Literature DB >> 10194684

Genetic and environmental smoothing of lactation curves with cubic splines.

I M White1, R Thompson, S Brotherstone.   

Abstract

Most approaches to modeling lactation curves involve parametric curves with fixed or random coefficients. In either case, the resulting models require the specification on an underlying parametric curve. The fitting of splines represents a semiparametric approach to the problem. In the context of animal breeding, cubic smoothing splines are particularly convenient because they can be incorporated into a suitably constructed mixed model. The potential for the use of splines in modeling lactation curves is explored with a simple example, and the results are compared with those using a random regression model. The spline model provides greater flexibility at the cost of additional computation. Splines are shown to be capable of picking up features of the lactation curve that are missed by the random regression model.

Entities:  

Mesh:

Year:  1999        PMID: 10194684     DOI: 10.3168/jds.S0022-0302(99)75277-X

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  12 in total

1.  Direct estimation of genetic principal components: simplified analysis of complex phenotypes.

Authors:  Mark Kirkpatrick; Karin Meyer
Journal:  Genetics       Date:  2004-12       Impact factor: 4.562

Review 2.  Up hill, down dale: quantitative genetics of curvaceous traits.

Authors:  Karin Meyer; Mark Kirkpatrick
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-07-29       Impact factor: 6.237

3.  High-throughput phenotyping platforms enhance genomic selection for wheat grain yield across populations and cycles in early stage.

Authors:  Jin Sun; Jesse A Poland; Suchismita Mondal; José Crossa; Philomin Juliana; Ravi P Singh; Jessica E Rutkoski; Jean-Luc Jannink; Leonardo Crespo-Herrera; Govindan Velu; Julio Huerta-Espino; Mark E Sorrells
Journal:  Theor Appl Genet       Date:  2019-02-18       Impact factor: 5.699

4.  Less is more? Ultra-low carbohydrate diet and working dogs' performance.

Authors:  Arnon Gal; Williams Cuttance; Nick Cave; Nicolas Lopez-Villalobos; Aaron Herndon; Juila Giles; Richard Burchell
Journal:  PLoS One       Date:  2021-12-23       Impact factor: 3.240

5.  Genomic prediction of traits related to canine hip dysplasia.

Authors:  Enrique Sánchez-Molano; Ricardo Pong-Wong; Dylan N Clements; Sarah C Blott; Pamela Wiener; John A Woolliams
Journal:  Front Genet       Date:  2015-03-13       Impact factor: 4.599

6.  Quantitative genetic analysis of the bTB diagnostic single intradermal comparative cervical test (SICCT).

Authors:  Smaragda Tsairidou; Susan Brotherstone; Mike Coffey; Stephen C Bishop; John A Woolliams
Journal:  Genet Sel Evol       Date:  2016-11-24       Impact factor: 4.297

7.  A strategy to estimate the rate of recruitment of inflammatory cells during bovine intramammary infection under field management.

Authors:  J Detilleux
Journal:  BMC Vet Res       Date:  2017-06-08       Impact factor: 2.741

8.  Balancing selection at a premature stop mutation in the myostatin gene underlies a recessive leg weakness syndrome in pigs.

Authors:  Oswald Matika; Diego Robledo; Ricardo Pong-Wong; Stephen C Bishop; Valentina Riggio; Heather Finlayson; Natalie R Lowe; Annabelle E Hoste; Grant A Walling; Jorge Del-Pozo; Alan L Archibald; John A Woolliams; Ross D Houston
Journal:  PLoS Genet       Date:  2019-01-30       Impact factor: 5.917

9.  Predicting Longitudinal Traits Derived from High-Throughput Phenomics in Contrasting Environments Using Genomic Legendre Polynomials and B-Splines.

Authors:  Mehdi Momen; Malachy T Campbell; Harkamal Walia; Gota Morota
Journal:  G3 (Bethesda)       Date:  2019-10-07       Impact factor: 3.154

10.  Estimated breeding values and association mapping for persistency and total milk yield using natural cubic smoothing splines.

Authors:  Klara L Verbyla; Arunas P Verbyla
Journal:  Genet Sel Evol       Date:  2009-11-05       Impact factor: 4.297

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.