Applications MLP and Other Methods in Artificial Intelligence of Fruit and Vegetable in Convective and Spray Drying
Round 1
Reviewer 1 Report
This paper studies the preservation of fruits and vegetables by spray drying from a theoretical point of view, although it is a simulation approach, it clarifies certain aspects of the model used (neural networks), which are faithful to said study. Therefore I suggest that it be accepted for publication in Applied Sciences.
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:
Comments and Suggestions for Authors
This paper studies the preservation of fruits and vegetables by spray drying from a theoretical point of view, although it is a simulation approach, it clarifies certain aspects of the model used (neural networks), which are faithful to said study. Therefore I suggest that it be accepted for publication in Applied Sciences.
Thank you for your opinion. We have also made corrections as requested by other reviewers.
Kind regards,
Krzysztof Przybył
Reviewer 2 Report
This subject addressed is within the scope of the journal. However, the manuscript in the present version contains several problems. Appropriate revisions should be undertaken in order to justify recommendation for publication.
1. It is mentioned that MLP literature mainly described. What are the advantages of adopting these particular methods over others in this case? How will this affect the results? More details should be furnished.
2. For readers to quickly catch your contribution, it would be better to highlight major difficulties and challenges, and your original achievements to overcome them, in a clearer way in abstract and introduction.
3. There is a serious concern regarding the novelty of this work. What new has been proposed?
4. Abstract needs to modify and to be revised to be quantitative. You can absorb readers' consideration by having some numerical results in this section.
5. There are some occasional grammatical problems within the text. It may need the attention of someone fluent in English language to enhance the readability.
6. The discussion section in the present form is relatively weak and should be strengthened with more details and justifications.
7. In conclusion section, limitations and recommendations of this research should be highlighted.
8. The authors have to add the state-of-the art references in the manuscripts.Authors should mention machine learning models few applications in other field to highlight successful AI usage, for example,LSTM-ALO,ANFIS-GBO,ELM-PSOGWO,LSSVM-IMVO,SVR-SAMOA, ANN-EMPA, ELM-CRFOA recently used in the literature of different time series modeling. Should add these and other recent literature
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:
Comments and Suggestions for Authors
This subject addressed is within the scope of the journal. However, the manuscript in the present version contains several problems. Appropriate revisions should be undertaken in order to justify recommendation for publication.
It is mentioned that MLP literature mainly described. What are the advantages of adopting these particular methods over others in this case? How will this affect the results? More details should be furnished.
The authors explained the use of MLP in the convective drying section. They added the effectiveness of MLP usage to the spray drying and others drying section:
Summing up, the qualitative assessment of the obtained powder in terms of customer requirements, requires a wide range of physicochemical determinations. Producers of fruit and vegetables powders struggle with the problems of repeatability of nutritional properties of powders both between batches and within one production batch. Appropriate selection of input parameters in the MLPN resulted in high efficiency of quality assessment of fruit and vegetable powders, considering the amount and type of carriers. In order to obtain homogeneous powders, it is necessary to monitor the quality and drying parameters of food powders (including the selection of the amount of carrier) on-line using artificial intelligence.
Summing up, the above research confirms the high efficiency of matching various AI methods, which translates into obtaining excellent forecasting or classification results obtained as a result of drying vegetables and fruits. The value of the fit coefficient below 0.7 would mean that the discrepancies be-tween the results of the designed AI methods and the model results for the network are not fully satisfactory in research work. A fit quality factor below 0.6 would mean that the fit of the model is mate. is not sufficient for ANN methods to be able to independently decide on the qualification of dried vegetables and fruits with sufficient accuracy.
- For readers to quickly catch your contribution, it would be better to highlight major difficulties and challenges, and your original achievements to overcome them, in a clearer way in abstract and introduction.
We re-wrote the abstract. We added key findings. We add sentence to clarify review in introduction. We corrected into the text.
- There is a serious concern regarding the novelty of this work. What new has been proposed?
We add sentence to clarify review:
The present review is based on studies to classifying the quality of dried material and prediction drying kinetics using artificial intelligence.
We change headings to clarify. In discussion we describe about novelty research activities among other algorithms in AI.
- Abstract needs to modify and to be revised to be quantitative. You can absorb readers' consideration by having some numerical results in this section.
We re-wrote the abstract. We corrected into the text.
- There are some occasional grammatical problems within the text. It may need the attention of someone fluent in English language to enhance the readability.
We corrected into the text.
The discussion section in the present form is relatively weak and should be strengthened with more details and justifications.
The opinions based on other reviewers, we believe that the discussion has been described comprehensively. We change headings to clarify a lot. We added summing to other section. We corrected a lot of words into the text for complete clarity.
- In conclusion section, limitations and recommendations of this research should be highlighted.
We reformulated conclusion. We corrected into the text.
- The authors have to add the state-of-the art references in the manuscripts. Authors should mention machine learning models few applications in other field to highlight successful AI usage, for example, LSTM-ALO,ANFIS-GBO,ELM-PSOGWO,LSSVM-IMVO,SVR-SAMOA, ANN-EMPA, ELM-CRFOA recently used in the literature of different time series modeling. Should add these and other recent literature
We corrected into the text. We added references:
Niu, M.; Zhang, Y.; Ren, Z. Deep Learning-Based PM2.5 Long Time-Series Prediction by Fusing Multisource Data—A Case Study of Beijing. Atmosphere 2023, 14, 340. https://doi.org/10.3390/atmos14020340
Yuan, X.; Chen, C.; Lei, X.; Yuan, Y.; Muhammad Adnan, R. Monthly runoff forecasting based on LSTM–ALO model. Stoch. Environ. Res. Risk Assess. 2018, 32, 2199–2212.
Adnan, R.M.; Mostafa, R.R.; Elbeltagi, A.; Yaseen, Z.M.; Shahid, S.; Kisi, O. Development of new machine learning model for streamflow prediction: Case studies in Pakistan. Stoch. Environ. Res. Risk Assess. 2022, 36, 999–1033.
Adnan, R.M.; Mostafa, R.R.; Islam, A.R.M.T.; Kisi, O.; Kuriqi, A.; Heddam, S. Estimating reference evapotranspiration using hybrid adaptive fuzzy inferencing coupled with heuristic algorithms. Comput. Electron. Agric. 2021, 191, 106541.
Ikram, R.M.A.; Dai, H.-L.; Ewees, A.A.; Shiri, J.; Kisi, O.; Zounemat-Kermani, M. Application of improved version of multi verse optimizer algorithm for modeling solar radiation. Energy Rep. 2022, 8, 12063–12080.
Adnan, R.M.; Kisi, O.; Mostafa, R.R.; Ahmed, A.N.; El-Shafie, A. The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction. Hydrol. Sci. J. 2022, 67, 161–174.
Ikram, R.M.A.; Dai, H.-L.; Chargari, M.M.; Al-Bahrani, M.; Mamlooki, M. Prediction of the FRP reinforced concrete beam shear capacity by using ELM-CRFOA. Measurement 2022, 205, 112230.
Kind regards,
Krzysztof Przybył
Reviewer 3 Report
I have reviewed the article " Applications MLP and other methods in Artificial Intelligence of fruit and vegetable in convective and spray drying".
Below are the comments and suggestions:
· Need to rephrase the sentence in the abstract “Artificial intelligence through artificial neural networks and other algorithms of machine learning have been one of the fastest growing fields of studies in the last ten and twenty years”. Also see this sentence “For 20 many researchers, it is a huge chance of faster and faster development, lower production costs, effective quality control and higher production efficiency.”
· Re-write the Abstract, it should contain some important findings as well. It is just showing some background.
· Write clear separate sections for methodology, results and discussions.
· The manuscript needs to be well structured with proper headings.
· The authors need to highlight the significance of the study.
· There are grammatical issues; proofread the manuscript carefully.
· See the sentence in conclusion section “It should be noted that artificial intelligence requires appropriate programming and supervision in order to ensure its effective activity. Thanks to continuous gathering and analysis of data, it is possible to apply artificial intelligence even in real time during the process of convective and spray drying.” Thanks ….? See below sentences as well… need to rephrase…
· Generally speaking, the application of AI in food drying has a big potential in order to ensure substantial benefits, including an improvement in productivity, accuracy and food safety.
· The article must be considered after the resubmission, if it is in a well-organized way.
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:
Comments and Suggestions for Authors
I have reviewed the article " Applications MLP and other methods in Artificial Intelligence of fruit and vegetable in convective and spray drying".
Below are the comments and suggestions:
- Need to rephrase the sentence in the abstract “Artificial intelligence through artificial neural networks and other algorithms of machine learning have been one of the fastest growing fields of studies in the last ten and twenty years”. Also see this sentence “For 20 many researchers, it is a huge chance of faster and faster development, lower production costs, effective quality control and higher production efficiency.”
We re-wrote the abstract. We reformulated the text. We corrected a lot of words into the text.
- Re-write the Abstract, it should contain some important findings as well. It is just showing some background.
We re-wrote the abstract. We added key findings and conclusions. We corrected into the text.
- Write clear separate sections for methodology, results and discussions.
We added. We corrected into the text.
- The manuscript needs to be well structured with proper headings.
We added and changed headings. We corrected into the text.
- The authors need to highlight the significance of the study.
We added in the introduction. We corrected into the text.
- There are grammatical issues; proofread the manuscript carefully.
We corrected into the text.
- See the sentence in conclusion section “It should be noted that artificial intelligence requires appropriate programming and supervision in order to ensure its effective activity. Thanks to continuous gathering and analysis of data, it is possible to apply artificial intelligence even in real time during the process of convective and spray drying.” Thanks ….? See below sentences as well… need to rephrase…
We reformulated conclusion. We corrected into the text.
- Generally speaking, the application of AI in food drying has a big potential in order to ensure substantial benefits, including an improvement in productivity, accuracy and food safety.
We reformulated conclusion. We corrected into the text.
- The article must be considered after the resubmission, if it is in a well-organized way.
Thank you for your valuable comments. We corrected into the text.
Kind regards,
Krzysztof Przybył
Round 2
Reviewer 2 Report
Accept in present form
Reviewer 3 Report
All my comments are addressed with suitable explanations. I have no further comments.
