Genetic Variability, Correlation among Agronomic Traits, and Genetic Progress in a Sugarcane Diversity Panel

Round 1

Reviewer 1 Report

The manuscript titled “Genetic variability, correlation among agronomic traits and genetic progress in a sugarcane diversity panel” is an interesting work assessing genotype variability and breeding progress in sugarcane. It is very well written, but still requires some work, especially in describing and discussing the results of the statistical analysis. Detailed remarks below:

 

Lines 135-138.The presented model is nothing else a mixed model Repeated Measures show eg.

Piepho, H.P., Büchse, A. and Richter, C. (2004), A Mixed Modelling Approach for Randomized Experiments with Repeated Measures. Journal of Agronomy and Crop Science, 190: 230-247. https://doi.org/10.1111/j.1439-037X.2004.00097.x

The terminology used by the authors may be confusing to many readers.

Line 169-175. It is surprising that the authors decided to divide the research into breeding progress by decades. The use of regression analysis (b1 and b0 estimation) only on 6 points is unreliable. Authors could base these studies directly on year accessions originated.

Figure 2. It is very illegible, it can only show points instead of object names and show their names only for important and interesting objects.

Table 2. How is it possible that R2 was negative for FIB.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Using the Brazilian Panel of Sugarcane Genotypes (BPSG) diversity panel, Baretto et al. studied genetic variability, correlations among 10 agronomic traits and the genetic gains in sugarcane breeding over six decades. The results their present provide valuable insight into the temporal adjusted means and genetic parameters, and how the traits are correlated, which are valuable to the advancing of breeding programs for sugarcane. For the most part, the manuscript was well written, however, it could benefit from minor revisions. 

## Quibbles ##

I took issue with the modelling of proportional/percentage data using linear mixed models. This is not an appropriate approach for continuous response variables bound on the interval (0, 1). In such cases, a beta mixed regression should be applied. I recommend the authors give beta (mixed) regression where applicable. Table 2 - A beta regression must be applied for traits measured in percentages. 

Line 225-227: Please color code these in Figure 1 using the traffic light system. While you are at it, all make the font size of the larger to make the figure more legible. This last point is applicable to all figures. 

Line 488: Not true. The raw data for the 10 traits is not presented in the data repository, just the two supplementary table. Please also upload a complete Excel spreadsheet with the raw data.

 

  

 

Author Response

Please see the attachment

Author Response File: Author Response.docx