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Article
Peer-Review Record

Application of Machine Learning Using Color and Texture Analysis to Recognize Microwave Vacuum Puffed Pork Snacks

Appl. Sci. 2022, 12(10), 5071; https://doi.org/10.3390/app12105071
by Tomasz Pawlak 1, Agnieszka A. Pilarska 2, Krzysztof Przybył 1,*, Jerzy Stangierski 3, Antoni Ryniecki 1, Dorota Cais-Sokolińska 1, Krzysztof Pilarski 4 and Barbara Peplińska 5
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Reviewer 4: Anonymous
Reviewer 5: Anonymous
Appl. Sci. 2022, 12(10), 5071; https://doi.org/10.3390/app12105071
Submission received: 13 April 2022 / Revised: 6 May 2022 / Accepted: 16 May 2022 / Published: 18 May 2022
(This article belongs to the Section Food Science and Technology)

Round 1

Reviewer 1 Report

The aim of the research was to create artificial neural networks (ANN), which will be characterized by high recognition efficiency of modified and unmodified puffed pork snacks. However, the results, discussions and conclusions do not focus on this. Besides, I have a few comments.

  1. The logic of introduction is unclear, and some descriptions are absolute.
  2. The sample treatment is crossed with the introduction and the results.
  3. Figure 2 is unclear
  4. Results and discussion did not focus on the purpose of the research,
  5. The conclusion is too long and has little correlation with the main purpose of the research.

 

Author Response

Dear Reviewer 1,

thank you very much for your valuable comments. I have made the changes as you recommended. This certainly improved and strengthened the substantive aspects of my study.

Response to Reviewer 1 Comments:

The aim of the research was to create artificial neural networks (ANN), which will be characterized by high recognition efficiency of modified and unmodified puffed pork snacks. However, the results, discussions and conclusions do not focus on this. Besides, I have a few comments.

We made the necessary correction. Comment taken into account in the text.

  1. The logic of introduction is unclear, and some descriptions are absolute.

We add paragraph, add references, deleted some not clear sentences. We corrected. Comment taken into account in the text.

  1. The sample treatment is crossed with the introduction and the results.

We add paragraph, add references, deleted some not clear sentences. We corrected. Comment taken into account in the text.

  1. Figure 2 is unclear

Figure has been corrected.

  1. Results and discussion did not focus on the purpose of the research,

We corrected as suggested the reviewer 4 too. Comment taken into account in the text.

  1. The conclusion is too long and has little correlation with the main purpose of the research.

We corrected. Comment taken into account in the text.

Author Response File: Author Response.docx

Reviewer 2 Report

The manuscript deals with the application of machine learning to recognize microwave vacuum puffed pork snacks. The manuscript presents an innovative application of this methodology in the characterization of a meat snack. 

Authors are requested to specify the experimental design, the treatments, the number of replicates per treatment and the use of papain and NaCl.

Authors are asked to check which is the “first paper”: number 30 (L108)  or 32 (L118)?

L90 – 95 The paragraph is not clear. It is requested to rewrite it. It must be specified to which matrix it refers (raw meat, pork meat, snack). There are numerous publications that address the instrumental quality of snack food. Authors are requested to review or rewrite this statement.

L90-91. Are you referring to pork?.

L106 correct muscle expression (italic). How many muscles were used in the trial? Was the pH measured?.

L126 It is requested to include the analysis of the images shown in figure 1.

L152 What does the Force parameter represents? The mechanical work (considering that the probe moves at a constant speed)?

L161 Add the values of the calibration tile.

L183  It is requested to use slope, not gradient. These terms are not equivalent.

L205-208  Add references.

L263 - 272 The topic expressed by the authors is very interesting, but it exceeds the scope of this manuscript. It would be necessary to define lexicons and homologise the methodologies before looking for general correlations. For the purpose of this publication, I suggest deleting this paragraph.

L301 Authors mention the sensory evaluation carried out in the previous work (32). In this publication, they worked with a group of trained and experienced judges. Therefore, it is not possible to extrapolate these results directly to consumers. Therefore, it is necessary to include specific references to sustain the hypotheses about the response of consumers.

L338 – 344 - 413 It is requested to include references that support the hypotheses related to the response of consumers.

L343 Explain how enzymatic modification would contribute to preserve red colour

L395 Correct: parameter b* in not from green to red.

L384 Was any data processing applied  prior to PCA, for example z-score normalization?

Tables. They must be corrected since not all the letters appear as superscripts.

Author Response

Dear Reviewer 2,

thank you very much for your valuable comments. I have made the changes as you recommended. This certainly improved and strengthened the substantive aspects of my study.

Response to Reviewer 2 Comments:

The manuscript deals with the application of machine learning to recognize microwave vacuum puffed pork snacks. The manuscript presents an innovative application of this methodology in the characterization of a meat snack. 

Authors are requested to specify the experimental design, the treatments, the number of replicates per treatment and the use of papain and NaCl.

A detailed description of the method for meat preprocessing using papain described by Pawlak et al. used in the first part of the paper (Pawlak et al., 2019).

Pawlak, T.; Gawałek, J.; Ryniecki, A.; Stangierski, J.; Siatkowski, I.; Peplińska, B.; Pospiech, E. Microwave vacuum drying and puffing of the meat tissue - process analysis. Dry. Technol. 2019, doi:10.1080/07373937.2018.1444635.

We corrected. Comment taken into account in the text.

Authors are asked to check which is the “first paper”: number 30 (L108)  or 32 (L118)?

Number 32:    

Pawlak, T.; Gawałek, J.; Ryniecki, A.; Stangierski, J.; Siatkowski, I.; Peplińska, B.; Pospiech, E. Microwave vacuum drying and puffing of the meat tissue - process analysis. Dry. Technol. 2019, doi:10.1080/07373937.2018.1444635.

We corrected. Comment taken into account in the text.

L90 – 95 The paragraph is not clear. It is requested to rewrite it. It must be specified to which matrix it refers (raw meat, pork meat, snack). There are numerous publications that address the instrumental quality of snack food. Authors are requested to review or rewrite this statement.

We corrected. Comment taken into account in the text.

L90-91. Are you referring to pork?

It’s a pork. We corrected. Comment taken into account in the text.

L106 correct muscle expression (italic). How many muscles were used in the trial? Was the pH measured?

The mass of pork longitudinal muscle used in the study was 500.0±0.4 g.

No pH measurement was done as part of the study. However, we did analyse a number of physical and chemical properties, allowing us to adequately prepare the raw material for the process of producing meat “puffs”. The authors focused on the process of tenderizing raw meat using papain, which enabled them to produce the best crispness of pork „puffs”. The authors will take the reviewer’s opinion into account in their future studies.

L126 It is requested to include the analysis of the images shown in figure 1.

We added section 2.2.: Examination of morphological structure using cryo-SEM.

We added section 3.2: Visualization of morphological structure using cryo-SEM.

We moved the paragraph about the description in Figure 1 and added a lot more information with the relevant review, as suggested by reviewer 4.

 

We corrected. Comment taken into account in the text.

L152 What does the Force parameter represents? The mechanical work (considering that the probe moves at a constant speed)?

The text has been corrected.

L161 Add the values of the calibration tile.

The text has been completed.

L183  It is requested to use slope, not gradient. These terms are not equivalent.

We corrected. Comment taken into account in the text.

L205-208 Add references.

Nummer, B.A.; Harrison, J.A.; Harrison, M.A.; Kendall, P.; Sofos, J.N.; Andress, E.L. Effects of Preparation Methods on the Microbiological Safety of Home-Dried Meat Jerky. J. Food Prot. 2004, 67, 2337–2341, doi:10.4315/0362-028X-67.10.2337.

Konieczny, P.; Stangierski, J.; Kijowski, J. Physical and chemical characteristics and acceptability of home style beef jerky. Meat Sci. 2007, 76, 253–257, doi:10.1016/J.MEATSCI.2006.11.006.

We corrected. Comment taken into account in the text.

L263 - 272 The topic expressed by the authors is very interesting, but it exceeds the scope of this manuscript. It would be necessary to define lexicons and homologise the methodologies before looking for general correlations. For the purpose of this publication, I suggest deleting this paragraph.

We deleted this paragraph. We moved lines 287-314 as suggested by the reviewer 4 too. We corrected. Comment taken into account in the text.

L301 Authors mention the sensory evaluation carried out in the previous work (32). In this publication, they worked with a group of trained and experienced judges. Therefore, it is not possible to extrapolate these results directly to consumers. Therefore, it is necessary to include specific references to sustain the hypotheses about the response of consumers.

We add reference: Pawlak, T.; Gawałek, J.; Ryniecki, A.; Stangierski, J.; Siatkowski, I.; Peplińska, B.; Pospiech, E. Microwave vacuum drying and puffing of the meat tissue - process analysis. Dry. Technol. 2019, doi:10.1080/07373937.2018.1444635.

We corrected. Comment taken into account in the text.

L338 – 344 - 413 It is requested to include references that support the hypotheses related to the response of consumers.

Add references as suggested by the reviewer 4 too:

Xiong, Y.L. Myofibrillar protein from different muscle fiber types: Implications of biochemical and functional properties in meat processing. http://dx.doi.org/10.1080/10408399409527665 2009, 34, 293–320, doi:10.1080/10408399409527665.

Nollet, L.M.L., & Toldra, F. (Eds.). (2008). Handbook of Muscle Foods Analysis (1st ed.). CRC Press. https://doi.org/10.1201/9781420045307

Ozuna, C.; Puig, A.; García-Pérez, J. V.; Mulet, A.; Cárcel, J.A. Influence of high intensity ultrasound application on mass transport, microstructure and textural properties of pork meat (Longissimus dorsi) brined at different NaCl concentrations. J. Food Eng. 2013, 119, 84–93, doi:10.1016/J.JFOODENG.2013.05.016.

We corrected. Comment taken into account in the text.

L343 Explain how enzymatic modification would contribute to preserve red colour

The material was tenderized using meat tenderizing salt produced by McCormick Polska; the salt contained papain, a proteolytic enzyme also referred to as a thiol protease (also known as sulfhydryl or cysteine protease).

The mixture of NaCl and papain, a plant enzyme (classified as a class 3 hydrolase) commercially known as „meat tenderizing salt”, imparts the meat snacks with the required crispness and specific taste, and improved its storage life.

Plant enzymes, on the other hand, primarily degrade proteins in the connective tissue – colagen and elastin, and have only a slight effect on muscle fibers (Ozuna et al., 2013).

Ozuna, C.; Puig, A.; García-Pérez, J. V.; Mulet, A.; Cárcel, J.A. Influence of high intensity ultrasound application on mass transport, microstructure and textural properties of pork meat (Longissimus dorsi) brined at different NaCl concentrations. J. Food Eng. 2013, 119, 84–93, doi:10.1016/J.JFOODENG.2013.05.016.

L395 Correct: parameter b* in not from green to red.

It should be: yellow to blue

We corrected. Comment taken into account in the text.

L384 Was any data processing applied prior to PCA, for example z-score normalization?

Yes. We scaled the data of each element of the set against the average value and standard deviation.

Tables. They must be corrected since not all the letters appear as superscripts.

We corrected. Comment taken into account in the text.

Author Response File: Author Response.docx

Reviewer 3 Report

This manuscript describes the preparation of puffed meat snacks obtained from unmodified and papain modified raw pork muscle (Psoas major), prepared by the process of microwave-vacuum puffing (MVP) under conditions described in the previous work. The obtained meat products underwent  instrumental analyses, in order to determine the basic chemical composition, color and texture.

The mechanical properties and color of the pork meat snack was used by machine learning process (artificial neural networks)  for the recognition and design of pork meat snacks based on color and mechanical (textural) properties to obtain the optimal final product.

The topic is relevant to the field because it uses the machine learning process as a new methodology and gives new information to the field. This work will add well to the published knowledge from this field.

The introduction covers all information needed and it gives good description of the area of research.

The used methodology is well selected and applied to give the needed answers. The methods and materials section needs some clarification and addition of the description of the sample preatrement (more details in needed corrections below).

The results and discussion are clear, well presented and conclusions are made based on the obtained data (minor corrections are needed – below).

The references are appropriate and sufficient but use of one reference (30) needs clarification more details in corrections below).

There are needed some corrections:

Line 90: Texture AND color

Line 105: in the section of Sample preparation it is missing the description of the method for meat preprocessing using papain 124 and NaCl; it should be added

Line 107: location of slaughterhouse (Poznan, Poland??); it should be added

Line 107-108: On the basis of process optimization of microwave-vacuum puffed pork snacks presented in the first part of the paper [30], - and paper (30) is about dried vegetables???Koszela, K.; Łukomski, M.; Mueller, W.; Górna, K.; Okoń, P.; Boniecki, P.; Zaborowicz, M.; Wojcieszak, D. Classification of 528 dried vegetables using computer image analysis and artificial neural networks. In Proceedings of the Proceedings of SPIE - 529 The International Society for Optical Engineering; 2017. 

Please explain

Line 187: process

Line 393: Table 6

Line 396: appears

Line 437: which part and which paper – it is not clear

Line 438: ‘were‘ is not needed

Author Response

Dear Reviewer 3,

thank you very much for your valuable comments. I have made the changes as you recommended. This certainly improved and strengthened the substantive aspects of my study.

Response to Reviewer 3 Comments:

This manuscript describes the preparation of puffed meat snacks obtained from unmodified and papain modified raw pork muscle (Psoas major), prepared by the process of microwave-vacuum puffing (MVP) under conditions described in the previous work. The obtained meat products underwent  instrumental analyses, in order to determine the basic chemical composition, color and texture.

The mechanical properties and color of the pork meat snack was used by machine learning process (artificial neural networks)  for the recognition and design of pork meat snacks based on color and mechanical (textural) properties to obtain the optimal final product.

The topic is relevant to the field because it uses the machine learning process as a new methodology and gives new information to the field. This work will add well to the published knowledge from this field.

The introduction covers all information needed and it gives good description of the area of research.

The used methodology is well selected and applied to give the needed answers. The methods and materials section needs some clarification and addition of the description of the sample preatrement (more details in needed corrections below).

The results and discussion are clear, well presented and conclusions are made based on the obtained data (minor corrections are needed – below).

The references are appropriate and sufficient but use of one reference (30) needs clarification more details in corrections below).

We corrected. Comment taken into account in the text.

There are needed some corrections:

Line 90: Texture AND color

We corrected. Comment taken into account in the text.

Line 105: in the section of Sample preparation it is missing the description of the method for meat preprocessing using papain 124 and NaCl; it should be added

A detailed description of the method for meat preprocessing using papain described by Pawlak et al. used in the first part of the paper (Pawlak et al., 2019).

Pawlak, T.; Gawałek, J.; Ryniecki, A.; Stangierski, J.; Siatkowski, I.; Peplińska, B.; Pospiech, E. Microwave vacuum drying and puffing of the meat tissue - process analysis. Dry. Technol. 2019, doi:10.1080/07373937.2018.1444635.

We corrected. Comment taken into account in the text.

Line 107: location of slaughterhouse (Poznan, Poland??); it should be added

We add information: Sokołów S.A. Robakowo, Poland

We corrected. Comment taken into account in the text.

Line 107-108: On the basis of process optimization of microwave-vacuum puffed pork snacks presented in the first part of the paper [30], - and paper (30) is about dried vegetables???Koszela, K.; Łukomski, M.; Mueller, W.; Górna, K.; Okoń, P.; Boniecki, P.; Zaborowicz, M.; Wojcieszak, D. Classification of 528 dried vegetables using computer image analysis and artificial neural networks. In Proceedings of the Proceedings of SPIE - 529 The International Society for Optical Engineering; 2017. Please explain

It should be number 32: Pawlak, T.; Gawałek, J.; Ryniecki, A.; Stangierski, J.; Siatkowski, I.; Peplińska, B.; Pospiech, E. Microwave vacuum drying and puffing of the meat tissue - process analysis. Dry. Technol. 2019, doi:10.1080/07373937.2018.1444635.

We corrected. Comment taken into account in the text.

Line 187: process

We corrected. Comment taken into account in the text.

Line 393: Table 6

We corrected. Comment taken into account in the text.

Line 396: appears

We corrected. Comment taken into account in the text.

Line 437: which part and which paper – it is not clear

Add reference: Pawlak, T.; Gawałek, J.; Ryniecki, A.; Stangierski, J.; Siatkowski, I.; Peplińska, B.; Pospiech, E. Microwave vacuum drying and puffing of the meat tissue - process analysis. Dry. Technol. 2019, doi:10.1080/07373937.2018.1444635.

We corrected. Comment taken into account in the text.

Line 438: ‘were‘ is not needed

We corrected. Comment taken into account in the text.

Author Response File: Author Response.docx

Reviewer 4 Report

Title

Reformulate to “Studying the effect of pretreatment with papain on color and texture of microwave-vacuum puffed pork snacks using machine learning” to be inclusive to the study objectives.

Abstract

Clear the aim of the work

Reformulate the abstract and add some data about color and texture

Introduction

Lines 34,35 not clear, reword to clear

Lines 42-55 and 65-77 brief

Add a couple of sentences about the enzymatic pretreatment on meat quality

Clear the enzymatic pretreatment in the study objectives

Line 107 adds the location of the slaughterhouse

Most of the comments regarding the Abstract and Introduction should illustrate the shortcomings in writing and style: the typing errors and inconsistency as well as the low quality of English. In further comments I will not focus on those kinds of corrections needed (and required), however, I expect that the MS will be checked in detail in order to correct those shortcomings, which significantly lowers the quality of this work and make it difficult to read and understand.

 

Materials and Methods

Sec 2.1, mention the enzymatic pretreatment

Move the SEM images to results with relevant review

Sec 2.4, add an equation to calculate ∆E

Results and Discussion

Add sec 3.1 physical properties including SEM images with relevant review

Line 226 scientific names must be italic

Line 227, add a citation

Lines 234, 237, 250 adjust citation based on journal instruction, check allover manuscript

Lines 287-314 move at the beginning of the section

Sec 3.3 calculate color differences ∆E

Reformulate tables 1-5 make the treatments at vertical scale

This is not a conclusion. You have written in the work what was determined and how. Please, focus on the actual conclusions. It does not have to be long.

Check the outputs of all references

 

 

 

 

 

 

Author Response

Dear Reviewer 4,

thank you very much for your valuable comments. I have made the changes as you recommended. This certainly improved and strengthened the substantive aspects of my study.

Response to Reviewer 4 Comments:

Title

Reformulate to “Studying the effect of pretreatment with papain on color and texture of microwave-vacuum puffed pork snacks using machine learning” to be inclusive to the study objectives.

Due to the opinions of other reviewers we decided to leave the title in its current form. We will also clearly specify the objective of the study as suggested by reviewer no. 5.

Abstract

We corrected. Comment taken into account in the text.

Clear the aim of the work

Therefore, the aim of this study was to analyze the mechanical properties and color of pork meat snacks (ready-to-eat dried products) manufactured under non-commercial conditions using laboratory equipment and use the results of the analysis as a training set in a machine learning process (artificial neural networks) to train AI to recognize and design pork meat snacks based on their color and mechanical (textural) properties to obtain the optimal final product.

We corrected. Comment taken into account in the text.

Reformulate the abstract and add some data about color and texture

We corrected. Comment taken into account in the text.

Introduction

Lines 34,35 not clear, reword to clear

We add paragraph, add references, deleted some not clear sentences. We corrected. Comment taken into account in the text.

Lines 42-55 and 65-77 brief

We add paragraph, add references, deleted some not clear sentences. We corrected. Comment taken into account in the text.

Add a couple of sentences about the enzymatic pretreatment on meat quality

We corrected. Comment taken into account in the text.

Clear the enzymatic pretreatment in the study objectives

We corrected. Comment taken into account in the text.

Line 107 adds the location of the slaughterhouse

We add information: Sokołów S.A. Robakowo, Poland

We corrected. Comment taken into account in the text.

Most of the comments regarding the Abstract and Introduction should illustrate the shortcomings in writing and style: the typing errors and inconsistency as well as the low quality of English. In further comments I will not focus on those kinds of corrections needed (and required), however, I expect that the MS will be checked in detail in order to correct those shortcomings, which significantly lowers the quality of this work and make it difficult to read and understand.

We corrected. Comment taken into account in the text.

Materials and Methods

Sec 2.1, mention the enzymatic pretreatment

We add to sec 2.1. a paragraph about enzymatic pretreatment of sample preparation:

 

„Puffing” the meat required the tenderization of the raw material using meat tenderizing salt produced by McCormick Polska; the salt contained papain, a proteolytic enzyme also referred to as a thiol protease (also known as sulfhydryl or cysteine protease).

We corrected. Comment taken into account in the text.

Move the SEM images to results with relevant review

We add section: 2.2. Examination of morphological structure using cryo-SEM and we add detailed information by references: 32: Pawlak, T.; Gawałek, J.; Ryniecki, A.; Stangierski, J.; Siatkowski, I.; Peplińska, B.; Pospiech, E. Microwave vacuum drying and puffing of the meat tissue - process analysis. Dry. Technol. 2019, doi:10.1080/07373937.2018.1444635.

We corrected. Comment taken into account in the text.

Sec 2.4, add an equation to calculate ∆E

We added in section 2.5.:

The color difference (ΔE) is the distance between two points in a three-dimensional space and is calculated using the following formula [02]:

 

[02] Yan, W.Q.; Zhang, M.; Huang, L.L.; Tang, J.; Mujumdar, A.S.; Sun, J.C. Studies on different combined microwave drying of carrot pieces. Int. J. Food Sci. Technol. 2010, 45, 2141–2148, doi:10.1111/J.1365-2621.2010.02380.X.

We made the necessary correction. Comment taken into account in the text.

Results and Discussion

Added section 3.1: physical properties including SEM images with relevant review

We added section: 3.2. Visualization of morphological structure using cryo-SEM

Studies indicate that the significant differences in the quality of processing between red and white groups of muscles that can be associated with differences in the functional properties of myofibrillar protein are related to the type of the fiber [03]. Intercellular spaces appear to be full of typical eutectic artifacts resulting from the aggregation of substances dissolved in water following sublimation caused by the use of the Cryo-Sem technique [04]. Bundles of muscle fibers in modified pork – preprocessed using papain and NaCL – appear to be denser than unmodified (non-preprocessed) pork. For comparison, Ozun et al. [05] were also able to demonstrate the increased desalination of the sample related to the „salting out” phenomenon. Apart from NaCl, papain, a plant enzyme (classified as a class 3 hydrolase) commercially known as „meat tenderizing salt”, was used in the study and successfully imparted the meat snacks (modified pork – preprocessed using papain and NaCL) with the required crispness and specific taste, and improved its storage life. Plant enzymes primarily degrade proteins in the connective tissue – colagen and elastin, and have only a slight effect on muscle fibers [06].

[03] Xiong, Y.L. Myofibrillar protein from different muscle fiber types: Implications of biochemical and functional properties in meat processing. http://dx.doi.org/10.1080/10408399409527665 2009, 34, 293–320, doi:10.1080/10408399409527665.

[04] Nollet, L.M.L.; Toldra, F. Handbook of Muscle Foods Analysis. Handb. Muscle Foods Anal. 2008, doi:10.1201/9781420045307.

[05] Ozuna, C.; Puig, A.; García-Pérez, J. V.; Mulet, A.; Cárcel, J.A. Influence of high intensity ultrasound application on mass transport, microstructure and textural properties of pork meat (Longissimus dorsi) brined at different NaCl concentrations. J. Food Eng. 2013, 119, 84–93, doi:10.1016/J.JFOODENG.2013.05.016.

[06] Powell, T.H.; Hunt, M.C.; Dikeman, M.E. Enzymatic assay to determine collagen thermal denaturation and solubilization. Meat Sci. 2000, 54, 307–311, doi:10.1016/S0309-1740(99)00092-3.

 

We made the necessary correction. Comment taken into account in the text.

Line 226 scientific names must be italic

We corrected. Comment taken into account in the text.

Line 227, add a citation

Lim, J.Y.; Yoon, J.W.; Hovde, C.J. A Brief Overview of Escherichia coli O157:H7 and Its Plasmid O157. J. Microbiol. Biotechnol. 2010, 20, 5, doi:10.4014/jmb.0908.08007.

Yoon, J.W.; Hovde, C.J. All blood, No stool: Enterohemorrhagic Escherichia coli O157:H7 infection. J. Vet. Sci. 2008, 9, 219–231, doi:10.4142/jvs.2008.9.3.219.

Oporto, B.; Esteban, J.I.; Aduriz, G.; Juste, R.A.; Hurtado, A. Escherichia coli O157:H7 and non-O157 Shiga toxin-producing E. coli in healthy cattle, sheep and swine herds in Northern Spain. Zoonoses Public Health 2008, 55, 73–81, doi:10.1111/j.1863-2378.2007.01080.x.

We corrected. Comment taken into account in the text.

Lines 234, 237, 250 adjust citation based on journal instruction, check allover manuscript

We corrected. Comment taken into account in the text.

Lines 287-314 move at the beginning of the section

We corrected. Comment taken into account in the text.

Sec 3.3 calculate color differences ∆E

We corrected. Comment taken into account in the text.

Reformulate tables 1-5 make the treatments at vertical scale

However, the authors believe that the structure of the tables should not be changed due to the opinions of other reviewers with regard to the paper as a whole. Thank you for the suggestion.

This is not a conclusion. You have written in the work what was determined and how. Please, focus on the actual conclusions. It does not have to be long.

We corrected. Comment taken into account in the text.

Check the outputs of all references

We corrected. Comment taken into account in the text.

Author Response File: Author Response.docx

Reviewer 5 Report

I think the paper is well written and does present an interesting way of analyzing product data.  The biggest issue I have is that I am not sure why or how the Multi-layer Perceptron Network (MLPN) adds anything to the analysis of the data.  Perhaps I missed it in this paper.  I think the authors ought to provide more information regarding the MLPN and why it was used and how the results were improved by its use.

As far as acceptance -- it may be that I do not quite understand the techniques -- if that is the case I offer my apologies.  

Author Response

Dear Reviewer 5,

thank you very much for your valuable comments. I have made the changes as you recommended. This certainly improved and strengthened the substantive aspects of my study.

Response to Reviewer 5 Comments:

 

I think the paper is well written and does present an interesting way of analyzing product data.  The biggest issue I have is that I am not sure why or how the Multi-layer Perceptron Network (MLPN) adds anything to the analysis of the data.  Perhaps I missed it in this paper.  I think the authors ought to provide more information regarding the MLPN and why it was used and how the results were improved by its use.

As far as acceptance -- it may be that I do not quite understand the techniques -- if that is the case I offer my apologies.  

We clear the aim of the work

We corrected. Comment taken into account in the text.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The authors are thanked for the time spent making the suggested changes. The changes introduced have significantly improved the manuscript.

Reviewer 4 Report

     Thanks for the authors effort in responding to all required comments. Now the manuscript  can be accepted  in the journal

Reviewer 5 Report

Line 53  The definition of ML was deleted.  It should be included again.

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