Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Selection index for economically important traits in Boer crossbred goats using principal component analysis

View through CrossRef
The optimal strategy for genetic selection is a selection index based on economic weight; however, in developing countries where economic weight estimation is not always evident and easy for breeders due to a lack of economic data. Thus, this study aimed to construct selection indices for crossbred goats, which could be used as an alternative to economic selection index and to explore the relationship among economically important traits. The data set contained records of birth weight (BW), weaning weight (WW), pre-weaning weight gain (ADG), pre-weaning Kleiber ratio (KR), pre-weaning relative growth rate (RGR), pre-weaning growth efficiency (GE), and pre-weaning survival (RR) of crossbred goats. Genetic parameter estimates were obtained using a single-trait animal model. General linear model, principal component analysis, and cluster procedures of SAS were also used for data analysis. Kid survival was negatively correlated with all investigated traits except BW. Traits such as KR, GE, RGR, WW, and ADG were highly and positively correlated. According to the Kaiser method, two principal components were selected from seven investigated traits. The first principal component (PC1) explained 57.71%, and the second principal component (PC2) explained 14.57% of the estimated breeding value variance, totaling 72.28% of the total genetic additive variance. PC1 explained most of the direct additive genetic variation and correlated with the estimated breeding value of WW, ADG, KR, GE, and RGR, whereas PC2 was correlated with the estimated breeding value of BW and RR. Besides, the cluster analysis categorized seven traits into two major groups. The first group includes BW and RR, whereas traits such as WW, ADG, KR, GE, and RGR were included in the second group. Therefore, two based selection indices, or principal component scores (PCS) were derived. Animals with higher PCS1 could be used to improve WW, ADG, KR, GE, and RGR, whereas animals with higher PCS2 scores could be used to improve BW and pre-weaning survival of crossbred kids. The selection of the most appropriate and specific selection index regarding the two groups of traits is determined by the breeding objectives defined for specific genetic improvement program. These selection indices could be used as an alternative approach when economic weights for traits of interests are not available to construct the economic selection index. However, further works should be done on refining the selection indices and validating them in independent datasets.
Title: Selection index for economically important traits in Boer crossbred goats using principal component analysis
Description:
The optimal strategy for genetic selection is a selection index based on economic weight; however, in developing countries where economic weight estimation is not always evident and easy for breeders due to a lack of economic data.
Thus, this study aimed to construct selection indices for crossbred goats, which could be used as an alternative to economic selection index and to explore the relationship among economically important traits.
The data set contained records of birth weight (BW), weaning weight (WW), pre-weaning weight gain (ADG), pre-weaning Kleiber ratio (KR), pre-weaning relative growth rate (RGR), pre-weaning growth efficiency (GE), and pre-weaning survival (RR) of crossbred goats.
Genetic parameter estimates were obtained using a single-trait animal model.
General linear model, principal component analysis, and cluster procedures of SAS were also used for data analysis.
Kid survival was negatively correlated with all investigated traits except BW.
Traits such as KR, GE, RGR, WW, and ADG were highly and positively correlated.
According to the Kaiser method, two principal components were selected from seven investigated traits.
The first principal component (PC1) explained 57.
71%, and the second principal component (PC2) explained 14.
57% of the estimated breeding value variance, totaling 72.
28% of the total genetic additive variance.
PC1 explained most of the direct additive genetic variation and correlated with the estimated breeding value of WW, ADG, KR, GE, and RGR, whereas PC2 was correlated with the estimated breeding value of BW and RR.
Besides, the cluster analysis categorized seven traits into two major groups.
The first group includes BW and RR, whereas traits such as WW, ADG, KR, GE, and RGR were included in the second group.
Therefore, two based selection indices, or principal component scores (PCS) were derived.
Animals with higher PCS1 could be used to improve WW, ADG, KR, GE, and RGR, whereas animals with higher PCS2 scores could be used to improve BW and pre-weaning survival of crossbred kids.
The selection of the most appropriate and specific selection index regarding the two groups of traits is determined by the breeding objectives defined for specific genetic improvement program.
These selection indices could be used as an alternative approach when economic weights for traits of interests are not available to construct the economic selection index.
However, further works should be done on refining the selection indices and validating them in independent datasets.

Related Results

Milk production, composition, and udder morphometric traits across various lactation stages of Boer goats and their crosses in Ethiopia
Milk production, composition, and udder morphometric traits across various lactation stages of Boer goats and their crosses in Ethiopia
This study was conducted at the Sheep and Goat Crossbreeding and Multiplication Center of Hawassa University, Ethiopia, to evaluate milk production, composition, and udder morpholo...
Risk factors for calcium carbonate urolithiasis in goats
Risk factors for calcium carbonate urolithiasis in goats
Abstract Objective—To identify demographic or signalment factors associated with calcium carbonate urolith formation in goats. Design—Retrospective case series and case-control stu...
Deep Learning for genomic prediction accounting for heterosis in crossbreeding systems
Deep Learning for genomic prediction accounting for heterosis in crossbreeding systems
Abstract Background Crossbreeding is used in animal breeding to combine desirable traits from different breeds and to exploit hybrid vigo...
Phenotypic characterization of Nguni goats in four agro-ecological zones of Limpopo province, South Africa
Phenotypic characterization of Nguni goats in four agro-ecological zones of Limpopo province, South Africa
The study was conducted to phenotypically characterize Nguni goats from four agro-ecological zones of Limpopo province, South Africa. A total of 426 goats were sampled from four ag...
Poems
Poems
poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poem...
Gastrointestinal Segments Influenced Fermentation End-Products, Microbiota and Microbial Abundances in Goats
Gastrointestinal Segments Influenced Fermentation End-Products, Microbiota and Microbial Abundances in Goats
Abstract Purpose: Carbohydrate diets altered fermentation end-products and microbial community in the gastrointestinal tracts (GIT) of goats. Gastrointestinal contents u...
Genetic study of reproductive, dairy and growth traits in Guzerá cattle
Genetic study of reproductive, dairy and growth traits in Guzerá cattle
The Guzerá breed is an important Brazilian genetic resource and has been widely used as a pure breed and in crossbreeding strategies to produce animals adapted to tropical climatic...

Back to Top