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Salinity stress tolerance prediction for biomass-related traits in maize (Zea mays L.) using genome-wide markers

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Title Salinity stress tolerance prediction for biomass-related traits in maize (Zea mays L.) using genome-wide markers
Not Available
 
Creator vishal singh
margaret krause
Devinder Sandhu
Rajandeep Sekhon
Amita Kaundal
 
Subject genomic prediction
salinity stress tolerance
maize breeding
 
Description Not Available
Maize (Zea mays L.) is the third most important cereal crop after rice (Oryza sativa)and wheat (Triticum aestivum). Salinity stress significantly affects vegetative biomassand grain yield and, therefore, reduces the food and silage productivity of maize.Selecting salt-tolerant genotypes is a cumbersome and time-consuming process thatrequires meticulous phenotyping. To predict salt tolerance in maize, we estimatedbreeding values for four biomass-related traits, including shoot length, shoot weight,root length, and root weight under salt-stressed and controlled conditions. A five-foldcross-validation method was used to select the best model among genomic best linearunbiased prediction (GBLUP), ridge-regression BLUP (rrBLUP), extended GBLUP,Bayesian Lasso, Bayesian ridge regression, BayesA, BayesB, and BayesC. Exam-ination of the effect of different marker densities on prediction accuracy revealedthat a set of low-density single nucleotide polymorphisms obtained through filteringbased on a combination of analysis of variance and linkage disequilibrium providedthe best prediction accuracy for all the traits. The average prediction accuracy incross-validations ranged from 0.46 to 0.77 across the four derived traits. The GBLUP,rrBLUP, and all Bayesian models except BayesB demonstrated comparable levels ofprediction accuracy that were superior to the other modeling approaches. These find-ings provide a roadmap for the deployment and optimization of genomic selection inbreeding for salt tolerance in maize.
Not Available
 
Date 2024-03-18T18:38:36Z
2024-03-18T18:38:36Z
2023-09-04
 
Type Research Paper
 
Identifier Not Available
https://doi.org/10.1002/tpg2.20385
http://krishi.icar.gov.in/jspui/handle/123456789/81660
 
Language English
 
Relation Not Available;
 
Publisher Wiley Periodicals LLC