Review Reports

Round 1

Reviewer 1 Report

It was a real pleasure for me to go through this manuscript. It reads very well, indicative of the serious that authors put in its preparation. More importantly, the experimental design and the statistical methods are adequate and clearly presented.

Stacking ensemble methods are gaining ground in predictive analysis techniques such as machine learning to improve the overall accuracy of the predictors. Here, authors successfully implemented a stacking method for genomic prediction using a Bayesian approach. As expected, the stacking method (Bayesian multi-output regressor stacking) outperformed the single trait single environment models, since a stacking method by essence takes advantage of the correct predictions made by each single predictor. 

Author Response

Dear reviewer,

 

Thank you for your reviews and comments. We appreciate the time taken and effort made to improve our manuscript. We hope you all the best as well.

 

Sincerely,

Sirjan sapkota

Reviewer 2 Report

See attached file.

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,

 

Thank you for your comments and suggestions. Please see the response in the file attached.

 

Sincerely,

Sirjan

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The authors have addressed all my previous concerns and should be accepted as is.