Response of Kentucky Bluegrass Turfgrass to Plant Growth Regulators
Round 1
Reviewer 1 Report
This manuscript, "Effect of Plant Growth Regulators on the Visual Quality of Kentucky Bluegrass (Poa pratensis L.)" (Agronomy-2215367), presents the effect of six different PGRs (Trinexapac Ethyl, Paclobutrazol, Flurprimidol, Mefluidide, Ethephon, and Gibberellic Acid) on the quality of Kentucky bluegrass, with a focus on color characteristics. Results showed that Trinexapac Ethyl and Flurprimidol improved the overall appearance, while Paclobutrazol and Gibberellic Acid decreased it. Paclobutrazol improved color assessment, while gibberellic acid had the opposite effect. Changes in leaf color were dependent on the PGRs and their rates, with gibberellic acid leading to lighter leaves with higher green and yellow hues and paclobutrazol leading to darker leaves with a lower green and “more reddish hue”.
In my review, this manuscript needs major reformulation for clarity. The information is not very interesting or appealing and needs better emphasis on why the work presents a novelty and how the agricultural sector and society can benefit from the application of PGRs. For example, introduction contains incorrect information, and many phrases do not provide the correct information for PGRs. The material and methods section are very extensive and contains many unnecessary details, which could benefit from rewriting. The results need to be summarized and highlight the main findings, and the discussion needs reformulation in some phrases. The conclusion also needs major reformulation, focusing mainly on the contribution and avoiding repeating the results. A future perspective and an overview of gaps that the manuscript has not yet solved would be beneficial. For example, the study could include in discussion other plants.
Additionally, the manuscript should be checked for consistency with the "Instructions for Authors" for all references. The images are of good quality. Other suggestions include:
Keywords in alphabetical order
Standardizing equipment/reagents/software nomenclature with manufacturer, city, state, country (three-letter)
Checking all manuscript for proper standardization “again Instructions for Authors” in Agronomy.
L42-47: This information and classification is not correct. For example, PGRs are chemicals that alter the normal growth and development of plants, but classification into five classes based on their method of action is not a widely accepted standard. It would be more accurate to classify PGRs based on their mode of action, such as hormonal mimics, inhibitors of hormone synthesis or transport, or inhibitors of cell division or elongation. Please check and rewrite.
L67-69: PBZ confers increased chlorophyll-based mass, increased dark-green colouration in leaves, increased tolerance to dissection, and maximized photosynthetic efficiency by area and mass. Please check all information.
L93-95: The meaning of this phrase is unclear; what is the scale 0-100 and 9-point system?
L181: In Table 2 and other tables 3, 4, 5, what does "fg" mean? Please describe in the legend.
In addition, please check the English grammar and style throughout the manuscript.
Check old references.
Best regards.
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
The article investigates the effect of different rates of PGRs on Kentucky bluegrass under greenhouse settings. Generally speaking, this article is in much better shape than similar articles I am asked to review for this journal, it is well written, the literature review is spot on (maybe even too vast sometimes), and the authors are not only after self-citations, so I definitely want to commend them for the nice job, it is a sign of respect for the reviewers. However, I have major concerns about statistical analysis and data collection and PGR application timing. While statistical analysis can be addressed, it is unfortunately too late for the latter. My specific comments follow:
Line 13: Do not separate paragraph in the abstract
Line 32: this is the best introduction I have read when compared to other articles submitted to this editor that investigate PGR applications on turfgrass in Poland. However, since the authors have done an excellent job reviewing previous research, they should know that turfgrass stands do not benefit from one single PGR application a year. Most of the PGRs used in the study are applied on a two week basis, sometimes monthly. The information that scientists and practitioners get from single applications is limited and does not apply in real world settings. This comment could potentially be rebutted, but it’ll mean expanding intro and/or discussion and explaining in great detail why only one PGR app was used in the study. Moreover, plenty of these PGR cannot be applied in Europe, so this information is relative.
Line 33: I guess it’s mowing
Line 136: are those rates based on label rate? Would R1 be label rate? Or R5?
Line 138: Here’s my major concern about the data collection. The authors do not specify WHEN in relation to application timing data were assessed. But it is clear that a T-0 data was not collected. Even though it’d be logical to think that all the data collected after application are indeed affected by PGR application, with no baseline data, this cannot be inferred. Science is based on solid basis that cannot be broken, and a baseline data accession (pretreatments) is utterly necessary to make sure that what is presented and discussed is the result of a treatment (a chemical application in this case). Moreover, other than when discussing regressions, authors are not presenting control data, which makes impossible to understand to which extent PGRs are influencing turfgrass performance.
Line 168: what happened to the year effect? If it was not included in the model arbitrarily it is a statistical error, and analysis needs to be redone incorporating it. If year and its interactions were not significant, then state it clearly
Line 173: results are not presented based on the outcome of the ANOVA table. This is a type I statistical error that cannot be overviewed. Table 2 and Table 8 are not only redundant, but it’s a mistake to include them, unless the three way interaction is significant. Table 3 to 6 are incorrect. If presenting a two way interaction then data presented should be presented averaged over cultivar and not separated. Basically, delete the rows with the cultivars and just present the means. If PGR is already presented in the interaction, then do not present it pooled over rate (e.g. delete the bottom part of table 3). This not only helps the reader while presenting a clearer overview of the data, but it’s the correct way to present data. Data for the controls must be included in the tables.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
The effect of different rates of PGRs on Kentucky blue grass quality with special focus on color characteristics was determined. The experimental design is reasonable, the workload is large, and it has important reference value for actual production. However, the following points still need to be improved.
1. Why did the authors choose these six PGRs? After all, according to the introduction, we know that PGRs can be divided into five categories from A to E. Why didn't the author choose one for each category?
2. Considering that this experiment involves two variables, variety and PGRs, the author needs to use two-factor analysis of variance to test whether each variable plays a significant role.
3. How is the difference significance marked in Table 2 and Table 5? Please indicate it in the note.
4. What is the meaning or basis of the author's setting of ΔE? After all, according to descriptions from Ln147 to 150, the larger the L value, the blacker the blade, and the best is when either a or b is negative (when the blade is green or blue). In this case, does a bigger square of a or b mean better results, or does a smaller square mean better results? Let's say that when we do the first process “a” goes from 1 to -4, then the square of Δa is going to be 9, and when we do the second process “a” goes from -2 to -5, the square of Δa is also going to be 9. Do the same two values mean that both treatments have the same effect?
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Dear, I consider the authors made important changes in the manuscript and it was highly improved. Best Regards
Author Response
Thank you for the positive recommendation.
Reviewer 2 Report
The authors did not address comments in a proper manner. Line 97-100 is actually not backed up by scientific evidence already present massively in scientific body literature as pointed out by another reviewer and myself (Practical Considerations in Using Growth Regulators on Turfgrass published in 1990). The rebuttal I was asking from was not addressed, these data may potentially be significant for the European turfgrass industry (even though in the US these data are already common knowledge), and my specific question about rates has been completely discarded and not taken in consideration. PGRs are commonly applied every 2 weeks, seldom every 4, usually by facilities that have less spray capability (e.g. minor league soccer fields). Even more, the application of GDD model for putting greens (among others: Growing Degree Day Models for Plant Growth Regulator Applications on Ultradwarf Hybrid Bermudagrass Putting Greens) makes the answer I received quite obsolete.
Averaging data over rating date is again arbitrary and presenting only the average deltas do not present the reader with its main point: how long do PGR have an effect on turf? How often should they be reapplied at each given date? Presenting data even when not significant is a huge statistical error. I am not asking to review the table, I am saying that presenting the table the way they stand now is pseudoscience and should not be find place in a scientific review. The tables are not acceptable in their current form must be formatted and present only those interactions and/or effects that were found significant at p<0.05. If the authors wish to present all the interactions they can try to set their p at 0.1 instead of 0.05.
Author Response
Please see the attachment
Author Response File: Author Response.pdf
