Authors:
Abdellatif Moussaid
1
;
Sanaa El Fkihi
2
and
Yahya Zennayi
3
Affiliations:
1
ENSIAS,UM5 & MASCIR FONDATION
;
2
ENSIAS,UM5
;
3
MASCIR FONDATION
Keyword(s):
Smart Agriculture, Artificial Intelligence, Citrus Monitoring, Remote Sensing, Machine Learning, Deep Learning
Abstract:
In recent years, with the emergence of new technologies, in particular artificial intelligence techniques and remote sensing data, agriculture has become intelligent. These technologies have helped us to improve the quality and quantity of yield, and to facilitate many difficult tasks for farmers.
In this paper, we will present an extensive review of the techniques and themes used in the field of agriculture in general, and citrus crop in particular, through the realization of a bibliometric and bibliographic study based on several published articles over the last years.
Through an in-depth analysis of several works, we have found that there are several factors that are very interesting in this field. In fact, we have many parameters related to trees such as detection and counting; canopy or crown size; tree location; detection of individual trees and missing trees, etc. We have also the effect of vegetation indices such as normalized difference vegetation index(NDVI), normalized di
fference red edge index(NDRE), modified chlorophyll absorption ratio index(MCARI), etc. Which are strongly correlated with fruit production. In addition, monitoring tree health and water stress is very interesting. All these factors and more can be obtained from high-resolution spectral images, using machine learning algorithms, remote sensing techniques, and image processing.
The purpose of this study is to explain how we can control the situation of orchards to have better yield.
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