Predicting soil water status remotely is appealing due to its low cost and large‐scale
application. During drought, plants can disconnect from the soil, causing disequilibrium …

Roots are essential for acquiring water and nutrients to sustain and support plant growth and
anchorage. However, they have been studied less than the aboveground traits in …

Collecting and analyzing hyperspectral imagery (HSI) of plant roots over time can enhance
our understanding of their function, responses to environmental factors, turnover, and …

Plant roots are difficult to monitor and study since they are hidden belowground.
Minirhizotrons offer an in-situ monitoring solution but their widespread adoption is still …

Plant phenoty** is essential in agricultural research for identifying resilient traits critical for
global food security. Analyzing root growth quantitatively is increasingly vital for evaluating a …

Roots optimize the acquisition of limited soil resources, but relationships between root forms
and functions have often been assumed rather than demonstrated. Furthermore, how root …

Current existing methods are either not very discriminative or too complex. In this work, an
effective and very simple plant recognition method is proposed. The main innovations of our …

Artificial Intelligence (AI) has been enhancing data analysis efficiency and accuracy during
plant phenoty**, which is vital for tackling global agricultural and environmental …

In the computer vision literature, many effective histogram-based features have been
developed. These engineered features include local binary patterns and edge histogram …

Feature representation is an important aspect of remote-sensing-based image classification.
While deep convolutional neural networks (DCNNs) are able to effectively amalgamate …