A scoping review of the relevant literature was carried out to identify the existing N
recommendation systems, their temporal and geographical diffusion, and knowledge gaps …

Abstract The Oklahoma State University algorithm (OSU) is the most widespread
recommendation system to calculate the optimal nitrogen (N) rate in cereal crops. This …

Cover crops and precision fertilization are two core strategies to advance sustainable
agriculture. Based on a review of proven achievements in remote sensing of vegetation, a …

Climate change is expected to have impacts on the balance of global food trade networks
and food security. Thus, seasonal forecasts of precipitation and temperature are an essential …

In this study, the spatial variability of nitrogen (N) balances were determined on
heterogeneous arable fields in southern Germany using digital methods (combine yield …

One challenge in precision nitrogen (N) management is the uncertainty in future weather
conditions at the time of decision-making. Crop growth models require a full season of …

Leaf chlorophyll content (LCC) is one of important indicators for photosynthesis evaluation
and crop nutrition diagnosis. For establishing an accuracy LCC diagnosis model, this study …

Hyperspectral imaging (HSI) technology provides an efficient and non-destructive tool for
studying leaf chlorophyll content (LCC) to evaluate photosynthesis capability and crop …

Crop nitrogen (N) demand is defined by various physiological, management and
environmental factors that interact with each other and involve temporal and spatial …

Agricultural crop management requires extensive and comprehensive tools that allow for a
full knowledge of the crops' status and growth dynamic. This study aims at estimating crop …