Recent Posts

Machine learning enables high-throughput phenotyping for analyses of the genetic architecture of bulliform cell patterning in maize (G3)

Bulliform cells lie in rows along the upper (adaxial) surface of the maize leaf, and through changes in volume contribute to leaf-rolling, which is a response to water deficit. Several mutants have been identified that affect bulliform cell formation and function, but as yet their occurance in natural…

Three-dimensional time-lapse analysis of maize root system archictecture (Plant Cell)

Root system architecture (RSA) profoundly affects plant nutritent uptake and response to drought, and is also famously extremely developmental plastic, which makes it difficult to identify genes that control root growth traits. Here, Jiang et al. analyzed 3D growth patterns over time of three maize lines…

GRANAR, a new computational tool to better understand the functional importance of root anatomy (bioRxiv)

Uptake of water by plants depends on root conductivity, which in turn is determined by hydraulic properties of individual cells and cell anatomy. Quantification of radial root anatomy is a time-consuming process, limiting our understanding of root anatomical features contributing to water uptake. Heymans…

A growth-based framework for leaf shape development and diversity (Cell)

The leaf shape is one of the features defining the diversity in the plant kingdom. However, it is still not understood how action of individual genes is linked to this morphological diversity. Kierzkowski et al. developed an imaging protocol to study the leaf primodium development to understand the cellular…

A diversity of traits contributes to salinity tolerance of wild Galapagos tomatoes seedlings (bioRxiv)

Domestication has been accompanied by a decrease in genetic diversity, so efforts to improve stress tolerance can be aided by exploring the crop’s wild relatives. Here, Pailles et al. examined salt tolerance in Galapagos tomatoes (Solanum cheesmaniae and Solanum galapagense), which grow “constantly…

Review: Deep learning on image-based plant phenotyping (Trends Plant Sci)

The development of deep learning brings opportunities to train computers to solve complex questions. Self-driving vehicles are classic examples of an application of deep learning in the real world. However, the large amounts of data that are required for building accurate models and avoiding overfitting…