The Mekong Delta paddies are known as hotspots of methane emission, but these emissions are not well studied. We analyzed methane emission patterns based on monitoring data from typical triple rice cropping paddies collected over 5 years. We found that the total emissions in a crop season doubled in the second crop, tripled in the third crop, and reset after the annual natural flood of the Mekong River. The emission peaks occurred around 0 to 3 weeks after starting irrigation, then gradually decreased. In general, the main source of emitted methane is rice-derived carbon by current-season photosynthates and the emission peaks at the rice heading stage. However, the contribution of the rice-derived carbon is negligible in the hotspot paddies because total emission is high. The increase in emission levels from the first to the third crop can be explained by the accumulation of rice residue from the preceding crops, especially rice straw incorporated into the soil. The reset of emission levels after the annual flood means that the rice straw is decomposed without methanogenesis in water with dissolved oxygen. Thus, the annual emission pattern shows that avoiding rice straw incorporating into soil and decomposing rice straw in paddy surface-water reduces methane emissions. FAO 2018). The Mekong Delta produces the half (23.8 million tons) . The climate of tropical monsoon (Am) enables high productivity by triple rice cropping (cropping three times a year). Rice paddies are a methane emission source, and the Mekong Delta is a hotspot (Vietnam is the world’s fifth largest rice producer (hotspot . Howeverst crop (winter-spring) begins after the natural flood, then after harvesting the rice straw is incorporated into the soil. The 2nd (spring-summer) and the 3rd crop (summer-autumn) follows without interval. Just after the 3rd crop, the natural flood starts so the straw is left on the paddies and decomposes under the floodwater. Then, the 1st crop begins again without incorporation of the straw in the soil (field leveling only), because they are sufficiently decomposed by that time.The Mekong’s natural flood of two months (starting from around late September to late October) limits the rice cultivation period. The 1Can Tho University (CTU) and the Japan International Research Center for Agricultural Sciences (JIRCAS) conducted joint research and monitored methane emissions in typical triple rice cropping paddies for 5 years . This paper is a specific analysis of a part of the data set from this project. We aimed to clarify the pattern of the methane emission.Oryza sativa) variety Jasmine was used for the 1st crop, and OM501 was used for the 2nd and 3rd crop every year. The average number of growth days per crop were 103, 89, and 92, for the 1st, 2nd, and 3rd crops, respectively. The average intervals between the 1st and the 2nd crop and the 2nd and the 3rd crop were 5.6 and 6.6 days, respectively. The average rice straw dry weight per crop were 9.0, 9.3, and 7.4 (Mg ha–1), for the 1st, 2nd, and 3rd crops, respectively, and the whole amount were returned. Rice straws were incorporated into the soil after the 1st and 2nd crop but left on the ground after the 3rd crop. Note, we confirmed that no rice straw (the source of methanogenesis) was lost to the floodwater. This study was conducted with the approval of the farmer.The observation was conducted on a farmer’s paddies (three fields) managed by the above typical triple-cropping in Thuan Hung village , Thot Not district, Can Tho city, Vietnam from 2011 to 2016. The soil is alluvium soil . Normally, from May to October is the rainy season. The farmer managed the water with continuous flooding. The low dike system could not protect their paddy fields from the annual flood. The rice , and the measurements were taken at 8 a.m. (ca. 90% of the average daily emissions). In periods of natural flood, chambers with attached Styrofoam floats were used. Measurements were taken once a week throughout the rice growing stage, but every 3 days for 2 weeks after seeding, heading stage, and around draining  from double cropping rice paddies in the Philippines after organic matter incorporation. However, we observed larger emissions , for the 1st, 2nd, and 3rd crops in average, respectively.–1 crop–1). The emission level doubled in the 2nd crop, and tripled in the 3rd crop, then reset after the natural flood  is small . Incorpo4 emission. The reset of emission levels after the annual flood means that the rice straw is decomposed without methanogenesis in water because the water includes dissolved oxygen. Convection of surface water transports new water to rice straws and new oxygen replenishes from the atmosphere when reducing the concentration of dissolved oxygen. Thus, the redox potential of water hardly achieves the level of methane generation. In fact, the rice straw on the paddy surface contribute to little methane emission because the emissions during the natural flood appeared to be a continuation of the emissions of the 3rd crop. If the rice plant residues were incorporated into the soil, the total emission of the flood period should be higher than that of the 3rd crop. Because the accumulation of organic matter is larger. In addition, although the absence of rice-derived carbon, the absence of rice plants doubles the methane emission from the field because of the lack of methanogenesis inhibition by rice plants .Data are available under the terms of the Though having 6 revisions, this manuscript is still difficult to understand. The author delivered the simple thing in a difficult way. Repeated same issues many times but obscured some issues. My previous suggestions are not fully acknowledged in this manuscript and this time may not as well.Abstract: In general, the main source of emitted methane is rice-derived carbon by current-season photosynthates and the emission peaks at the rice heading stage. However, the contribution of the rice-derived carbon is negligible in the hotspot paddies because total emission is high” The above sentences come from nowhere. Photosynthesis is not included in this study and CH4 should not come from photosynthesis. The second sentence is not reasonable since the carbon is from the decomposition of rice straw.Emission pattern in each cropping: Three types of methane emission patterns are not clear. When is the heading stage? When is the early stage of rice growth? What is the methanogenesis substrate from the present rice? The authors also mention that no peak at the heading stage because of the high emission levels. What mean by this sentence? Is it higher than the detection limit of the device? Overall, please rewrite this section.Figure 2: Please make notices on the seeding, harvesting, heading, flooding stages in the figure. Here are the difficulties:Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?NoIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?NoReviewer Expertise:Environmental EngineeringI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. I read the revised manuscript (ver. 6) and the Author Response (dated on 15 Feb 2021) to my comments on its ver. 5 (13 Jul 2020) that was reported to me on 15 Feb 2021. As a result, I recognize that some improvements were added to the revised manuscript. However, the latest version of the manuscript (ver. 6) still has a number of problems in the presentation and interpretation of the experiment and its results. Judging from the ‘Author Response (dated on 15 Feb 2021)’, I am afraid that the authors make a big misunderstanding about my comments that were repeatedly asked in Reviewer Reports. The authors insisted that “You didn't give us any response so we understood that you accepted our response”. However, this is wholly to misconceive my comments to the previous version (ver. 5) on 13 Jul 2020. In this previous response, I have requested to respond my previous comments to ver. 2 and 4. However, many of these comments are not appropriately responded to in the latest version. Consequently, I have no other choice than reporting that the response of the authors is still unsatisfactory to accept. I am listing problems of the manuscript below and request authors to revise the manuscript in response to each comment. I hope the authors also explain how they responded to each of the comments, as a general procedure in responding to the peer review in most scientific journals. I fully agree with your suggestion that we should reduce the effort of the Editorial Team. But if you think so, you should respond to the comments from reviewers completely and conscientiously.Fundamental problems:Introduction: Scientific questions and objectives of this study are not clear. Background (Why did you study methane emissions from paddy fields? What gaps of knowledge did you try to approach?) and objectives of the study should be clearly presented. It seems that this study has aimed at more than that mentioned in the last sentence of ‘Introduction’, not only to clarify the pattern of the methane emissions but also to propose a possible option for reducing the emissions.There is a fundamental lack of discussion with referring to previous studies by other researchers who reported methane emissions from paddy fields. There are a number of reports on the intensity, patterns, and reduction options for methane emissions from paddy fields. A sweeping revision is necessary in the Discussion section.Other specific problems:Abstract, line 2: The statement that ‘these emissions are not well studied’ is incorrect. A number of field measurements for methane emissions from paddy fields in the Mekong Delta have been published, such as Vo et al., 2018 , and references cited in this paper.Abstract, line 11: It is not reasonable to state that the contribution of the rice-derived carbon is ‘negligible’. It is stated to be ‘small’ in the text.Introduction, 1st paragraph, line 2: It is necessary to clarify ‘the half’ of what.Introduction, 2nd paragraph, last phrase: It is necessary to indicate the evidence or possible mechanisms that the straw in the soil is sufficiently decomposed before the beginning of the 1st crop.Methods, Site description: Chemical properties of the soil at the site are suggested to report, in addition to the type and texture, because the information is essential for discussing the intensity of methane emissions from paddy fields. I would suggest reporting, at least, organic carbon content and pH.Methods, Methane measurement: How many replications of the measurement did you conduct? It is necessary to mention that the data for emission rates from each replication are averaged.Methods, Statistical analysis: It is necessary to explain ‘descriptive statistics’ more, including the method to test statistical significance.Results, Emission level, lines 6–8: The reasons for larger emissions of CH4 in the study field should be discussed here or in ‘Discussion’.compared with that in the 1st crop,” then … (the phrase in “ “ should be added). Same corrections should be made at Abstract, lines 4–7 and Discussion, Emission pattern, lines 1–3.Results, Emission level, lines 10–12: The emission level doubled in the 2nd crop, and tripled in the 3rd crop, “Results, Emission pattern in each cropping, lines 1–11: This statement is not the results in this study. Therefore, it should be moved to Discussion.Results, Emission pattern in each cropping, lines 11–12: It is questionable to discuss the emission patterns with reference to the study of Oda & Chiem (2019) because it reported only the results in the winter-spring season. A wider discussion with referring other studies is expected.Discussion, Reset of emission lines 17–20: The discussion about the effect of rice plants on the methane emissions is just a speculation from the result of Oda & Chiem (2019). Therefore, it cannot be concluded.Discussion, Method for methane reduction, the last sentence: The statement is vague. It is requested to specify how practical technologies are considered by deducing from this study. Also, the same comment to Conclusion lines 7–9.Figure 1: What do the error bars indicate? Are they 95% CI of inter-annual variations of emissions? It is necessary to clarify it by adding in the caption.Figures 1 and 2: The period of data ‘Flood’ is confusing. It is recommended to correct it with ‘Annual flood’.Many inappropriate usages of English grammar and expressions are found throughout the manuscript. Therefore, it is recommended to edit the manuscript by an English expert.Is the work clearly and accurately presented and does it cite the current literature?NoIf applicable, is the statistical analysis and its interpretation appropriate?NoAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?NoReviewer Expertise:biogeochemistry, soil scienceI confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. I read the revised manuscript (ver. 5) and the Author Response (dated on 23 Mar 2020) to my comments on its ver. 4 (12 Mar 2020) that was reported me on 26 Jun 2020. Although some revisions have made in the manuscript, the latest version of the manuscript (ver. 5) still has a number of problems and misunderstandings in presentation and interpretation of the experiment and its results. I do not recognize the revisions in response to most of my previous comments to ver. 2 and 4. As a result, in conclusion, I have to report that the response is still unsatisfactory to accept.Is the work clearly and accurately presented and does it cite the current literature?NoIf applicable, is the statistical analysis and its interpretation appropriate?NoAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?NoReviewer Expertise:biogeochemistry, soil scienceI confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. We hope the misunderstandings should be clarified in the response so that we could know the misunderstandings. You didn't give us any response so we understood that you accepted our response. You and we should reduce the effort of the Editorial Team. In summary, the manuscript is still lacking in scientific sound and requires extensive revision. The contradictions between this finding and the previous studies have not yet been logically justified. Oda and Chiem (2019) mentioned the methanogenesis inhibited by rice plants, but this study shows higher methane during the cropping cycles than those in the non-cropping phase. The authors said that "No rice straw is incorporated before the flood period. That is the difference in the conclusion of Oda and Chiem (2019)."  It is not clear to me what "incorporated" means and how it results in the different outcomes between these two studies. Is It is sound inconsistency with the statement that "We confirmed that no rice straw (the source of methanogenesis) was lost to the floodwater."4, CO2, SOC, Dissolve forms, bio uptake, etc.) from the paddy field during the natural flood. The authors persuaded that the no-plant flood mentioned in Oda and Chiem (2019) had no rice straw, but in this study, there was straw left in the field during the natural flood. The authors also conclude that soil organic alone under flooding promotes methane emission, but soil organic with rice straw incorporated was not. The authors said that the reason is due to sufficient DO. This conclusion was puzzling. How to prove that the flood in the previous study has insufficient DO, but there was adequate for this study? The authors, therefore, should discuss more the pathways of C losses  It is not clear to me what "incorporated" means and how it results in the different outcomes between these two studies.We've noticed that a sentence is unclear to indicate the work of Oda & Chiem *2019).We revised the manuscript as follows.Discussion- Emission pattern. Because the contribution of the present rice-derived carbon is small .Incorporation of organic matter just before rice cultivation largely increases the methane emission in the paddy field . However, that just after the 3rd crop, the natural flood starts so the straw is left on the paddies. No rice straw is incorporatedinto soil before the flood periodand that resulted the reduction of CH4 emission.""The total emissions in a crop season doubled in the second crop, tripled in the third crop, and reset after the natural flood. This can be explained by the accumulation of rice residue from the preceding crops, especially by the rice straw incorporated into the soil2) How to prove that the flood in the previous study has insufficient DO, but there was adequate for this study?The difference of DO is clear because the location of rice straws is different. We emphasized this by adding the reference of Wassmann et al. in the above paragraph.3) This recommendation might not be useful and need to open for multidisciplinary discussions.We revised the manuscript as follows.in this area. However, environmental sustainability should be considered the conversion of CH4 to other carbon forms could also result in additional ecological problems. In addition, socioeconomics should be considered since minimizing cropping cycles may not be socially acceptable.""Our results indicate that the main cause of the increase in methane emissions was the incorporation of rice straw into the soil. In contrast, decomposing rice straw in paddy surface-water generated less methane. Thus, decomposing rice straw in paddy surface-water is an effective method to reduce methane emissionsThe conclusion also added the following sentence.However, the effects of CH4 conversion to other carbon forms and of socioeconomics should be clarified. "" First, the purpose of this study is not to propose a technology. Therefore, in the revised manuscript, we limited our conclusions to the results of the analysis. Second, you have pointed out the contradiction with existing studies, but the two are not contradictory. The point is not whether there is rice straw in the rice paddies, but whether the straw is incorporating into the soil. In the revised manuscript, I clearly stated: "incorporating into the soil" to avoid misunderstanding. The data show that the methane production is obviously different depending on whether the rice straw is in the soil or in the water. Also, if the rice straw is not continuously incorporated into the soil, the amount of methane produced is smaller. Methane is produced in a reduced state. In other words, the reduction of methane production in the presence of large amounts of rice straw is evidence of the presence of dissolved oxygen. The revised manuscript explained in detail the continuous supply of dissolved oxygen in the water. Consistently, the authors have not well communicated in their writing and poorly reviewing the previous studies resulting in devaluing the work despite interesting methodology. For example, the authors cited their own articles, and readers cannot clearly distinguish ones from the previous studies and one of this study. Though, there is some inconsistency between the previous study of Oda and Chiem (2019) — “the absence of rice plants doubles the methane emission from the field because of the lack of methanogenesis inhibition by rice plants”— and the Figure 1 of this study. The authors are not attempting to discuss this inconsistency but try to discuss their new findings without citing any supporting evidence from other previous works.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?NoIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?NoReviewer Expertise:NAI confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. Thank you for reviewing and we are sorry to late to respond.1) For example, the authors cited their own articles, and readers cannot clearly distinguish ones from the previous studies and one of this study. Oda & Chiem (2019) is a field experiment conducted in the year 2018; instead, this work is "a specific analysis of a part of the data set; Introduction L. 15" of an old project (2011-2016). We are sorry that the relation is a little complicated; however, that is a fact. What we call "data analysis" can do at any time.We welcome if you give us a piece of advice for the way to dissolve this problem.2) There is some inconsistency between the previous study of Oda and Chiem (2019) — “the absence of rice plants doubles the methane emission from the field because of the lack of methanogenesis inhibition by rice plants” — and the Figure 1 of this study. The authors are not attempting to discuss this inconsistency but try to discuss their new findings without citing any supporting evidence from other previous works.The sentence is in the result section and the inconsistency is discussed in the discussion sections as follows. "This can be explained by the accumulation of rice residue from the preceding crops, especially by the rice straw incorporated into the soil, because the contribution of the present rice-derived carbon is small; Discussion L. 2"Remember that "Just after the 3rd crop, the natural flood starts so the straw is left on the paddies; Introduction L. 10". No rice straw is incorporated before the flood period. No rice straw is incorporated before the flood period. That is the difference in the conditions of Oda & Chiem 2019.We are waiting that your response. I read the revised manuscript (ver. 4) and the Author Response (dated on 21 Feb 2020) to my comments on its ver. 2 (12 Nov 2019) that was reported on 19 Feb 2020. As a result, I found that the response was quite unsatisfactory to accept. The authors responded to many of my comments that they think the matter of writing style is not constructive. However, I do not agree with that because those comments are not the matter of writing style but that of fundamental requirements for a scientific paper. I cannot understand their statement that ‘because that is largely affected by the background of the main journal we have read’.nd paragraph lines 1–4)’. Then, when was the period ‘Flood’ in Figure 1? It is difficult to understand the periods written in the ‘Emission level’ section of Results: ‘after the natural flood (line 11)’, ‘during the flood period and the 1st crop (lines 12–13)’, and ‘the flood period (line 14)’. Also, the term ‘natural flood’ or ‘annual flood’ is still unclear. It is written that ‘natural flood of two months (starting from around late September to late October) limits the rice cultivation period. The 1st crop (winter-spring) begins after the natural flood, …  is still unclear. The ‘previous’ report  reported that rice suppressed overall methane emissions.     In conclusion, because of the result of above-mentioned assessment, I have no other choice to recommend ‘reject’ for this paper, despite that it includes original and remarkable findings that are valuable to the scientific communities.Is the work clearly and accurately presented and does it cite the current literature?NoIf applicable, is the statistical analysis and its interpretation appropriate?NoAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?NoReviewer Expertise:biogeochemistry, soil scienceI confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. *The authors responded to many of my comments that they think the matter of writing style is not constructive.That’s a misunderstanding. That is because we think most of your comments are not the matter of writing style but that of fundamental requirements for a scientific paper. *When was the period ‘Flood’ in Figure 1?You can see the period in Figure 2.*How much of the straw was returned?We returned all; therefore, we don't mention how much.*Significance testThat means significant at 5% level when the 95%CI do not overlap.*Soil propertiesWe can show a paper which conducted the same place. The paper shows that the soil is the silty-clay Fluvisol soils .*The reason why the result was not consistent to the ‘previous’ reportThat is explained in the discussion section as follows. "The reset of emission levels after the annual flood means that the rice straw is decomposed without methanogenesis in water". This high emission resulted from rice straw incorporation. This improvement has been more scientific sounds. The authors discuss based on the experimental results. The manuscript; however, has major concerns on the unclear conclusion, miscommunication, and writing problems.Methods:Rice variety should be firstly introduced in scientific names.Results:Unbalance parenthesis when introducing the methane emissions from 1st, 2nd, and 3rd cropping periods.The sentence on “The total emission should be higher than that of the 3rd crop: because the absence of rice plants doubles the methane emission from the field ” is not understandable. What is the total emission? Why does the absence of rice plants cause double emission?The sentence on ”In the present study, the pattern was the same as the previous study ” is also hard to understand. What is the present study? Oda and Chiem (2019) or this study? If the author means this study, it was also not the same as the previous study since no emission peaked at the heading stage.Figure 2 should provide additional information on the heading stage, irrigation period, and period of the full canopy developmentDiscussion:4 forms without methanogenesis and how to be confident that the DO in the water did not deplete for the entire 2-month flooding.the sentence on “the rice straw is decomposed without methanogenesis in the water because the water includes dissolved oxygen” is doubtful. The author should discuss more how CH Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?NoIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?NoReviewer Expertise:Environmental EngineerI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. We deeply thank you for giving valuable suggestions.Rice variety should be firstly introduced in scientific names. We added.Unbalance parenthesis. We corrected.The sentence on “The total emission should be higher than that of the 3rd crop: because the absence of rice plants doubles the methane emission from the field ” is not understandable. What is the total emission? Why does the absence of rice plants cause double emission? We added the value of the total emission and clarified the sentence and added the reason.The sentence on ”In the present study, the pattern was the same as the previous study ” is also hard to understand. What is the present study? Oda and Chiem (2019) or this study? If the author means this study, it was also not the same as the previous study since no emission peaked at the heading stage. We clarified the sentence.Figure 2 should provide additional information on the heading stage, irrigation period, and period of the full canopy development. We added the information for the heading stage and the irrigation period. Unfortunately, we don't have data on the period of full canopy development.Discussion:  the sentence on “the rice straw is decomposed without methanogenesis in the water because the water includes dissolved oxygen” is doubtful. The author should discuss more how CH4 forms without methanogenesis and how to be confident that the DO in the water did not deplete for the entire 2-month flooding. 1) We added the explanation for CH4 forms without methanogenesis. 2) We added a possible explanation for the DO in the water did not deplete. The study reports original and remarkable findings in increasing methane emissions from triple cropping of rice. Although it is not clearly stated in the manuscript, there are very few studies that reported methane emissions from triple rice cropping. In addition, the major finding of this study, that is the increasing methane emissions in the 2nd crop relative to the 1st one, and further in the 3rd crop, in response to the accumulation of rice residue from the preceding crops, is a remarkable fact for understanding the intensity of emissions, as well as designing options for climate change mitigation. Therefore, the research is recognized to be valuable in reporting in an international scientific journal. However, at the same time, I have to report that current manuscript has substantial lack of basic components and requirements as a scientific paper at each section throughout the manuscript, even though this paper has submitted as a Brief Report. Note that filling those lack of details is essential as a scientific paper to make sure that readers have enough information to understand the description of the work. The specific points of problems are listed below. As a result, I can approve the manuscript only after it was revised by responding to my comments in an appropriate manner.Introduction: Background (the need for this study) and objectives of the study should be clearly presented. Why did you study methane emissions from paddy fields? What gaps of knowledge did you try to approach? What are the objectives of this study?  Methods:The major finding of this study is the importance of straw incorporation into the soil after harvesting rice for increasing methane emissions in the following season. From this viewpoint, it is requested to report management of rice straw after every harvest more quantitatively in detail in the Method section. It is required to provide the amount of rice straw (and preferably that of stubbles and roots) returned to the fields from previous harvest, because it is essential to discuss the increase in methane emissions. Otherwise, it is vague to discuss the emission pattern in Discussion.   Data analysis: The statistical analysis for judging the differences in methane emissions among the seasons is insufficient, because no statistical analysis was made for the data in Figure 1. As a result, it is difficult to conclude the differences in methane emissions among the seasons.   Results:In this section, the results of experiment should be simply presented. Information of previous studies and discussion with them should be presented in Introduction or Discussion sections, respectively. From this, the sentences in Line 1–6 of ‘Emission level’ part and in Line 1–11 of ‘Emission pattern’ part should be moved.  Data presentation: The amounts of total seasonal methane emission should be numerically presented, at least those of five-year average for each crop with the values of interannual variation.  Discussion: There is fundamental lack of discussion with referring to previous studies by other researches who reported methane emissions from paddy fields. A sweeping revision is necessary in this section.  Throughout the manuscript, the term ‘natural flood’ or ‘annual flood’ should be corrected to ‘fallow flood’ because it is confusing. ‘After natural  flood’ can be ‘during the fallow flood period after harvesting the 3rd crop’.et al., 2018 , and references cited in the paper.Abstract, Line 2: The statement that ‘these emissions are not well studied’ is incorrect. A number of field measurements for methane emissions from paddy fields in the Mekong Delta have been published, such as VoIntroduction, 1st paragraph, Line 9: The statement that ‘this has not been well studied’ is incorrect. IPCC Guidelines provides the quantitative effects of rice straw incorporation on increasing methane emissions as a scaling factor based on a number of field measurements including those in the Mekong Delta. Introduction, 3rd paragraph, Lines 6–8: The reference that shows effectiveness of the strategy should be cited.Methods, Site description: It is suggested to report the type of soil and its characteristics, because the information is essential for discussing the intensity of methane emissions from paddy fields and is not presented in the previous paper. I would suggest to report, at least, soil texture, organic carbon content, and pH, all of which are recognizes as the major factors controlling methane emissions. Figures 1 and 2: The period of data ‘Flood’ is confusing. It is recommended to correct it with ‘Fallow flood’.compared with that in the 1st crop, then reset after the fallow flood. Same correction should be made at Discussion, Emission pattern, Lines 1–3.Results, Emission level, Lines 9–11: The emission level doubled in the 2nd crop, and tripled in the 3rd crop, during the fallow flood should be higher …Results, Emission level, Lines 13–: The total emission Results, Emission level, Lines 13–15: Why the result was not consistent to the ‘previous’ report. Please discuss it.Results, Emission pattern, Lines 1–11: This statement is not the results in this study. Therefore, it should be moved to Discussion. Also, the difference of data in ‘previous’ study and this one should be clarified. Understanding from the ‘previous’ paper , the ‘previous’ study reported the results of experiments during 2016 and 2017, whereas this study during 2011 and 2016. If it is correct, using the term ‘previous’ is not appropriate.Discussion, 2nd paragraph, Line 6: no methane emission -> little methane emission In addition, some minor comments are listed below:Is the work clearly and accurately presented and does it cite the current literature?NoIf applicable, is the statistical analysis and its interpretation appropriate?NoAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?NoReviewer Expertise:biogeochemistry, soil sciencesI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Thank you for deeply considering our manuscript. We considering your helpful comments and improved the manuscript. However, we are afraid that adopting the term "fallow flood" is not right in case of the Mekong Delta triple cropping rice. In addition, we think the matter of writing style is not constructive because that is largely affected by the background of the main journal we have read. Finally, we are glad to have helpful comments from you. The details of our response are as follows. Introduction: •    Background (the need for this study) and objectives of the study should be clearly presented. Why did you study methane emissions from paddy fields? What gaps of knowledge did you try to approach? What are the objectives of this study? *As you mention "there are very few studies that reported methane emissions from triple rice cropping." That is the reason. We described more clearly the aim of the study. Methods: •    The amount of rice straw  *They were added. Data analysis: •    No statistical analysis was made for the data in Figure 1. *You mention the significant tests, don’t you? Now, that is no longer recommended; instead, 95% confidential interval is recommended (https://www.nature.com/articles/d41586-019-00857-9). That can be known from the SD and the n. However, we found that the figure is needed correction of the way of calculation of the mean . In addition, the error bars were not SD but were SE. We corrected the figure and show the 95% confidential interval (CI). We deeply thank that you give us a chance to correct the error bars. Results: •    In this section, the results of experiment should be simply presented. Information of previous studies and discussion with them should be presented in Introduction or Discussion sections, respectively. From this, the sentences in Line 1–6 of ‘Emission level’ part and in Line 1–11 of ‘Emission pattern’ part should be moved. *This is a matter of writing style. The consideration of the values using citations is common in the results section. Data presentation: •    The amounts of total seasonal methane emission should be numerically presented, at least those of five-year average for each crop with the values of interannual variation. *We showed them as a range, but we changed that as each average. Discussion: •    There is fundamental lack of discussion with referring to previous studies by other researches who reported methane emissions from paddy fields. A sweeping revision is necessary in this section. *This is a matter of writing style. We cited the studies in the introduction section. As you know, they are few. In addition, some minor comments are listed below: 1.    Throughout the manuscript, the term ‘natural flood’ or ‘annual flood’ should be corrected to ‘fallow flood’ because it is confusing. ‘After natural  flood’ can be ‘during the fallow flood period after harvesting the 3rd crop’. *There is no fallow flood. We show the condition by describing the cropping days and the intervals in the manuscript. 2.    Abstract, Line 2: The statement that ‘these emissions are not well studied’ is incorrect. A number of field measurements for methane emissions from paddy fields in the Mekong Delta have been published, such as Vo et al., 2018 , and references cited in the paper. *We cited the description “not well studied” of Vo et al. The situation has not changed after a year. 3.    Introduction, 1st paragraph, Line 9: The statement that ‘this has not been well studied’ is incorrect. IPCC Guidelines provides the quantitative effects of rice straw incorporation on increasing methane emissions as a scaling factor based on a number of field measurements including those in the Mekong Delta.  *See above. We think this kind of rebuttal is not constructive. 4.    Introduction, 3rd paragraph, Lines 6–8: The reference that shows effectiveness of the strategy should be cited. *This is a matter of writing style. Showing the main finding of the work at the end of the introduction section is common. 5.    Methods, Site description: It is suggested to report the type of soil and its characteristics, because the information is essential for discussing the intensity of methane emissions from paddy fields and is not presented in the previous paper. I would suggest to report, at least, soil texture, organic carbon content, and pH, all of which are recognizes as the major factors controlling methane emissions.  *The details of the soil properties will be published in another paper. That is the reason why we don’t describe the details. We think this kind of problem that comes from closed science should be diminished in the future. 6.    Figures 1 and 2: The period of data ‘Flood’ is confusing. It is recommended to correct it with ‘Fallow flood’. *We think the word “Fallow flood” imagines a fallow paddy with ponding water. The paddy in the Mekong Delta is really a flood, a natural disaster. 7.    Results, Emission level, Lines 9–11: The emission level doubled in the 2nd crop, and tripled in the 3rd crop, compared with that in the 1st crop, then reset after the fallow flood. Same correction should be made at Discussion, Emission pattern, Lines 1–3. *You understood correctly without the phrase, “compared with that in the 1st crop”. Flood is not fallow. We think this kind of rebuttal is not constructive. 8.    Results, Emission level, Lines 13–: The total emission during the fallow flood should be higher … *We cannot agree to use the term. 9.    Results, Emission level, Lines 13–15: Why the result was not consistent to the ‘previous’ report. Please discuss it. *That is in the discussions section. The reset of emission levels after the annual flood means that the rice straw is decomposed without methanogenesis in water because the water includes dissolved oxygen. 10.    Results, Emission pattern, Lines 1–11: This statement is not the results in this study. Therefore, it should be moved to Discussion. Also, the difference of data in ‘previous’ study and this one should be clarified. *Generally, “what the data are” is describes in the results section; instead “what the data meaning” is describes in the discussions sections. According to these criteria, Lines 1-11 is suitable for the results section.  Understanding from the ‘previous’ paper , the ‘previous’ study reported the results of experiments during 2016 and 2017, whereas this study during 2011 and 2016. If it is correct, using the term ‘previous’ is not appropriate. *Only published studies can cite in the paper. They are called previous studies, not future studies. We think this kind of rebuttal is not constructive. 11.    Discussion, 2nd paragraph, Line 6: no methane emission -> little methane emission *Theoretically and practically "no" but we follow your recommendation for avoiding unconstructive rebuttal. Thank you. 4 is usual in the studied areas but no scientific evidence is shown in context.I still have concerns about the accuracy of the methodology applied for this work since the result is double the maximum value given by prior studies conducted in the same region. Though the author is convinced that extremely high CH Furthermore, the suggestion given by the authors on the decomposing rice straw in flooding field may not be feasible due to a lower gain of the farmers. The authors are convinced that the yield in the tripled crop is low, and the farmers will have much more profit by practising organic farming. This discussion is out of the ring because there is no evidence on rice yield, and organic farming is out of the scope of this work.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?NoIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?NoReviewer Expertise:Environmental EngineerI confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. 1) MethodologyWe followed the standard method so replication by others is capable. As you know,  to say overestimate requires grounds; however, data for methane emission in triple cropping rice is little. Note conditions of the reference we indicate are milder than that of the present study. We think the discussion should start waiting for more data.Importantly, the theme of this brief report is not the emission levels but is the pattern, especially the role of the flood period reducing methane emission. They are not affected by whether we overestimated or underestimated. 2) DiscussionsWe guess that you might be confusing the personal response and the manuscript because of the system. That is actually "out of the ring".We hope you agree with the above explanations. https://www.naro.affrc.go.jp/org/warc/research_results/skk_seika/h06/94017-z1.jpg). The total amount roughly estimated about 2000 kg CH4 ha-1 crop-1. The result obtained under the condition of 5 Mg of wheat straw and 6 Mg of rice straw. Wheat straw is rapidly decomposed than rice straw. The fresh rice straw in the Mekon Delta triple-cropping rice is considered the middle of those organic materials. We added the information of the quantity of applied rice straw to the revised manuscript. That is about 9 Mg per crop. We think this additional information provides enough reason to understand the high emission in our results.We found an example of high emission in Japan . Other factors such as rice varieties, weather, fertilization... should be discussed. In this case, these factors differed among seasons, why did only straw incorporation influence on CH4 emissions?The authors just explained the difference of CHConclusion: 4 emission increase being due to straw incorporation is not clear. As above commented, the conclusion on CHIs the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?PartlyAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:Low carbon rice productionI confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. Thank you very much for giving valuable comments.1. Introduction: a general information in order to explain this study is a representativeThank you. We added.2. Methods2-1. Site description:The sentence was improved to clarify that the present study was an observation of typical farmer’s paddies mentioned in the introduction (including rice straw treatment).2-2. Farmers practices:Thank you. We added the reference. The height of the stubble is about 30 cm. The daily average water levels were monitored with water level loggers at the corner of the fields; the average levels were 2.0 cm (−0.6 to 6.1 cm) until drained (the data will be published in another paper).2-3. Methane measurement:Thank you. We added.3. Statistical analysis:Figure 1 is clear enough to omit ANOVA (see the standard deviation (not SE)).4. Discussion:The information on straw incorporation in the observed fields is mentioned in the introduction. Rice straw incorporation enhances methane emission. We added a referred to our previous study that is a kind of short review of the effect of straw incorporation. 1996 IPCC Guidelines for National Greenhouse Gas Inventories: Reference Manual. The study on triple rice cropping in the Mekong River Delta is quite interesting since few studies carried on such the cropping system, but usually estimating the total flux based upon one single cropping experiment.The idea of estimating methane emissions from rice paddy fields is not novel. Many publications, including those conducted in SE Asia, have been widely accepted, such that collected and reported in the My first significant concern in this work is involved with the methodology of methane sampling and analysis. The closed chamber method used in this study  had not yet been validated with other traditional closed chamber studies. Furthermore, methane emission using this method seems to return significantly higher methane emissions compared to those emissions reported worldwide in the IPCC report. Since very much high emission rates can result in significantly overestimating methane emissions from the SE Asia region, I suggest the authors carefully discuss the reliability of the proposed method in comparison to the traditional method. My last concern is on the suggestions given by the authors. They claim that decomposing rice straw in paddy surface-water (nonrice period) is an effective method to reduce methane emissions. This suggestion is not conforming to the fact that the wetland system is a significant source of methane emission. I think the author could mean lower methane emission during the nonrice flooding period, but the conclusion written in the manuscript is not clear that way. Although, I think the conclusion given by the authors is not feasible since promoting long-term nonrice flooding instead of rice cropping could mean lower rice yield.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?NoIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?NoReviewer Expertise:NAI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Thank you for giving valuable comments for improving our manuscript.1. The methodology of methane sampling and analysis.Our methodology is the traditional method and there are high emission data in An Giang province. The water management conditions are better than our site because of the full-dike system. Thus, we think our data are reliable. We added the explanations.2. Suggestion by authorsWe agree with you that the wetland system is a significant source of methane emission. We also agree with you that the methane emission in the paddy field is extremely high compared to the simple wetland. Our finding is that the cause of the high emission in the paddy field is the incorporation of rice straws. The recent spread of combine harvesting decreases the need for rice straw burning. The methane emission will increase much more. Therefore, decreasing the methane emission of the paddy field to the levels of the simple wetland is still significant according to the data. Our suggestion is directly led by the results of the present study; although there are many other indirect options.J Environ Manage. 2018). However, utilizing rice straw enables organic farming and that brings much profit by the high unit price. We are trying to establish cultivation practice. Furthermore, using the ratooning triple cropping is also possible.For the yield of rice, we think by the profit. A recent study reported that the profit of triple rice is only 6% higher than double cropping (


The authors wish to make the following corrections to their paper :In the abstract and introduction section, the words “gram negative” should be replaced with “Gram positive” in first sentence.In Section 6, the first line of the second paragraph, the second word should be replaced with “laboratory evolved resistance”. In the third sentence of same paragraph, reference 72 in the original paper should be replaced with reference [In the third paragraph of this section, sentence five should be replaced with “Instead, a low proteolytic activity was found in resistant insects”. The last reference in this paragraph  should be replaced by reference  in this In the fourth paragraph of this section, the first line should be replaced with “no cross resistance to Vip3C has been observed in insects of different species, previously found to be resistant to Cry1A, Cry2Ab, Dipel (Mixture of Cry1 and Cry2)”. The third sentence of this paragraph should be replaced with “The biochemical basis of resistance could not be established by the down regulation of membrane bound alkaline phosphatase (mALP) isoform HvmALP1, observed in Vip3 resistant insects, and results does not support it to be the functional receptor of Vip3”.The reference in the second paragraph of Section 9.1 and the seventh row of Table 2  should be replaced by reference  in this Toxins by this change. The manuscript will be updated and the original will remain online on the article webpage. We have also rearranged all references and citations according to the correct order. We apologize for any inconvenience caused to our readers.We apologize for any inconvenience caused to readers of


DON). The experimental pigs were divided equally in a control group and three DON-challenged groups. Pigs in each of the challenged groups received a diet contaminated with DON for 7 days early on (from 113 to 119 days of age), later on (from 134 to 140 days of age) or in both periods of the experiment. Results showed that the target feed intake trajectory of each pig could be estimated independently of the challenge. The procedure also estimated relatively accurately the times when DON was given to each challenged group. Results of the quantification of the feed intake response indicated that age and previous exposure to DON have an effect on the resilience capacity of the animals. The correlation between resistance and resilience traits was modest, indicating that these are different elements of robustness. The feed intake analysis procedure proved its capacity to detect and quantify the response of animals to perturbations, and the resulting response traits can potentially be used in breeding strategies.Quantifying robustness of farm animals is essential before it can be implemented in breeding and management strategies. A generic modelling and data analysis procedure was developed to quantify the feed intake response of growing pigs to perturbations in terms of resistance and resilience. The objective of this study was to apply this procedure to quantify these traits in 155 pigs from an experiment where they received diets with or without cereals contaminated with the mycotoxin deoxynivalenol ( The feed intake analysis procedure shows its capacity to detect and quantify the feed intake response of growing pigs to a known perturbation and characterise these as resistance and resilience traits. These traits can be a potential source for genetic selection to breed animals for enhanced robustness.et al., et al.  has been of great interest in livestock production, especially through genetic selection Knap, . A prere, et al. ). Animal et al., .et al., et al.  can now be recorded at the individual level and with a very high frequency. Information extracted from this type of data has shown to be useful to characterise individual animal resilience  can have a profound effect on pigs due to their limited metabolic capacity to detoxify DON  and three DON-challenged groups . Pigs from group CC received a normal finishing diet throughout the study. Pigs from challenged groups also received the normal diet except during the challenge periods. The challenge periods lasted 7 days each during which pigs received a DON-contaminated diet. Pigs from group DC received a DON-contaminated diet early on in the experiment  and pigs from group CD received the DON-contaminated diet later on in the experiment . Pigs from group DD received the DON-contaminated diet during both aforementioned periods. All pigs were kept in the same room throughout the experiment. During the challenge periods, challenged and non-challenged pigs were kept in two separated zones to avoid cross-contaminations by faeces and urine. Feed was provided ad libitum during the experiment. Feed intake of individual pigs was recorded by automatic feeding stations and was computed on a daily basis.Data from an experiment about the impact of DON on the feed intake of growing pigs were used  rather than the daily feed intake (DFI) is used to detect perturbations in this procedure. The detection of perturbations is based on the hypothesis that there is a target trajectory curve of CFI (target CFI) that a pig desires to consume in a non-perturbed state. As a result of a perturbing factor, the CFI of the pig will deviate from the target CFI. Once the perturbing factor is over, the pig will try to regain its target CFI through compensatory feed intake. In the data analysis procedure, the target CFI was estimated by repeatedly fitting a polynomial function to CFI data in combination with the (temporary) elimination of data that lie below the fitted curve . Then, a B-spline regression was used to fit a polynomial function to deviations from the target CFI. Information extracted from the B-spline function was used to estimate the start of each deviation and the time at which the difference between the CFI and the target CFI reached a maximum value. This maximum deviation corresponds to the point at which the pig starts to recover from a perturbation to regain its target CFI.A data analysis and modelling procedure was developed to quantify the feed intake response of growing pigs to perturbations in terms of resistance and resilience (Nguyen-Ba Ratio(t)) is used as the driving force for a resilience mechanism that limits the negative effect of the perturbing factor. As soon as the perturbing factor is over, its negative effect on DFI disappears, but the resilience mechanism remains active. This results in compensatory feed intake that allows the CFI to approach the target CFI. The resilience and compensatory feed intake capacity of the animal are characterised by the parameter k2.The second step quantifies the animal’s response to a perturbation. It is hypothesised that a perturbing factor has an immediate and constant negative effect on DFI that can be characterised by three parameters: t_start, t_stop and k1. The first two parameters indicate the time when a perturbation starts and ends, whereas k1 refers to the immediate and constant reduction in DFI at the start of the perturbation. The reduction in DFI will cause the CFI to deviate from the target CFI. The ratio between the CFI and the target CFI  of distribution of the DON-contaminated diet, these criteria were not applied here. Any period during which the CFI deviated from the target CFI was characterised by the start time, the magnitude of the deviation and the duration .et al., The Ratio(t) defines the intensity of the resilience mechanism, which varies with time. For example, the CFI will be small at an early stage of life and a small reduction in DFI will result in a considerable reduction in Ratio(t). At later stages of life, the CFI will be much larger and the same perturbation will have little impact on Ratio(t). Ignoring the time dependency of Ratio(t) will lead to a biased estimation of k2. The original procedure was therefore modified to calculate Ratio(t) between CFI and the target CFI since the onset of the perturbation, and not since the start of the measurements. Equation  shows thwhere ‘t’i(t)’ is the dynamic change in CFI at time ‘t’ when the pig responds to a perturbation i  and ‘Ratioi(t)’ represents the ratio associated with perturbation i as described in equation (i(t)’. The sum of the changes relative to the target DFI results in the actual DFI as:Pigs in the group DD received the DON challenge twice. Each perturbation was modelled with independent resistance and resilience mechanisms as shown in Figure i(t) will be negative during the period of the perturbing factor and positive thereafter. The independence of the mechanisms of disturbance and recovery means that an animal may be recovering from the first challenge (through compensatory DFI) while, at the same time, it is affected by another challenge resulting in a reduction in DFI.The value of PerturbationBecause the change in DFI is constant during the period when the DON-contaminated diets are distributed, two other traits were estimated. The constant reduction in DFI during the DON challenge resulting from the resistance and resilience mechanisms can be calculated as k3 = k1/(1 + k2). Likewise, the instantaneous increase in DFI once the feeding of the DON-contaminated diet stops is given by k4 = k1 × k2/(1 + k2).In the original procedure, all four parameters of the perturbation model  were estimated. With the current dataset, it appeared difficult to estimate all these parameters, because the period of distributing the DON-contaminated diet lasted only 7 days. For group DD, this would require the estimation of 11 parameters and, with 55 DFI observations, this can easily lead to an overparameterisation of the model. It was therefore decided to fix t_start and t_stop at the start and end times of the distribution of the DON-contaminated diets.Parameter estimates for the target CFI and results from the B-spline functions were compared among the four groups to evaluate the capacity of the procedure to detect perturbations. The quantification of the response to DON challenges was carried out in the three challenged groups . Since the parameters t_start and t_stop were fixed, only the resistance and resilience parameters were estimated. The k3 is the constant reduction in DFI during the perturbation and is easier to interpret than k1. The model was therefore parameterised to estimate k2 and k3, and k1 and k4 were calculated from these parameter estimates.http://cran.r-project.org/). The optimisation was performed by the non-linear function ‘nlsLM’ of the package ‘minpack.lm’. To characterise the pig’s response to a perturbation, equations  0, CFImid-point and CFIlast) and the average daily feed intake (ADFI) were compared among the four groups , the estimation procedure did not converge and data for these pigs were not considered further in the analysis.The estimated model parameters are given in Table v. 0.42 for group CD; P = 0.39). However, pigs those challenged early in life had a significant lower value of k2 than those challenged later in life .The effect of age or BW can be assessed by comparing the results of pigs receiving the DON-contaminated diet early on  with those of pigs receiving the DON challenge for the first time later on in life . For k3, no difference was found between the early and late DON challenge  and only tended to differ from zero for the late challenge period (P = 0.08).The correlations between k2 and k3 for the two DON challenge periods are given in Figure The capacity of an animal to minimise the effect of environmental perturbations and to quickly retrieve its pre-perturbed condition, usually termed resistance and resilience, are important elements in sustainable livestock production. The complex and dynamic nature of the mechanisms of animal’s response to a perturbation makes modelling a promising approach to propose and to quantify the underlying mechanisms. This study demonstrates that a modelling and data analysis procedure can be applied to characterise resistance and resilience traits of animals, allowing to identify variability among growing pigs in their feed intake response to a DON-contaminated diet.et al., et al., et al., Determining the production potential of an animal is important for animal breeding but can be difficult to estimate because deviations of this potential can occur due to disturbances, resulting in the actually measured production trait  than for a rate variable (kg of feed/day). The notion of a target is also represented in growth models such as the logistic or Gompertz functions, in which the growth rate is a function of the target mature BW. Revilla et al.  used thiad libitum after 1 year, the previously restricted pigs had initially the same growth rate as those that were not restricted, but stopped growing at the same chronological age as the non-restricted pigs. This indicates that restricted pigs could not reach the same target mature BW as the control group (or that they had changed their target mature BW).The assumption of the existence of a target trajectory that the animal seeks to attain is debatable. There may be situations in which the animal responds to a perturbation but where it will not (or cannot) seek to regain the target trajectory. A classic example of this is the study of Lister and McCance  who restThe start time and time required for the maximum deviation estimated by the procedure corresponded reasonably well to the actual start and the end of DON challenge. The relatively short challenge period of 7 days in combination with a perturbation model with potentially four parameters could lead to difficulties to estimate the model parameters and it was therefore decided to fix the t_start and t_tstop at the actual distribution times of the DON-contaminated diet. Although these time points were close to the corresponding parameters estimated by the procedure, there were cases where the procedure indicated that the perturbation started before the distribution of the DON-contaminated diet . This may be due to another unidentified perturbing factor not related to the experiment.et al, Fixing the start and end times of perturbation to the times during which the DON-contaminated diet was distributed does not allow to estimate a ‘lag time’ during which the animal is exposed but does not respond to the perturbing factor ) is used as a driving force for the resilience mechanism in the model. As indicated before, we have changed the time point from whereon Ratio(t) was determined. This change has consequences on the simulated response during the perturbation, but it also has implications on the interpretation of the model in terms of resistance and resilience. The k1 is seen as the immediate and constant response to a perturbation , which is counteracted by the resilience parameter k2. In the original approach, this resulted in that the reduction in DFI during the perturbation gradually diminished because of the two mechanisms. This gradual decrease was provoked by the time dependency of Ratio(t) that also caused that estimates of k2 became time-dependent. This issue was solved by determining Ratio(t) from the start of each perturbation, which results in a constant reduction in DFI during the perturbing period (k3). The k3 is thus to be interpreted as the result of a constant resistance mechanism (k1) and a constant resilience mechanism (k4). The k4 also reflects the degree of compensatory feed intake over and above the target DFI at t_tstop. Although k3 is to some extent ‘observable’ in DFI data, this is not the case for k1. There were a number of cases where both k1 and k4 exceeded 100%, with values of k3 in the 0% to 100% range. Values greater than 100% for k1 are difficult to interpret biologically because this would mean that the animal tries to have a negative DFI. Values greater than 100% are possible for k4 if the animal is capable to double its DFI during compensatory feed intake. Rather than interpreting k3 in terms of k1 and k4, k3 can also be interpreted by itself, implying that resistance is the only mechanism during the perturbation and that resilience only starts once the perturbation is over (through k2 or k4).et al. . Pigs that had received the DON-contaminated diet early in life were less affected by receiving this diet again later on compared with those that received it for the first time and they also tended to recover faster .Parameters estimated from the model confirmed findings of the experiment  was greater for the late-challenged pigs  compared to the early challenged pigs. Gut capacity is often assumed to be a limiting factor for feed intake in young pigs and gut capacity increases with BW (Nyachoti et al., et al., et al., et al. (et al., et al., From the effects of both age and repeated exposure to DON, it is tempting to speculate that the adaptation of pigs relies more on resilience than on resistance mechanisms. The immune system is one of the major targets of mycotoxins (Pierron , et al.  caused a et al.,  and inhiConsiderable variation among pigs in their response to a DON-contaminated diet was observed in this study Figure . Bishop et al. (This study showed the possibility to apply the model proposed by Nguyen-Ba et al.  to situa


This paper presents a strategy to cooperatively enhance the vehicular localization in vehicle-to-everything (V2X) networks by exchanges and updates of local data in a consensus-based manner. Where each vehicle in the network can obtain its location estimate despite its possible inaccuracy, the proposed strategy takes advantage of the abundance of the local estimates to improve the overall accuracy. During the execution of the strategy, vehicles exchange each other’s inter-vehicular relationship pertaining to measured distances and angles in order to update their own estimates. The iteration of the update rules leads to averaging out the measurement errors within the network, resulting in all vehicles’ localization error to retain similar magnitudes and orientations with respect to the ground truth locations. Furthermore, the estimate error of the anchor—the vehicle with the most reliable localization performance—is temporarily aggravated through the iteration. Such circumstances are exploited to simultaneously counteract the estimate errors and effectively improve the localization performance. Simulated experiments are conducted in order to observe the nature and its effects of the operations. The outcomes of the experiments and analysis of the protocol suggest that the presented technique successfully enhances the localization performances, while making additional insights regarding performance according to environmental changes and different implementation techniques. The realization of autonomous vehicular networks has been rendered achievable and imminent due to the recent advancements in various communication application areas, including fifth generation (5G) mobile communication and millimeter-wave (mmWave) technologies . To ensuCooperative localization can be realized in centralized or distributed manners . The cenTo that end, distributed localization techniques with data-driven parameter estimation, such as maximum a posterior estimation ,6,7,8, MTo overcome these challenges, this work aims at a simple strategy of improving the accuracy of vehicular localization. The strategy is composed of two main steps—updates based on consensus and compensation. In the first half of the update phase, individual vehicles repeatedly, but not necessarily synchronously, exchange and update their location estimates in a consensus-based manner. The consensus-based protocol averages the local estimates by exchanging location data and measuring relative measurement with respect to each other. The iterative updates thus cause all neighboring vehicles to possess similar magnitudes and orientations of the localization error. Since the repetitive updates average out the local estimate errors, it is noticeable that the localization of the best-performing vehicle, called anchor, is bound to degrade. Such an observation is taken into advantage in the second half, the compensation phase, of the proposed strategy. In the compensation step, the homogenized measurement errors are significantly removed by counteracting the degradation of the location estimate of the best-performing vehicle among the neighboring vehicles. The entailed computations are maintained as simple as basic arithmetic operations and evaluation of d (CRLB) .An uncomplicated strategy to enhance localization performance in vehicular networks is constructed. The strategy involves the exchange of local data and the exploitation of a superior anchor vehicle within the vehicular network. Using local estimates of different qualities, the proposed strategy enhances the overall accuracy of all vehicles’ localization to that of the anchor. The execution of the protocol does not involve a central manager, thus greatly improving the adaptability of the protocol to networks of different scales.Mathematical formulations for the analyses of the different stages of the proposed strategy are made. Despite the computational simplicity, the analytically found optimal estimator efficiency is ultimately achieved in terms of CRLB.Visual representations of the experiments based on 3GPP TR 37.885 urban scenario specifications are provided and discussed. The effects of the execution of the proposed strategy are observed under diverse scenarios. Comparisons to centralized localization are also made in order to show the effectiveness of the distributed protocol for the intended environments.The major contributions of the paper are summarized as:The remaining parts of the paper are organized as follows—In a local vehicular ad-hoc network, Sidelink  is deploThe ground truth position of vehicle measured ,23. In pi, with its position denoted by The strategy for vehicles to cooperatively improve the localization accuracy proceeds in two separate steps: consensus-based updates and compensation. Each step is respectively discussed in detail in the following subsections.The first step of the strategy is consensus-based updates. The location estimates of the vehicles are exchanged in a consensus-based and iterative manner. Prior to the initialization of the update, an individual vehicle in the network performs the self-localization. The resulting location estimate is exchanged with each other after the initial measurement is made. These exchanges are not necessarily made in a synchronous manner but only for pairs with pairwise connection available in the network. With the exchanged information at hand, the measurements of distance and AoA with respect to each neighboring vehicle are available. With the collected measurements, new estimates can be calculated by combining the neighboring vehicles’ location estimates and the pairs of distance and AoA with respect to the corresponding partner. In this manner, one new location estimate can be obtained for each neighboring vehicle. If each of t is found in a linear combination of four different types of the measurement noises. Through such decomposition, the localization error at time t can be expressed as weighted sums of four different types of noises, as For each update, new location estimate m-by-n zero matrix. In a fully connected network, Since the sensory noise levels nth power of The resulting linear system described by –6) sugg sugg6) snth power of Noting that t, asTo observe particular values of weights The above expressions show that the update rules on self-localization noises In general cases where the self-localization and pair-wise measurement noises occur in random directions, the increase of ld Ch as∥pv(t)−pvAs discussed in the preceding subsection, the noises pertaining to the pairwise measurements steadily increase as the updates are repeated. While this causes the overall magnitude of the localization error to increase, similarities between the remaining localization errors are made. The compensation is designed to counteract the accumulated error by taking advantage of such similarities and the anchor’s superior localization performance.If the measurement noise has zero mean, the magnitude of the average of the noises is less significant compared to many of the vehicles’ innate noises since noises in the different directions cancel out upon the addition. Since the agents have relatively low measurement accuracy, the agents’ localization estimates become reliable after the consensus-based updates. On the contrary, the anchor initially possesses more accurate location estimate than the agents. During the updates, the anchor receives relatively inaccurate measurements from its neighbors, thus resulting with the aggravated estimate after the updates. These characteristics can be manipulated by undoing the updates of all vehicles with respect to the anchor. In other words, the vehicles’ location estimates can be compensated by Continuing from the analysis of the previous subsection, the compensated estimate of vehicle With the above expression of the estimate, the CRLB of the estimator can be found asThe corresponding Fischer information The resulting CRLB in  indicateIn the compensation phase, the anchor is responsible for the broadcast of the compensation information to the network. However, for a single broadcast to suffice, the connections among all pairs of vehicles are required. Some vehicles nevertheless may not be able to successfully receive information from the anchor because of the lack of direct connections. Furthermore, temporary connection malfunction between the anchor and the agents causes the failure in the compensation. In the current description of the proposed strategy, the vehicles postpone the next update until other vehicles receive the compensation successfully. Forcing a synchronous operation in such a way diminishes the purpose of the distributed algorithm.Algorithm 1 Strategy of improvement of localization of   1: At time   2: Measure while   with meaWith the adoption of the practical implementation, each iteration of the update includes a portion of the compensation. When the update is halted by the convergence of the estimates, all portions of the compensation is conveyed to all vehicles in the network. If the practical implementation of the proposed strategy is applied under the identical system settings, the estimates therefore converge to the ones shown in For the same test case, the reduction of the localization error at each step is shown in The experiment on specific setup of the previous section poses questions regarding how changes in the system setup affects the performance of the localization strategy. For comprehensive comparison of the effect of the proposed strategy under diverse circumstances, the improvement factor (IF) is introduced asUnder this definition, While To observe whether the proposed strategy achieves the optimal performance, The MSE of the proposed strategy under communication setbacks are also compared with the CRLB. In particular, results under A strategy to improve the accuracy of the localization estimate in V2X networks in a consensus-based manner is developed and analyzed. Furthermore, a theoretically intuitive two-step implementation of the proposed strategy is presented and compared in terms of the protocol and the accuracy. The expected accuracy of each step of the strategy is analyzed and the CRLB of the resulting estimator is obtained. While the computations of the strategy are kept very undemanding, the estimator nevertheless achieves its optimum given by the CRLB. The time requirement to fulfill the localization enhancement is thus mainly determined by the propagation delay adjusted by a threshold to the communication distance. Achievement of the optimal estimator is verified by the simulation results under various configurations. Additional insights on the performance changes under various setups are made. With reasonable amount of handicaps, the proposed strategy deviates from the optimum but yet successfully enhances the localization accuracy. The decision making upon the employment of the proposed strategy based on the comparison with the initial MSE is also investigated.


We expect these results to help others who are planning multicentre clinical trials in the UK. Ethical approval from NRES Committee South West (IRAS number 225959).When planning a multicentre clinical trial, it can be difficult to predict the time needed to open individual sites, and this in turn impacts on the total number of sites needed, the budget and the time frame for a clinical trial to be delivered successfully. This is of particular importance for funding applications with a limited time frame and budget such as NIHR RfPB. It is more efficient and cost-effective to open the total number of sites needed at the outset of a trial, rather than to respond later to slow site opening and recruitment. Here, we share our experience of successfully delivering a multicentre clinical trial for a rare disease within a limited time frame and budget by approximately doubling the number of sites initially predicted to be needed. We initially predicted 20 sites would be needed to deliver the clinical trial, but early on in the trial, the number of sites was more than doubled to allow successful recruitment of the target sample size within the desired time frame. Of the 48 ethically approved sites, the median time from ethical approval of a site to opening for recruitment was 182 days  and ranged from 18 to 613 days. In four (9%) of these sites, part of the delay was due to pharmacy sign off not being given when R&D had issued capacity and capability (C&C). Delays due to pharmacy sign off varied from 10 days to over 3 months delay in two sites (94 days and 102 days). A mathematical solution to the problem of planning a study with a short recruitment window has been given to support the planning and costing of grants with fixed time constraints: number of sites = 2017-001171-23. Registered on 26 June 2017EudraCT Number  Allowing for 3 months study set-up, 12 months patient follow-up, 3 months data cleaning and analysis and 3 months write up, this leaves only 15 months for site set-up and patient recruitment. Although grants often estimate 3 months to set up and open sites in the UK, it has been unclear whether this is realistic due to the number of processes required. In the UK, a central study set up includes ethics and regulatory approval, study documents including protocol, sponsor and database set up as well as formation of trial management groups. Site set up and opening requirements include capacity and capability sign off, pharmacy approval, staff delegation logs and site initiation visits.Grant applications made to the NIHR Research for Patient Benefit (RfPB) funding stream may be for a maximum total duration of 3 years from start to finish (n = 120). The grant application included an initial estimation that 20 sites would be needed to achieve this sample size, allowing 3 months to set up and open these sites and 15 months to recruit patients. Here, we demonstrate why the actual number of sites needed was far greater than anticipated due to the longer time frame needed to open sites, which was highly variable and rarely within 3 months. Early on in the trial, the number of sites was more than doubled to allow successful recruitment of the target sample size within the desired time frame. These results may help others when planning the time frame and number of sites needed for a multicentre clinical trial in the UK.We successfully applied for NIHR RfPB funding for a multicentre-randomised controlled trial in patients with immune thrombocytopenia (ITP) . As thisFollowing ethical approval, all sites were sent the trial paperwork and capacity and capability sign off was requested. In addition, pharmacy sign off and delegation logs were sought. The site initiation visits were performed remotely, enabling flexible and timely availability from the trial team. The sponsor issued permission to the co-ordinating trials unit to proceed with opening recruitment at each site, once it was satisfied that all the necessary study-wide actions had been undertaken prior to the first site opening to recruitment. Site recruitment was monitored by the overseeing trials unit. Each month, sites provided screening reports, and all Trial Management Groups were updated on screening and recruitment numbers, with comparison to projected target recruitment. Non-recruiting sites were contacted personally by the chief investigator, and regular newsletters were sent to sites with information about recruitment rates.The time it took from formal ethical approval of participating sites to being fully open to recruitment has been plotted using a Kaplan-Meier curve. The Kaplan-Meier was used to produce the median delay with 95% confidence intervals. We also looked at the time to the recruitment of the first patient for all sites that were open to recruitment. In each case, sites that did not open before the study closed or sites which did not recruit before the study closed had their data censored at that point.For some sites, local confirmation of C&C and the green light from the sponsor was given prior to pharmacy sign off and the proportion of sites delayed by this, and the time delay this produced has also been summarised.A mathematical solution to the problem of planning a study with a short recruitment window has been given to support the planning and costing of grants with fixed time constraints. The formula is given in the last paragraph of the “At the stage of funding application, we had estimated that 20 sites would be needed to achieve a recruitment of 120 patients within 15 months. Initially, ethical approval was sought for 29 sites to allow recruitment contingency, and we received ethical permission from these hospitals to be participating sites on 12 June 2017. Following this, to boost recruitment further, we added another two sites in September 2017, 10 November 2017, 6 January 2018 and the final one in June 2018.Of the total 48 sites included in the ethics submissions, 43 (90%) opened to recruitment, one of which was closed to recruitment a month later due to a change in PI who declined to sign the delegation log. The remaining five sites failed to open for a variety of reasons: PI change, lack of staff/trial team/pharmacy capacity, restructuring and no further contact. The additional sites were set up within the initially funded grant and without extra cost to the funder. The cost of the site set up was minimised by remote site initiation visits, and within the grant, hospitals received a payment for each patient recruited. In addition, in the UK, sites receive some financial support to set up NIHR portfolio studies like this.The median time from ethical approval of a site to being open to recruitment was 182 days  and ranged from 18 to 613 days for one site that opened very close to the end date and did not recruit any patients. This is represented in the Kaplan-Meier curve in Fig. Part of the delay for 4 (9%) sites was due to pharmacy sign off not having been given before the site issued C&C. Delays due to pharmacy sign off varied from 10 days delay to over 3 months delay in two sites (94 days and 102 days).In addition, further paperwork was requested for seven trusts (16%) at which the PI changed or changed their name—one of which did not re-open to recruitment as mentioned earlier.Of the 43 open sites, 37 recruited to the study. The median time from opening to the recruitment of the first patient was 87 months [95% CI 41 to 130 days]. Only 13 of the 34 sites (35%) were able to recruit the first patient within 30 days of opening which was expected due to the rare nature of this disease.p values of 0.21 and 0.07, respectively, using the log rank test). When these two delays were combined, the resulting total time to the recruitment of the first patient at London sites had a median time of 427 days compared with non-London sites of 261 days (p = 0.045) as seen in Fig. Compared to the rest of the UK, the six sites based in London were slower to open (median of 242 days) and to recruit the first patient (median of 150 days) although this did not reach statistical significance  = 180 which is 75% of the original prediction.To compensate for an unexpectedly slow set-up, additional sites are usually added in a later ethics amendment. Setting these sites up later means that their available recruitment window is shortened by both a 6-month latency in recognising the need to increase the number of sites and a 6-month latency in time to being open to recruitment. Therefore, to make up the 25% lost capacity in a 15-month recruitment window , a study would need to recruit an additional 50% more sites (60/(15 − 6 − 6) = 20 sites).The most efficient method is to open additional sites from the start of the trial. Not only does this increase the potential recruitment window at sites, but it also reduces the trial team resource needed to submit additional ethical amendments and later site initiation visits. A study that needed 20 sites for 12 months would recruit 27 sites for a 15-month accrual period with the knowledge that some sites would be much slower than others to open for recruiting with an average latency of 6 months. If the accrual period is limited to 12 months, the number of sites that the study would need to involve doubles to 40.required sample size divided by ).The formula for the number of sites required that could be used to plan a future trial becomes: Large multisite clinical trials of a medicinal product can pose particular challenges when costing the grant application, owing to the significant variation in the length of time it takes sites to open to recruitment. A trial with a short recruitment window will suffer the most from delays in this process. For example, to complete a trial with a 12-month recruitment window to time and target, double the number of sites may be needed. Funders may need to be aware of the increased costs associated with the burden of obtaining additional sites or might consider allowing extensions for trials of rare diseases. In addition, close monitoring of site opening and recruitment are also essential, with proactive measures taken if the trial is behind target.