluated as a rapid and objective WB detection method. Freshly deboned broiler breast filets (15 filets × 2 categories × 3 trials) were sorted (hand-palpation) into severe woody (SW) and normal (N) categories were analyzed for BIA values, cook loss, texture (BMORS) method. SW filets had significantly ( P < 0.05) higher resistance and reactance compared to N indicating BIA can be used to detect WB filets. In another experiment, we determined the ability of the BIA to differentiate between four WB severity levels using the whole filet. Significant differences were observed in resistance and reactance of normal and other WB categories, however, there were no significant differences among mild, moderate and severe WB categories. Segmental BIA of those filets indicated that BIA can be used to separate cranial, medial and caudal region of the breast filet based on the presence of WB myopathy. Accidental discovery of spaghetti breast in the samples demonstrated the significance of compounding different factors in analyzing WB meat using BIA.

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Woody breast (WB) myopathy affected meat has a tough texture, higher cook loss, and decreased water holding capacity (WHC), and thus lower consumer acceptability. The WB meat can be ground and further converted into further processed products or frozen, stored, and shipped to further processors. Freezing and thawing of ground WB meat may further affect the quality of WB meat products. Hence, research is required to determine the effect of pre-blended phosphates on the quality of ground WB meat as well as its cryoprotective effect during frozen storage. The objective of this experiment was to investigate the effect of pre-blended phosphate levels on meat quality in WB and normal breast (NB) fillets before and after freezing. NB fillets and severely affected WB fillets were procured from a local commercial processor. The meat was separated into various treatment groups according to the sodium tripolyphosphate (STPP) inclusion levels (0, 0.25, and 0.5% w/w). The meat was ground with respective phosphate treatments and subdivided into vacuum-sealed bags (n = 240; 1 kg each). Half of the bags (n = 120) from each treatment were taken for meat quality analysis, while the other bags were placed in a freezer (−18 °C) for 6 days. Fresh samples were analyzed within 6–8 h while the frozen samples were thawed for 18 h at 4°C prior to analysis. Samples (n = 10) were analyzed for gel strength, pH, color (L* a* b*), proximate composition, and randomly selected samples (n = 5) were analyzed for aerobic plate count (APC). Experiments were repeated in two separate replications and the data was analyzed using the Proc Glimmix model procedure in SAS (v. 9.4) (Cary, NC, USA) with LSMeans Separation at p ≤ 0.05. The gel strength (g) of the fresh ground NB meat (883.7 g) was higher than the gel strength of woody meat (720.8 g) with 0% phosphate (p ≤ 0.05). Addition of phosphate (0.25 and 0.5%) significantly increased the gel strength of fresh woody meat but it was significantly lower than NB meat added with 0.25 and 0.5% phosphate treatment. After freezing, ground NB meat samples with 0.25 and 0.5% phosphate had higher gel strength compared to fresh and frozen ground WB meat (p ≤ 0.05). Pre-blended STPP raised the pH in all treatments (p < 0.05). Treatments did not have any clear impact on APC of ground WB or NB meat. Addition of pre-blended sodium tripolyphosphate increases the functionality of fresh and frozen ground WB meat, as well as NB meat.

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.