Going beyond previous work, this paper presents a systematic literature review that explores
the deployment of satellites, drones, and ground-based sensors for yield prediction in …

In this paper, we propose an innovative approach for robust prediction of processing tomato
yield using open-source AutoML techniques and statistical analysis. Sentinel-2 satellite …

Anthocyanins are severity indicators for apple mosaic disease and can be used to monitor
tree health. However, most of the current studies have focused on healthy leaves, and few …

Estimation of fruit quality parameters are usually based on destructive techniques which are
tedious, costly and unreliable when dealing with huge amounts of fruits. Alternatively, non …

Predicting tomato yield is crucial for agricultural production planning, management, market
supply, and risk management. While yield prediction in precision agriculture presents a …

Over the last years the use of Machine Learning in agriculture has increased in order to
reach the increasing demands of the food sector. However, over the last few years there …

A major issue in several farming areas of the Mediterranean basin consists of drought and
salinity stress. This stress is mainly due to a steady exposition of warm daily temperature …

Biomass is strictly related to nitrogen (N) status, and its non-destructive estimation can be of
interest to precision N management. Some spectral vegetation indices (SVIs) were …

Crop production plays an important role in the Canadian Prairie economy. Crop yield
models based on satellite data offer promise for obtaining consistent yield estimates across …

Precisely predicting wheat yields is essential for food security and agricultural planning, but
implementing a useful prediction model is a complex task as their utility for management …