Over the past ten years, plant phenoty** technologies that utilize sensing and data mining
approaches to estimate crop traits in a high-throughput and objective manner, have been …

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 …

Soybean yield predictions in Brazil are of great interest for market behavior, to drive
governmental policies and to increase global food security. In Brazil soybean yield data …

Despite significant progress has been made towards crop yield prediction with remote
sensing, there exist knowledge gaps on (1) the impacts of temporal resolution of imaging …

Monitoring and prediction of within-field crop variability can support farmers to make the right
decisions in different situations. The current advances in remote sensing and the availability …

Crop yield prediction for an ongoing season is crucial for food security interventions and
commodity markets for decisions such as inventory management, understanding yield …

Farmer's management decisions and environmental factors are the main drivers for field
spatial and temporal yield variability. In this study, a 22 ha field cultivated with corn for more …

Yield monitoring systems in fruit production mostly rely on color features, making the
discrimination of fruits challenging due to varying light conditions. The implementation of …

Yield maps provide essential information to guide precision agriculture (PA) practices. Yet,
on-board yield monitoring for sugarcane can be challenging. At the same time, orbital …

Map** crop within-field yield variability provide an essential piece of information for
precision agriculture applications. Leaf Area Index (LAI) is an important parameter that …