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Article
Peer-Review Record

Evaluation of Alfalfa and Grass Species in Binary and Complex Mixtures on Performance under Soil Salinity Conditions

Agronomy 2022, 12(7), 1672; https://doi.org/10.3390/agronomy12071672
by Enkhjargal Darambazar 1, Kathy Larson 2, Jeff Schoenau 3, Gravel Wang 3, Bill Biligetu 4, Daalkhaijav Damiran 1 and Herbert A. Lardner 1,*
Reviewer 1: Anonymous
Reviewer 2:
Agronomy 2022, 12(7), 1672; https://doi.org/10.3390/agronomy12071672
Submission received: 7 June 2022 / Revised: 2 July 2022 / Accepted: 11 July 2022 / Published: 13 July 2022
(This article belongs to the Section Grassland and Pasture Science)

Round 1

Reviewer 1 Report

Research article: „Evaluation of Alfalfa and Grass Species in Binary and Complex Mixtures on Performance Under Soil Salinity Conditions" concerns the issue of optimal management of saline agricultural soils. As the simulations show, the problem of salinization will become more burdensome, therefore research aimed at protecting the environment against it as well as using salt-affected soil for cultivation is becoming more needed.

I have no comments on the substantive issues. The paper is expertly written and demonstrates the deep knowledge of the Authors in this field. I found only single editorial errors, such as the use of single quotation marks in the cultivars’ names, e.g. in lines 65, 71, 329, 330 (the Authors do not use them in most of the manuscript). It was good to standardize the nomenclature. Section 3.6, unfortunately, starts at the bottom of the page.

The statistical analysis is not entirely clear to me. It looks very advanced, but for every reader (also less familiar with statistics) it should be clear which results are statistically significant and which are not.

What I would like to change is the way in which some results are presented. While the tables are correct and careful, the large number of them (9) make reading the manuscript tedious towards the end. In my opinion, adding a chart, e.g. prepared as a result of principal component analysis (PCA score plot) would clearly summarize the obtained results.

June 20, 2022

 

Author Response

RESPONSE TO REVIEWERS’ QUESTIONS AND COMMENTS

Agronomy-1784703

Darambazar et al. “Evaluation of Alfalfa and Grass Species in Binary and Complex Mixtures on Performance Under Soil Salinity Conditions”

 

Reviewer 1

I found only single editorial errors, such as the use of single quotation marks in the cultivars’ names, e.g. in lines 65, 71, 329, 330 (the Authors do not use them in most of the manuscript). It was good to standardize the nomenclature.

Comment accepted. The single quotation marks in the cultivar name are now consistently used throughout the manuscript.

Section 3.6, unfortunately, starts at the bottom of the page.

Comment accepted. It is corrected to Section 3.5 and starts now higher, in line 412.

The statistical analysis is not entirely clear to me. It looks very advanced, but for every reader (also less familiar with statistics) it should be clear which results are statistically significant and which are not.

Comment accepted. This section is more revised to make it clear and easily readable, including to read “Treatment means were determined using Tukey’s multiple range test and were considered significant when p0.05, and trending towards significance when 0.05 p 0.10.”

What I would like to change is the way in which some results are presented. While the tables are correct and careful, the large number of them (9) make reading the manuscript tedious towards the end. In my opinion, adding a chart, e.g. prepared as a result of principal component analysis (PCA score plot) would clearly summarize the obtained results.

Comment accepted. One table is now presented as a chart. We also agree with relatively large number of data reported in this manuscript. We also know that there is limited information on yield and nutrient composition, nutrient uptake parameters ‘Halo’ alfalfa and its binary mixtures. Therefore, numbers of these parameters reported in this manuscript can be used as reference for animal nutrition/crop production system modeling. In addition, to our knowledge, there is limited published information on this subject. Therefore, other tables in this version of manuscript would add more detailed information. We carefully considered reviewers opinion about principal component analysis but due to size limits of the manuscript, we did not include PCA in this version of manuscript.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear Authors,

Your manuscript addressed an essential aspect of forage agriculture and will be beneficial in semi-arid and arid environments where salinity is a common issue. 

Some comments for consideration: (1) The experimental design is not stated in the materials and method section. RCBD?

(2) I believe each nutritive value parameter method can be better described under the materials and method section. Rather than 'according to AOAC 2012'.  

(3) Lines 197 - 198, and 212, there is a repetition of the 'Proc Mixed Model' need to delete one. 

 

Author Response

RESPONSE TO REVIEWERS’ QUESTIONS AND COMMENTS

Agronomy-1784703

Darambazar et al. “Evaluation of Alfalfa and Grass Species in Binary and Complex Mixtures on Performance Under Soil Salinity Conditions”

 

 

Reviewer 2

Some comments for consideration: (1) The experimental design is not stated in the materials and method section. RCBD?

Comment accepted. Revised to read “Replicated treatments (n = 4) were randomly allocated to a total of 16 plots (Figure 1). Each plot was 6.2 × 1.2 m in size with 7.4 m2 plot area. There was a 0.5-m gap between treatment plots and a 2-m gap between replicates (blocks). The experimental design was a Randomized Complete Block Design.

(2) I believe each nutritive value parameter method can be better described under the materials and method section. Rather than 'according to AOAC 2012'.

Comment accepted. Each nutritive value analysis method is now mentioned and briefly described in the Materials and Methods section.

(3) Lines 197 - 198, and 212, there is a repetition of the 'Proc Mixed Model' need to delete one.

Deleted the repetitions of the 'Proc Mixed Model' in the lines.

Author Response File: Author Response.pdf

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