Review Reports - Design and Employing of a Non-Linear Response Surface Model to Predict the Microbial Loads in Anaerobic Digestion of Cow Manure: Batch Balloon Digester

Round 1

Reviewer 1 Report

1. What is the novelty of the work? Alongside the literature review provide, authors should also articulate how current work is improving upon previous efforts in the field.

2. English writing needs to be polished. Use of articles are incorrect in many places.

3. Fig. 2 is very messy. For example, it is nob obvious which y-axis one should look into for the black symbols etc.

4. What is a 'multi'-contour?

5. Legends are missing in Fig. 4.

6. Why the model always under-predicts the total bacteria counts? Please justify with physical reasoning.

Author Response

Dear Reviewer 1

Thanks for providing us with queries and comments on our manuscript. Indeed, upon implementation in our revised manuscript, it has gone a long way to add value to the overall manuscript. In line with the general comments the revised manuscript has been restructured to allow for chronology of the paper. All the major relevant introduced materials in the revised manuscript are highlighted. Also, the study contribution is also specified. Finally, the entire manuscript is edited for English language proficiency.

Specific queries or comments for Reviewer 1

REVIEWER 1

Open Review

(x) I would not like to sign my review report

( ) I would like to sign my review report

English language and style

( ) Extensive editing of English language and style required

(x) Moderate English changes required

( ) English language and style are fine/minor spell check required

( ) I don't feel qualified to judge about the English language and style

Yes Can be improved Must be improved Not applicable

Is the content succinctly described and contextualized with respect to previous and present theoretical background and empirical research (if applicable) on the topic?

( ) (x) ( ) ( )

Are all the cited references relevant to the research?

(x) ( ) ( ) ( )

Are the research design, questions, hypotheses and methods clearly stated?

( ) ( ) (x) ( )

Are the arguments and discussion of findings coherent, balanced and compelling?

( ) ( ) (x) ( )

For empirical research, are the results clearly presented?

( ) (x) ( ) ( )

Is the article adequately referenced?

( ) ( ) ( ) ( )

Are the conclusions thoroughly supported by the results presented in the article or referenced in secondary literature?

(x) ( ) ( ) ( )

Comments and Suggestions for Authors

What is the novelty of the work? Alongside the literature review provide, authors should also articulate how current work is improving upon previous efforts in the field.

Response: The novelty of the study is the employment of a statistical test known as the reliefF to rank the selected input parameters (number of days, daily slurry temperature and pH) according to the weights of importance to the output parameter (total bacteria counts). The study also utilized the developed response surface model in establishing of simulation that comprised of 2D multi-contour surface plots to show the variation in each input parameter with the predicted target while the others are held constant.

The contribution from the study in the field ranges from the ability to explicitly decouple the input variables in the developed response surface model into a 2D plots showing the variation in each predictor to the modelled output while the other input parameters are held constant. All the input parameters are capable to be categories into primary and secondary factors via the application of the reliefF test. The study also formulated a data acquisition system with no remote communication to monitor the biogas yield for the balloon digester.

Both the novelty and contribution of the study in the field of advanced monitoring in the area of data acquisition system and mathematical model development has been included in the revised manuscript.

English writing needs to be polished. Use of articles are incorrect in many places.

Response: The whole manuscript has undergone English language editing in conjunction with technical proofreading to increase the language proficiency of the revised manuscript. And the few references in the text that where not properly matching the actual references has been corrected in the revised manuscript.

Fig. 2 is very messy. For example, it is not obvious which y-axis one should look into for the black symbols etc.

Response: In light to the comment of the messy graphs on fig 2, we have decided to plot all the choosed parameters on a single y-axis to avoid any potential ambiguities. This single figure provides a better visual presentation of the variation of the output with the selected critical parameters in a bid to describe the dynamic anaerobic process occurring during the hydraulic retention time.

What is a 'multi'-contour?

Response: multi-contour referred to figurative mapping of many inputs (two or more) to a single output either in a plane or 2D surface plots. In this study, the multiple input parameters (number of days, slurry temperature and pH) and the output (model log of bacteria counts) are represented in a 2D multiple surface plots with the aid of a simulation in MATLAB derived with the developed response surface model.

Legends are missing in Fig. 4.

Response: The legend along are included in Fig. 4 of the revised manuscript.

Why the model always under-predicts the total bacteria counts? Please justify with physical reasoning.

Response: Based on the fig 5; we can conveniently confirm that the model is not under-predicting as there are sample of data points where the model under-predicts the actuals (i.e where the data points are below the continuous graph) and there are also sample data points where the model over- predict the actual (i.e where the data points are above the continuous graph). This is a perfect visual confirmation of an acceptable model as sample data set are found on both above and below the modelled curve. Therefore, the model is accurately predicting the targets with a very good determination coefficient and roots mean square error in both the case of the testing and validation sample data set.

Author Response File: Author Response.pdf

Reviewer 2 Report

See the attached

Comments for author File: Comments.pdf

Author Response

Dear Reviewer 2

Specific queries or comments for Reviewer 2

REVIEWER 2

Open Review

(x) I would not like to sign my review report

( ) I would like to sign my review report

English language and style

( ) Extensive editing of English language and style required

( ) Moderate English changes required

(x) English language and style are fine/minor spell check required

( ) I don't feel qualified to judge about the English language and style

Yes Can be improved Must be improved Not applicable

Is the content succinctly described and contextualized with respect to previous and present theoretical background and empirical research (if applicable) on the topic?

( ) ( ) (x) ( )

Are all the cited references relevant to the research?

( ) (x) ( ) ( )

Are the research design, questions, hypotheses and methods clearly stated?

( ) ( ) (x) ( )

Are the arguments and discussion of findings coherent, balanced and compelling?

( ) (x) ( ) ( )

For empirical research, are the results clearly presented?

(x) ( ) ( ) ( )

Is the article adequately referenced?

(x) ( ) ( ) ( )

Are the conclusions thoroughly supported by the results presented in the article or referenced in secondary literature?

(x) ( ) ( ) ( )

Comments and Suggestions for Authors

See the attached

Comments

Abstract:

Information such as motivation, research question, application of the study result, and areas of

further study are missing in the abstract.

Response: The abstract is word bound and just 200 words accepted, we had to exclude aspect as research question, application of the study result and future study in the abstract but these aspect are integrated into the body of the revised manuscript. In addition, research questions are derived based on the objectives of the study.

The application of the study result is the utilization of the 2D multi-contour surface plots in demonstration of the variation in each predictor (number of days, daily slurry temperature and pH) with the total bacteria counts while the others are held constant. Secondly, the used of the reliefF test to rank the predictors into primary and secondary factors depending on the weights of importance to the output parameter (log of total bacteria counts).

Recommendation for future study

Response: We have included some recommendation for future study in the revised manuscript. This includes the conduction of the experiment during the other months of the year (January to June) as ambient weather condition may influenced the biogas yield in the balloon digester. The study should also be conducted with the balloon digester charged with cow manure on a continuous mode. A study should be conducted with co-digestion (between the cow manure and other animal waste (e.g pig, since the university owned a piggery farm) as the feedstock to charge the balloon digester.

Comment: Introduction

The addition of data on global biogas generation, consumption, market value, etc can be added to

improve the introduction section.

The motivation for the study, research question, aim, and study delineation are clearly missing in

the introduction section. The last paragraph of section 1.0 does not properly capture what was

done. A subsection can be added for the research question, motivation, study aim, and study

delineation. Section 1.3 can as well be expanded.

Response: Additional materials has been included on the global biogas generation, consumption and market value in the introduction section in the revised manuscript.

A section has been included for the research questions, the aim and delineation of the study in the revised manuscript.

Aim of study: The aim of the study was to design and built a data logging acquisition system to monitor the potential biogas yield and to develop a response surface model to predict the total bacteria counts using number of days, slurry temperature and pH as the predictors. This has been added in the revised manuscript.

Motivation: Limited study has been conducted on the mathematical modelling of biogas production using balloon type digester and especially applying the non-linear surface response models. Therefore, the study exploits the prediction of potential biogas yield using a non-linear regression model known as the response surface model and a 2D multi-contour surface plots to show the variation in each predictor with the model output (predicted log of total bacteria counts) while the others are held constant.

Research questions

The following research questions can be formulated to achieve the objectives of the study,

Can data acquisition system be design and built to measure the ambient and physico-chemical parameters as well as the quality and quantity of potential biogas production in a balloon type digester?
Can a statistical test be conducted to confirm if the input parameters (number of days, slurry temperature and pH) influenced the total bacteria counts?

Can a response surface model be developed to predict the total bacteria counts in a balloon digester using the number of days, slurry temperature and pH as the predictors.

Can a 2D multi-contour surface plots be generated to simulate the variation in each of the input parameter with the model output while the rest are held constant?

Delineation of the study has been added in the revised manuscript.

The study was only conducted in one location and in one place (at the Physics research centre-university of Fort Hare, Alice campus) in South Africa and only utilized cow waste as the slurry for the balloon digester. The designed and analysis of the fabricated balloon digester was not taking into consideration in the study as the study was based on an accredited fabricated heat seal plastic domestic digester that was roll-out by Government of South Africa.

Comments

Clearly, the generation of biogas from cow manure is not new, the authors should review some recent and relevant literature on this topic and clearly expose the research gap that necessitated this study. Another subsection can be included in the literature review before section 1.3

Response: In the revised manuscript recent references has been added in the literature section on the research conducted on anaerobic digestion process using cow dung as feedstock.

Since it is a research article, and the number of pages are to be efficiently optimized, we have included some considerable references in the revised manuscript.

Comments

In section 2.1.1, rather than showing only the table, the materials used for the experiment should

be briefly described.

Response: In the revised manuscript, a brief description has been included for the materials that were used in the study and the section has been merged with experimental setup.

Comment

Section 2.2. If the samples were taken between the 26th-30th of June 2015 and the experiment was

carried out from July to December 2015, why are the authors reporting in 2022?

Response:

The first part of the work only based on the characterization of the bacteria present during the anaerobic digestion process inside the balloon digester charged with cow dung has been published in 2019. This paper has been referenced in the revised manuscript.

Comments

Table 2. I think the result of the characterization of the cow manure samples is part of the result of

this study. It should be presented in section 3. Any justification for the result presented in Table

Response

The core focused of the study is not on the characterization, and therefore we mention in table 2, just to support the fact that cow manure is biodegradable. The section 3 is focusing on the input and out parameters used in the development of the mathematical model and the validation of the developed model.

Comments

The result of the analysis of the biogas generated from the cow manure samples is not presented

by the authors. I think this becomes important when the authors mentioned the percentage of

methane and CO2 in the abstract (Line 17). The result is from which of the feedstock sample?

Response:

There results were based on the cumulative cow manure sample that was collected from same source over five consecutive days to charge the digester in a single batch mode. The analysis was based on determination of the averages of the percentage of methane and carbon-dioxide during the collection process of the biogas yield at the end of the retention time when the control valve was open. The respective sensors from the biogas analyzer were capable of sensing and measured the composition of the biogas and their percentages while the analyzer data logger stored the recorded measurement.

Comments

The authors should include some of the design parameters, considerations, analysis, and data of

the balloon digesters.

Response

No actual designed was carried out on the balloon digester as it was a customized and commercialized in the South Africa market but certified by SABS. Hence the authors only designed the concrete structure including the influent and effluent tanks, the insulation cover and the connecting tubing linking balloon digester to the biogas collecting chambers and the specific dimension of the structure is included in the revised manuscript.

Comment

The authors should bring up and include the sustainability aspect of the study to justify the

publication of the article in the journal.

Response

The sustainability aspect of the work is the harnessing of waste in the form of cow dung and converting to biogas which is a source of renewable energy and the product called digestate is used as rich fertilizer in the agricultural sector. The element of sustainability has been captured in the revised manuscript in the introduction section.

Addition introduction

An efficient balance of meeting the rising energy demand and limiting its environmental consequences is a call of concern in the 21st century [1]. Government in different countries without the exemption of South Africa have been exploring strategies in developing regulations and policies to encourage eco-friendly renewable energy generation in conjunction with conservation measures and technological innovations. However, as part of the mitigated challenges in the domain of energy production and environmental impact, South Africa has embarked on the utilization of biogas plants to produce biogas as one of the sources of renewable energy. The study focused on the designed and deployment of a data acquisition system to monitor the potential biogas yield and to develop a response surface model to predict the total bacteria counts in a balloon digester charged with cow waste.

A review on the world biogas generation over the past 10 years shows an increase of almost 90% in biogas industry with a figure of 120 GW in 2019 as opposed to 65 GW in 2010 [2]. The authors proved that in 2017, Europe contributed to 70% of the world biogas generation with an energy consumption of 64 TWh. The conclusion from the review revealed that Europe has the highest promotion rate of biogas generation while the consumption rate in India and China is maximum due to their up-to-date policies and procedures.

Research on the review of biogas plants installation and its generated electricity in Africa, shows that South Africa has the largest share of the installed biogas plants (approximately 700 plants) and only 300 of the plants have been in operation since 2007 [3]. The study predict that the installed biogas plants have the potential of generating 148 GWh electricity through appropriate investment and implementation schemes.

Reference

[1] Lu, Y., Khan, Z.A., Alvarez-Alvarado, M.S., Zhang, Y., Huang, Z. and Imran, M., 2020. A critical review of sustainable energy policies for the promotion of renewable energy sources. Sustainability, 12(12), p.5078.

[2] Abanades, S., Abbaspour, H., Ahmadi, A., Das, B., Ehyaei, M.A., Esmaeilion, F., El Haj Assad, M., Hajilounezhad, T., Jamali, D.H., Hmida, A. and Ozgoli, H.A., 2021. A critical review of biogas production and usage with legislations framework across the globe. International Journal of Environmental Science and Technology, pp.1-24.

[3] Kemausuor, F., Adaramola, M.S. and Morken, J., 2018. A review of commercial biogas systems and lessons for Africa. Energies, 11(11), p.2984.

Paper dealing bacteria characterization of the cow waste charged in a balloon digester. The work was published in 2019 and mentioned in the study. But the current study focused on the development of response surface model which is a form of nonlinear regression model to predict the total viable bacteria counts.

References

Manyi-Loh, C., Mamphweli, S., Meyer, E. and Okoh, A., 2019. Characterizing Bacteria and Methanogens in a Balloon-Type Digester Fed with Dairy Cattle Manure for Anaerobic Mono-Digestion. Polish Journal of Environmental Studies, 28(3).

Author Response File: Author Response.pdf

Reviewer 3 Report

Tangwe et al., submitted the paper entitled “Design and employing of a non-linear response surface model to predict the microbial loads in anaerobic digestion of cow manure: Single mode batch balloon digester” to publish in “Sustainability (I. F = 3.889)”. In this paper, they have predicted the microbial loads in anaerobic digestion of cow manure via non-linear response surface model with statistical approach. The work seems to be an impressive one and presentation is nice, thus can be published after addressing the queries.

1. Why the author chosen six months for data prediction? What happens after six months? How about the Earth-pit Plants in anerobic digestion?

2. Explain the variables presented in equations 5 and 6, currently it is fall short.

3. why derived models in Tables 5 to 7 have no data? Give certain explanation for the readers.

4. Resolution of figures, especially Figures 2, 4 and 5 must be improved.

5. In table 2, for standard deviations please add ± symbol, if it is applicable. How about RSD values?

6. Improve the font size of X and Y-axis of all the figures to readable fashion.

Author Response

Dear Reviewer 3

Specific queries or comments for Reviewer 3

REVIEWER 3

Open Review

( ) I would not like to sign my review report

(x) I would like to sign my review report

English language and style

( ) Extensive editing of English language and style required

( ) Moderate English changes required

(x) English language and style are fine/minor spell check required

( ) I don't feel qualified to judge about the English language and style

Yes Can be improved Must be improved Not applicable

Is the content succinctly described and contextualized with respect to previous and present theoretical background and empirical research (if applicable) on the topic?

(x) ( ) ( ) ( )

Are all the cited references relevant to the research?

(x) ( ) ( ) ( )

Are the research design, questions, hypotheses and methods clearly stated?

(x) ( ) ( ) ( )

Are the arguments and discussion of findings coherent, balanced and compelling?

(x) ( ) ( ) ( )

For empirical research, are the results clearly presented?

(x) ( ) ( ) ( )

Is the article adequately referenced?

(x) ( ) ( ) ( )

Are the conclusions thoroughly supported by the results presented in the article or referenced in secondary literature?

(x) ( ) ( ) ( )

Comments and Suggestions for Authors

Why the author chosen six months for data prediction? What happens after six months? How about the Earth-pit Plants in anaerobic digestion?

Response: The six month was equivalent to the hydraulic retention period and hence after this time the digester stop producing biogas. The digestate was discarded into a dug hole that saved as digestate’s revoir and was in term used for agriculture which is outside the scope of this study.

Response: The anaerobic digestion of the Earth-pit plant did not form any fall on the scope of this study and therefore authors have reversed comment on this specific anaerobic process in the revised manuscript.

Explain the variables presented in equations 5 and 6, currently it is fall short.

Response: In the revised manuscript, all the variables in equation 5 and 6 has been fully explained as per reviewer’s recommendation.

why derived models in Tables 5 to 7 have no data? Give certain explanation for the readers.

Response: The data set were used in the derivation of the developed mathematical model and in Tables 5 and 7, our interest is to show all the input and output parameters as well as the critical parameters (determination coefficient, p-values and root mean square errors) that were used to ascertain the accuracy of the developed model.

Resolution of figures, especially Figures 2, 4 and 5 must be improved.

Response: In the revised manuscript, the resolution of Figures 2, 4, and 5 has been improved to enhance their qualities of the figures and complied to the standard for the journal.

In table 2, for standard deviations please add ± symbol, if it is applicable. How about RSD values?

Response: In the revised manuscript, the uncertainties in the standard deviations has been included as per recommendation from the reviewer. We are using the RMSE instead of the RSD values.

Improve the font size of X and Y-axis of all the figures to readable fashion.

Response: The font size of X and Y in all the figures has been increased in the revised manuscript.

Author Response File: Author Response.pdf

Reviewer 4 Report

In this manuscript, Tangwe et al. investigated total viable bacterial counts over days, daily mean ambient temperature, and pH from a balloon-type biodigester filled with 2500 L of cow manure with a retention period of 6 months. I find this manuscript very interesting and acceptable after major revision. Here are some comments that need to be addressed.

1. The authors built a model to predict total viable counts rather than biogas production. The authors need to clarify the importance of bacterial counts for biogas production or to clarify the relationship between bacterial counts and actual biogas production.

2. In Figure 5, how did the authors create the test dataset?

3. The response surface model can accurately predict the total viable count, and the coefficient of determination, root mean square error and the p-value are 0.959, 0.197, and 0.602, respectively. From what I understand, the p-value should be low if the model is accurate. Please clarify why the p-value in your model is as high as 0.602.

4. In practice, the biogas generator is operated by regularly feeding and discharging slurry and biogas. In this study, there appears to be no slurry going in and out. Please clarify how the knowledge generated in this study guides the design of practical biogas generators.

5. In Figure 2, why is there no data recorded between day 80 and day 120? After day 120, the critical parameters changed significantly, especially the slurry temperature, pH, and log bacterial counts. Can you please discuss what the model would look like if you only considered the first 80 days of data?

Author Response

Dear Reviewer 4

Specific queries or comments for Reviewer 4

REVIEWER 4

Open Review

( ) I would not like to sign my review report

(x) I would like to sign my review report

English language and style

( ) Extensive editing of English language and style required

( ) Moderate English changes required

(x) English language and style are fine/minor spell check required

( ) I don't feel qualified to judge about the English language and style

Yes Can be improved Must be improved Not applicable

Is the content succinctly described and contextualized with respect to previous and present theoretical background and empirical research (if applicable) on the topic?

( ) (x) ( ) ( )

Are all the cited references relevant to the research?

(x) ( ) ( ) ( )

Are the research design, questions, hypotheses and methods clearly stated?

( ) (x) ( ) ( )

Are the arguments and discussion of findings coherent, balanced and compelling?

( ) (x) ( ) ( )

For empirical research, are the results clearly presented?

( ) (x) ( ) ( )

Is the article adequately referenced?

(x) ( ) ( ) ( )

Are the conclusions thoroughly supported by the results presented in the article or referenced in secondary literature?

( ) (x) ( ) ( )

Comments and Suggestions for Authors

The authors built a model to predict total viable counts rather than biogas production. The authors need to clarify the importance of bacterial counts for biogas production or to clarify the relationship between bacterial counts and actual biogas production.

Response: We agreed with the reviewer that ideally the actual biogas yield was supposed to be the output (target) for the developed model instead of the total bacteria counts. But there is a strong positive correlation between the total bacteria counts and the actual biogas production. And based on the tremendous challenge involved in collecting daily biogas yield from the balloon digester into the collection biogas chamber as opposed to collection of the daily slurry samples for the determination of the total bacteria counts. Hence, the total bacteria counts were used in the development of the mathematical model while the cumulative volume of biogas was measured and stored in the collection biogas chamber.

In Figure 5, how did the authors create the test dataset?

Response: The full dataset for the hydraulic retention time (six months) were randomly split into two data set (test data set and the validated data set) in the ratio of 60 and 40%, respectively using the random function in MATLAB.

3.The response surface model can accurately predict the total viable count, and the coefficient of determination, root mean square error and the p-value are 0.959, 0.197, and 0.602, respectively. From what I understand, the p-value should be low if the model is accurate. Please clarify why the p-value in your model is as high as 0.602.

Response: The p-value is the probability from a null-hypothesis test which can be used to verify if any mean significant difference exists between any two groups. And is a powerful parameter when using the one-way analysis of variance (ANOVA) test to check whether a mean significant difference exist among groups. Generally, performing the one-way ANOVA test between two groups (actual bacterial counts for the test dataset and model outputs for the test dataset) with a 95% confidence level, a p-value < 0.05, implies there is a mean significant difference between the two groups and the model is not accurately predicting the measured output. Alternatively, a p-value > 0.05, implies there is no significant difference between the two groups. Therefore, the model is accurately predicting the actual total bacteria counts and both the actual and predicted total bacteria counts are very closed to each other. And the higher the p-value (p-value =0.62) is a strong indication that the predicted total bacteria counts mimic the actual total bacteria counts.

In practice, the biogas generator is operated by regularly feeding and discharging slurry and biogas. In this study, there appears to be no slurry going in and out. Please clarify how the knowledge generated in this study guides the design of practical biogas generators.

Response: There are two modes of charging a biodigester which is either continuous mode or single mode. In this study, the single mode was used and as a future work, we intend to use the continuous mode in the charging process and make a comparison of the performance of the system based on the single and continuous modes of charging.

In Figure 2, why is there no data recorded between day 80 and day 120? After day 120, the critical parameters changed significantly, especially the slurry temperature, pH, and log bacterial counts. Can you please discuss what the model would look like if you only considered the first 80 days of data?

Response:

There are data between day 80 and day 120, and we randomly choose the data points to show on the graphs just to avoid messy plots, but the line graphs were traced following the data points as presented in Figure 2 of the revised manuscript.

After day 120, the sudden changed in the critical parameter was influenced by the ambient weather temperature which starts to decrease and affected both slurry temperature and pH. Also, as time progresses, the amount of biodegradable matter in the slurry decreases leading to lower total bacteria counts.

Response: The used of the developed model by considering just the first 80 days may failed to describe or forecast the dynamics of the anaerobic digestion process occurring in the digester (total viable bacteria counts) as the duration have not cover the full retention time for the anaerobic digestion. Therefore for better prediction with the developed model , the full data set of the anaerobic digestion produced must be used that span the for ranged for both the test and validation data set.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

The authors have substantially addressed the issues raised in the first review. I suggest that the article be accepted for publication in its present form.

However, with the addition of two new figures, The Figures need to be renumbered.

Reviewer 4 Report

I have no more concerns