Mapping of the Susceptibility of Colombian Musaceae Lands to a Deadly Disease: Fusarium oxysporum f. sp. cubense Tropical Race 4
, Oscar Silva-Escobar 3, Antonio González-Ulloa 4, Mauricio Soto-Suarez 1 and Mónica Betancourt-Vásquez 1
Round 1
Reviewer 1 Report
The article is well written. It makes an important contribution to understanding how the disease caused by Fusarium oxysporum occurs in Colombia. The only concern that arises for me is that Colombia has a high environmental heterogeneity and the evaluation of the occurrence of Fusarium oxysporum as a function of soils, altitude and climate is a very simplified view.
Author Response
Response to Reviewer 1 Comments
Point 1: The article is well written. It makes an important contribution to understanding how the disease caused by Fusarium oxysporum occurs in Colombia. The only concern that arises for me is that Colombia has a high environmental heterogeneity and the evaluation of the occurrence of Fusarium oxysporum as a function of soils, altitude, and climate is a very simplified view.
Response 1: Thank you for your insightful review of our article. We appreciate your positive feedback on the overall quality of the writing and the contribution it makes to understanding the occurrence of Fusarium oxysporum in Colombia. We also acknowledge and understand your concern regarding the potential oversimplification of the relationship between Fusarium oxysporum occurrence and environmental factors such as soils, altitude, and climate in Colombia.
Colombia's environmental heterogeneity is indeed a significant factor to consider when studying the occurrence of any disease, including Fusarium oxysporum. The country's diverse topography, varying climatic conditions, and wide range of soil types undoubtedly play crucial roles in shaping the distribution and dynamics of pathogenic organisms. Our article aimed to provide a broad overview of the disease's occurrence, emphasizing its presence in Colombia and offering initial insights into the potential environmental factors involved.
However, we recognize that a more comprehensive understanding of the disease would benefit from a deeper exploration of the specific interactions between Fusarium oxysporum and the diverse environmental conditions found across Colombia. Future research should certainly take into account the influence of factors such as soil characteristics (e.g., pH, organic matter content, texture), altitudinal gradients, and microclimatic variations, which undoubtedly contribute to the complexity of the disease dynamics.
We encourage researchers to conduct more detailed investigations that delve into the intricate relationships between Fusarium oxysporum and the environmental heterogeneity of Colombia. Such studies could utilize advanced analytical techniques, including geospatial analysis, molecular profiling, and comprehensive field surveys to capture the nuanced interactions between the pathogen, the host plants, and the various environmental variables.
By acknowledging the limitations of our study and the importance of further research, we hope to stimulate more comprehensive investigations into the complex dynamics of Fusarium oxysporum in Colombia. This will ultimately contribute to a more refined understanding of the disease's occurrence, management strategies, and the development of targeted interventions.
Once again, we appreciate your valuable feedback, which will undoubtedly enhance the quality and impact of our research.
Reviewer 2 Report
The manuscript "Understanding the Susceptibility of Colombian Musaceae Lands to a Deadly Disease: Fusarium oxysporum f. sp. cubense Tropical Race 4" offers an excellent tool for the future monitoring of Fusarium in the Colombian territory.
I suggest a few changes:
Abstract:
please change the word paper with study, experiment, work...
please specify some of these "expert criteria" or rephrase
Introduction:
lines 40-48, please summarize all this information in a table or in a figure with the map of the territory and the percentage of harvested/production area, there are too many numbers, the texts results boring and difficult to comprehend.
lines 89-94, please clarify the objectives of the study with numbers and formulate some hypothesis/expected results
lines 99-102, please add this part with the above part about the aims of the work (line 89-94).
Materials & Methods:
lines 123-137, please specify if the precipitation and temperature data are of one year, a specific range of years, if they are an average of different years... it is not clear. Moreover the maps of the figures 1 b, c and d have different dates (2012, 2017, 2018). This part is not clear.
line 194 and "scattered" in the text, please explain better this concept of "expert knowledge", it is not a scientific criteria.
Table 2 and 3, please specify what are Ici and Isi in the captions. And, why do the drainage classes reach up to 7 if only 4 appear in the table?
Did you confirm the efficiency of this method/model using some known affected and not-affected farm?
In general in the manuscript there are too many figure/graphs, this makes the text boring and hard to follow. Please, evaluate which figures can be passed in the supplemental information section.
The text is easily understandable, it does not need linguistic revisions.
Author Response
Response to Reviewer 2 Comments
Point 1: The manuscript "Understanding the Susceptibility of Colombian Musaceae Lands to a Deadly Disease: Fusarium oxysporum f. sp. cubense Tropical Race 4" offers an excellent tool for the future monitoring of Fusarium in the Colombian territory.
Response 1: Thank you for your insightful review of our article. We appreciate your positive feedback on the overall quality of the writing and the contribution it makes to understanding the occurrence of Fusarium oxysporum in Colombia.
I suggest a few changes:
Abstract:
please change the word paper with study, experiment, work...
Response: corrected: This work
please specify some of these "expert criteria" or rephrase
Response: corrected. These criteria are typically selected based on the existing scientific literature, consultation with domain experts, and consideration of established methods for assessing soil health and disease susceptibility in banana plantations.
Introduction:
lines 40-48, please summarize all this information in a table or in a figure with the map of the territory and the percentage of harvested/production area, there are too many numbers, the texts results boring and difficult to comprehend.
Response: corrected. The information was summarized
lines 89-94, please clarify the objectives of the study with numbers and formulate some hypothesis/expected results
Response: corrected: hypothesis: Musaceae lands with certain environmental characteristics will exhibit greater susceptibility to Foc TR4. Therefore, it is expected to map and determine the percentage of lands with different degrees of susceptibility…
lines 99-102, please add this part with the above part about the aims of the work (line 89-94).
Response: corrected.
Materials & Methods:
lines 123-137, please specify if the precipitation and temperature data are of one year, a specific range of years, if they are an average of different years... it is not clear. Moreover the maps of the figures 1 b, c and d have different dates (2012, 2017, 2018). This part is not clear.
Response:
The years mentioned (2012, 2017, 2018), refer the publication year (bibliographic reference). Considering the doubt raised by the commentary: "average annual precipitation" and "average annual average temperature" were added into text, and, in addition, in Figures 1 c and d, the period with which each average corresponds was added (Average annual precipitation: 1976 – 2005; Average annual temperature: 1970 – 2000).
line 194 and "scattered" in the text, please explain better this concept of "expert knowledge", it is not a scientific criteria.
Response: Expert knowledge refers to the specialized and in-depth understanding possessed by people who have extensive experience, knowledge, and qualifications in a specific field or topic. It is derived from years of hands-on involvement, research, and study, enabling experts to possess comprehensive knowledge and a deep understanding of complex phenomena within their domain. Expert knowledge is built on a foundation of both theoretical understanding and practical application, enabling experts to provide valuable information, make informed judgments, and offer trusted solutions or advice within their area of expertise.
After obtaining the results of the expert knowledge, these results must be submitted to a scientific validation with a statistical method, in our case, the supervised method of machine learning as the algorithm for Random Forest classification, which accurately, effectively, the knowledge expert can be used to determine the susceptibility of lands.
Table 2 and 3, please specify what are Ici and Isi in the captions. And, why do the drainage classes reach up to 7 if only 4 appear in the table?
Response: corrected. Table 2 Note: the importance of climatic conditions (Ici) and Table 3, the importance of soil conditions (Isi). The drainage classes reach up to 7 in the table 3.
Did you confirm the efficiency of this method/model using some known affected and not-affected farm?
Response 1: Thanks for your comment. Very interesting indeed, the representative sample for the validation model consisted of affected and unaffected farms.
In general in the manuscript there are too many figure/graphs, this makes the text boring and hard to follow. Please, evaluate which figures can be passed in the supplemental information section.
Response 1: Thanks for the observation, the authors consider that the figures can remain in the text of the manuscript.
Reviewer 3 Report
Understanding the Susceptibility of Colombian Musaceae Lands to a Deadly Disease: Fusarium oxysporum f. sp. cubense Tropical Race 4
In this work the authors reefer to Fusarium oxysporum f sp. cubensis Tropical Race 4, Foc TR4, which can be a real threat for all the Musaceae lands in Colombia. It is known that agricultural and environmental conditions in Colombian lands where Musaceae are cultivated are favorable for the establishment and spread of this highly devastating pathogen. They demonstrate via modelling and calculations the susceptibility of Musaceae lands in Colombia to Foc TR4. Beforehand they have studied the areas by characterizing climatic, edaphic, and density factors of Musaceae productive systems in the Colombian territory, which is very diverse, and mapped the areas in Colombo with different levels of susceptibility to Foc RT4. They put in their model crucial factors such as precipitation, temperature, soil characteristics, and farming conditions that influencie disease dynamics. By their calculations methods using Random Forest they provide insight into the potential impact of Foc TR4 710 on the production of banana in Colombo.
The authors have done a very precise and profound conceptualization. They refer to current references for their methodology and investigation. Since this disease is approaching in South-American countries such as Colombia it is very important for farmers to know whether their region is susceptible and be prepared for the spread of this pathogen. This paper is very worth to be published as it provides findings that are essential for the conservation of Musaceae in Colombia.
Below there is list for some suggestions and corrections
Title: I’m just wondering whether the word ‘understanding’ really fits to the work; instead one could also write 'mapping' or something similar indicating the model-based susceptibility
Suggestions for Keywords: edaphic factors; agri-environmental suitability; predisposing factor, land management
L 09: I think you mean agri-environmental suitability
L 204: analyses
L 215: Please define the category “Importance” in tables 2 and 3, Ici Isi with is the classification, for example what does I = 15 or 7 mean? Where is this value derived from?
L 233: (equation)
L 246: ‘It’ can be deleted
L 307: zero
L489: “remote lands”
L505: you probably mean: using PCA the susceptibility classes were not distinguishable
L555-556: I suggest to stick to the abbreviations as you did before; generally, in the whole text
L558-560: I am wondering whether it is right written: in Figure 14 b the class 3 (pale blue) belongs to the highest influence and class 1 (orange) to the least influence regarding precipitation?
L634: Figure X shows; which figure do you mean by figure X?
L692: the bracket can be deleted
L851: degradation
Figures 7, 8, 11: suggestion for the title of the x-axis: Fraction of Foc TR4 susceptibility per department
Figures 12 & 13, 14: generally, I suggest to declare the figures more precise: Results of principal component analysis (PCA) or PLS-DA of what, or Random Forest classification for what? Besides, even if the text gets much longer it would be much easier for the reader to follow the figures if you would explain in the captions the abbreviations DI, DC, T, P, etc.
Author Response
Response to Reviewer 3 Comments
Point 1: In this work the authors reefer to Fusarium oxysporum f sp. cubensis Tropical Race 4, Foc TR4, which can be a real threat for all the Musaceae lands in Colombia. It is known that agricultural and environmental conditions in Colombian lands where Musaceae are cultivated are favorable for the establishment and spread of this highly devastating pathogen. They demonstrate via modelling and calculations the susceptibility of Musaceae lands in Colombia to Foc TR4. Beforehand they have studied the areas by characterizing climatic, edaphic, and density factors of Musaceae productive systems in the Colombian territory, which is very diverse, and mapped the areas in Colombo with different levels of susceptibility to Foc RT4. They put in their model crucial factors such as precipitation, temperature, soil characteristics, and farming conditions that influencie disease dynamics. By their calculations methods using Random Forest they provide insight into the potential impact of Foc TR4 710 on the production of banana in Colombo.
The authors have done a very precise and profound conceptualization. They refer to current references for their methodology and investigation. Since this disease is approaching in South-American countries such as Colombia it is very important for farmers to know whether their region is susceptible and be prepared for the spread of this pathogen. This paper is very worth to be published as it provides findings that are essential for the conservation of Musaceae in Colombia.
Response 1: Thank you for your insightful review of our article. We appreciate your positive feedback on the overall quality of the writing and the contribution it makes to understanding the occurrence of Fusarium oxysporum in Colombia.
Below there is list for some suggestions and corrections
Title: I’m just wondering whether the word ‘understanding’ really fits to the work; instead one could also write 'mapping' or something similar indicating the model-based susceptibility
Response: corrected.
Suggestions for Keywords: edaphic factors; agri-environmental suitability; predisposing factor, land management
Response: corrected.
L 09: I think you mean agri-environmental suitability
Response: corrected.
L 204: analyses
Response: corrected.
L 215: Please define the category “Importance” in tables 2 and 3, Ici Isi with is the classification, for example what does I = 15 or 7 mean? Where is this value derived from?
Response:
An explanation note was added in each table. The variable name (“importance”) was rewritten as “expert-assigned importance” (implying that it is a weighing value determined following the “expert knowledge”, previously defined in text).
L 233: (equation)
Response: corrected.
L 246: ‘It’ can be deleted
Response: corrected.
L 307: zero
Response: corrected.
L489: “remote lands”
Response: corrected.
L505: you probably mean: using PCA the susceptibility classes were not distinguishable
Response: corrected.
L555-556: I suggest to stick to the abbreviations as you did before; generally, in the whole text
Response: corrected.
L558-560: I am wondering whether it is right written: in Figure 14 b the class 3 (pale blue) belongs to the highest influence and class 1 (orange) to the least influence regarding precipitation?
Response: corrected. Class: 0 (very low), 1 (low), 2 (medium), 3 (high), 4 (very high).
L634: Figure X shows; which figure do you mean by figure X?
Response: corrected. Figure 11a
L692: the bracket can be deleted
Response: corrected.
L851: degradation
Response: corrected.
Figures 7, 8, 11: suggestion for the title of the x-axis: Fraction of Foc TR4 susceptibility per department
Response: corrected.
Figures 12 & 13, 14: generally, I suggest to declare the figures more precise: Results of principal component analysis (PCA) or PLS-DA of what, or Random Forest classification for what? Besides, even if the text gets much longer it would be much easier for the reader to follow the figures if you would explain in the captions the abbreviations DI, DC, T, P, etc.
Response: corrected. Results of principal component analysis (PCA) for dimension reduction: ….(PLS-DA) (n=1029) for distinguishing susceptibility classes and Random Forest classification (n=1029) for accuracy assessment of the susceptibility classes obtained by expert knowledge
