In the past, there have been drought events in different parts of the world, which have
negatively influenced the productivity and production of various crops including wheat …

The rapid increases of the global population and climate change pose major challenges to a
sustainable production of food to meet consumer demands. Process-based models (PBMs) …

Deep learning presents many opportunities for image-based plant phenoty**. Here we
consider the capability of deep convolutional neural networks to perform the leaf counting …

Rhododendron delavayi Franch. is globally famous as an ornamental plant. Its distribution in
southwest China covers several different habitats and environments. However, not much …

Background Root system architecture (RSA) traits are of interest for breeding selection;
however, measurement of these traits is difficult, resource intensive, and results in large …

Root crown phenoty** measures the top portion of crop root systems and can be used for
marker-assisted breeding, genetic map**, and understanding how roots influence soil …

Image analysis has become a powerful technique for most plant scientists. In recent years
dozens of image analysis tools have been published in plant science journals. These tools …

High-throughput phenoty** (HTP) platforms are capable of monitoring the phenotypic
variation of plants through multiple types of sensors, such as red green and blue (RGB) …

One of the most challenging computer vision problems in the plant sciences is the
segmentation of roots and soil in X-ray tomography. So far, this has been addressed using …

Computational models of plants have identified gaps in our understanding of biological
systems, and have revealed ways to optimize cellular processes or organ‐level architecture …