Responses of the Lodging Resistance of Indica Rice Cultivars to Temperature and Solar Radiation under Field Conditions

Round 1

Reviewer 1 Report (Previous Reviewer 1)

Discusses lodging response to temperature and solar radiation in rice.  I have concerns regarding the appropriateness of the statistics used to reach specific conclusions and basic experimental set up.  If looking at lodging and lodging characteristics, why where the susceptible lines removed from the study? Those might help show a clear difference between the traits and sowing dates.  The study was conducted at two different locations, but no clear reason was given as to why one location was only tested for a year. This can occur due to many reasons, however appropriate statistics are then used to normalize the data, which does not appear to be the case here. More detailed observations below: 

Introduction –  Overall, the introduction does not set up the reader to understand why the experiment was conducted or contained enough background information to understand the discussion section.

Methods-

Note: uneven sampling (how will they deal with unbalanced data?)

Line 165:  formula needs to be defined in more detail.

Lines 200 – 209: formulas need to be defined in more detail

Bending moment defined in paper is not “bending moment” (magnitude of applied force times distance of the force from the point of support).  Fresh weight/biomass does not constitute all the forces applied to the plant.  How do you take into account torque or horizontal forces?  

Line 225-229:  Wording is very confusing.  What where the other 20 lines used for?  How did you compare lodging without including susceptible lines?

Line 229:  No need to mention EXEL as data entry tool, only statistic tool needs to be cited.

Need to explain the temperature and altitude difference of the two site locations in relation to why they were chosen for this study.

Results-

Line 270: Spelling “similay” to “similar”

Figure 4:  Data shows strong location effects.  Those effects appear to be stronger than sowing data How can you tell sowing date is a causing the changes in LI and delta BM  

Figure 5: Data is separated into two clusters.  What is the difference between those two clusters?  Location? Sowing data?

Table 1: Not mentioned analysis was conducted in methods.  What was the effect (z-score?) What was the accuracy of the path model (list 3-5 accuracy index values).   

Table2: Why only showing correlations between Tmean? 

Table3: Same question as for table2.

Discussion –

More comparison of this data with other studies of both rice and different crops is needed. 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report (Previous Reviewer 2)

Review Report: Manuscript agronomy-1915764 “Responses of the Lodging Resistance of Indica Rice Varieties to Temperature and Solar Radiation under Field Conditions”

Manuscript investigated genotypic variations in lodging resistance to temperature and solar radiation regimes in rice cultivars. Different temperature and solar radiation conditions were imposed by sowing rice cultivars at two experimental sites and on three sowing dates. Temperature stress is critical abiotic stress which hampers the performance and productivity of crops, including rice. Its impact is aggravated and uncertain under changing climatic conditions.

Factors affecting Lodging:

·       Genotypic characteristics like plant height, plumpness of leaf sheath, stem thickness are among the significant features of plants to determine resistance to lodging (Zhang et al., 2014)

·       Among the environmental factors, Wind speed and and rainall intensity are the most important causes of lodging in cereals and other crops. In this experiment data of Wind speed and rainfall are missing. Moreover, solar radiation data is extracted not actual.

·       Considering management factors, soil properties, nutrient status, irrigation, and fertilizer application (rate, ratio, and splits) have a strong influence on cop lodging.

·       All these factors are not properly described in this manuscript.

 

·       Shift Fig S1 and Table S2, S3, S4 from Supplementary to the main article

·       Clearly describe the objective/s of the study

·       Add a table indicating Experimental Year, Season, Sowing Dates, and Experimental Location. Why inconsistent sowing date interval? At Ezhou location, 15 days interval, however, at Xindu interval is nine days. Describe the season of the experiment instead of

 

·       L-31: revise Keywords

·       Replace varieties with cultivars

·       L-53: “ratio value” revise as “ratio”

·       L-54: under what type of conditions?

·       Define △BM

·       L-58: describe why lodging can be associated with the grain filling stage.

·       L-59-60: which of these factors are described in this study?

·       Describe: Temperature variation at the grain filling stage influence translocation of photosynthates and ultimately determines grain filling duration, grain weight and grain development. (See Rehmani et al., 2014 & Rehmani et al., 2021; Wang et al., 2017). 

·       L-147-148: revise the text, why data was not available?

·       L-169: describe growth duration in days. Moreover, add a table indicating variations in the growth duration of each cultivar

 

Year	Season	Sowing Date	Location	Cultivars
2015	April-September	April 11, April 20, April 28	Xindu	32 30 plants of each cultivar
2017	May-October	May 8 May 23 June 7	Ezhou	32 30 plants of each cultivar
2018	May-October	May 10 May 25 June 9	Ezhou	32 30 plants of each cultivar

 

 

·       L-500-502: Authors have described the conclusion before the “Conclusion” section. Shift to Conclusion Section

·       L-510: briefly describe how temperature and solar radiation varied during both experimental sites and experimental years

·       Conclusion is descriptive in nature, describe some key findings supported with numeral analysis

 

 

Although manuscript is focused on a critical aspect of rice production, critical for regional and global food security, however, the current version of this manuscript is not suitable for publication, it needs significant improvements

 

Suggested Readings

Rehmani M.I.A., Ding C., Li G., Ata-Ul-Karim S.T., Hadifa A., Bashir M.A., Hashem M., Alamri S., Al-Zubair F., Ding Y. (2021) Vulnerability of rice production to temperature extremes during rice reproductive stage in Yangtze River Valley, China. Journal of King Saud University - Science 33:101599. DOI: https://doi.org/10.1016/j.jksus.2021.101599.

Rehmani M.I.A., Wei G., Hussain N., Ding C., Li G., Liu Z., Wang S., Ding Y. (2014) Yield and quality responses of two indica rice hybrids to post-anthesis asymmetric day and night open-field warming in lower reaches of Yangtze River delta. Field Crops Research 156:231-241. DOI: https://doi.org/10.1016/j.fcr.2013.09.019.

Zhang et al., 2014. Lodging resistance characteristics of high-yielding rice populations. Field Crops Research. 161: 64-74

Weng, F., Zhang, W., Wu, X. et al. Impact of low-temperature, overcast and rainy weather during the reproductive growth stage on lodging resistance of rice. Sci Rep 7, 46596 (2017). https://doi.org/10.1038/srep46596

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report (New Reviewer)

Dear Authors,

The relevance of the article is very high, but I detected that the research design inappropriate, that's why the statistical analyses are not correct. For general conclusion, you need to analyze all location and examined years, not just separately. 

Introduction:

- in row 50: The reference of 16 and 18 is not about lodging index. This article of 16 is containing only one time „lodging index” in the introduction part. Moreover, the article of 18 is highlighted that difficult to find index of lodging that can be considered completely reliable! So these article did not contain the definition of lodging index, therefore please add more precise reference to this sentence.

- row 54: In general, any abbreviation should be explained at the first time it appears. Therefore, please add the meaning of △BM in brackets

- row 73-74: You wrote “decrease in solar radiation have been recorded” and the 51. reference is reported this from 1961 to 1990 in the USA.  This negative trends were true in Asia and North America, whereas Europe and Oceania were not (https://doi.org/10.1175/JCLI-D-21-0165.1). Secondly, this reference said the solar radiation is increasing (https://doi.org/10.1007/s00382-022-06438-3 .

 

Material and methods: You have 2 locations and three different years. But there is no data from both locations in every year? How did you detect seasonal effect? How did you make a comparison between locations and among years? Because based on the meteorological data Ezhou’s two years are very similar, so it can be interpreting that there is no significant difference in these two years, therefore you can use these two years as a repetition! But for this, you have to have statistical proof. In SPSS when you run ANOVA you need to add year and location as a RANDOM FACTOR to determined their effect on lodging parameters. If the random factors are significant, you cannot use them as a repetition, so cannot calculate for example means. In this form, Xindu’s data cannot use for this analyze, because there is no it's pair. The correct experimental design could be Xindu 2015, 2017, 2018 and Ezhou 2015, 2017 and 2018. Only in this case you can interpret the seasonal and location effects on lodging parameters.

 

In Table 2: My suggestion is to modify the caption of the table from “The determined growth durations of twelve indica rice varieties in all the sowing dates across two locations and three years.” to The determined growth durations (days) of twelve indica rice varieties in all the sowing dates across two locations and three years.

 

row 169: “by the the different” - one ‘the’ should be delete

 

Result:

In Figure 1:  - You should explain where is the significant differences. Among different sowing time or among the sowing time inside one group for example SD1-SD2-SD3? Please clarify it. Secondly, LSD is the weakest Post Hoc test. I recommend that you use a stronger test, for example Tukey.

in 262: “The average daily temperature (Tmean) of the 12 indica rice varieties” should be corrected to The average daily temperature (Tmean) of the experiment….

in 272: The same mistake. “The average solar radiation of the 12 indica rice varieties”. Varieties does not have solar radiation! Please correct it.

in 285-287: Based on a simple line chart with standard deviation, is not to declare “temperature and solar radiation treatments with significant differences were established”. Here, you have to present the output of the ANOVA table with significance level with random factors (location and years) to declare they are significantly differed or not.

299-300: It is not clear how Lodging index can increase because of the later sowing time. Based on your calculation in material and methods LI= BM/M × 100%. LI will increase if 1) the BM increase and M remain stable or decrease, or 2) BM remain stable and M is decrease. So my question if 1) situation is the right how it is possible that the plant height and/or plant biomass influenced by different sowing date? So if the 2) statement is the right, how it is possible to decrease breaking resistance if the plant height and weight are stable?

367-380: There is no related information in Material and Methods part how did you calculate direct and indirect effect of temperature and solar radiation on the relative LI and △BM. Please add this information to MM!

Table 2: How it is possible that the correlation coefficient which calculated all location is so different from separately calculations? For example, in the case of culm length the three coefficients are 0.424, 0.024 and -0.303. How got 0.794 when you calculated it together? This is the situation for the other parameters, too.

 

402-414: You share the result of one location and one year of culm parameters. That’s OK, because you indicate this in the material and methods. BUT all of your figures (Figure 1-4) is about how much the differences among 3 group. Why do you think that 1 location data in 1 year is enough to represents the effect of temperature on the lodging related traits?

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report (Previous Reviewer 2)

Authors have significantly revised the manuscript. Current version of manuscript is acceptable for publication. Minor Proofreading before final publication is suggested.

Reviewer 3 Report (New Reviewer)

Dear Authors, 

Thank you for your favorable attitude towards the suggestions and for making exhaustive additions to the manuscript. I accept all of your response and modifications.

 

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

This lodging experiment takes a unique look at temperature and solar radiation on lodging.  The idea is an intriguing one, however as reviewer I have concerns about methodology and justification of statistics.

-An argument for studying solar radiation is not clearly established in the introduction, unlike increased temperatures. Citations listed describe shading and not solar radiation.

-Figure 1 should be in Results section not methods.

-Culm traits were only measured for one year at one site.

-Line 182: Bending moment is the torque applied to each side of the beam (culm) anywhere along its length. Your base formula has calculated linear density, not torque or force.  Therefore, any other calculation (line 185) relying on the data is suspect to what is actually being calculated.  

-Line 199: Klason lignin is the gold standard for measurement of lignin in forage quantification.  Please add the sensitivity range for the commercial lignin assay kit compared to Klason lignin assays.

-Line 214: Describe in brief the methodology cited.

-Statistics-

Both temperature and solar radiation are known to have interactions.  How did you test those interactions for significance? Unclear how lodging susceptible groups were characterized.  Where they chosen based on historical data or randomly.  Was the LI used to validate or characterize the groups. What validation of lodging classification was used?  Field observations? CI ?

Table 1.  How can lodging classification have different temps and radiation for each SD if planted sowed in a side-by-side experiment?  Either this needs to be explained in more detail or there is an error in table 1.  Modeling the solar radiation can be acceptable for large scale areas, however comparing those estimates to small plots with only one year of trait data for culm traits is not enough to make any conclusions.  Authors needed to have plot level measurements of solar radiation.

Reviewer 2 Report

The manuscript entitled "Influence of Temperature and Solar Radiation on Lodging Resistance in Paddy Rice" tried to establish link temperature and solar radiation with the lodging in rice. Influence of temperature and solar radiation on rice growth and yield is well established, however, limited literature is available regarding lodging in response to variation in temperature and solar radiation

Thorough revision required

Major Issues:

Plant Lodging is influenced by various factors, and authors were unable to fairly discuss below-mentioned aspects of crop lodging

1. Soil characteristics (Soil Texture, bulk density, soil nutrient status, soil moisture etc)
2. Climatic conditions of location (wind speed, rainfall, solar radiation)
3. Plant characteristics (plant height, plant age, stem characteristics, root characteristics) will define stalk/stem lodging or root lodging.
4. Management practices (tillage, rate of fertilizer and their ratios, irrigation, organic matter incorporation)

Inconsistent Sowing treatments

Soil Description is missing: Spatiotemporal variations (two cites and three experimental years) in soil characteristics [Soil type (texture), bulk density, nutrient status] can significantly influence results of experiment.

Zhang, S., Y. Yang, W. Zhai, Z. Tong, T. Shen, Y. C. Li, M. Zhang, G. C. Sigua, J. Chen and F. Ding. 2019. Controlled-Release Nitrogen Fertilizer Improved Lodging Resistance and Potassium and Silicon Uptake of Direct-Seeded Rice. Crop Science. 59: 2733-2740. https://acsess.onlinelibrary.wiley.com/doi/abs/10.2135/cropsci2018.12.0765

Climate Date: precipitation and wind data of experiment duration are missing

Niu, L., S. Feng, W. Ding and G. Li. 2016. Influence of Speed and Rainfall on Large-Scale Wheat Lodging from 2007 to 2014 in China. PLOS ONE. 11: e0157677.

 

Authors need to justify sowing date as treatments, arranging sowing dates as “Day of the Year” and found an inconsistent trend.

Sowing Date	Day of the year	Year	Date
SD1	101	2015	April 11th, 2015
SD2	110	2015	April 20th, 2015
SD3	118	2015	April 28th, 2015
SD4	128	2017	May 8th, 2017
SD5	143	2017	May 23rd, 2017
SD6	158	2017	June 7th, 2017
SD7	130	2018	May 10th, 2018
SD8	145	2018	May 25th, 2018
SD9	160	2018	June 9th, 2018

 

General comments:

Thoroughly revise manuscript considering abovementioned facts.

Add graphical abstract for better understanding of processes involved

Abstract: Numerical data regarding obtained results is missing, authors rewrite the abstract.

 

L-98: revise heading 2.1 Plants and Groups

L-102: Revise “experimental plants” as ”experimental material”

“lodging-middle group” revise as “lodging-moderate group”

Although description of sub-species are given in the Table S1, authors need to briefly describe details of subspecies (japonica, indica, hybrid etc) in heading 2.1.

L-111, which rice growing season?

Table 1: how these parameters were measured?

Conclusion is also descriptive, without adding numerical data and relative anomalies among the variables

 

Suggested readings:

Dahiya, S., S. Kumar and C. Chaudhary. 2018. Lodging: Significance and preventive measures for increasing crop production. Int. J. Chem. Stud. 6: 700-705.

Niu, L., S. Feng, W. Ding and G. Li. 2016. Influence of Speed and Rainfall on Large-Scale Wheat Lodging from 2007 to 2014 in China. PLOS ONE. 11: e0157677.

Shah, L., M. Yahya, S. M. A. Shah, M. Nadeem, A. Ali, A. Ali, J. Wang, M. W. Riaz, S. Rehman, W. Wu, R. M. Khan, A. Abbas, A. Riaz, G. B. Anis, H. Si, H. Jiang and C. Ma. 2019. Improving Lodging Resistance: Using Wheat and Rice as Classical Examples. International Journal of Molecular Sciences. 20: 4211.

Zhang, S., Y. Yang, W. Zhai, Z. Tong, T. Shen, Y. C. Li, M. Zhang, G. C. Sigua, J. Chen and F. Ding. 2019. Controlled-Release Nitrogen Fertilizer Improved Lodging Resistance and Potassium and Silicon Uptake of Direct-Seeded Rice. Crop Science. 59: 2733-2740.

 

Regards

Comments for author File: Comments.pdf