Application of a Multilayer Perceptron Artificial Neural Network for the Prediction and Optimization of the Andrographolide Content in Andrographis paniculata

Round 1

Reviewer 1 Report

Figure quality could be improved.

Long tables (1, 2, 3, 5, 6, 7) could be moved to a supplementary file. For each field / column, a range of values could be added to the main text.

In 2.4. Optimization of andrographolide content, how were the initial and the final values for nitrogen, phosphorus and potassium selected?

Author Response

Response to reviewer 1 comments

Comments to the Author

Figure quality could be improved.

Response: The figure quality has been enhanced to 1200 dpi in the revised manuscript.  

Comments to the Author

Long tables (1, 2, 3, 5, 6, 7) could be moved to a supplementary file. For each field / column, a range of values could be added to the main text.

Response: The tables 1,2,3,5,6 and 7 has been moved to supplementary file. The range of values were added in the manuscript wherever applicable.  

Comments to the Author

In 2.4. Optimization of andrographolide content, how were the initial and the final values for nitrogen, phosphorus and potassium selected?

Response: The description has been reframed to clearly state how the initial and final values of nitrogen, phosphorus and potassium were selected for optimization study. 

Reviewer 2 Report

Authors propose a multilayer perceptron artificial neural network to determine the factors affecting the andrographolide content in Andrographis paniculata.

The manuscript is well organized and the results are critically discussed.

I suggest to revise the submission, taking particular care to:

• keywords   the number of keywords should be increased to help serching
• extraction procedure    even if reference 44 cites Champati et al., more details about the quantification procedure of % extracted from the plant (recovery) should be detailed
• Tables are too long   I suggest to add all the tables as supplementary material 
• authors generally report 2018-2019 monthly average of climatic factors. I suggest to state the year each sample was taken, simply by adding a column to one of the tables 
• check english (minor revision)

Author Response

Response to reviewer 2 comments

Authors propose a multilayer perceptron artificial neural network to determine the factors affecting the andrographolide content in Andrographis paniculata.

The manuscript is well organized and the results are critically discussed.

I suggest to revise the submission, taking particular care to:

Comments to the Author

Keywords- the number of keywords should be increased to help searching

Response: 3 more keyword has been added

Comments to the Author

Extraction procedure-even if reference 44 cites Champati et al., more details about the quantification procedure of % extracted from the plant (recovery) should be detailed

Response: The method has been elaborated and added in the appropriate section in the manuscript

Comments to the Author

Tables are too long   I suggest to add all the tables as supplementary material 

authors generally report 2018-2019 monthly average of climatic factors. I suggest to state the year each sample was taken, simply by adding a column to one of the tables 

Response: Thank you for your suggestion. The year of samples collection has been added to Table 5 of supplementary file.

Comments to the Author

Check English (minor revision)

Response: The grammar and syntax error has been checked thoroughly.

Round 2

Reviewer 2 Report

The manuscript has been sufficiently improved. I suggest publication in Molecules