Research Note: Prospects for early detection of breast muscle myopathies by automated image analysis.

White Striping (WS), Wooden Breast (WB), and Spaghetti Meat (SM) are documented breast muscle myopathies (BMM) affecting broiler chickens' product quality, profitability and welfare. This study evaluated the efficacy of our newly developed deep learning-based automated image analysis tool for early detection of morphometric parameters related to BMM in broiler chickens. Male chicks were utilized, and muscle samples were collected on d 14 of rearing. Histological procedures, including microscopic scoring, blood vessel count, and collagen quantification, were conducted. A previous study demonstrated our automated image analysis as a reliable tool for evaluating myofiber size, conforming with manual histological measurements. A threshold for BMM detection was established by normalizing and consolidating myofiber diameter and area into a unified metric based on automated measurements, also termed as "relative myofiber size value." Results show that severe myopathy broilers consistently exhibited lower relative myofiber size values, effectively detecting myopathy severity. Our study, aimed as proof of concept, underscores the potential of our automated image analysis tool as an early detection method for BMM.

In-ovo feeding with creatine monohydrate: implications for chicken energy reserves and breast muscle development during the pre-post hatching period.

The most dynamic period throughout the lifespan of broiler chickens is the pre-post-hatching period, entailing profound effects on their energy status, survival rate, body weight, and muscle growth. Given the significance of this pivotal period, we evaluated the effect of in-ovo feeding (IOF) with creatine monohydrate on late-term embryos' and hatchlings' energy reserves and post-hatch breast muscle development. The results demonstrate that IOF with creatine elevates the levels of high-energy-value molecules (creatine and glycogen) in the liver, breast muscle and yolk sac tissues 48 h post IOF, on embryonic day 19 (p < 0.03). Despite this evidence, using a novel automated image analysis tool on day 14 post-hatch, we found a significantly higher number of myofibers with lower diameter and area in the IOF creatine group compared to the control and IOF NaCl groups (p < 0.004). Gene expression analysis, at hatch, revealed that IOF creatine group had significantly higher expression levels of myogenin (MYOG) and insulin-like growth factor 1 (IGF1), related to differentiation of myogenic cells (p < 0.01), and lower expression of myogenic differentiation protein 1 (MyoD), related to their proliferation (p < 0.04). These results imply a possible effect of IOF with creatine on breast muscle development through differential expression of genes involved in myogenic proliferation and differentiation. The findings provide valuable insights into the potential of pre-hatch enrichment with creatine in modulating post-hatch muscle growth and development.

A deep learning-based automated image analysis for histological evaluation of broiler pectoral muscle.

Global market demand for chicken breast muscle with high yield and quality, together with the high incidence rate of breast muscle abnormalities in recent years highlights the need for tools that can provide a rapid and precise evaluation of breast muscle development and morphology. In this study, we used a novel deep learning-based automated image analysis workflow combining Fiji (ImageJ) with Cellpose and MorphoLibJ plugins to generate an automated diameter and cross-sectional area quantification for broiler breast muscle. We compared data of myofiber diameter from 14-day-old broiler chicks, generated either by manual analysis or by automated analysis. Comparison between manual and automated analysis methods exhibited a striking accuracy rate of up to 99.91%. Moreover, the automated analysis method was much faster. When the automated analysis method was implemented on 84 breast muscle cross-section images it characterized 59,128 myofibers within 4.2 h, while manual analysis of 27 breast muscle cross-section images enabled analysis of 17,333 myofibers in 54 h. The automated image analysis method was also more productive, producing data sets of both diameter and cross-sectional area at an 80-fold higher rate than the manual analysis (26,279 vs. 321 data sets per hour, respectively). In order to demonstrate the ability of this automated image analysis tool to detect differences in breast muscle histomorphology, we applied it on cross sections from chicks of control and in ovo feeding group, injected with a methionine source [2-hydroxy-4-(methylthio) butanoic calcium salt (HMTBa)], known to effect skeletal muscle histomorphology. Analysis was performed on 19,807 myofibers from the control group and 21,755 myofibers from the HMTBa group and was completed in less than 1 h. The clear advantages of this automated image analysis workflow characterized by high precision, high speed, and high productiveness demonstrate its potential to be implemented as a reproducible and readily adaptable research or diagnostic tool for chicken breast muscle development and morphology.