Quantitatively Determine the Iron Content in the Fruit of ‘Huangguan’ Pear Using Near-Infrared Spectroscopy

Round 1

Reviewer 1 Report

My comments

1. 'Huangguan' pear has excellent quality, please mention the nature of quality.

2. The section 3. Should not be the “Conclusion” I think there is some typographical mistake.

3. All the abbreviations should be thorough checked.

4. The pictures are in low quality and cannot be read properly.

5. There should be a separate heading of conclusion after the section of discussion.

Overall manuscript is very interesting and can be considered for publication after addressing the few comments.

Thank you.

Comments for author File: Comments.docx

The English can be improved.

Author Response

We are very grateful to you for your critical comments and thoughtful suggestions. Based on these comments and suggestions, we have carefully modified the original manuscript. All changes made to the text are shown in red so that they can be easily identified. We hope that it now meets your standards for publication. Some explanations regarding the revisions to the manuscript are provided below.

1. 'Huangguan' pear has excellent quality, please mention the nature of quality.

Thank you for your kind suggestions! For the quality of ‘Huangguan’ pears, we added the following: 'Huangguan' pear has excellent quality, its fruit yields a high amount and is rich in minerals and vitamins, making it delicious and juicy.

 

2. The section 3. Should not be the “Conclusion” I think there is some typographical mistake.

Thank you for your careful review! We've changed it to “Results”.

 

3. All the abbreviations should be thorough checked.

Thank you for your careful review! We have checked all the abbreviations.

 

4. The pictures are in low quality and cannot be read properly.

Thank you for your careful review! We have re-uploaded higher quality images.

 

5. There should be a separate heading of conclusion after the section of discussion.

Thank you for your careful review! We have added a conclusion title to the end of the discussion section, which reads as follows:

5. Conclusions

In summary, the results of this paper prove that the nondestructive prediction of iron content in the peel and pulp of 'Huangguan' pear can be quickly and accurately realized by using a miniature near-infrared spectrometer, the model fitting effect is good, and actual production practice can be carried out, which can help identify difficult physiological diseases such as yellow leaf disease and guide practical agricultural methods. This study can provide part of the theoretical basis for near-infrared spectroscopy in the nondestructive detection of mineral elements in 'Huangguan' pear fruit, and subsequent research will further expand the number and range of samples and further improve the universality and accuracy of the model. Using a variety of pear fruit samples, the contents of N, K, Ca, and other mineral elements were determined to construct a wide and comprehensive pear fruit mineral element detection model. Combined with a computer, a small portable near-infrared spectroscopy mineral element detection instrument was made to further realize direct detection in the field and apply the test theory to actual production.

Author Response File: Author Response.docx

Reviewer 2 Report

Dear authors,
After reading and analyzing your manuscript, In general, this work is interesting, besides I think it has scientific quality. I give you the following remarks:

·         I think of the title that the word quickly is a bit of an exaggeration

·         the abstract part is perfect.

·         the introduction part is great too

·         In the part:

3.2. Raw spectral data analysis

[33,34] After the spectrum ………….., we do not start a paragraph with references.

·         “The main chemical components in pears include flavonoids, triterpenes, phenolic acids, luminolates, polysaccharides, etc. The entire spectral curve is a rich reflection of the pear fruit's interior data.” Justify this information by a reference.

·         I see a lack of references in parts especially the discussion and Modeling part, compared with studies already done on similar samples.

·         The design of the article does not respect the order of writing an article: introduction, material and methods, results and discussion, conclusion.

·         Also absence of other physicochemical analyzes of the Huangguan variety pear, pH, ash, humidity, heavy metals, organic matter, mineral matter. Is it possible to add a table of these parameters?

·         the results part is perfect.

·         Absence of the conclusion and perspectives part.

 

Best regards

Comments for author File: Comments.docx

Author Response

We are very grateful to you for your critical comments and thoughtful suggestions. Based on these comments and suggestions, we have carefully modified the original manuscript. All changes made to the text are shown in red so that they can be easily identified. We hope that it now meets your standards for publication. Some explanations regarding the revisions to the manuscript are provided below.

• I think of the title that the word quickly is a bit of an exaggeration

Thank you for your kind suggestion! We have replaced ‘quickly’ with ‘quantitatively’.

• In the part:

3.2. Raw spectral data analysis

[33,34] After the spectrum ………….., we do not start a paragraph with references.

Thanks for the reminder, we have inserted the references into the right place.

• “The main chemical components in pears include flavonoids, triterpenes, phenolic acids, luminolates, polysaccharides, etc. The entire spectral curve is a rich reflection of the pear fruit's interior data.” Justify this information by a reference.

Thank you for your careful review! We have added the following reference to support this information.

1. Li, X.; Wang, T.; Bin, Z.; Gao, W.; Cao, J.; Huang, L. Chemical composition and antioxidant and anti-inflammatory potential of peels and flesh from 10 different pear varieties (Pyrus spp.). Food Chemistry 2014, 152, 531-538, doi:10.1016/j.foodchem.2013.12.010.
2. Fang, J.; Jin, X.; Wu, L.; Zhang, Y.; Jia, B.; Ye, Z.; Heng, W.; Liu, L. Prediction Models for the Content of Calcium, Boron and Potassium in the Fruit of 'Huangguan' Pears Established by Using Near-Infrared Spectroscopy. Foods 2022, 11, doi:10.3390/foods11223642.

• I see a lack of references in parts especially the discussion and Modeling part, compared with studies already done on similar samples.

Thank you for your careful review! We have added references to the discussion and modeling section.

 

1. Sorrenti, G.; Toselli, M. Post-harvest foliar-applied Fe(II)-sulfate promotes Fe nutrition of pear trees grown in calcareous soil. Journal of Plant Nutrition 2020, 43, 3020-3034, doi:10.1080/01904167.2020.1798998.

 

2. Morales, F.; Belkhodja, R.; Abadia, A.; Abadia, J. Photosystem II efficiency and mechanisms of energy dissipation in iron-deficient, field-grown pear trees (Pyrus communis L.). Photosynthesis Research 2000, 63, 9-21, doi:10.1023/a:1006389915424.

 

3. Tsagkaris, A.S.; Bechynska, K.; Ntakoulas, D.D.; Pasias, I.N.; Weller, P.; Proestos, C.; Hajslova, J. Investigating the impact of spectral data pre-processing to assess honey botanical origin through Fourier transform infrared spectroscopy (FTIR). Journal of Food Composition and Analysis 2023, 119, doi:10.1016/j.jfca.2023.105276.

 

4. Aparatana, K.; Naomasa, Y.; Sano, M.; Watanabe, K.; Mitsuoka, M.; Ueno, M.; Kawamitsu, Y.; Taira, E. Predicting sugarcane quality using a portable visible near infrared spectrometer and a benchtop near infrared spectrometer. Journal of near Infrared Spectroscopy 2023, 31, 14-23, doi:10.1177/09670335221136545.

 

5. Greenhall, J.; Sinha, D.N.; Pantea, C. Genetic algorithm-wavelet transform feature extraction for data-driven acoustic resonance spectroscopy. IEEE transactions on ultrasonics, ferroelectrics, and frequency control 2023, PP, doi:10.1109/tuffc.2023.3278494.

 

6. Grgic, F.; Jurina, T.; Valinger, D.; Kljusuric, J.G.; Tusek, A.J.; Benkovic, M. Near-Infrared Spectroscopy Coupled with Chemometrics and Artificial Neural Network Modeling for Prediction of Emulsion Droplet Diameters. Micromachines 2022, 13, doi:10.3390/mi13111876.

 

 

• The design of the article does not respect the order of writing an article: introduction, material and methods, results and discussion, conclusion.

Thank you for your careful review! We have correctly changed the order of the article.

 

• Also absence of other physicochemical analyzes of the Huangguan variety pear, pH, ash, humidity, heavy metals, organic matter, mineral matter. Is it possible to add a table of these parameters?

Thank you for your careful review! In general, humidity and PH are not the physical and chemical properties of the fruit. We have introduced the varieties and organic matter of ‘Huangguan’ in the article, and other physical and chemical properties are not considered due to the weak correlation with the purpose of the experiment in this article, we will make a comprehensive analysis of the above physical and chemical properties of you in further experiments, and hope you can accept our views. Thank you very much for your kind comments!

• Absence of the conclusion and perspectives part.

Thank you for your careful review! We have added this part.

 

5. Conclusions

In summary, the results of this paper prove that the nondestructive prediction of iron content in the peel and pulp of 'Huangguan' pear can be quickly and accurately realized by using a miniature near-infrared spectrometer, the model fitting effect is good, and actual production practice can be carried out, which can help identify difficult physiological diseases such as yellow leaf disease and guide practical agricultural methods. This study can provide part of the theoretical basis for near-infrared spectroscopy in the nondestructive detection of mineral elements in 'Huangguan' pear fruit, and subsequent research will further expand the number and range of samples and further improve the universality and accuracy of the model. Using a variety of pear fruit samples, the contents of N, K, Ca, and other mineral elements were determined to construct a wide and comprehensive pear fruit mineral element detection model. Combined with a computer, a small portable near-infrared spectroscopy mineral element detection instrument was made to further realize direct detection in the field and apply the test theory to actual production.

Author Response File: Author Response.docx

Reviewer 3 Report

The method is not new, it was described as quick method in other papers published in Journal of Near Infrared Spectroscopy such as "Multi-task deep learning of near infrared spectra for improved grain quality trait predictions"; "Review of portable near infrared spectrometers: Current status and new techniques" etc. NIR method is non destructive technology which permit to miniaturization of spectrophotometer with high level of performances. Moreover NIR permit to left in integrity the chemical composition of raw materials analyzed. 

Study describe a quick method to determinate the Iron content (is not specify in title if is total content or partial content) in the fruit of "Huangguan" a pear variety cultivated in China. The method permit a quick action when the Iron level from leafs are low and the same permit to determinate the Iron content from peal and pulp of "Huangguan" fruits.

I recommend the publish of the manuscript after a minor revision and I asked the authors to answer at several questions.

1st question: how is influenced the Iron content from peals and fruits by soil chemical concentration, climatic factors; temperature average during night and day and the exposure of trees on sun light, how many hours of sun light are during 24 hours?

2nd question: there is a correlation between leaf iron content, leaf disease, ripening methods and Iron content from "Huangguan" peal and pulp. 

3rd question authors describe at line 105 that the experiment is based on genetic algoritm. Please describe the algoritm from point of view of molecular analyses (genetic sequences).

 

 

 

Author Response

We appreciate your question, and we answered it.

1st question: how is influenced the Iron content from peals and fruits by soil chemical concentration, climatic factors; temperature average during night and day and the exposure of trees on sun light, how many hours of sun light are during 24 hours?

Thank you for your questions.

Plants can only replenish themselves by absorbing external iron, and the iron content in the soil will directly affect the absorption of iron by plants. If the soil has a higher iron content, the plant is usually able to absorb more iron, which increases the iron content in the fruit. Conversely, if the iron content in the soil is low, the plant may not be able to fully absorb iron, resulting in a decrease in the iron content in the fruit, it is also important that the ratio of iron to other chemical elements is reasonable, and certain ions such as Cu²⁺, Mn²⁺, etc. will affect the effectiveness of Fe²⁺.

Climatic conditions have an important impact on plant growth and development. In general, suitable climatic conditions are conducive to the uptake and utilization of nutrients by plants. If climatic conditions are unstable or extreme, such as excessive drought or excessive humidity, it may affect plant growth and root development, thus affecting the absorption of iron by plants and changes in iron content in fruits.

Temperature is one of the important factors in plant growth and metabolic activity. The suitable temperature range is conducive to the uptake and utilization of nutrients by plants. In general, higher average diurnal temperatures can promote plant growth and metabolic activity, which may help increase the iron content of the fruit.

Light is one of the key factors for plants to carry out photosynthesis. Photosynthesis is the process by which plants synthesize organic matter, which also requires the participation of trace elements such as iron. Adequate light promotes photosynthesis in plants, which can help increase the iron content in the fruit. Usually,When the quality of light is good，it takes at least four hours of light time, and eight hours of light is sufficient.

It is important to note that the extent to which iron content in the fruit is specifically affected is influenced by different plant varieties, soil types, and environmental conditions, so results may vary.

Hope the above answers satisfy you!

 

2nd question: there is a correlation between leaf iron content, leaf disease, ripening methods and Iron content from "Huangguan" peal and pulp.

Thank you for your questions.

After the plant absorbs iron, it is preferentially supplied to the buds, new leaves, and developing fruits of the plant, and once the iron enters the plant cells and tissues, it is difficult to retransport. Under normal circumstances, if the iron content in the peel and pulp is low, the plant leaves are likely to be iron deficient, and combined with some abnormal phenomena shown by plant leaves, it can help determine the physiological diseases of leaves, such as iron deficiency yellow leaf disease. When the plant fruit is ripe, the content of mineral elements in the fruit such as iron will tend to a certain range, and whether the fruit is ripe can be judged according to the iron content in the fruit. We've added some content to the discussion, thank you for your question.

 

3rd question authors describe at line 105 that the experiment is based on genetic algoritm. Please describe the algoritm from point of view of molecular analyses (genetic sequences).

Thank you for your questions.

We apologize for not explaining the genetic algorithm clearly, the genetic algorithm in this article refers to the extraction of spectral characteristic wavelengths using genetic algorithms in combination with computers, and we have added explanations in the introduction.

 

 

Author Response File: Author Response.docx