Under changing climate and burgeoning food production demands, climate-smart
agriculture (CSA) practices are the need of the hour. Physically-based crop models have …

Precision coffee-growing technologies contribute to increased yield, operational efficiency,
and final product quality. In addition, they strengthen coffee growing in the global agricultural …

Accurate canopy mapping and head-volume estimation of large areas of broccoli is an
important prerequisite for precision farming since it provides important phenotypic traits …

Abstract Unmanned Aerial Vehicles (UAVs) combined with machine learning have a great
potential for crop yield estimation. In this study, a UAV equipped with an RGB (Red, Green …

Leaf area index (LAI) is a widely used plant biophysical parameter required for modelling
plant photosynthesis and crop yield estimation. UAV remote sensing plays an increasingly …

Nowadays, agriculture faces several challenges in ensuring food safety. Water scarcity is
one of the main challenges facing farmers in the rainfed agriculture sector, especially during …

The objective of this study was to evaluate the potential of the practical application of
unmanned aerial vehicles and RGB vegetation indices (VIs) in the monitoring of a coffee …

Coffee ripeness monitoring is a key indicator for defining the moment of starting the harvest,
especially because the coffee quality is related to the fruit ripeness degree. The most used …

The fraction of absorbed photosynthetically active radiation (fAPAR) is a critical biophysical
parameter for crop growth monitoring and yield estimation. Remote sensing provides an …

Leaf area is a component of crop growth and yield prediction models. Few studies have
used the structure from motion (SfM) algorithm, which is based on the principles of traditional …