Monitoring of Natural Occurrence and Severity of Leaf and Glume Blotch Diseases of Winter Wheat and Winter Triticale Incited by Necrotrophic Fungi Parastagonospora spp. and Zymoseptoria tritici

Round 1

Reviewer 1 Report

This is an interesting study which furthers our understanding of the meteorological factors that correlate with incidence of the three main diseases of temperate-grown wheat. In my view, its greatest novelty comes from the fact that it considers the three fungal diseases together.  I think it makes a small but interesting contribution to the field. 

However, a few improvements could be made to the manuscript:

At present, the manuscript is rather hard to read and take in. Improving the English language would help here - the errors are subtle but just add a bit to the challenge of reading and following.

Figure legends and table legends don't contain enough information. For example - Table 1 has pairs of pathogens, but no explanation of the pairings in the legend; Figure 3 has divisions within each year, but doesn't tell us what these are (I know they are the locations shown in fig 1, but it's not clarified in the legend to fig 3). 

Methods are sometimes not described or not described in enough detail, at least in the main MS, which needs to stand alone. Again, as an example: ELISAs are mentioned in passing, when discussing the presence of fungus in different parts of the plant, but no details are given as to what ELISAs were done, on which samples, and by what methodology. The authors should check carefully that all the methods are fully described.

I think the structure could also be improved, possibly by adding some extra paragraph breaks subtitles to the results/discussion section. However, I would consider restructuring this section altogether. It currently lists findings but the actual discussion of these findings is limited. I would like to know more about:

• Why specific meteorological variables were significant for the different pathogens. What is it in their biology, infection cycle, or occurrence that explains, for example, why some pathogens are affected by snowfall and others not? 

• What is the conclusion from the discussion of pathogen occurrence on different parts of the plant? Does this matter? Does it explain the results in any way? Is it new knowledge?

• How does the model advance previous work in modelling Septoria? There have been previous correlative models using weather data to predict disease burden, eg the work of Michael Shaw. What is the breakthrough here? 

• Could this new model be expanded to predict overall disease burden from the 3 pathogens considered here? This would indeed be a breakthrough, as combining info from all three could suggest a more finely tuned fungicide regime for growers. 

Author Response

Dear Editor and Reviewers,

We would like to thank you very much for your decision concerning our manuscript PP2021-RA-00066DR1 entitled: "Monitoring of natural occurrence and severity of leaf and glume blotch diseases of winter wheat and winter triticale incited by necrotrophic fungi Parastagonospora spp. and Zymoseptoria tritici". We appreciate that you found our manuscript valuable and acceptable for publication in the Agronomy journal after minor revision.

We truly appreciate all comments of the Reviewers. We have adopted all suggestions in our revised version of the manuscript as we found them very constructive. Thank you for taking the time and energy to help us improve the manuscript. Following the Reviewer’s guidance, we spent more time reading and came to the revision process better prepared.

On behalf of all co-authors, I uploaded the response for both Reviewers in the online system.

We hope, the Editor and the Reviewers will be satisfied with our correction of the original manuscript, and the manuscript in the present form will be suitable to publish in the Agronomy journal.

Sławomir Bartosiak

(on behalf of all co-authors)

Comments and Suggestions for Authors

Reviewer R1:

This is an interesting study which furthers our understanding of the meteorological factors that correlate with incidence of the three main diseases of temperate-grown wheat. In my view, its greatest novelty comes from the fact that it considers the three fungal diseases together.  I think it makes a small but interesting contribution to the field. 

However, a few improvements could be made to the manuscript:

At present, the manuscript is rather hard to read and take in. Improving the English language would help here - the errors are subtle but just add a bit to the challenge of reading and following.

Our response:

 Reviewer R1:

Figure legends and table legends don't contain enough information. For example - Table 1 has pairs of pathogens, but no explanation of the pairings in the legend;

Our response:

Thank you very much. We introduced additional information to ensure that figure legends and table legends contain enough information.

In Table 1 legends we introduced information, that t-student test for the number of isolations was calculated between pairs of different necrotrophic pathogens (three combinations of pathogen pairs for both, winter wheat and winter triticale).

Figure 3 has divisions within each year, but doesn't tell us what these are (I know they are the locations shown in fig 1, but it's not clarified in the legend to fig 3). 

Our response:

Reviewer R1:

Methods are sometimes not described or not described in enough detail, at least in the main MS, which needs to stand alone. Again, as an example: ELISAs are mentioned in passing, when discussing the presence of fungus in different parts of the plant, but no details are given as to what ELISAs were done, on which samples, and by what methodology. The authors should check carefully that all the methods are fully described.

Our response:

Reviewer R1:

I think the structure could also be improved, possibly by adding some extra paragraph breaks subtitles to the results/discussion section.

Our response:

Thank you, we tried our best. We added the subsections and new subtitles (3.2.1 – 3.2.4) in the lines: 276, 348, 383, 432.

Reviewer R1:

However, I would consider restructuring this section altogether.

It currently lists findings but the actual discussion of these findings is limited. I would like to know more about:

• Why specific meteorological variables were significant for the different pathogens. What is it in their biology, infection cycle, or occurrence that explains, for example, why some pathogens are affected by snowfall and others not? 

Our response:

Thank you very much for the valuable suggestions, we added many new elements of the discussion using your ideas.

In the lines 436 – 453 we added the text: “P. nodorum and P. avenae are close relatives [51]. Both pathogens have similar life cycles and origin, therefore eight common meteorological factors were identified among those pathogens, while there were no common significant meteorological factors between P. nodorum and Z. tritici. Number of days with snowfall correlated negatively with Parastagonospora spp. occurrence in cold winter months with low minimum temperatures. Snow cover was beneficial in overwintering of P. nodorum putatively due to the thermal isolation of infected plant debris from extreme low temperatures.

Historically occurrence of SNB was related to high precipitation during the growing season (R² = 0.43), while Z. tritici was particularly common in warm and relatively dry regions, especially with low nongrowing season precipitation (R² = -0,58) [3]. Monitoring of Z. tritici employing sensitive molecular methods in the UK showed short peaks in Z. tritici occurrence from 1840 to 1860 and from 1980 to 2000 [29]. Before 1980, Z. tritici was not common in the UK, therefore probably in Europe especially in regions on similar geographical latitude.”

Reviewer R1:

• What is the conclusion from the discussion of pathogen occurrence on different parts of the plant? Does this matter? Does it explain the results in any way? Is it new knowledge?

Our response:

In the lines 257 – 264 we added the text: „P. nodorum can easily cause lesions on both, glumes and leaves under favourable conditions. In research by Shaw et al. [29], a strong correlation between Phaeosphaeria nodorum abundance on the wheat grain and leaf was observed (r = 0.7). The pathogen was more detrimental on the ears when compared to the leaves, because spores can easily be transferred with seed and no airborne spores would be necessary to begin a disease outbreak in the following years [29]. There was also a high risk of grain quality deterioration in following years.”

Reviewer R1:

• How does the model advance previous work in modelling Septoria? There have been previous correlative models using weather data to predict disease burden, eg the work of Michael Shaw. What is the breakthrough here?

Our response:

In the lines 505-513 we added the text: “The P. nodorum classification models developed by Mehra et al. [50] in 2017 using the RF algorithm based on the aforementioned factors explained the 79 % of total data variability. Ten years earlier Shaw et al. [29] developed multiple regression models based on meteorological factors for Phaeosphaeria nodorum and Mycosphaerella graminicola DNA abundance in leaf and stem, which explained respectively 55% and 47% of variance. To date there were not presented the statistical models based on prediction data for Parastagonospora spp. and Z. tritici occurrence on wheat and triticale in Poland. The developed models take into account not only wheat as a host but also triticale which is specific and significant crop in Poland.”

Reviewer R1:

• Could this new model be expanded to predict overall disease burden from the 3 pathogens considered here? This would indeed be a breakthrough, as combining info from all three could suggest a more finely tuned fungicide regime for growers. 

Our response:

In the lines 572 – 575 we added the text: “There is also a possibility to combine models for all described pathogens to predict overall disease burden by addition of outputs since all observations were made in the same scale (35 leaves× plot ^-1 = 350 leaves× 100m^-2) facilitating disease risk assessment.”

We also would like to indicate, that our models estimate spatial disease occurrence in June. Earlier predictions would be impossible due to the lack of meteorological data from April-June which are necessary input variables for the model. These models are good in the spatial prediction of disease severity in upcoming years (in June) but not necessarily fungicides application in a specific time because models include meteorological parameters in April, May, June and these months are critical in case of fungicides application. Of course, there is the possibility to develop similar models estimating the risk of disease outbreaks without factors in the April – June period (critical period for fungicide applications) at a cost of lower efficiency. Another solution is to use developed models through input estimated variables for a negative scenario in the April-June period (favorable conditions for disease development) and a positive scenario (unfavorable conditions for disease development).

Reviewer 2 Report

In Introduction described teleomorphic and anamorphic names of pathogens,
but in the rest of the text often used different names and abreviations. I recommend using the same throughout the text. Can the correlation be considered significant if the coefficient is 0.2?
Should formula (1) be represented as an Figure 2?
Inaccuracies on lines 105 and 177 and difficult to understand Figure 3.

Author Response

Dear Editor and Reviewers,

We would like to thank you very much for your decision concerning our manuscript PP2021-RA-00066DR1 entitled: "Monitoring of natural occurrence and severity of leaf and glume blotch diseases of winter wheat and winter triticale incited by necrotrophic fungi Parastagonospora spp. and Zymoseptoria tritici". We appreciate that you found our manuscript valuable and acceptable for publication in the Agronomy journal after minor revision.

We truly appreciate all comments of the Reviewers. We have adopted all suggestions in our revised version of the manuscript as we found them very constructive. Thank you for taking the time and energy to help us improve the manuscript. Following the Reviewer’s guidance, we spent more time reading and came to the revision process better prepared.

On behalf of all co-authors, I uploaded the response for both Reviewers in the online system.

We hope, the Editor and the Reviewers will be satisfied with our correction of the original manuscript, and the manuscript in the present form will be suitable to publish in the Agronomy journal.

Sławomir Bartosiak

(on behalf of all co-authors)

Comments and Suggestions for Authors

Reviewer R2

In Introduction described teleomorphic and anamorphic names of pathogens, but in the rest of the text often used different names and abreviations. I recommend using the same throughout the text.

Our response:

Thank you very much for the valuable suggestion – the Reviewer is right. In the literature, pathogen names such as: Zymoseptoria tritici, Parastagonospora nodroum and Parastagonospora avenae are used. However, old names (and their abbreviations) like Septoria tritici blotch (STB), Stagonospora nodorum blotch (SNB), Stagonospora avenae blotch (SAB) are presented in many recent papers, respectively. To make the text uniform and easier to read, we introduced the newest version of the names throughout whole text (presented in track changes mode).
 
Line 55 – 56, we deleted syn. names repeated in earlier lines 38 – 39

Line 245 – S. tritici was changed to Z. tritici

Line 398 Septoria tritici was changed to Z. tritici,

We’ve corrected pathogens names (SNB, SAB, STB) in lines: 60, 69, 124, 231, 384, 393, 415 - 417, 451, 459, 470, 475, 477, 485, 494, 497, 515, 518, 554, 555.

Reviewer R2

Can the correlation be considered significant if the coefficient is 0.2?

Our response:

We found, that for a sample large enough, r = 0.2 can be statistically significant, but the strength of the linear relationship between variables remains very low. Our intention in the manuscript, was to present all of the correlation factors concerning the model, even they were low, provided that p was lower than 0.05. The models based on p<0.01 had worse efficiency metrics (RMSE).

Reviewer R2  
Should formula (1) be represented as an Figure 2?

Our response:

Thank you very much, the Reviewer is right, it is not a figure. I’ve changed title of an equation and description in the lines 175-180 according to the Reviewer’s suggestion.

Reviewer R2
Inaccuracies on lines 105 and 177 and

Our response:

We hope to understand the suggestion correctly - closing parenthesis in lines 105 and 177 was corrected.

Reviewer R2

difficult to understand Figure 3.

Our response:

To understand Figure 3, we added X axis subtitles to clarify variables in figure, lines: 270-278.