Inheritance of growth traits and impact of selection on carcass and egg quality traits in Vanashree, an improved indigenous chicken

Nondestructive estimation method of live chicken leg weight based on deep learning

In the broiler-breeding industry, phenotype determination is critical. Leg weight is a fundamental indicator for breeding, and noninvasive testing technology can reduce damage to animals. This study proposes a broiler leg weight estimation system comprising a weight-estimation model and computed tomography (CT) acquisition equipment. The weight-estimation model can automatically process the scan results of live broiler chickens from the CT acquisition equipment. The weight-estimation model comprises an improved you-only-look-once (YOLOv5) segmentation algorithm and a random forest fitting network. The segmentation head was introduced into the YOLOv5 network, combined with a multiscale attention mechanism and an atrous spatial pyramid pooling architecture, and a new network model, YOLO- measuring chicken leg weight (YOLO-MCLW), was proposed to improve segmentation efficiency and accuracy. Morphological parameters were extracted from the obtained mask image, and a random forest network was used for fitting. The experiments show that the system exhibited an average absolute error of 7.27 g and an average percentage error of 4.82% in tests on 50 individual legs of 25 broiler chickens. The prediction R2 of broiler chicken legs can reaches 88.98%, the segmentation intersection over union result reaches 95.45%, and 37.04 images are processed per second. This system provides technical support for the part determination of broiler chickens in commercial breeding.

Carcass Characteristics, Meat Quality and Nutritional Composition of Kadaknath, a Native Chicken Breed of India

The study was carried out to investigate the carcass and meat quality traits and nutritional profile of the meat of the Kadaknath, a unique native chicken breed in comparison with commercial broilers. The yield of the carcass, breast and giblets of the Kadaknath was lesser (p < 0.01), while that of the legs, wings, back, and neck was higher (p < 0.01) than broilers. The meat of the Kadaknath was significantly (p < 0.0001) darker (42.44, 50.92) and more yellow (6.23, 8.99) than broilers. The decline in pH of the meat was lower (p < 0.001) in the Kadaknath compared to broilers. Kadaknath meat had more protein and less fat, moisture and ash content than broilers (p < 0.01). Furthermore, it was richer (p < 0.01) in 11 amino acids, including those which are known to impart a sweet and umami taste, than the meat of broilers (3 amino acids). Both genotypes were almost similar in meeting the daily requirements of indispensable amino acids of adult human. The study concluded that the Kadaknath differed in carcass and meat quality characteristics from the broilers, and the nutritional quality of Kadaknath meat in terms of high protein and less fat and higher content of amino acids (tasty type) was better in Kadaknath meat as compared to broiler meat.

Data Mining as a Tool to Infer Chicken Carcass and Meat Cut Quality from Autochthonous Genotypes

The present research aims to develop a carcass quality characterization methodology for minority chicken populations. The clustering patterns described across local chicken genotypes by the meat cuts from the carcass were evaluated via a comprehensive meta-analysis of ninety-one research documents published over the last 20 years. These documents characterized the meat quality of native chicken breeds. After the evaluation of their contents, thirty-nine variables were identified. Variables were sorted into eight clusters as follows; weight-related traits, water-holding capacity, colour-related traits, histological properties, texture-related traits, pH, content of flavour-related nucleotides, and gross nutrients. Multicollinearity analyses (VIF ≤ 5) were run to discard redundancies. Chicken sex, firmness, chewiness, L* meat 72 h post-mortem, a* meat 72 h post-mortem, b* meat 72 h post-mortem, and pH 72 h post-mortem were deemed redundant and discarded from the study. Data-mining chi-squared automatic interaction detection (CHAID)-based algorithms were used to develop a decision-tree-validated tool. Certain variables such as carcass/cut weight, pH, carcass yield, slaughter age, protein, cold weight, and L* meat reported a high explanatory potential. These outcomes act as a reference guide to be followed when designing studies of carcass quality-related traits in local native breeds and market commercialization strategies.

Variability of Meat and Carcass Quality from Worldwide Native Chicken Breeds

The present research aimed to determine the differential clustering patterns of carcass and meat quality traits in local chicken breeds from around the world and to develop a method to productively characterize minority bird populations. For this, a comprehensive meta-analysis of 91 research documents that dealt with the study of chicken local breeds through the last 20 years was performed. Thirty-nine traits were sorted into the following clusters: weight-related traits, histological properties, pH, color traits, water-holding capacity, texture-related traits, flavor content-related nucleotides, and gross nutrients. Multicollinearity problems reported for pH 72 h post mortem, L* meat 72 h post mortem, a* meat 72 h post mortem, sex, firmness, and chewiness, were thus discarded from further analyses (VIF < 5). Data-mining cross-validation and chi-squared automatic interaction detection (CHAID) decision tree development allowed us to detect similarities across genotypes. Easily collectable trait, such as shear force, muscle fiber diameter, carcass/pieces weight, and pH, presented high explanatory potential of breed variability. Hence, the aforementioned variables must be considered in the experimental methodology of characterization of carcass and meat from native genotypes. This research enables the characterization of local chicken populations to satisfy the needs of specific commercial niches for poultry meat consumers.

Genetic parameters of growth traits, trend of production and reproduction traits, and meat quality status of Ghagus, an indigenous chicken of India

Indigenous chickens play a vital role in providing nutritional security and economic support for the rural and tribal people in tropical countries like India. Ghagus, an indigenous chicken breed of India, was characterized for growth, production, and reproduction (fertility and hatchability) traits over different generations and for carcass and meat quality traits. Heritability, and genetic and phenotypic correlations among growth traits were estimated using mixed model least squares and maximum likelihood methods. Estimates of heritability of growth traits such as bodyweights at different age and 8-week shank length were high (0.32 to 0.39) in initial generation and moderate to high during latest generation (0.20 to 0.42). The correlations of growth traits with 40-week egg production were positive and significant (P < 0.001). There was improvement in 8-week bodyweight (559.3 ± 4.40 g) by 177 g over the generations. The average egg production up to 40 weeks over the generations was 35.66 eggs. There was also a significant (P < 0.001) increase in egg weights over the generations. The fertility (mean 89.3%) ranged from 85.2 to 92.3%. The hatchability on fertile egg set (mean 90.8%) ranged from 86.5 to 94.1% and it was improved by 3.9% over the generations. The carcass and meat quality study revealed that this breed has the lean meat, high protein, and attractive meat color with desirable meat quality characteristics. The study concluded that the Ghagus breed with self-propagation capacity has the potential to be improved as an indigenous meat-type breed to meet the ever-increasing demand for indigenous chickens' meat in the country.