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Advances in Hass avocado irrigation scheduling under digital agriculture approach
Author(s) -
Edwin Erazo-Mesa,
Andrés Echeverri-Sánchez,
Joaquín Guillermo RamírezGil
Publication year - 2022
Publication title -
revista colombiana de ciencias hortícolas/revista colombiana de ciencias hortícolas
Language(s) - English
Resource type - Journals
eISSN - 2422-3719
pISSN - 2011-2173
DOI - 10.17584/rcch.2022v16i1.13456
Subject(s) - irrigation , irrigation scheduling , software portability , computer science , agriculture , agricultural engineering , schedule , precision agriculture , environmental science , remote sensing , geography , operating system , agronomy , ecology , engineering , biology
Under tropical conditions, Hass avocado irrigation is a controversial issue due to insufficient scientific evidence. The rapid progression of technological advances and its incorporation in agriculture have expanded options to improve the irrigation scheduling (IS) of Hass avocado. The concept featuring those technological advances in agriculture is digital agriculture (DA). Here, we present a mixture of well-known studies in the Hass avocado irrigation focused on proximal sensing (PS) technologies and recent studies emphasizing the potential of remote sensing (RS), and application technologies to schedule the irrigation. PS takes advantage of the soil or trees' proximity to output reliable measurements with a high temporal resolution, while RS provides a broad set of spectral data in continuous and large areas that can be transformed into crop-related biophysical variables. Applications – a term grouping mobile (smartphone) apps, desktop programs, and web-based platforms – offers portability, high precision, and graphic visualization of variables obtained or estimated by sensors. Integrating RS and PS technologies through user-friendly applications can represent a suitable option to improve Hass avocado irrigation in developing countries. Our review is presented in the following sections: general introduction, DA approach definition, use of proximal sensing, use of remote sensing, and scheduling irrigation applications.

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