Using of Digital Agriculture, Machine Learning, Remote Sensing and Smart Approaches in Fruit Orchards

Abstract

In recent years, advances in remote sensing technologies have made considerable progress in the monitoring of orchards. These technologies provide externally, gently and non-destructively, cost-effective and scalable solutions to assess crop quality and health, detect abiotic and biotic stress factors and optimise orchard management practices. The objective of this paper is to provide a comprehensive review of recent advancements in the field of remote sensing techniques, machine learning, deep learning, unmanned aerial vehicles, and intelligent systems in orchard management. This review aims to offer a comprehensive overview of the application of these techniques in orchards and to propose relevant recommendations. Firstly, the paper sets out the principles of remote sensing using various sensors and platforms for the purpose of creating a data pool through the use of broad spectrum, hyperspectral and thermal imaging technologies. The paper then examines in detail the studies on these issues and the resulting detailed information obtained about fruit trees and the environmental environments in which they are located. The subsequent discourse delves into the applications of remote sensing in the context of monitoring fundamental biophysical parameters, including vegetation indices, canopy structure, and water stress. The text does not address the subject of the development of decision-making processes for operational requirements in orchard management, with the objective of ensuring accuracy and timeliness. Furthermore, the text goes on to explore the ways in which diseases can be detected before they reach the damage threshold, the estimated yield, and the practical benefits of remote sensing in precision agriculture applications in orchards, with the aid of illustrative examples. The challenges that may be encountered, such as the processing of data, the integration of data sources, and the scalability of the system, have been thoroughly examined in conjunction with the research and technological advancements. In addition, the study encompassed the following: The utilisation of digital agriculture, machine learning, remote sensing and smart system techniques has been demonstrated to be a highly effective means of increasing fruit production. It is hypothesised that the implementation of such novel approaches in the domain of fruit orchard management by researchers and decision-makers will engender contributions to the enhancement of fruit yield and the sustainability of fruit production.