ArticleJournal of animal science2021
Genetic and phenotypic parameters for body weights, harvest length, and growth curve parameters in American mink.
Article in Journal of animal science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Identification of consensus homozygous regions and their associations with growth and feed efficiency traits in American mink.BMC genomic data · 2024Article
- Genome-wide association studies for economically important traits in mink using copy number variation.Scientific reports · 2024Article
- Genetic and phenotypic correlations between Aleutian disease tests with body weight, growth, and feed efficiency traits in mink.Journal of animal science · 2022Article
- Applying Machine Learning Algorithms for the Classification of Mink Infected with Aleutian Disease Using Different Data Sources.Animals : an open access journal from MDPI · 2022Article
- Genetic and phenotypic parameters for feed efficiency and component traits in American mink.Journal of animal science · 2022Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding the genetics underlying growth curve is important for selection of animals with better growth potential, but little is known about the genetics of growth curve parameters in mink. This study estimated the genetic parameters for body weights (BWs), harvest length (HL), and growth parameters derived from the Richards model. For this purpose, individual BW of 1,088 mink measured seven times in 3-wk intervals (weeks 13 to 31 of life) were used for growth curve modeling using the Richards model. The BW traits included BW at week 13 (BW13), 16 (BW16), 19 (BW19), 22 (BW22), 25 (BW25), 28 (BW28), and 31 (BW31). Univariate analyses indicated that sex and birth-year had significant effects (P < 0.05) on BW, HL, asymptotic weight (α), growth rate at mature (k), shape parameter (m), weight at the inflection point (WIP), and age at the inflection point (AIP). In contrast, the color type had only significant effect (P < 0.05) on BW31 and HL. Estimated heritabilities (±SE) were ranged from 0.36 ± 0.13 (BW13) to 0.46 ± 0.10 (BW22) for BW and were 0.51 ± 0.09, 0.29 ± 0.09, 0.30 ± 0.09, 0.33 ± 0.1, 0.44 ± 0.10, and 0.47 ± 0.10 for HL, α, k, m, WIP, and AIP, respectively. The parameter α had non-significant (P > 0.05) genetic correlations (±SE) with k (-0.21 ± 0.23) and m (-0.10 ± 0.22), suggesting that changing shape parameters (k and m) will not influence asymptotic weight (α). Strong significant (P < 0.05) phenotypic (from 0.46 ± 0.03 to 0.60 ± 0.03) and genetic (0.70±0.13 to 0.88±0.09) correlations were observed between HL and different BW measures. The α, AIP, and WIP parameters had significant (P < 0.05) genetic correlations with HL indicated that selection for higher α, AIP, and WIP values would increase HL. Parameters k and m had nonsignificant (P > 0.05) genetic correlations with HL, indicating the change of the curve shape could not influence HL. Overall, the results suggest that growth curve parameters are heritable and can respond to genetic or genomic selection for optimizing the performance in mink.
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