Estimate and Temporal Monitoring of Height and Diameter of the Canopy of Recently Transplanted Coffee by a Remotely Piloted Aircraft System

Nicole Lopes Bento,Lucas Santos Santana,Brenon Diennevan Souza Barbosa,Gabriel Araújo E Silva Ferraz,Daniel Veiga Soares,Rafael Alexandre Pena Barata

doi:10.3390/agriengineering4010015

Nicole Lopes Bento, Lucas Santos Santana + Show 4 more

Open Access

https://doi.org/10.3390/agriengineering4010015

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Journal: AgriEngineering	Publication Date: Feb 24, 2022
Citations: 4	License type: CC BY 4.0

Affiliation: Universidade Federal de Lavras

Abstract

Digital agriculture is fundamental to potential improvements in the field by optimizing processes and providing intelligent decision making. This study aims to calculate the height and canopy diameter of recently transplanted coffee plants over three periods of crop development using aerial images, verify statistical differences between field measurements and aerial images, estimate linear equations between field data and aerial images, and monitor the temporal profile of the growth and development of the cultivar understudy in the field based on information extracted from aerial images through a Remotely Piloted Aircraft System (RPAS). The study area comprises a recently transplanted five-month-old Coffea arabica L. cultivar IAC J10 with information of height and crown diameter collected in the field and aerial images obtained by RPAS. As a result, it was possible to calculate the height and diameter of the canopy of coffee plants by aerial images obtained by RPAS. The linear estimation equation for height and crown diameter was determined with satisfactory results by coefficients R and R2 and performance metrics MAE, RMSE, and regression residuals, and it was possible to monitor the temporal profile of the height of the coffee cultivar in the field based on aerial images.

Highlights

Brazil is currently the largest producer and exporter of coffee in the world, and MinasGerais is a prominent state in the country, according to the first survey of the year 2022 by the National Supply Company—CONAB, with an estimated production of 3.342 tons of coffee, which represents 16.8% more compared to 2021 [1]
Collecting crown height and diameter data manually in the field is difficult, especially when performed in large coffee areas, so using Remotely Piloted Aircraft System (RPAS) images to obtain such variables is interesting, as it optimizes the collection of such information in a reliable and automated way
This study proves that this methodology is satisfactory and efficient and corroborates the results found by Santos et al [5], with application in adult coffee trees

Summary

Introduction

Brazil is currently the largest producer and exporter of coffee in the world, and MinasGerais is a prominent state in the country, according to the first survey of the year 2022 by the National Supply Company—CONAB, with an estimated production of 3.342 tons of coffee, which represents 16.8% more compared to 2021 [1]. Digital agriculture proposes the use of technologies that aim to help the producer to monitor the rural property with the use of software and devices responsible for data collection and processing, providing early action on problems, real-time monitoring, use of optimization improvements in the field, and intelligent and efficient decision making [3]. RPA is a typical application of digital agriculture, acting as a tool for the characterization, mapping, monitoring, study, and management of environmental and agricultural properties, due to the possibility of obtaining periodic information with applicability to different areas and lower costs when compared to traditional methodologies [5] Added to this, this tool allows the coffee grower to manage their production more and assertively, directing objectives and promoting important gains in the fields, aiming to maximize the profitability of crops, making agribusiness more competitive [6]

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