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All Outputs (52)

Field Phenotyping for the Future (2018)
Journal Article
Atkinson, J. A., Jackson, R. J., Bentley, A. R., Ober, E., & Wells, D. M. (in press). Field Phenotyping for the Future. Annual Plant Reviews Online, https://doi.org/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
Gibbs, J., Pound, M., French, A. P., Wells, D. M., Murchie, E., & Pridmore, T. (2018). Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction. Plant Physiology, 178(2), 524-534. https://doi.org/10.1104/pp.18.00664

© 2018 American Society of Plant Biologists. All rights reserved. Three-dimensional (3D) computer-generated models of plants are urgently needed to support both phenotyping and simulation-based studies such as photosynthesis modeling. However, the co... 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, 1-8. https://doi.org/10.1016/j.copbio.2018.06.002

© 2018 The Authors 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 r... Read More about Uncovering the hidden half of plants using new advances in root phenotyping.

Erratum: Author Correction: A mechanistic framework for auxin dependent Arabidopsis root hair elongation to low external phosphate (Nature communications (2018) 9 1 (1409)) (2018)
Journal Article
Bhosale, R., Giri, J., Pandey, B. K., Giehl, R. F. H., Hartmann, A., Traini, R., …Swarup, R. (2018). Erratum: Author Correction: A mechanistic framework for auxin dependent Arabidopsis root hair elongation to low external phosphate (Nature communications (2018) 9 1 (1409)). Nature Communications, 9(1), 1818. https://doi.org/10.1038/s41467-018-04281-x

The original version of this Article omitted the following from the Acknowledgements: 'We also thank DBT-CREST BT/HRD/03/01/2002.'This has been corrected in both the PDF and HTML versions of the Article.

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), 1-9. https://doi.org/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. (2018). Root gravitropism: quantification, challenges, and solutions. Methods in Molecular Biology, 1761, 103-112. https://doi.org/10.1007/978-1-4939-7747-5_8

© 2018, Springer Science+Business Media, LLC. 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 chapter describes a high-throughput, autom... 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), 255-256. https://doi.org/10.1016/j.devcel.2017.10.020

© 2017 Elsevier Inc. 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... 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.

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. (2017). Shaping 3D root system architecture. Current Biology, 27(17), R919-R930. https://doi.org/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.

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), https://doi.org/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.

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), Article gix083. https://doi.org/10.1093/gigascience/gix083

© The Author 2017. 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, h... Read More about Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

Linear discriminant analysis reveals differences in root architecture in wheat seedlings related to 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 related to nitrogen uptake efficiency. Journal of Experimental Botany, 68(17), 4969-4981. https://doi.org/10.1093/jxb/erx300

© The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. Root architecture impacts water and nutrient uptake efficiency. Identifying exactly which root architectural properties influence these agronom... Read More about Linear discriminant analysis reveals differences in root architecture in wheat seedlings related to nitrogen uptake efficiency.

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), Article 17057. 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.

Quiescent center initiation in the Arabidopsis lateral root primordia is dependent on the SCARECROW transcription factor (2016)
Journal Article
Goh, T., Toyokura, K., Wells, D. M., Swarup, K., Yamamoto, M., Mimura, T., …Guyomarc'h, S. (2016). Quiescent center initiation in the Arabidopsis lateral root primordia is dependent on the SCARECROW transcription factor. Development, 143(18), 3363-3371. https://doi.org/10.1242/dev.135319

Lateral root (LR) formation is an important determinant of root system architecture. In Arabidopsis, LRs originate from pericycle cells, which undergo a programme of morphogenesis to generate a new LR meristem. Despite its importance for root meriste... Read More about Quiescent center initiation in the Arabidopsis lateral root primordia is dependent on the SCARECROW transcription factor.

Approaches to three-dimensional reconstruction of plant shoot topology and geometry (2016)
Journal Article
Gibbs, J., Pound, M. P., French, A. P., Wells, D. M., Murchie, E. H., & Pridmore, T. P. (2016). Approaches to three-dimensional reconstruction of plant shoot topology and geometry. Functional Plant Biology, 44(1), 62-75. https://doi.org/10.1071/FP16167

There are currently 805 million people classified as chronically undernourished, and yet the World’s population is still increasing. At the same time, global warming is causing more frequent and severe flooding and drought, thus destroying crops and... Read More about Approaches to three-dimensional reconstruction of plant shoot topology and geometry.

Characterization of pearl millet root architecture and anatomy reveals three types of lateral roots (2016)
Journal Article
Passot, S., Gnacko, F., Moukouanga, D., Lucas, M., Guyomarc’h, S., Ortega, B. M., …Laplaze, L. (2016). Characterization of pearl millet root architecture and anatomy reveals three types of lateral roots. Frontiers in Plant Science, 7(June2016), https://doi.org/10.3389/fpls.2016.00829

© 2016 Passot, Gnacko, Moukouanga, Lucas, Guyomarc’h, Moreno Ortega, Atkinson, Belko, Bennett, Gantet, Wells, Guédon, Vigouroux, Verdeil, Muller and Laplaze. Pearl millet plays an important role for food security in arid regions of Africa and India.... Read More about Characterization of pearl millet root architecture and anatomy reveals three types of lateral roots.

Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping (2016)
Working Paper
Pound, M. P., Burgess, A. J., Wilson, M. H., Atkinson, J. A., Griffiths, M., Jackson, A. S., …French, A. P. Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping

Deep learning is an emerging field that promises unparalleled results on many data analysis problems. We show the success offered by such techniques when applied to the challenging problem of image-based plant phenotyping, and demonstrate state-of-th... Read More about Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping.

Three-dimensional reconstruction of plant shoots from multiple images using an active vision system (2015)
Journal Article
Gibbs, J., Pound, M. P., Wells, D. M., Murchie, E. H., French, A. P., & Pridmore, T. P. (2015). Three-dimensional reconstruction of plant shoots from multiple images using an active vision system

The reconstruction of 3D models of plant shoots is a challenging problem central to the emerging discipline of plant phenomics – the quantitative measurement of plant structure and function. Current approaches are, however, often limited by the use o... Read More about Three-dimensional reconstruction of plant shoots from multiple images using an active vision system.

The circadian clock rephases during lateral root organ initiation in Arabidopsis thaliana (2015)
Journal Article
Voß, U., Wilson, M. H., Kenobi, K., Gould, P. D., Robertson, F. C., Peer, W. A., …Bennett, M. J. (2015). The circadian clock rephases during lateral root organ initiation in Arabidopsis thaliana. Nature Communications, 6(1), Article 7641. https://doi.org/10.1038/ncomms8641

The endogenous circadian clock enables organisms to adapt their growth and development to environmental changes. Here we describe how the circadian clock is employed to coordinate responses to the key signal auxin during lateral root (LR) emergence.... Read More about The circadian clock rephases during lateral root organ initiation in Arabidopsis thaliana.