Machine Learning (ML) algorithms have been used as an alternative to conventional and
geostatistical methods in digital mapping of soil attributes. An advantage of ML algorithms is …

Management zones (MZs) are efficient for applying site-specific management in agricultural
fields. This study proposes an approach for generating MZs using time-series clustering …

Variable rate application (VRA) is a crucial tool in precision agriculture, utilizing platforms
such as Google Earth Engine (GEE) to access vast satellite image datasets and employ …

Diverse on-farm agronomic data, gathered via precision agriculture (PA), require depuration
and joint analysis of multiple georeferenced field characteristics such as crop yields, and soil …

The identification of zones within an agricultural field that respond differently to
environmental factors and agronomic management is a key requirement for the adoption of …

One of the main questions facing precision agriculture is the evaluation of different
algorithms for the delineation of homogeneous management zones. In the present study, a …

Site-specific agricultural management (SSM) relies on identifying within-field spatial
variability and is used for variable rate input of resources. Precision agricultural …

Precision agriculture has been increasingly practised in recent years. Under precision
management, farmland is divided into several management zones to implement different …

Despite the promise of precision agriculture for increasing the productivity by implementing
site-specific management, farmers remain skeptical and its utilization rate is lower than …

In modern agriculture, understanding the spatio-temporal variability in crop fields and the
implications of environmental factors in soil management are important for sustainable …