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Identification of sex in broiler chickens allows researchers to reduce the level of variation in an experiment caused by the sex effect. Broiler breeds commonly used in research are no longer feather sexable because of the change in their genetics. Other alternate sexing methods are costly and difficult to apply on a large scale. Therefore, a sexing method is required that is both cost effective and highly sensitive as well as having the ability to offer high throughput genotyping. In this study, high-resolution melting ( HRM ) analysis was used to detect DNA variations present in the gene chromodomain helicase DNA binding 1 protein ( CHD1 ) on the Z and W chromosomes ( CHD1Z and CHD1W , respectively) of chickens. In addition, a simplified DNA extraction protocol, which made use of the basal part of chicken feathers, was developed to speed up the sexing procedure. Three pairs of primers, that is, CHD1UNEHRM1F/R, CHD1UNEHRM2F/R, and CHD1UNEHRM3F/R, flanking the polymorphic regions between CHD1Z and CHD1W were used to differentiate male and female chickens via distinct melting curves, typical of homozygous or heterozygous genotypes. The assay was validated by the HRM-sexing of 1,318 broiler chicks and verified by examining the sex of the birds after dissection. This method allows for the sexing of birds within a couple of days, which makes it applicable for use on a large scale such as in nutritional experiments.

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The availability of sexed day-old broiler chicks is becoming an issue as feather sexing is no longer possible. This has great implications for broiler researchers as the use of randomly distributed mixed-sex birds may result in a greater between-pen variation and thus less statistical power than the use of single-sex birds. The objective of this study was to evaluate the effect of including sex proportion as a covariate in an analysis of covariance (ANCOVA) on the statistical power compared to analysis of variance (ANOVA) where sex was not considered. The statistical parameters examined include mean square error (MSE), the F-statistic, model fit, model significance and observed power. A total of 4 separate experiments that used mixed-sex broilers with unequal numbers of male and female birds per pen were conducted during which performance of the birds was measured. The male % in each pen was recorded during each experiment and corrected for mortality. The performance results were analysed by ANOVA and the statistical parameters were then compared to ANCOVA where sex proportion was included as a covariate. The results showed that a set of assumptions first needed to be met to run ANCOVA. In addition, if the ANOVA results show a high level of model significance and power, then ANCOVA may not be necessary. In other circumstances where the assumptions are met and model significance and observed power are low, the inclusion of sex proportion as a covariate in the analysis will help to reduce MSE, increase the F-statistic value and improve the model significance, model fit and observed power. Therefore, it is suggested that sex proportion should be considered as a covariate in ANCOVA to improve statistical power in nutritional experiments when male and female broilers are unequally and randomly distributed in pens.