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Climate-Aware and IoT-Enabled Selection of the Most Suitable Stone Fruit Tree Variety

The application of new technologies such as the Internet of Things offers the opportunity to improve current agricultural development, facilitate daily tasks, and turn farms into efficient and sustainable production systems. The use of these new technologies enables the digital transformation proces...

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Autores principales: López-Morales, Juan A., Martínez, Juan A., Caro, Manuel, Erena, Manuel, Skarmeta, Antonio F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199955/
https://www.ncbi.nlm.nih.gov/pubmed/34205137
http://dx.doi.org/10.3390/s21113867
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author López-Morales, Juan A.
Martínez, Juan A.
Caro, Manuel
Erena, Manuel
Skarmeta, Antonio F.
author_facet López-Morales, Juan A.
Martínez, Juan A.
Caro, Manuel
Erena, Manuel
Skarmeta, Antonio F.
author_sort López-Morales, Juan A.
collection PubMed
description The application of new technologies such as the Internet of Things offers the opportunity to improve current agricultural development, facilitate daily tasks, and turn farms into efficient and sustainable production systems. The use of these new technologies enables the digital transformation process demanded by the sector and provides agricultural collectives with more optimized analysis and prediction tools. Due to climate change, one of the farm industry’s problems is the advance or decay in the cycle of stone fruit trees. The objective is to recommend whether a specific area meets the minimum climatic requirements for planting certain stone fruit trees based on climatic data and bioclimatic indicators. The methodology used implements a large amount of meteorological data to generate information on specific climatic conditions and interactions on crops. In this work, a pilot study has been carried out in the Region of Murcia using an IoT platform. We simulate scenarios for the development of stone fruit varieties better adapted to the environment. Based on the standard, open interfaces, and protocols, the platform integrates heterogeneous information sources and interoperability with other third-party solutions to exchange and exploit such information.
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spelling pubmed-81999552021-06-14 Climate-Aware and IoT-Enabled Selection of the Most Suitable Stone Fruit Tree Variety López-Morales, Juan A. Martínez, Juan A. Caro, Manuel Erena, Manuel Skarmeta, Antonio F. Sensors (Basel) Article The application of new technologies such as the Internet of Things offers the opportunity to improve current agricultural development, facilitate daily tasks, and turn farms into efficient and sustainable production systems. The use of these new technologies enables the digital transformation process demanded by the sector and provides agricultural collectives with more optimized analysis and prediction tools. Due to climate change, one of the farm industry’s problems is the advance or decay in the cycle of stone fruit trees. The objective is to recommend whether a specific area meets the minimum climatic requirements for planting certain stone fruit trees based on climatic data and bioclimatic indicators. The methodology used implements a large amount of meteorological data to generate information on specific climatic conditions and interactions on crops. In this work, a pilot study has been carried out in the Region of Murcia using an IoT platform. We simulate scenarios for the development of stone fruit varieties better adapted to the environment. Based on the standard, open interfaces, and protocols, the platform integrates heterogeneous information sources and interoperability with other third-party solutions to exchange and exploit such information. MDPI 2021-06-03 /pmc/articles/PMC8199955/ /pubmed/34205137 http://dx.doi.org/10.3390/s21113867 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
López-Morales, Juan A.
Martínez, Juan A.
Caro, Manuel
Erena, Manuel
Skarmeta, Antonio F.
Climate-Aware and IoT-Enabled Selection of the Most Suitable Stone Fruit Tree Variety
title Climate-Aware and IoT-Enabled Selection of the Most Suitable Stone Fruit Tree Variety
title_full Climate-Aware and IoT-Enabled Selection of the Most Suitable Stone Fruit Tree Variety
title_fullStr Climate-Aware and IoT-Enabled Selection of the Most Suitable Stone Fruit Tree Variety
title_full_unstemmed Climate-Aware and IoT-Enabled Selection of the Most Suitable Stone Fruit Tree Variety
title_short Climate-Aware and IoT-Enabled Selection of the Most Suitable Stone Fruit Tree Variety
title_sort climate-aware and iot-enabled selection of the most suitable stone fruit tree variety
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199955/
https://www.ncbi.nlm.nih.gov/pubmed/34205137
http://dx.doi.org/10.3390/s21113867
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