Nitrogen fertilization has a crucial role in sugar beet production, especially concerning root
yield and quality. This study employed a machine learning approach to predict root yield and …

There are various methods often regard to done for analysis of the subject of a particular
group of specimen. There may be more or fewer, but by using classification techniques with …

Uncrewed aerial systems (UASs) provide high temporal and spatial resolution information
for crop health monitoring and informed management decisions to improve yields. However …

Corn (Zea mays L.) nitrogen (N) management requires monitoring plant N concentration
(Nc) with remote sensing tools to improve N use, increasing both profitability and …

Maturity is an important trait in dry pea breeding programs, but the conventional process
predominately used to measure this trait can be time-consuming, labor-intensive, and prone …

Accurate assessing leaf nitrogen content (LNC) is crucial for actual production and fertilizer
management. In this research, a portable device was designed to rapidly and non …

Foliar nitrogen (N) plays a central role in photosynthetic machinery of plants, regulating their
growth rates. However, field-based methods for monitoring plant N concentration are costly …

In-season sensing can account for field variability and improve nitrogen (N) management;
however, opportunities exist for refinement. The purpose of this study was to compare …

Fast diagnostics from hyperspectral data and machine learning (ML) models to predict
nitrogen (N) and pigment content in maize crops is challenging to optimize nitrogen …

Nitrogen is an essential plant nutrient, but in excess amounts in the soil can cause
significant water quality problems. Since nitrate is very soluble and is not retained by soil, it …