Advances in Hass avocado irrigation scheduling under digital agriculture approach

Abstract

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.

Population Dynamics and Estimation of Damage of the Spittlebug Aeneolamia varia on Sugarcane in Colombia by Using remote Sensing and Machine Learning Tools

“…This study is illustrating how sampling tools do not only generate information for longitudinal analysis of populations, using elements of descriptive and inferential statistics (Binns et al 2000), but also can incorporate the space dimension using location and elements of spatial statistics. Additionally, the remote sensing and GEE platform tools used to indirectly detect injury and damage associated with pest infestation is an example of a useful application associated with the agriculture 4.0 approach (Tyagi 2016;Erazo-Mesa et al 2022), where advanced technologies, whose objective is the management of information, will enhance the decision-making process (Kamilaris et al 2017;Erazo-Mesa et al 2022) with multiple economic benefits and environmental indicators in the production systems where they are implemented (Karmas et al 2016;Kamilaris et al 2017;Méndez-Vázquez et al 2019).…”