Round 1

Reviewer 1 Report

In this work, the Authors demonstrated the feasibility using the hyperspectral images to LCC prediction from robust machine learning models in order to analyze physiological responses of two glycophosate-resistant and wild non resistant varietes of maize to glyphosate stress.

Moreover, They investigated the potential of using a time-series rapid ChlF transient to dynamically dissect the photosynthetic physiological response of different glyphosate tolerance in maize cultivars.

By combination of LCC with ChlF data, the Authors confirmed the connection between oxidative stress caused by glyphosate and the detrimental effects on photosynthesis.

The research problem has been correctly outlined in the introduction. The research scheme and the research procedure are correct and logically presented and illustrated in the form of a diagram. The results are presented completely and illustrated with clear figures. The discussion exhaustively presents the structural responses and physiological mechanisms related to the response of both varieties to stresses related to the application of glycosides.

 

 

 

Minor comments:

line 287 photosynthetic response ?

Author Response

Response to Reviewer 1 Comments

Point 1: In this work, the Authors demonstrated the feasibility using the hyperspectral images to LCC prediction from robust machine learning models in order to analyze physiological responses of two glyphosate-resistant and wild nonresistant varieties of maize to glyphosate stress. Moreover, they investigated the potential of using a time-series rapid ChlF transient to dynamically dissect the photosynthetic physiological response of different glyphosate tolerance in maize cultivars. By combination of LCC with ChlF data, the Authors confirmed the connection between oxidative stress caused by glyphosate and the detrimental effects on photosynthesis. The research problem has been correctly outlined in the introduction. The research scheme and the research procedure are correct and logically presented and illustrated in the form of a diagram. The results are presented completely and illustrated with clear figures. The discussion exhaustively presents the structural responses and physiological mechanisms related to the response of both varieties to stresses related to the application of glycosides.

 Response 1: Dear reviewer, thank you very much for your thoughtful review of the manuscript entitled “Time-series monitoring of transgenic maize seedlings phenotyping exhibiting glyphosate tolerance”. All your raised comments are greatly helpful for further improving our manuscript, as well as the important guiding significance to our research. We have studied and responded specifically to the comment accordingly, which we hope to meet with approval.

 

Point 2: Minor comments: line 287 photosynthetic response?

Response 2: Thank you for your useful reminding. You have helped us find a mistake caused by our negligence. We added "response" after "photosynthetic" in line 289, please check it.

Reviewer 2 Report

The authors apply machine learning techniques to the results of optical measurements (hyperspectral reflection spectra + chlorophyll fluorescence transients) to study the difference between glyphosate-tolerant and glyphosate-sensitive maize cultivars. This seams to be a valid approach to plant phenotyping, however the manuscript should be improved in several aspects.

The authors perform extensive analysis of OJIP curves and suggest several types of primary photosynthesis disruption caused by glyphosate. They assume that glyphosate-tolerant vars exhibit some mechanisms protecting their photosynthetic apparatus from damage occurring after glyphosate treatment. But the mechanism of glyphosate action is well studied, and there is no need to suppose that photosynthetic apparatus plays any role in glyphosate tolerance/sensitivity. The damage of photosynthetic apparatus is an inevitable consequence of the shikimate pathway block, and we surely may use changes in LCC and ChlF transients as indicators of plant photosynthesis capacity/activity for fast phenotyping - but I see no reason to believe these damage has anything to do with glyphosate sensitivity. If the authors suppose that higher ability to protect from ROS, photoinactivation, etc may increase glyphosate tolerance - they should show this in experiments; however I cannot imagine how can such protective mechanisms overcome inability to synthesize folates and aromatic amino acids. Discussion on this topic should be added.

It seems to me that the major conclusion of this work is that after 6 days after glyphosate treatment glyphosate-sensitive plants exhibit significant changes in leaf reflection and photosynthetic activity, and this may be useful for phenotyping. However, this simple result is missing both from the Conclusions section and from the Abstract.

Data analysis methods implemented in this paper are of great interest for scientific community. It would be great if the authors include their Matlab scripts within the Supplementary Information.

The authors should carefully read the manuscript to ensure proper English language usage.

Lines 92-106 should be deleted.

Explanation of 'c' and 'p' subscripts (line 269) should be moved to the beginning of the paragraph.

Line 315 - should it read Figure 5A?

Lines 326-327 - your result does not show this. You may suggest this mechanism in Discussion, but even there it would be too speculative (see above).

Line 450 - should it read GR instead of GS? Or please explain your idea better.

Lines 545, 553-554 - subscripts.

Author Response

Please see the attachment.

Author Response File: Author Response.docx