Breed and feed affect amino acid contents of egg yolk and eggshell color in chickens

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Abstract

Genetic and environmental factors regulate hen egg traits. To demonstrate the possibility of producing designer eggs through genetic and environmental factors, we investigated the effects of breed and feed on egg traits using 2 chicken breeds, Rhode Island Red (RIR) and Australorp (AUS), and 2 feeds, mixed feed and fermented feed. A total of 40 eggs were collected at 33 wk of age (0 mo under mixed feed) and 1, 1.5, and 2 mo after switching to fermented feed. Two-way ANOVA mixed design was used to evaluate 10 egg traits: weight, length of the long axis, length of the short axis, eggshell weight, yolk weight, albumen weight, eggshell thickness, eggshell lightness, redness, and yellowness, and 19 yolk amino acids. The results revealed significant breed effects on eggshell redness and yellowness, with higher values of these traits in RIR eggs compared with AUS eggs. There was a significant effect of feed on eggshell lightness, with a lighter color observed under fermented feed compared with mixed feed. Significant effects of breed and breed × feed were found for yolk cysteine content. Eggs from AUS had a higher yolk cysteine content than those from RIR. The cysteine content in AUS eggs increased gradually after starting fermented feed, although RIR remained relatively constant over time. These findings suggest that it is possible to produce designer eggs with enriched components, including yolk amino acids, by adjusting both genetic and environmental factors. This represents a first step in understanding the mechanisms underlying the production of value-added eggs in chickens.

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Generalized eta and omega squared statistics: measures of effect size for some common research designs.

Stephen Olejnik, James Algina (2003)

The editorial policies of several prominent educational and psychological journals require that researchers report some measure of effect size along with tests for statistical significance. In analysis of variance contexts, this requirement might be met by using eta squared or omega squared statistics. Current procedures for computing these measures of effect often do not consider the effect that design features of the study have on the size of these statistics. Because research-design features can have a large effect on the estimated proportion of explained variance, the use of partial eta or omega squared can be misleading. The present article provides formulas for computing generalized eta and omega squared statistics, which provide estimates of effect size that are comparable across a variety of research designs.

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Microbial diversity and community composition of caecal microbiota in commercial and indigenous Indian chickens determined using 16s rDNA amplicon sequencing

Ramesh J Pandit, Ankit T Hinsu, Namrata V. Patel … (2018)

Background The caecal microbiota plays a key role in chicken health and performance, influencing digestion and absorption of nutrients, and contributing to defence against colonisation by invading pathogens. Measures of productivity and resistance to pathogen colonisation are directly influenced by chicken genotype, but host driven variation in microbiome structure is also likely to exert a considerable indirect influence. Methods Here, we define the caecal microbiome of indigenous Indian Aseel and Kadaknath chicken breeds and compare them with the global commercial broiler Cobb400 and Ross 308 lines using 16S rDNA V3-V4 hypervariable amplicon sequencing. Results Each caecal microbiome was dominated by the genera Bacteroides, unclassified bacteria, unclassified Clostridiales, Clostridium, Alistipes, Faecalibacterium, Eubacterium and Blautia. Geographic location (a measure recognised to include variation in environmental and climatic factors, but also likely to feature varied management practices) and chicken line/breed were both found to exert significant impacts (p < 0.05) on caecal microbiome composition. Linear discriminant analysis effect size (LEfSe) revealed 42 breed-specific biomarkers in the chicken lines reared under controlled conditions at two different locations. Conclusion Chicken breed-specific variation in bacterial occurrence, correlation between genera and clustering of operational taxonomic units indicate scope for quantitative genetic analysis and the possibility of selective breeding of chickens for defined enteric microbiota. Electronic supplementary material The online version of this article (10.1186/s40168-018-0501-9) contains supplementary material, which is available to authorized users.