The dynamics of population and production of Native Chicken under extensive- and semi-intensive maintenance

This study evaluated kampung chickens’ growth rate and production performance in extensive and semi-intensive rearing in Central Java, Indonesia. The survey method was employed for this study. The targets used in the study were kampung chicken farmers in the Banyumas and Kebumen areas. The survey method is carried out by collecting data, observing and measuring population, production performance, including meat and egg production. The data obtained, processed, and presented in the tables and graphs, calculated the population and production of chicken to evaluate its growth. The performance of chicken production, including egg production, egg weight, number of eggs hatched, and hatchability, was analyzed using general linear model (GLM) analysis. The result showed a 1.9% growth rate of the native chicken population, in which the hens outnumbered the roosters. The meat and egg production growth rates were 8.2% and 6.8%, respectively, between 2016 and 2020 in Central Java. Native chickens kept under semi-intensive maintenance produced more eggs than those in an extensive system. Conclusively, native chicken of Central Java experienced growth in population and production of meat and egg. The semi-intensive system, compared to the extensive system, had a higher rate of eggs production.

PSXII-9 Modeling genetic differences of combined broiler chicken populations in single-step GBLUP

The objectives of this study were to model the inclusion of a group of external birds into a local broiler chicken population for the purpose of genomic evaluations and evaluating the behavior of two accuracy estimators under different model specifications. The pedigree was composed by 242,413 birds and genotypes were available for 107,216 birds. A five-trait model that included one growth, two yield, and two efficiency traits was used for the analyses. The strategies to model the introduction of external birds were to include a fixed effect representing the origin of parents and to use UPG or metafounders. Genomic estimated breeding values (GEBV) were obtained with single-step GBLUP (ssGBLUP) using the Algorithm for Proven and Young (APY). Bias, dispersion, and accuracy of GEBV for the validation birds, i.e., from the most recent generation, were computed. The bias and dispersion were estimated with the LR-method, whereas accuracy was estimated by the LR-method and predictive ability. Models with fixed UPG and estimated inbreeding or random UPG resulted in similar GEBV. The inclusion of an extra fixed effect in the model made the GEBV unbiased and reduced the inflation, while models without such an effect were significantly biased. Genomic predictions with metafounders were slightly biased and inflated due to the unbalanced number of observations assigned to each metafounder. When combining local and external populations, the greatest accuracy and smallest bias can be obtained by adding an extra fixed effect to account for the origin of parents plus UPG with estimated inbreeding or random UPG. To estimate the accuracy, the LR-method is more consistent among models, whereas predictive ability greatly depends on the model specification, that is, on the fixed effects included in the model. When changing model specification, the largest variation for the LR-method was 20%, while for predictive ability was 110%.

Probiotic Pediococcus pentosaceus ABY 118 to Modulation of ChIFN-γ and ChIL-10 in Broilers Infected by Eimeria tenella Oocyst

Eimeria causes coccidiosis, which has long been recognized as a disease in chickens that significantly affects the economy. The global chicken population continues to grow, and its contribution to food security increases, making it increasingly important to produce chicken meat that is safe for human and health. This study aims to prove Pediococcus pentosaceus ABY 118 to modulation of ChIFN-γ and ChIL-10 in chickens infected with E. tenella oocysts. This study used 100 of day-old chickens (DOC), randomly divided into 5 treatments; each treatment consists of 20 chickens. The treatments was as follows: P0 (−): negative control; P0 (+): positive control; P1: monensin; P2: probiotic 1.5 × 108 CFU/ml; and P3: probiotic 3.0 × 108 CFU/ml. At the age of 20 days, Eimeria tenella (E. tenella) oocysts were inoculated orally at a dose of 1 × 104. The probiotic P. pentosaceus ABY 118 was given orally through drinking water from DOC to 35 days. Monensin was given orally through feed from the age of 14–26 days. The results of statistical analysis showed that there was a significant difference ( P < 0.05) between treatments on ChIFN-γ and ChIL-10 at 6 and 8 days postinfected with E. tenella oocysts. Based on the results of this study, it can be concluded that the use of P. pentosaceus ABY 118 isolates at a dose of 1.5 × 108 CFU/ml and 3.0 × 108 CFU/ml per liter of drinking water can increase health by stimulation of ChIFN-γ and ChIL-10 in broiler infected with E. tenella oocyst.

Genome-Wide Run of Homozygosity Analysis Reveals Candidate Genomic Regions Associated with Environmental Adaptations of Tibetan Native Chickens

Background In Tibet, two most important breeds are Tibetan chicken and Lhasa white chicken, and the duo exhibit specific adaptations to high altitude and produce indispensable protein for humans living in the plateau. These breeds were partly included in conservation plans as their biodiversity is important as a genetic resource. However, population genetic analysis of the chickens is rarely investigated. Based on whole-genome sequencing data of 113 chickens from 4 Tibetan chicken population including Shigatse (SH), Nyemo (NM), Dagze (DZ) and Nyingchi (LZ), as well as Lhasa white (LW) chicken population, we performed genetic diversity and differentiation, run of homozygosity (ROH), genomic inbreeding and selection signature analyses. Results Our results showed high genetic diversity across the five chicken populations. The linkage disequilibrium decay was highest in LZ, and moderate level of genetic differentiation was found between LZ and other populations (Fst ranging from 0.05 to 0.10). Furthermore, the highest ROH-based inbreeding estimate (FROH) was 0.11 in LZ, whereas it ranges from 0.04 to 0.06 in the other four chicken populations. In total, 74, 111, 62, 42 and 54 ROHs containing SNPs with concurrency ranked top 1% were identified for SH, NM, DZ, LZ and LW, respectively. BDNF, CCDC34, LGR4, LIN7C, GLS, LOC101747789, MYO1B, STAT1 and STAT4 were shared genes harbored by these ROHs in the five populations, suggesting their important roles in adaptation of the chickens. Combined with selection signature analysis, we also identified a common candidate genomic region harboring AMY2A, NTNG1 and VAV3 genes. These genes have been reported to contribute to digestion, neurite growth and high-altitude adaptation, which could be involved in selection during evolution process. Conclusions High genetic diversity was observed in Tibetan native chickens. Nyingchi population, possessing highest FROH, is genetically distant from other chicken population. Candidate genes in ROH islands could aid the genetic characterization of the five Tibetan native chicken populations. Our findings contribute to the understanding of genetic diversity and offer valuable insights for the genetic mechanism of adaptation, as well as provide veritable tools that can help in the design and implementation of breeding and conservation strategies for Tibetan native chickens.

​Identification of Single Nucleotide Polymorphism (SNP) C-2161G in the Promoter Region of Prolactin Gene and its Association with Egg Production in Tellicherry Native Chicken

Background: Prolactin is a physiological candidate gene which has significant effects on egg production in poultry. Also, it plays a major role on incubation behaviour (broodiness) in birds. The main objective of the present study was identification of single nucleotide polymorphism (SNP) C-2161G in the promoter region of prolactin gene and its association with egg production in Tellicherry native chicken population. Methods: A total of 200 blood samples were collected from the randomly selected birds of Tellicherry native chicken in All India Co-ordinated Research Project on Poultry improvement (AICRP) farm, Mannuthy, Thrissur, Kerala. Isolation of Genomic DNA was done and the isolated samples were subjected to polymerase chain reaction (PCR) followed by restriction fragment length polymorphism (RFLP) analysis to identify the SNP C-2161G of prolactin gene. Result: On the basis of RFLP patterns, birds were designated with three different genotypes namely CC, CG and GG. The allelic and genotypic frequency was calculated. The observed genotypic frequency at the SNP site C-2161G was CC (0.61), CG (0.160) and GG (0.23) and the frequency of allele was 0.69 for C and 0.31 for G. The egg production was shown to be statistically similar for the genotypes of SNP C-2161G.

Automated Chicken Counting in Surveillance Camera Environments Based on the Point Supervision Algorithm: LC-DenseFCN

The density of a chicken population has a great influence on the health and growth of the chickens. For free-range chicken producers, an appropriate population density can increase their economic benefit and be utilized for estimating the economic value of the flock. However, it is very difficult to calculate the density of chickens quickly and accurately because of the complicated environmental background and the dynamic number of chickens. Therefore, we propose an automated method for quickly and accurately counting the number of chickens on a chicken farm, rather than doing so manually. The contributions of this paper are twofold: (1) we innovatively designed a full convolutional network—DenseFCN—and counted the chickens in an image using the method of point supervision, which achieved an accuracy of 93.84% and 9.27 frames per second (FPS); (2) the point supervision method was used to detect the density of chickens. Compared with the current mainstream object detection method, the higher effectiveness of this method was proven. From the performance evaluation of the algorithm, the proposed method is practical for measuring the density statistics of chickens in a farm environment and provides a new feasible tool for the density estimation of farm poultry breeding.

The Status of Laying Traits in Indigenous Chicken of Bangladesh: A Review

This paper covers the review of diversified performance of laying traits of Bangladeshi indigenous chicken in both in situ and ex situ including few global studies. Indigenous chicken constitutes about 80% of the total chicken population in Bangladesh and their different genotypes distribute throughout the country having distinct morphological and productive characteristics. The common native genotypes (usually non-descript or deshi) provide 35-45 eggs annually with 83-96% egg fertility and 75-88% hatchability in free range while better performance is observed in extensive system. Although Naked Neck and Hilly chicken genotypes perform superior but they are not available like common deshi. The genetic improvement of laying traits is a challenging work for the village chicken in Bangladesh, however, the planned breeding strategies along with improvement management system could enhance the activity. The results presented in this review would be a guideline for selection of indigenous chicken to improve further its productivity and conservation aspect. Thus, a conceptual breeding strategy is proposed here for the improvement of laying traits in village chicken in-situ as uncontrolled mating occurs there compared to ex-situ condition.

Genetic Diversity of Six Duck Populations in India

Background: The variety of indigenous duck germplasm contribute maximum to the poultry industry in India, besides chicken population. In southern part of India, the available duck genetic resource, particularly Arni ducks (comprises of Sanyasi and Keeri ducks) of Tamil Nadu, has its own characteristics with innate potentiality of higher productivity without any input system of management. Genetic characterization and diversity of indigenous duck genetic resources has not been properly studied. In the present study, the genetic diversity of Arni ducks with other indigenous and exotic duck germplasm were analysed with microsatellite markers. Method: Genomic DNA was isolated from the blood samples of six duck populations. Molecular characterization was carried out with duck specific FAO recommended microsatellite markers. The genotyping of ducks was done based on the size of 4324 PCR amplicons of 23 microsatellite loci, which were subjected to capillary electrophoresis using automatic sequencer.Result: A total of 222 alleles in six duck populations across 23 microsatellite loci with a mean of 9.65 ± 0.95 alleles were found. Kuttanad duck variety had the highest number of alleles (139) followed by Sanyasi (136), Keeri (129), Muscovy (118), Assam (91) and White Pekin (78) ducks. The mean observed number of alleles was 6.04 ± 0.59, 5.91 ± 0.76, 5.61 ± 3.17, 5.13 ± 0.44, 3.96 ± 0.76 and 3.39 ± 0.40 in Kuttanad, Sanyasi, Keeri, Muscovy, Assam and White Pekin ducks respectively. The overall mean polymorphism information content (PIC) values among the six duck populations was 0.6269. In most of the duck populations, the mean PIC value was more than 0.5 except in Assam (0.4815) and White Pekin (0.3725) ducks. The observed heterozygosity was the highest in Keeri ducks (0.5217) and lowest in White Pekin ducks (0.2766), while, the mean expected heterozygosity was the highest in Sanyasi (0.5628) and lowest in White Pekin (0.4038) ducks. The variations in the observed and expected number of alleles, differences in PIC of various microsatellite loci might be attributed to the genetic variability of the duck populations, number and type of microsatellite primers utilised for analysis and the genetic diversity of the duck breeds under study. Higher FST value indicates the substantial degree of breed differentiation among the studied duck populations.