Results 1 to 10 of about 8,065,022 (158)

Genomic Selection in Cereal Breeding

open access: yesAgronomy, 2019
Genomic Selection (GS) is a method in plant breeding to predict the genetic value of untested lines based on genome-wide marker data. The method has been widely explored with simulated data and also in real plant breeding programs.
Charlotte D. Robertsen   +2 more
doaj   +4 more sources

Genome-association analysis of Korean Holstein milk traits using genomic estimated breeding value [PDF]

open access: yesAsian-Australasian Journal of Animal Sciences, 2017
Objective Holsteins are known as the world’s highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data.
Donghyun Shin   +4 more
doaj   +2 more sources

Genomic Selection for Milk Production Traits in Xinjiang Brown Cattle

open access: yesAnimals, 2022
One-step genomic selection is a method for improving the reliability of the breeding value estimation. This study aimed to compare the reliability of pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased ...
Menghua Zhang   +8 more
doaj   +1 more source

Statistical considerations for genomic selection [PDF]

open access: yesFrontiers of Agricultural Science and Engineering, 2017
Genomic selection is becoming increasingly important in animal and plant breeding, and is attracting greater attention for human disease risk prediction.
Huimin KANG, Lei ZHOU, Jianfeng LIU
doaj   +1 more source

Validation of selection accuracy for the total number of piglets born in Landrace pigs using genomic selection [PDF]

open access: yesAsian-Australasian Journal of Animal Sciences, 2017
Objective This study was to determine the relationship between estimated breeding value and phenotype information after farrowing when juvenile selection was made in candidate pigs without phenotype information.
Jae-Don Oh, Chong-Sam Na, Kyung-Do Park
doaj   +1 more source

Selective genotyping to implement genomic selection in beef cattle breeding

open access: yesFrontiers in Genetics, 2023
Genomic selection (GS) plays an essential role in livestock genetic improvement programs. In dairy cattle, the method is already a recognized tool to estimate the breeding values of young animals and reduce generation intervals.
Maryam Esrafili Taze Kand Mohammaddiyeh   +4 more
doaj   +1 more source

Application of Genomic Data for Reliability Improvement of Pig Breeding Value Estimates

open access: yesAnimals, 2021
Replacement pigs’ genomic prediction for reproduction (total number and born alive piglets in the first parity), meat, fatness and growth traits (muscle depth, days to 100 kg and backfat thickness over 6–7 rib) was tested using single-step genomic best ...
Ekaterina Melnikova   +10 more
doaj   +1 more source

The characteristics of bovine satellite cells with highly scored genomic estimated breeding value

open access: yesJournal of Animal Reproduction and Biotechnology, 2023
Background: The grading of Hanwoo (Korean native cattle) is based on four economic traits, and efforts have been continuously made to improve the genetic traits associated with these traits.
Jae Ho Han   +3 more
doaj   +1 more source

Genomic Selection in Sugarcane: Current Status and Future Prospects

open access: yesFrontiers in Plant Science, 2021
Sugarcane is a C4 and agro-industry-based crop with a high potential for biomass production. It serves as raw material for the production of sugar, ethanol, and electricity.
Channappa Mahadevaiah   +9 more
doaj   +1 more source

Genetic architecture of fresh-market tomato yield

open access: yesBMC Plant Biology, 2023
Background The fresh-market tomato (Solanum lycopersicum) is bred for direct consumption and is selected for a high yield of large fruits. To understand the genetic variations (distinct types of DNA sequence polymorphism) that influence the yield, we ...
Prashant Bhandari   +2 more
doaj   +1 more source

Home - About - Disclaimer - Privacy