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Auxin fluxes through plasmodesmata modify root-tip auxin distribution (2020)
Journal Article
Mellor, N. L., Voß, U., Janes, G., Bennett, M. J., Wells, D. M., & Band, L. R. (in press). Auxin fluxes through plasmodesmata modify root-tip auxin distribution. Development,

Auxin is a key signal regulating plant growth and development. It is well established that auxin dynamics depend on the spatial distribution of efflux and influx carriers on the cell membranes. In this study, we employ a systems approach to character... Read More about Auxin fluxes through plasmodesmata modify root-tip auxin distribution.

RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures (2019)
Journal Article
Yasrab, R., Atkinson, J. A., Wells, D. M., French, A. P., Pridmore, T. P., & Pound, M. P. (2019). RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures. GigaScience, 8(11), https://doi.org/10.1093/gigascience/giz123

© The Author(s) 2019. Published by Oxford University Press. BACKGROUND: In recent years quantitative analysis of root growth has become increasingly important as a way to explore the influence of abiotic stress such as high temperature and drought on... Read More about RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures.

RootNav 2.0: Deep Learning for Automatic Navigation of Complex Plant Root Architectures (2019)
Journal Article
Yasrab, R., Atkinson, J. A., Wells, D. M., French, A. P., Pridmore, T. P., & Pound, M. P. (2019). RootNav 2.0: Deep Learning for Automatic Navigation of Complex Plant Root Architectures. GigaScience, 8(11), https://doi.org/10.1101/709147

We present a new image analysis approach that provides fully-automatic extraction of complex root system architectures from a range of plant species in varied imaging setups. Driven by modern deep-learning approaches, RootNav 2.0 replaces previously... Read More about RootNav 2.0: Deep Learning for Automatic Navigation of Complex Plant Root Architectures.

Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling (2019)
Journal Article
Gibbs, J., French, A., Murchie, E., Wells, D., Pound, M., & Pridmore, T. (2019). Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1-1. https://doi.org/10.1109/TCBB.2019.2896908

Plant phenotyping is the quantitative description of a plant’s physiological, biochemical and anatomical status which can be used in trait selection and helps to provide mechanisms to link underlying genetics with yield. Here, an active vision- based... Read More about Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling.

Rice plants overexpressing OsEPF1 show reduced stomatal density and increased root cortical aerenchyma formation (2019)
Journal Article
Mohammed, U., Caine, R. S., Atkinson, J. A., Harrison, E. L., Wells, D., Chater, C. C., …Murchie, E. H. (2019). Rice plants overexpressing OsEPF1 show reduced stomatal density and increased root cortical aerenchyma formation. Scientific Reports, 9(1), https://doi.org/10.1038/s41598-019-41922-7

Stomata are adjustable pores in the aerial epidermis of plants. The role of stomata is usually described in terms of the trade-off between CO2 uptake and water loss. Little consideration has been given to their interaction with below-ground developme... Read More about Rice plants overexpressing OsEPF1 show reduced stomatal density and increased root cortical aerenchyma formation.

Identification of nitrogen-dependent QTL and underlying genes for root system architecture in hexaploid wheat (2019)
Other
Griffiths, M., Atkinson, J. A., Gardiner, L., Swarup, R., Pound, M. P., Wilson, M. H., …Wells, D. M. (2019). Identification of nitrogen-dependent QTL and underlying genes for root system architecture in hexaploid wheat

The root system architecture (RSA) of a crop has a profound effect on the uptake of nutrients and consequently the potential yield. However, little is known about the genetic basis of RSA and resource dependent response in wheat (Triticum aestivum L.... Read More about Identification of nitrogen-dependent QTL and underlying genes for root system architecture in hexaploid wheat.

Field Phenotyping for the Future (2018)
Book Chapter
Atkinson, J. A., Jackson, R. J., Bentley, A. R., Ober, E., & Wells, D. M. (2018). Field Phenotyping for the Future. Wiley. doi:10.1002/9781119312994.apr0651

Global agricultural production has to double by 2050 to meet the demands of an increasing population and the challenges of a changing climate. Plant phenomics (the characterization of the full set of phenotypes of a given species) has been proposed a... Read More about Field Phenotyping for the Future.

Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction (2018)
Journal Article
PRIDMORE, T., Gibbs, J., Pound, M., French, A., Wells, D., & Murchie, E. (2018). Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction. Plant Physiology, 178(2), 524-534. doi:10.1104/pp.18.00664

Three-dimensional (3D) computer-generated models of plants are urgently needed to support both phenotyping and simulation-based studies such as photosynthesis modelling. However, the construction of accurate 3D plant models is challenging as plants a... Read More about Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction.

Uncovering the hidden half of plants using new advances in root phenotyping (2018)
Journal Article
Atkinson, J. A., Pound, M. P., Bennett, M. J., & Wells, D. M. (2019). Uncovering the hidden half of plants using new advances in root phenotyping. Current Opinion in Biotechnology, 55, doi:10.1016/j.copbio.2018.06.002

Major increases in crop yield are required to keep pace with population growth and climate change. Improvements to the architecture of crop roots promise to deliver increases in water and nutrient use efficiency but profiling the root phenome (i.e.,... Read More about Uncovering the hidden half of plants using new advances in root phenotyping.

A mechanistic framework for auxin dependent Arabidopsis root hair elongation to low external phosphate (2018)
Journal Article
Giehl, R. F. H., Bhosale, R., Giri, J., Pandey, B. K., Giehl, R. F., Hartmann, A., …Swarup, R. (2018). A mechanistic framework for auxin dependent Arabidopsis root hair elongation to low external phosphate. Nature Communications, 9, 1-9. doi:10.1038/s41467-018-03851-3

Phosphate (P) is an essential macronutrient for plant growth. Roots employ adaptive mechanisms to forage for P in soil. Root hair elongation is particularly important since P is immobile. Here we report that auxin plays a critical role promoting root... Read More about A mechanistic framework for auxin dependent Arabidopsis root hair elongation to low external phosphate.

Root gravitropism: quantification, challenges, and solutions (2018)
Journal Article
Muller, L., Bennett, M. J., French, A., Wells, D. M., & Swarup, R. (in press). Root gravitropism: quantification, challenges, and solutions. Methods in Molecular Biology, 1761, doi:10.1007/978-1-4939-7747-5_8

Better understanding of root traits such as root angle and root gravitropism will be crucial for development of crops with improved resource use efficiency. This paper describes a high-throughput, automated image analysis method to trace Arabidopsis... Read More about Root gravitropism: quantification, challenges, and solutions.

Adding a piece to the leaf epidermal cell shape puzzle (2017)
Journal Article
von Wangenheim, D., Wells, D. M., & Bennett, M. J. (2017). Adding a piece to the leaf epidermal cell shape puzzle. Developmental Cell, 43(3), doi:10.1016/j.devcel.2017.10.020

The jigsaw puzzle-shaped pavement cells in the leaf epidermis collectively function as a load-bearing tissue that controls organ growth. In this issue of Developmental Cell, Majda et al. (2017) shed light on how the jigsaw shape can arise from locali... Read More about Adding a piece to the leaf epidermal cell shape puzzle.

An updated protocol for high throughput plant tissue sectioning (2017)
Journal Article
Atkinson, J. A., & Wells, D. M. (2017). An updated protocol for high throughput plant tissue sectioning. Frontiers in Plant Science, 8, https://doi.org/10.3389/fpls.2017.01721

Quantification of the tissue and cellular structure of plant material is essential for the study of a variety of plant sciences applications. Currently, many methods for sectioning plant material are either low throughput or involve free-hand section... Read More about An updated protocol for high throughput plant tissue sectioning.

Linear discriminant analysis reveals differences in root architecture in wheat seedlings by nitrogen uptake efficiency (2017)
Journal Article
Kenobi, K., Atkinson, J. A., Wells, D. M., Gaju, O., deSilva, J. G., Foulkes, M. J., …Bennett, M. J. (2017). Linear discriminant analysis reveals differences in root architecture in wheat seedlings by nitrogen uptake efficiency. Journal of Experimental Botany, 68(17), https://doi.org/10.1093/jxb/erx300

Root architecture impacts water and nutrient uptake efficiency. Identifying exactly which root architectural properties influence these agronomic traits can prove challenging. In this paper approximately 300 wheat plants were divided into four grou... Read More about Linear discriminant analysis reveals differences in root architecture in wheat seedlings by nitrogen uptake efficiency.

Shaping 3D root system architecture (2017)
Journal Article
Morris, E. C., Griffiths, M., Golebiowska, A., Mairhofer, S., Burr-Hersey, J., Goh, T., …Bennett, M. J. (in press). Shaping 3D root system architecture. Current Biology, 27(17), doi:10.1016/j.cub.2017.06.043

Plants are sessile organisms rooted in one place. The soil resources that plants require are often distributed in a highly heterogeneous pattern. To aid foraging, plants have evolved roots whose growth and development are highly responsive to soil si... Read More about Shaping 3D root system architecture.

Deep machine learning provides state-of-the-art performance in image-based plant phenotyping (2017)
Journal Article
Pound, M. P., Atkinson, J. A., Townsend, A. J., Wilson, M. H., Griffiths, M., Jackson, A. S., …French, A. P. (2017). Deep machine learning provides state-of-the-art performance in image-based plant phenotyping. GigaScience, 6(10), doi:10.1093/gigascience/gix083

In plant phenotyping, it has become important to be able to measure many features on large image sets in order to aid genetic discovery. The size of the datasets, now often captured robotically, often precludes manual inspection, hence the motivation... Read More about Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies (2017)
Journal Article
Atkinson, J. A., Lobet, G., Noll, M., Meyer, P. E., Griffiths, M., & Wells, D. M. (2017). Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies. GigaScience, 6(10), doi:10.1093/gigascience/gix084

Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a... Read More about Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies (2017)
Other
Atkinson, J. A., Lobet, G., Noll, M., Meyer, P. E., Griffiths, M., & Wells, D. M. (2017). Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies

Background: Genetic analyses of plant root system development require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to e... Read More about Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies.

Root hydrotropism is controlled via a cortex-specific growth mechanism (2017)
Journal Article
Dietrich, D., Pang, L., Kobayashi, A., Fozard, J. A., Boudolf, V., Bhosale, R., …Bennett, M. J. (2017). Root hydrotropism is controlled via a cortex-specific growth mechanism. Nature Plants, 3(6), https://doi.org/10.1038/nplants.2017.57

Plants can acclimate by using tropisms to link the direction of growth to environmental conditions. Hydrotropism allows roots to forage for water, a process known to depend on abscisic acid (ABA) but whose molecular and cellular basis remains unclear... Read More about Root hydrotropism is controlled via a cortex-specific growth mechanism.