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Article
Peer-Review Record

UAV Multispectral Imaging Potential to Monitor and Predict Agronomic Characteristics of Different Forage Associations

Agronomy 2021, 11(9), 1697; https://doi.org/10.3390/agronomy11091697
by Javier Plaza 1,*, Marco Criado 2, Nilda Sánchez 3, Rodrigo Pérez-Sánchez 1, Carlos Palacios 4 and Francisco Charfolé 3
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Agronomy 2021, 11(9), 1697; https://doi.org/10.3390/agronomy11091697
Submission received: 20 June 2021 / Revised: 24 July 2021 / Accepted: 23 August 2021 / Published: 25 August 2021

Round 1

Reviewer 1 Report

Dear Authors,

The work presented here presents an interesting take on the practical implementation of precision agriculture.

It is very well written, contains all the components of a scientific article while maintaining the appropriate proportion of the text.

In my opinion, the authors should expand the part results and discussion of results, in which they would refer even more precisely to the predictive application of such models.

Presented research concerns one growing season - I suggest that the article should be published as a "pilot study" and not as an article. Please consider the following few comments:

In the abstract, please write where the experiments were carried out.

Material and methods. Please state in the article what experimental system (scatterplot) was used in the research presented.

Please describe the procedure for drying the samples.

Is the method you have presented for determining LAI correct? Please provide literature sources in which other authors have used the method you presented.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

The paper addresses the research area related to agronomic parameters prediction by using spectral indices derived from UAV imagery.

It aims to predict the six biophysical parameters during the land-use changes in the ecotone and the whole basin by using the growing cycle of several forage associations.

The authors claim that the VIS-NIR bands were able to lead to a successful prediction of the agronomic parameters.

As a general comment, the manuscript is fluent and well structured.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report

This study investigated the biophiscal parameters estimated from vegetation indices using multispectral camera onboard UAV over several forage associations. This topic is relevant to Agronomy journal and it is interesting to apply this method to forage associations. However, the field experiment design and plan were not explained clearly enough. So I have some doubts on the final results and conclusion.

My main comments are:

- section 2.2: 

Provide more details about how measurments were performend, such as number of destructive plants, sampling foot print, height of camera when took photos to calculate FVC. They are important to know the reliability of ground measurements.

Another question is how you distinguish these measurements from assosication level or plant level. It is not clear enough.

- Section 2.3: 

How did you solve the gaps or holes due to destructive measurements?

How about the illumination conditions when the flights were taken? Have you used the DLS on micasense camera and how did you use it?

- Line 198 - 199: This is not clear. You made destructive measurements leading to holes in the fields. Then how did you extract values from orthoimage of VI?

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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