Agriculture is considered one of the most important sectors that play a strategic role in
ensuring food security. However, with the increasing world's population, agri-food demands …

Abstract Machine learning is an important decision support tool for crop yield prediction,
including supporting decisions on what crops to grow and what to do during the growing …

Various forms of machine learning (ML) methods have historically played a valuable role in
environmental remote sensing research. With an increasing amount of “big data” from earth …

Agriculture plays an important role in sustaining all human activities. Major challenges such
as overpopulation, competition for resources poses a threat to the food security of the planet …

Preharvest crop yield prediction is critical for grain policy making and food security. Early
estimation of yield at field or plot scale also contributes to high-throughput plant phenotyping …

Normalized difference vegetation index (NDVI) derived from satellites has been ubiquitously
utilized in the field of remote sensing. Nevertheless, there are multitudinous contaminations …

There is a rapid increase in the adoption of emerging technologies like the Internet of Things
(IoT), Unmanned Aerial Vehicles (UAV), Internet of Underground Things (IoUT), Data …

Machine learning has emerged with big data technologies and high-performance computing
to create new opportunities for data intensive science in the multi-disciplinary agri …

Many studies have applied machine learning to crop yield prediction with a focus on specific
case studies. The data and methods they used may not be transferable to other crops and …

Accurate yield estimation and optimised nitrogen management is essential in agriculture.
Remote sensing (RS) systems are being more widely used in building decision support tools …