Rui Xie

• PhD
• PhD Student at University of Twente

Phenolic compounds constitute an essential part of the plant’s secondary metabolites and play a crucial role in ecosystem functioning, including nutrient cycling and plant defence against biotic and abiotic stressors. Quantifying the phenolic compounds across global biomes is important for monitoring the biological diversity and ecosystem processes...

Machine learning algorithms, in particular, kernel-based machine learning methods such as Gaussian processes regression (GPR) have shown to be promising alternatives to traditional empirical methods for retrieving vegetation parameters from remotely sensed data. However, the performance of GPR in predicting forest biophysical parameters has hardly...

Foliar functional traits are dynamic plant properties that vary across space and time, serving as principal tools for monitoring plant physiology and terrestrial ecosystem processes. Phenolics are the most crucial secondary metabolites that play key roles in plant defence against biotic and abiotic stressors, leaf decomposition, as well as conseque...

Total phenolics are an important group of secondary metabolites universally distributed in vascular plants and play an essential role in the defence of plants against biotic and abiotic stressors (also known as “defence traits”). Accurate quantification of total phenolics is key for understanding the phytochemical diversity and plant response to en...

Machine learning algorithms, and specifically kernel-based methods such as Gaussian processes regression (GPR), have been shown to outperform traditional empirical methods for retrieving vegetation traits. GPR is attractive for its property of automatically generating uncertainty estimates for predicted traits. GPR has been increasingly used for th...