Corn Cultivation and Its Relationship with Soil Quality: A Focus on Soil Quality Index Methodologies

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

 

1）Abstract, please add more data for comparsion, for example: "Among these, 𝑆𝑄𝐼𝑎 was the most sensitive 22 and efficient in assessing soil quality, showing values from very low to low." 
2）Introduction, please give more contents about 𝑆𝑄𝐼 in the glable world, meanwhile, please add the advantages and disadvantages of different specific tools to SQI.

3) 2.1 Selection of agricultural soils, please add soil name by FAO ot others. Then, please change Table 1. Agricultural soils sampled to figure, because figure was better than table.
4) 4. Discussion, according to the results of this study, how should soil mangement be applied to promote corn growth improvement? Please further study or provide suggestions.

5) 4. Conclusions, now it was longer, please shorten.

Author Response

Please see the pdf file.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

There are some problems in the format and content of this article, and specific comments are as follows:

1. In Figure 1, when presenting the results of analysing each soil indicator, some data points and error bars are not well differentiated, which affects the accurate of the data; the unit labelling of some indicators on the axes is not clear, and the identification of different soil samples in the legend is not clear enough.
2. The Spearman correlation matrix and Mantel test results presented in Figure 2 lack a clear description of the degree of correlation represented by the colours in the matrix, and are only marked with asterisks for significant values, which makes it difficult to intuitively judge the strength of the correlation between the indicators.
3. Some of the numbers in the correlation matrix in Figure 3b are too lightly coloured.
4. After the presentation of Figure 4, the reasons for the differences in the distribution of soil quality indices in the figure were not sufficiently analysed. The authors only mentioned the ability of the indices to group soils, without delving deeper into the reasons why the quality indices of the different soil samples showed such differences, and the implications of these differences for maize cultivation.
5. After line 96, please add a statement about the randomness or representativeness of the sample selection, for example, ‘Sample selection was based on a random sampling method that ensured that the samples selected were representative of the maize-growing soils in the area.’
6. The reference labelling in the text is simply a serial number after the method and does not follow a uniform format specification for citing literature, e.g. line 114.
7. When citing the table, the content of the icon is not briefly summarised, so please link the table to the text and briefly summarise it.
8. In lines 198-235, when discussing the physical and chemical properties of the soil, please analyse and explain the outliers or extreme values.
9. Some of the references cited are in incorrectly format, e.g., line 239. According to Chen et al.[41], soil microorganisms may facilitate the decomposition of urea-based fertilizers...
10. It is recommended that the interactions between indicators be analysed in a comprehensive manner, e.g. to show how soil texture affects the decomposition and accumulation of OM, which in turn affects the TOC, TN and C/N indicators, and how changes in these indicators feedback to affect the cation exchange capacity of the soil.

Author Response

Please see the pdf file

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript presented is relevant because it uses a large sample of soil from different locations in Mexico with corn crops. However, the statistical analysis is not clearly explained in the text.

The data were analyzed using non-parametric statistics. However, it would be necessary to apply a Box-Cox transformation to the data to perform the analysis of variance. The analysis used in the results led to the formation of many overlapping groups, making it difficult to evaluate differences between soils. Moreover, you need to specify the assumptions of principal component analysis (such as continuous variables, linear relationships between all variables, sampling adequacy, suitability for data reduction, and absence of significant outliers).

The results and discussion sections need improvement. For example, the authors discuss a result that contradicts what is observed in the graphs. We confirmed this mistake when they stated that the pH variable separated the soils into two groups, but the figure shows no significant difference between them. The principal component analysis resulted in three components that explain 71.3% of the variation. However, only two principal components are shown in Figure 3a. Figure 3b provides information on all three components. The presentation and discussion of Figure 3 (a and b) are confusing and need improvement. In summary, the manuscript requires general improvement. We recommend re-writing statistical analysis, results and discussion, and conclusions.

Comments and Suggestions 

Line 33 – Reference: Use the data from the FAO and not cite information in another article.

Line 39 – Reference: Use the data from the FAO and not cite information in another article.

Line 132 - Enter the meaning of the acronym SAR (Sodium Adsorption Ratio). You must include this information

Line 138 - Why were the data not transformed to validate the assumptions of the variance analysis?

Line 144 - Were the assumptions of principal component analysis (continuous variables, linear relationship between all variables, sampling adequacy, suitable for data reduction, no significant outliers) observed? You must write this information in a few words.

Line 153 - You need to make a table with SQI equations. This table allows us to see all the information at the same time. Thus, the text remains better to read.

Line 199 - How do you explain the resulting variation in Table 2? Look at the coefficient of variation (%): pH=3.72; EC=61.54; SND= 30.28; CLY=11.19; SLT=17.64; WHC= 15.25; TOC= 26.79; OM= 25.68; TN= 53.64; CN= 127.92; P= 56.25; K =21.94; Ca = 20.36; Mg = 14.53; Fe = 54.69; Zn = 75.00; Mn = 48.00; Cu = 162.50; B = 63.16; S = 50.00; CEC = 15.24; ESP = 50.56; and SAR = 54.55.

Line 216 - The results in Table 2 indicate the presence of outliers. This way you need to do outliers analysis to look for disturbances in the normal distribution of the data. If you did outliers analysis effect, please indicate in the text.

Line 220 - The analysis classified the soils into at least two distinct groups. However, most soils exhibited similar behavior across both Group 1 and Group 2 regarding the variables SND, SLT, TOC, TN, CEC, CLY, WHC, OM, and ESP. Consequently, there is an overlap between the groups denoted by "ab." It is important to clarify which soils were more distinctly separated, such as with the SND variable, where Co1 displayed higher values compared to Ac3 and IR3, which did not show significant differences between each other.

Lines 236 and 237 - The information in figure 1a shows no difference between the soils. Therefore, this statement is not correct.

Lines 247 to 253 - The statements in this paragraph contradict the result obtained. The correct soils were not presented in the text. The soils with the highest WHC were Sa2 and SA6, not Ac1. It can be seen that the other soils behaved in such a way that they could not be separated from the Sa2, Sa6 and Ac1 treatments due to the overlap of the groups.

Lines 255 to 259 - You should present the values considered in literature to be low, medium and high for the variables: organic matter, carbon and nitrogen in soils like the study presented.

Lines 273 and 274 - The reference that supports this statement is missing

Lines 278 to 282 - The values that define what is moderate sodium are missing. The reference supporting this statement is missing.

Lines 283 to 286 - Include values that are considered high (K, Ca, Mg, and Na), citing the appropriate references. The reference that supports this statement is missing.

Line 299 - Phosphorus and Sulphur are classified as macronutrients. It is not possible to definitively determine whether soil Sa1 has high or low levels of phosphorus. In Figure 1n, this soil is represented as part of an overlapping group due to the statistical test employed.

Lines 314 to 315 - Explain this further by demonstrating that nutrients promote better crop growth and improve crop productivity. Include references.

Lines 339 to 341 - The correlation between organic matter and carbon and nitrogen is expected. Several articles support this correlation. Therefore, I recommend including bibliographical references to justify this result.

Lines 349 to 353 - The text needs improvement. Figure 3a shows only two principal components, while the text refers to three.

Lines 370 to 379 - You need to explain what the quality standard represents to determine what is better or worse. This information is missing from the text.

Lines 398 to 399 - Include references to justify this statement

Lines 408 to 414 - You still need to discuss this result and explain why it occurred. Present other similar indices and compare them with the results obtained regarding efficiency.

Lines 474 to 494 - The conclusions highlight only the main indicators: CLY, WHC, Na, and C/N, as well as the primary soil quality index.

 

Comments for author File: Comments.pdf

Author Response

Please see the pdf file

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The revised MS was well, so I suggest it can be accepted in this journal.

Reviewer 2 Report

Comments and Suggestions for Authors

The authors answered all my review comments. I have no more comments.