Magnetic resonance imaging (MRI) enables nondestructive 3D imaging and quantification of roots or root system architecture in soil and is suited for automated a

Roots are vital to plants for soil exploration and uptake of water and nutrients. Root performance is critical for growth and yield of plants, in particular when resources are limited. Since roots develop in strong interaction with the soil matrix, tools are required that can visualize and quantify root growth in opaque soil at best in 3D. Two modalities that are suited for such investigations are X-ray Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Due to the different physical principles they are based on, these modalities have their specific potentials and challenges for root phenotyping. We compared the two methods by imaging the same root systems grown in 3 different pot sizes with inner diameters of 34 mm, 56 mm or 81 mm. Both methods successfully visualized roots of two weeks old bean plants in all three pot sizes. Similar root images and almost the same root length were obtained for roots grown in the small pot, while more root details showed up in the CT images compared to MRI. For the medium sized pot, MRI showed more roots and higher root lengths whereas at some spots thin roots were only found by CT and the high water content apparently affected CT more than MRI. For the large pot, MRI detected much more roots including some laterals than CT. Both techniques performed equally well for pots with small diameters which are best suited to monitor root development of seedlings. To investigate specific root details or finely graduated root diameters of thin roots, CT was advantageous as it provided the higher spatial resolution. For larger pot diameters, MRI delivered higher fractions of the root systems than CT, most likely because of the strong root-to-soil contrast achievable by MRI. Since complementary information can be gathered with CT and MRI, a combination of the two modalities could open a whole range of additional possibilities like analysis of root system traits in different soil structures or under varying soil moisture.

Updates in nanopore technology have made it possible to obtain gigabases of sequence data. Prior to this, nanopore sequencing technology was mainly used to analyze microbial samples. Here, we describe the generation of a comprehensive nanopore sequencing data set with a median read length of 11,979 bp for a self-compatible accession of the wild tomato species Solanum pennellii. We describe the assembly of its genome to a contig N50 of 2.5 MB. The assembly pipeline comprised initial read correction with Canu and assembly with SMARTdenovo. The resulting raw nanopore-based de novo genome is structurally highly similar to that of the reference S. pennellii LA716 accession but has a high error rate and was rich in homopolymer deletions. After polishing the assembly with Illumina reads, we obtained an error rate of <0.02% when assessed versus the same Illumina data. We obtained a gene completeness of 96.53%, slightly surpassing that of the reference S. pennellii. Taken together, our data indicate that such long read sequencing data can be used to affordably sequence and assemble gigabase-sized plant genomes.

Plant phenotyping enables noninvasive quantification of plant structure and function and interactions with environments. High-capacity phenotyping reaches hitherto inaccessible phenotypic characteristics. Diverse, challenging, and valuable applications of phenotyping have originated among scientists, prebreeders, and breeders as they study the phenotypic diversity of genetic resources and apply increasingly complex traits to crop improvement. Noninvasive technologies are used to analyze experimental and breeding populations. We cover the most recent research in controlled-environment and field phenotyping for seed, shoot, and root traits. Select field phenotyping technologies have become state of the art and show promise for speeding up the breeding process in early generations. We highlight the technologies behind the rapid advances in proximal and remote sensing of plants in fields. We conclude by discussing the new disciplines working with the phenotyping community: data science, to address the challenge of generating FAIR (findable, accessible, interoperable, and reusable) data, and robotics, to apply phenotyping directly on farms.

• Aims Production of biomass and yield in natural and agronomic conditions depend on the endogenous growth capacity of plants and on the environmental conditions constraining it. Sink growth drives the competition for carbon, nutrients and water within the plant, and determines the structure of leaves and roots that supply resources to the plant later on. For their outstanding importance, analyses of internal growth mechanisms and of environmental impact on plant growth are long-standing topics in plant sciences. • Scope Recent technological developments have made it feasible to study the dynamics of plant growth in temporal and spatial scales that are relevant to link macroscopic growth with molecular control. These developments provided first insights into the truly dynamic interaction between environment and endogenous control of plant growth. • Conclusions Evidence is presented in this paper that the relative importance of endogenous control versus the impact of the dynamics of the environment depends on the frequency pattern of the environmental conditions to which the tissue is exposed. It can further be speculated that this is not only relevant within individual plants (hence leaves versus roots), but also crucial for the adaptation of plant species to the various dynamics of their environments. The following are discussed: mechanisms linking growth and concentrations of primary metabolites, and differences and homologies between spatial and temporal patterns of root and leaf growth with metabolite patterns.

Plants are much more dynamic than we usually expect them to be. This dynamic behaviour is of paramount importance for their performance under natural conditions, when resources are distributed heterogeneously in space and time. However, plants are not only the cue ball of their physical and chemical environment. Endogenous rhythms and networks controlling photosynthesis and growth buffer plant processes from external fluctuations. This review highlights recent evidence of the importance of dynamic temporal and spatial organization of photosynthesis and of growth in leaves and roots. These central processes for plant performance differ strongly in their dependence on environmental impact and endogenous properties, respectively. Growth involves a wealth of processes ranging from the supply of resources from external and internal sources to the growth processes themselves. In contrast, photosynthesis can only take place when light and CO₂ are present and thus clearly requires ‘input from the environment’. Nevertheless, growth and photosynthesis are connected to each other via mechanisms that are still not fully understood. Recent advances in imaging technology have provided new insights into the dynamics of plant–environment interactions. Such processes do not only play a crucial role in understanding stress response of plants under extreme environmental conditions. Dynamics of plants under modest growth conditions rise from endogenous mechanisms as well as exogenous impact too. It is thus an important task for future research to identify how dynamic external conditions interact with plant‐internal signalling networks to optimize plant behaviour in real time and to understand how plants have adapted to characteristic spatial and temporal properties of the resources from their environment, on which they depend on.