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

Author:

López-Morales Juan A.ORCID,Martínez Juan A.ORCID,Caro Manuel,Erena ManuelORCID,Skarmeta Antonio F.ORCID

Abstract

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.

Funder

H2020 European Institute of Innovation and Technology

PRIMA

European Regional Development Fund

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference53 articles.

1. Dormancy of Trees in Winter

2. Unveiling winter dormancy through empirical experiments

3. Declining chilling and its impact on temperate perennial crops

4. Agroseguro—Informe Sobre Siniestralidad del Ejercicio 2020https://agroseguro.es/fileadmin/propietario/Home/INFORMES_SINIESTRALIDAD/0.11._Informe_TOTAL_SINIESTRALIDADES_2020_30_noviembre_2020.pdf

5. Open data model for (precision) agriculture applications and agricultural pollution monitoring;Rezník,2015

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