Genome-Enabled Prediction Models for Yield Related Traits in Chickpea
نویسندگان
چکیده
منابع مشابه
Genome-Enabled Prediction Models for Yield Related Traits in Chickpea
Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped extensively for yield and yield related traits at two different locations (Delhi and Patancheru,...
متن کاملThreshold Models for Genome-Enabled Prediction of Ordinal Categorical Traits in Plant Breeding
Categorical scores for disease susceptibility or resistance often are recorded in plant breeding. The aim of this study was to introduce genomic models for analyzing ordinal characters and to assess the predictive ability of genomic predictions for ordered categorical phenotypes using a threshold model counterpart of the Genomic Best Linear Unbiased Predictor (i.e., TGBLUP). The threshold model...
متن کاملDistribution in genome of Quantitative trait loci (QTL) for yield and yield-related traits in common wheat (Triticum aestivum L.)
A major objective of quantitative trait loci (QTL) studies is to find genes/markers that can be used in breeding programs via marker assisted selection (MAS). From an extensive review, we surveyed the distribution of QTL for yield and yield-related traits on wheat genome. In order to identify the important regions involving in these traits, QTL meta-analysis was performed. As a result, 55 MQTL ...
متن کاملComparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-lineari...
متن کاملGenome-enabled prediction for tick resistance in Hereford and Braford beef cattle via reaction norm models.
Very few studies have been conducted to infer genotype × environment interaction (G×E) based in genomic prediction models using SNP markers. Therefore, our main objective was to compare a conventional genomic-based single-step model (HBLUP) with its reaction norm model extension (genomic 1-step linear reaction norm model [HLRNM]) to provide EBV for tick resistance as well as to compare predicti...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Plant Science
سال: 2016
ISSN: 1664-462X
DOI: 10.3389/fpls.2016.01666