Computer vision is a field that involves making a machine “see”. This technology uses a
camera and computer instead of the human eye to identify, track and measure targets for …

The key elements that underpin food security require the adaptation of agricultural systems
to support productivity increases while minimizing inputs and the adverse effects of climate …

Early prediction of grain yield helps scientists to make better breeding decisions for wheat.
Use of machine learning (ML) methods for fusion of unmanned aerial vehicle (UAV)-based …

Rapid and accurate biomass and yield estimation facilitates efficient plant phenotyping and
site-specific crop management. A low altitude unmanned aerial vehicle (UAV) was used to …

Rapid and non-destructive potato above ground biomass (AGB) monitoring is a crucial step
in the development of smart agriculture because AGB is closely related to crop growth, yield …

When dealing with multiple growth stages, estimates of above-ground biomass (AGB) based
on optical vegetation indices (VIs) are difficult for two reasons:(i) optical VIs saturate at …

The increasing demand of smart agriculture has led to the significant growth and
development in the field of crop estimation and prediction improving its productivity. The …

Monitoring the aboveground biomass (AGB) of maize is essential for improving site-specific
nutrient management and predicting yield to ensure food safety. A low-altitude unmanned …

Optimizing nitrogen (N) management in rice is crucial for China's food security and
sustainable agricultural development. Nondestructive crop growth monitoring based on …

Corn yields vary spatially and temporally in the plots as a result of weather, altitude, variety,
plant density, available water, nutrients, and planting date; these are the main factors that …