Dynamic Optimization of Greenhouse Tomato Irrigation Schedule Based on Water, Fertilizer and Air Coupled Production Function

Round 1

Reviewer 1 Report

Manuscript on "Dynamic Optimization of Greenhouse Tomato Irrigation Schedule Based on Water, Fertilizer and Air Coupled Production Function" was written well. all section result, discussion were written in depth. However, conclusion can be concise. Only significant point can drawn in conclusion section.        

Author Response

Thanks for your suggestion. This study put forward a novel method to construct a crop production function of water, fertilizer and air coupled irrigation. Soil types and crop varieties may lead to variations in parameters of crop production function, but the suggested method was common used. We refined the conclusion and emphasized the implicated significance of this research as below.

The main conclusions are as follows:

(i) The aeration rate of 24.55 mg L⁻¹ DO in irrigation water and the nitrogen application rate of 281.43 kg ha⁻¹ is the best combination scheme under ASDI.

(ii) In areas where irrigation can be adequately ensured, an irrigation quota of 420 mm was recommended to maximize the yield. When compared with non-aeration treatment, the net yield in ASDI increased by 11012 USD ha⁻¹ per crop season on average.

The results could provide a reference method for the optimization of technical parameters of water – fertilizer – air coupled irrigation. Further study should be done to verify the model applicability in the field conditions and to offset the uncertainty of other factors, such as price fluctuation. (lines 589 - 598)

Author Response File: Author Response.docx

Reviewer 2 Report

Comments

 

SUMMARY

The paper addresses the research area of optimization of irrigation schedule in the MDPI Agronomy journal. I believe that the target journal is an appropriate forum for this article. This study aims to (1) establish water, fertilizer, and air-coupled production functions of tomato water regulation at different growth stages based on the Jen-sen model; (2) resolve the maximum potential yield of fertilizer and air combination parameters, and subdivide the crop growth stage by water sensitive index curve; (3) optimize the water distribution scheme of tomato high yield under multiple irrigation quotas via dynamic programming method, and thus provide the theoretical basis for the popularization and application of ASDI in greenhouse cultivation.

 

BROAD COMMENT

This study is of great importance for irrigated agriculture in China. The Introduction section is written with recent references. The methods were well described and in detail allowing a good understanding of the results of the study. The authors discussed well the results of the study. However, I have some concerns about the different parts of the manuscript. I suggest a major revision to address a few issues. If the authors address carefully the comments, I’ll recommend the publication of the manuscript in the journal.

 

SPECIFIC COMMENTS

-        I see no difference between equations 4 and 5. Please check this.

-        In section 2.4.3, what do you mean by planning and solving tools?

Include the details about this in the manuscript.

-        In section 2.4.3. statistical analysis technique, you mentioned that you analyzed variance. This is a parametric test; this assumes that the normality and homogeneity of the data should be verified before analyzing variance. This is a potential source of bias for the results. The authors failed to do that.

I suggest the authors do these tests.

-        I would suggest the authors include in the manuscript the graph of the crop productivity function they built from the data collected in the experiments carried out in the study.

 

-        The authors failed to include the implications of the findings of the study in the abstract as well as in the conclusion.

Comments for author File: Comments.docx

Author Response

Dear reviewer, thank you for providing constructive comments and suggestions. We have carefully revised the paper and paid our high attention. The detail is given below. In addition, the English of the paper is revised and edited by a native English speaker who is also professional in the field research.

 

Point 1:   I see no difference between equations 4 and 5. Please check this.

Response 1: We are very sorry for our negligence. The formula about NPFP was replicated by "PFPN=Y/N×1000". （lines 224-225）

 

Point 2:  In section 2.4.3, what do you mean by planning and solving tools? Include the details about this in the manuscript.

Response 2: The planning and solving tool is a data analysis plug-in in excel. We didn't describe it too much. However, in section 3.3 a description was inserted as: " After setting the objective function and constraint conditions in the excel table, the maximum output Y_a was iteratively solved according to the plug-in solver tool. Under the nitrogen application rate of 281.43 kg ha^-1, the optimal water distribution scheme under different irrigation quotas was shown in Table 7. "（lines 414-419）

 

Point 3: In section 2.4.3. statistical analysis technique, you mentioned that you analyzed variance. This is a parametric test; this assumes that the normality and homogeneity of the data should be verified before analyzing variance. This is a potential source of bias for the results. The authors failed to do that. I suggest the authors do these tests.

Response 3: Thank you for your suggestion. The results of the normality test indecateed that the Shapiro-Wilk test at the level of P > 0.05. Meanwhile, the scatter points in Q-Q diagram and P-P diagram were both located in the same straight line, suggesting that crop yield, WUE and NPFP indicators meet with the assumption of normal distribution. In addition, the test of homogeneity of variances showed that crop yield, WUE and NPFP indicators met with the assumption of normal distribution at P > 0.05, suggesting that the requirement of data homogeneity for one-way ANOVA.

 

Point 4:   I would suggest the authors include in the manuscript the graph of the crop productivity function they built from the data collected in the experiments carried out in the study.

Response 4: Thanks for your suggestion. The variation of potential crop yield with irrigation parameters (irrigation quota, aeration rate and N application rate) can be reflected through crop productivity function intuitively. After constructing the productivity function, we draw the relationship diagram among the crop yeild and the factors of water, fertilizer and air coupled irrigation, it was included in lines 384 - 391.

 

Point 5: The authors failed to include the implications of the findings of the study in the abstract as well as in the conclusion.

Response 5: We deeply agree with you. This study put forward a noval method to construct a crop production function of water, fertilizer and air coupled irrigation. Soil types and crop varieties may cause the changes of parameter in crop production functions. The suggested method was common used. We refined the abstract and conclusion and emphasized the implicted significance of this research. (lines 595-596)

Author Response File: Author Response.docx