Genotype-by-Environment Interaction and Stability of Canola (Brassica napus L.) for Weed Suppression through Improved Interference
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsComments for authors
I do not have any line numbering in the document. I will refer the comments to the relevant part. Thank you for your understanding.
None of the work focuses on the evaluation of the allelopathic effects of the genotypes considered in the field. The manuscript should be rewritten without focusing on the mechanism of allelopathy as is currently the case in this version. Furthermore, in several places in the text you use the term allelopathic lines, but no evidence is provided to confirm that these lines produce more secondary metabolites. In this case, how is it possible to distinguish this from root competition?
Title
Abstract
P1: “NSW” please define the abbreviation “New South Wales” in the abstract
General comment: same comment as above concerning the allelopathic mechanism
Introduction
P2: competition is the negative interaction between two or more individuals for resources
General comments:
A recent paper considered weed management from the angle of improving the characteristics of crop plants by taking into account the different non-chemical levers available, including amongst others crop competitiveness and allelopathy: Debaeke, P., Perronne, R., Colbach, N., Moreau, D., Barre, P., Lecouviour, F., & Durand-Tardif, M. (2024). Non-chemical weed management: Which crop functions and traits to improve through breeding?. Crop Protection, 106631.
A recent paper considered crop allelopathy in field conditions for weed management, highlighting the difficulty of assessing allelopathy in the field, although work is beginning in this direction (e.g. Reiss et al. 2018a,b): Mahé, I., Chauvel, B., Colbach, N., Cordeau, S., Gfeller, A., Reiss, A., & Moreau, D. (2022). Deciphering field-based evidences for crop allelopathy in weed regulation. A review. Agronomy for Sustainable Development, 42(3), 50.
It should be noted that secondary metabolites produced by oilseed rape can also promote certain weed species. This is the case for the parasitic plant Phelipanche ramosa, see e.g.: Auger, B., Pouvreau, J. B., Pouponneau, K., Yoneyama, K., Montiel, G., Le Bizec, B., ... & Simier, P. (2012). Germination stimulants of Phelipanche ramosa in the rhizosphere of Brassica napus are derived from the glucosinolate pathway. Molecular plant-microbe interactions, 25(7), 993-1004.
Materials and Methods
Table 1: the first two lines are unclear, the information seems mixed
General comment: using spontaneous weed flora is always risky to assess the competitiveness and allelopathic capacity of a crop genotype given the probable heterogeneity of density of weed emergence. Furthermore, the number of weeds is often less informative than the weed biomass produced, because the number of weeds is very dependent on the seed bank. For future work, it seems more relevant to sow a species mimicking the weed and characterized by a very high and homogeneous emergence rate to ensure a more precise comparison between crop genotypes
Results
Figure 1: coefficient
Figure 1: maybe I misunderstood the MM section, but your sowing rate seemed higher than the number of plants shown in the Figure. Moreover, I have not understand that you had a modality without oilseed rape. Please clarify.
P5 3.2: “Negative relationships between the number of lateral canola roots (r = −0.18) or specific canola stem density (r = −0.19) and weed biomass were ob-served.”. Not clear if it is statistically significant. Please rephrase.
Figure 3: why only the average of weed biomass and not all the points in the form of boxplots. please clarify or modify
Figure 4: I do not really understand the relevance of this figure because the results have already been highlighted above. The AMMI biplot is applied here on a limited number of situations, and it turns out to be less relevant than the other statistical analyses already presented. Thus, I suggest removing this analysis.
General comment: some statistical analyses shown in the Results section are not described in the MM section. Please describe analyses concerning Figures 1 and 2 in the MM section.
Discussion
P9: “Research has shown this potential in wheat [53], barley [11,12], rice [19–21,24,46] and canola [5].”. As noted above, this is mostly true under controlled conditions, but field evaluation is still very complex See e.g. Mahé et al. 2022
P9: “Therefore, weed-suppressing genotypes have potential for integrated weed management and further work is needed to produce a genotype with combined competitive ability and allelopathy”. I totally agree with this sentence, but given the current state of knowledge and the costs that would be necessary to distinguish the part of the interference phenomenon related to competition and to allelopathy, breeders will not be able, in the near future, to easily improve these two components separately.
P9 “Bertholdsson [12] found that early weed biomass was significantly lower in the highly allelopathic wheat lines compared with the non-allelopathic lines”. I agree, but Bertholdsson also showed that these allelopathic lines had a negative effect on grain yield, which is a major problem for breeders.
P10: Information on the study by Asaduzzaman et al. [6] should be presented in the Introduction
P10: “Correlation coefficient is a measure of the extent and direction of the relationship between any two traits (variables).”. Why include this sentence in the Discussion. Please remove
Author Response
Comments for authors
I do not have any line numbering in the document. I will refer the comments to the relevant part. Thank you for your understanding.
None of the work focuses on the evaluation of the allelopathic effects of the genotypes considered in the field. The manuscript should be rewritten without focusing on the mechanism of allelopathy as is currently the case in this version. Furthermore, in several places in the text you use the term allelopathic lines, but no evidence is provided to confirm that these lines produce more secondary metabolites. In this case, how is it possible to distinguish this from root competition?
Author response: Thank you for your insightful comments and for highlighting key aspects of our manuscript. We appreciate your feedback and have made the following revisions:
We acknowledge that the manuscript overemphasizes allelopathy, which is not the primary focus of our study, as indicated by the title. We included two allelopathic canola varieties (AV-OPAL and PAK85388-502) and have cited relevant references in the revised manuscript (see lines 68-70 and 117-118, see reference 20). We revised the manuscript to emphasize both competition and allelopathy, rather than focusing solely on allelopathy. We have clarified how root competition might influence weed suppression and ensured our conclusions are based on the study's evidence.
P1: “NSW” please define the abbreviation “New South Wales” in the abstract
Author response: Amended
General comment: same comment as above concerning the allelopathic mechanism
Introduction
P2: competition is the negative interaction between two or more individuals for resources
General comments:
A recent paper considered weed management from the angle of improving the characteristics of crop plants by taking into account the different non-chemical levers available, including amongst others crop competitiveness and allelopathy: Debaeke, P., Perronne, R., Colbach, N., Moreau, D., Barre, P., Lecouviour, F., & Durand-Tardif, M. (2024). Non-chemical weed management: Which crop functions and traits to improve through breeding?. Crop Protection, 106631.
A recent paper considered crop allelopathy in field conditions for weed management, highlighting the difficulty of assessing allelopathy in the field, although work is beginning in this direction (e.g. Reiss et al. 2018a,b): Mahé, I., Chauvel, B., Colbach, N., Cordeau, S., Gfeller, A., Reiss, A., & Moreau, D. (2022). Deciphering field-based evidences for crop allelopathy in weed regulation. A review. Agronomy for Sustainable Development, 42(3), 50.
It should be noted that secondary metabolites produced by oilseed rape can also promote certain weed species. This is the case for the parasitic plant Phelipanche ramosa, see e.g.: Auger, B., Pouvreau, J. B., Pouponneau, K., Yoneyama, K., Montiel, G., Le Bizec, B., ... & Simier, P. (2012). Germination stimulants of Phelipanche ramosa in the rhizosphere of Brassica napus are derived from the glucosinolate pathway. Molecular plant-microbe interactions, 25(7), 993-1004.
Author response: Thank you for your feedback. We have cited the relevant references and updated the manuscript to reflect the following: crop performance against weeds can be improved by taking account both competitiveness and allelopathy [23]. The assessing crop allelopathy in the field is challenging however research work is beginning in this direction [24-25]. Please see line 75-78.
Materials and Methods
Table 1: the first two lines are unclear, the information seems mixed
Author response : A table note now presented to make clear “Weeds counting and weed biomass (dry matter) were measured in two 0.5 x 0.5 meter quadrants per plot in Wagga Wagga (2016, 2013) and Temora (2016)”
General comment: using spontaneous weed flora is always risky to assess the competitiveness and allelopathic capacity of a crop genotype given the probable heterogeneity of density of weed emergence. Furthermore, the number of weeds is often less informative than the weed biomass produced, because the number of weeds is very dependent on the seed bank. For future work, it seems more relevant to sow a species mimicking the weed and characterized by a very high and homogeneous emergence rate to ensure a more precise comparison between crop genotypes
Author response: Thank you for your valuable feedback. We recognise the challenges associated with using spontaneous weed flora due to its variable density and seed bank effects. We appreciate your suggestion to use a more uniform weed species with high emergence rates for future work. This approach will indeed provide a more consistent and precise comparison of crop genotypes in terms of competitiveness and allelopathic capacity. We will consider incorporating this method in our future research to enhance the reliability of our results.
Results
Figure 1: coefficient
Author response: Overall co-efficient for two locations have been added in Figure 1.
Figure 1: maybe I misunderstood the MM section, but your sowing rate seemed higher than the number of plants shown in the Figure. Moreover, I have not understand that you had a modality without oilseed rape. Please clarify.
Author response: Thank you for your comment. While a higher seed rate was initially applied, uneven germination resulted in a lower final plant density. To ensure accurate comparisons, we standardized plant numbers for analysis in this figure by considering only identical plant populations.
P5 3.2: “Negative relationships between the number of lateral canola roots (r = −0.18) or specific canola stem density (r = −0.19) and weed biomass were observed.”. Not clear if it is statistically significant. Please rephrase.
Author response: We observed a significant negative correlation (r = -0.18*) between the number of lateral canola roots and weed biomass, and a similar trend (r = -0.19*) with specific canola stem density. We have updated the statement in revised MS. Please see line: 207-208
Figure 3: why only the average of weed biomass and not all the points in the form of boxplots. please clarify or modify.
Author response: The boxplots did not illustrate distinct differences the measured biomass variable in Temora 2016 and Wagga 2016 data points and due to data (response) it was difficult to separate genotypes in this location. To fully understand these relationships (visually) therefore mean values are presented in line plot.
Figure 4: I do not really understand the relevance of this figure because the results have already been highlighted above. The AMMI biplot is applied here on a limited number of situations, and it turns out to be less relevant than the other statistical analyses already presented. Thus, I suggest removing this analysis.
Author response: We agreed and remove the Figure 4
General comment: some statistical analyses shown in the Results section are not described in the MM section. Please describe analyses concerning Figures 1 and 2 in the MM section.
Author response: We have added additional statistical information in MM section for Fig 1 and 2. Please see line: 169-171.
Discussion
P9: “Research has shown this potential in wheat [53], barley [11,12], rice [19–21,24,46] and canola [5].”. As noted above, this is mostly true under controlled conditions, but field evaluation is still very complex See e.g. Mahé et al. 2022
Author response: We agree and acknowledged this in introduction section please see lines: 69-74.
P9: “Therefore, weed-suppressing genotypes have potential for integrated weed management and further work is needed to produce a genotype with combined competitive ability and allelopathy”. I totally agree with this sentence, but given the current state of knowledge and the costs that would be necessary to distinguish the part of the interference phenomenon related to competition and to allelopathy, breeders will not be able, in the near future, to easily improve these two components separately.
Author response: We agree and revised our MS.
P9 “Bertholdsson [12] found that early weed biomass was significantly lower in the highly allelopathic wheat lines compared with the non-allelopathic lines”. I agree, but Bertholdsson also showed that these allelopathic lines had a negative effect on grain yield, which is a major problem for breeders.
Author response: We agree and revised our MS. Please see line: 287-288.
P10: Information on the study by Asaduzzaman et al. [6] should be presented in the Introduction
Author response: We agree and revised our MS.
P10: “Correlation coefficient is a measure of the extent and direction of the relationship between any two traits (variables).”. Why include this sentence in the Discussion. Please remove
Author response: removed.
Reviewer 2 Report
Comments and Suggestions for AuthorsReview of the manuscript entitled „Genotype-by-environment interaction and stability of canola (Brassica napus L) for weed suppression through improved interference ”
In the reviewed manuscript, the authors present findings regarding the impact of selected morphological, anatomical and physiological characteristics of four canola genotypes (varieties, breeding lines) and the density of their plants in the field on competitive ability of against weeds. The experimental design, the equipment used, the method of measuring the tested features, statistical analysis and presentation of the results are correct and generally accepted for this type of research. Noteworthy is the statistical processing of data, which allowed to eliminate the influence of the environmental factor on the competitive ability of the tested canola genotypes against weeds. The research is interesting because it focuses on a little-known aspect of variety assessment, which is competitiveness with weeds. Most often, the value of crop varieties is assessed in terms of the size and quality of the crop and tolerance to pathogens, pests and unfavorable abiotic factors.
Detailed comments
In the abstract, the authors write about the role of allelopathy and chemical compounds limiting the development of weeds in canola field, l.26-28: “Results showed that canola genotypes PAK85388-502 and AV-OPAL were more weed suppressive than AV-GARNET and BAROSSA and may release specific bioactive compounds in their surroundings to suppress neighbouring weeds”. However, testing of allelochemicals was not the subject of the present research. The results came from publications cited in the manuscript. Therefore, the topic of allelopathy should not be included in the abstract, which should only describe findings related to the present research. The information related to allelochemicals is important and it is good that it is included in the chapter ‘Discussion’ on where it belongs. One of the important elements of agrotechnical methods of protection against weeds is the sowing date of the crop, but also the dynamics of seed germination and the biology of the development of seedlings of the crop plant. According to the manuscript, the authors assessed selected features of canola genotypes at the early flowering stage. It is advisable to describe very briefly the dynamics of canola germination and the rate of covering the soil by canola seedlings in the early stages of development, which could have had a weed suppression effect. The authors use the phrase “unfavourable conditions than under favourable conditions" - l. 228 and further in the text. It is worth explaining what the criterion was for determining conditions as unfavourable or favourable. The non-parametric Shukla's stability variance parameter [50] and regression model proposed by Eberhart and Russell [22] determines only the general role of environmental factors. It is worth specifying how environmental factors were qualified in the conditions of the described research.
In my opinion, the presented research is innovative and interesting. After the authors respond to the comments included in this review, the manuscript may be subject to further editorial work.
Date of manuscript received: 14 August 2024
Date of this review: 19 August 2024
Author Response
Review of the manuscript entitled „Genotype-by-environment interaction and stability of canola (Brassica napus L) for weed suppression through improved interference ”
In the reviewed manuscript, the authors present findings regarding the impact of selected morphological, anatomical and physiological characteristics of four canola genotypes (varieties, breeding lines) and the density of their plants in the field on competitive ability of against weeds. The experimental design, the equipment used, the method of measuring the tested features, statistical analysis and presentation of the results are correct and generally accepted for this type of research. Noteworthy is the statistical processing of data, which allowed to eliminate the influence of the environmental factor on the competitive ability of the tested canola genotypes against weeds. The research is interesting because it focuses on a little-known aspect of variety assessment, which is competitiveness with weeds. Most often, the value of crop varieties is assessed in terms of the size and quality of the crop and tolerance to pathogens, pests and unfavorable abiotic factors.
Author response: We thank to reviewer for such comments
Detailed comments
In the abstract, the authors write about the role of allelopathy and chemical compounds limiting the development of weeds in canola field, l.26-28: “Results showed that canola genotypes PAK85388-502 and AV-OPAL were more weed suppressive than AV-GARNET and BAROSSA and may release specific bioactive compounds in their surroundings to suppress neighbouring weeds”. However, testing of allelochemicals was not the subject of the present research. The results came from publications cited in the manuscript. Therefore, the topic of allelopathy should not be included in the abstract, which should only describe findings related to the present research. The information related to allelochemicals is important and it is good that it is included in the chapter ‘Discussion’ on where it belongs. One of the important elements of agrotechnical methods of protection against weeds is the sowing date of the crop, but also the dynamics of seed germination and the biology of the development of seedlings of the crop plant. According to the manuscript, the authors assessed selected features of canola genotypes at the early flowering stage. It is advisable to describe very briefly the dynamics of canola germination and the rate of covering the soil by canola seedlings in the early stages of development, which could have had a weed suppression effect. The authors use the phrase “unfavourable conditions than under favourable conditions" - l. 228 and further in the text. It is worth explaining what the criterion was for determining conditions as unfavourable or favourable. The non-parametric Shukla's stability variance parameter [50] and regression model proposed by Eberhart and Russell [22] determines only the general role of environmental factors. It is worth specifying how environmental factors were qualified in the conditions of the described research.
In my opinion, the presented research is innovative and interesting. After the authors respond to the comments included in this review, the manuscript may be subject to further editorial work.
Author response: Thank you for your detailed feedback and valuable suggestions. We appreciate your time and effort in reviewing our manuscript. We have carefully addressed each of your comments as follows:
- You are correct that our current research did not directly test allelochemicals but rather referenced related findings from previous publications. We have revised the abstract to focus solely on the findings of our present research. The revised abstract has eliminated references to allelopathy and instead highlight the specific results and conclusions of our study.
- We agree that understanding the dynamics of canola germination and seedling development is important for a comprehensive discussion of weed suppression. We will consider such suggestion in our future allelopathy research. Thanks again for this!.
- We appreciate your suggestion to clarify the criteria used to define “unfavourable” and “favourable” conditions. We have added definition/explanations of all of these as table note of our revised MS.
“Favourable environments- these are environmental conditions that are conducive to the optimal growth and development of the genotypes. Unfavorable envrioemnts-these conditions are less ideal for the genotypes, often causing stress or suboptimal growth.
Shukla test evaluates how genotypes respond to different environmental conditions to identify those that are stable and adaptable versus those sensitive to environmental changes.
A low b0 value suggests less variability observed in genotypes for suppression among environments condition, while a low RMSE value indicates regression model fitted very well. The data range for weed biomass is 769 − 2 = 767, and 1% of this range is 7.67, which is considered a threshold for a low RMSE value”
