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Light Drone-Based Application to Assess Soil Tillage Quality Parameters

The evaluation of soil tillage quality parameters, such as cloddiness and surface roughness produced by tillage tools, is based on traditional methods ranging, respectively, from manual or mechanical sieving of ground samples to handheld rulers, non-contact devices or Precision Agriculture technics,...

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Autores principales: Fanigliulo, Roberto, Antonucci, Francesca, Figorilli, Simone, Pochi, Daniele, Pallottino, Federico, Fornaciari, Laura, Grilli, Renato, Costa, Corrado
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038634/
https://www.ncbi.nlm.nih.gov/pubmed/32012986
http://dx.doi.org/10.3390/s20030728
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author Fanigliulo, Roberto
Antonucci, Francesca
Figorilli, Simone
Pochi, Daniele
Pallottino, Federico
Fornaciari, Laura
Grilli, Renato
Costa, Corrado
author_facet Fanigliulo, Roberto
Antonucci, Francesca
Figorilli, Simone
Pochi, Daniele
Pallottino, Federico
Fornaciari, Laura
Grilli, Renato
Costa, Corrado
author_sort Fanigliulo, Roberto
collection PubMed
description The evaluation of soil tillage quality parameters, such as cloddiness and surface roughness produced by tillage tools, is based on traditional methods ranging, respectively, from manual or mechanical sieving of ground samples to handheld rulers, non-contact devices or Precision Agriculture technics, such as laser profile meters. The aim of the study was to compare traditional methods of soil roughness and cloddiness assessment (laser profile meter and manual sieving), with light drone RGB 3D imaging techniques for the evaluation of different tillage methods (ploughed, harrowed and grassed). Light drone application was able to replicate the results obtained by the traditional methods, introducing advantages in terms of time, repeatability and analysed surface while reducing the human error during the data collection on the one hand and allowing a labour-intensive field monitoring solution for digital farming on the other. Indeed, the profilometer positioning introduces errors and may lead to false reading due to limited data collection. Future work could be done in order to streamline the data processing operation and so to produce a practical application ready to use and stimulate the adoption of new evaluation indices of soil cloddiness, such as Entropy and the Angular Second Moment (ASM), which seem more suitable than the classic ones to achieved data referred to more extended surfaces.
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spelling pubmed-70386342020-03-09 Light Drone-Based Application to Assess Soil Tillage Quality Parameters Fanigliulo, Roberto Antonucci, Francesca Figorilli, Simone Pochi, Daniele Pallottino, Federico Fornaciari, Laura Grilli, Renato Costa, Corrado Sensors (Basel) Article The evaluation of soil tillage quality parameters, such as cloddiness and surface roughness produced by tillage tools, is based on traditional methods ranging, respectively, from manual or mechanical sieving of ground samples to handheld rulers, non-contact devices or Precision Agriculture technics, such as laser profile meters. The aim of the study was to compare traditional methods of soil roughness and cloddiness assessment (laser profile meter and manual sieving), with light drone RGB 3D imaging techniques for the evaluation of different tillage methods (ploughed, harrowed and grassed). Light drone application was able to replicate the results obtained by the traditional methods, introducing advantages in terms of time, repeatability and analysed surface while reducing the human error during the data collection on the one hand and allowing a labour-intensive field monitoring solution for digital farming on the other. Indeed, the profilometer positioning introduces errors and may lead to false reading due to limited data collection. Future work could be done in order to streamline the data processing operation and so to produce a practical application ready to use and stimulate the adoption of new evaluation indices of soil cloddiness, such as Entropy and the Angular Second Moment (ASM), which seem more suitable than the classic ones to achieved data referred to more extended surfaces. MDPI 2020-01-28 /pmc/articles/PMC7038634/ /pubmed/32012986 http://dx.doi.org/10.3390/s20030728 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fanigliulo, Roberto
Antonucci, Francesca
Figorilli, Simone
Pochi, Daniele
Pallottino, Federico
Fornaciari, Laura
Grilli, Renato
Costa, Corrado
Light Drone-Based Application to Assess Soil Tillage Quality Parameters
title Light Drone-Based Application to Assess Soil Tillage Quality Parameters
title_full Light Drone-Based Application to Assess Soil Tillage Quality Parameters
title_fullStr Light Drone-Based Application to Assess Soil Tillage Quality Parameters
title_full_unstemmed Light Drone-Based Application to Assess Soil Tillage Quality Parameters
title_short Light Drone-Based Application to Assess Soil Tillage Quality Parameters
title_sort light drone-based application to assess soil tillage quality parameters
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038634/
https://www.ncbi.nlm.nih.gov/pubmed/32012986
http://dx.doi.org/10.3390/s20030728
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