Dr DARREN WELLS's Outputs (74)

Deep Learning for Multi-task Plant Phenotyping (2017)
Preprint / Working Paper
Pound, M. P., Atkinson, J. A., Wells, D. M., Pridmore, T. P., & French, A. P. (2017). Deep Learning for Multi-task Plant Phenotyping

Plant phenotyping has continued to pose a challenge to computer vision for many years. There is a particular demand to accurately quantify images of crops, and the natural variability and structure of these plants presents unique difficulties. Recent... Read More about Deep Learning for Multi-task Plant Phenotyping.

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., von Wangenheim, D., Atkinson, B., Sturrock, C. J., Lynch, J. P., Vissenberg, K., Ritz, K., Wells, D. M., Mooney, S. J., & 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., Bulat, A., Tzimiropoulos, G., Wells, D. M., Murchie, E. H., Pridmore, T. P., & 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., Dryden, I. L., Wood, A. T., & 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., Antoni, R., Nguyen, T., Hiratsuka, S., Fujii, N., Miyazawa, Y., Bae, T.-W., Wells, D. M., Owen, M. R., Band, L. R., Dyson, R. J., Jensen, O. E., King, J. R., Tracy, S. R., Sturrock, C. J., …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.

Supporting data for "Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping" (2016)
Data
(2016). Supporting data for "Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping". [Data]. https://doi.org/10.5524/100343

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 Supporting data for "Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping".

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., Weijers, D., Fukaki, H., Laplaze, L., Bennett, M. J., & 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., Atkinson, J. A., Belko, M. N., Bennett, M. J., Gantet, P., Wells, D. M., Guédon, Y., Vigouroux, Y., Verdeil, J.-L., Muller, B., & 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)
Preprint / Working Paper
Pound, M. P., Burgess, A. J., Wilson, M. H., Atkinson, J. A., Griffiths, M., Jackson, A. S., Bulat, A., Tzimiropoulos, G., Wells, D. M., Murchie, E. H., Pridmore, T. P., & 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., Lucas, M., Swarup, K., Casimiro, I., Holman, T. J., Wells, D. M., Péret, B., Goh, T., Fukaki, H., Hodgman, T. C., Laplaze, L., Halliday, K. J., Ljung, K., Murphy, A. S., Hall, A. J., …Bennett, M. J. (2015). The circadian clock rephases during lateral root organ initiation in Arabidopsis thaliana. Nature Communications, 6, 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.

Imaging and Quantitative Methods for Studying Cytoskeletal Rearrangements During Root Development and Gravitropism (2015)
Book Chapter
Jacques, E., Wells, D. M., Bennett, M. J., & Vissenberg, K. (2015). Imaging and Quantitative Methods for Studying Cytoskeletal Rearrangements During Root Development and Gravitropism. In E. B. Blancaflor (Ed.), Plant Gravitropism; Methods and Protocols (81-89). Springer New York. https://doi.org/10.1007/978-1-4939-2697-8_8

High-resolution imaging of cytoskeletal structures paves the way for standardized methods to quantify cytoskeletal organization. Here we provide a detailed description of the analysis performed to determine the microtubule patterns in gravistimulated... Read More about Imaging and Quantitative Methods for Studying Cytoskeletal Rearrangements During Root Development and Gravitropism.

Multi-omics analysis identifies genes mediating the extension of cell walls in the Arabidopsis thaliana root elongation zone (2015)
Journal Article
Wilson, M. H., Holman, T. J., Sørensen, I., Cancho-Sanchez, E., Wells, D. M., Swarup, R., Knox, J. P., Willats, W. G., Ubeda-Tomás, S., Holdsworth, M. J., Bennett, M. J., Vissenberg, K., & Hodgman, T. C. (2015). Multi-omics analysis identifies genes mediating the extension of cell walls in the Arabidopsis thaliana root elongation zone. Frontiers in Cell and Developmental Biology, 3(FEB), Article 10. https://doi.org/10.3389/fcell.2015.00010

Plant cell wall composition is important for regulating growth rates, especially in roots. However, neither analyses of cell wall composition nor transcriptomes on their own can comprehensively reveal which genes and processes are mediating growth an... Read More about Multi-omics analysis identifies genes mediating the extension of cell walls in the Arabidopsis thaliana root elongation zone.

Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat (2015)
Journal Article
Atkinson, J. A., Wingen, L. U., Griffiths, M., Pound, M. P., Gaju, O., Foulkes, M. J., Le Gouis, J., Griffiths, S., Bennett, M. J., King, J., & Wells, D. M. (2015). Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat. Journal of Experimental Botany, 66(8), 2283-2292. https://doi.org/10.1093/jxb/erv006

Seedling root traits of wheat (Triticum aestivum L.) have been shown to be important for efficient establishment and linked to mature plant traits such as height and yield. A root phenotyping pipeline, consisting of a germination paper-based screen c... Read More about Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat.

On the evaluation of methods for the recovery of plant root systems from X-ray computed tomography images (2014)
Journal Article
Mairhofer, S., Sturrock, C., Wells, D. M., Bennett, M. J., Mooney, S. J., & Pridmore, T. P. (2014). On the evaluation of methods for the recovery of plant root systems from X-ray computed tomography images. Functional Plant Biology, 42(5), 460-470. https://doi.org/10.1071/FP14071

© CSIRO 2015. X-ray microcomputed tomography (μCT) allows nondestructive visualisation of plant root systems within their soil environment and thus offers an alternative to the commonly used destructive methodologies for the examination of plant root... Read More about On the evaluation of methods for the recovery of plant root systems from X-ray computed tomography images.

Quantification of Fluorescent Reporters in Plant Cells (2014)
Book Chapter
Pound, M., French, A. P., & Wells, D. M. (2015). Quantification of Fluorescent Reporters in Plant Cells. In J. M. Estevez (Ed.), Plant Cell Expansion: Methods and Protocols (123-131). Springer. https://doi.org/10.1007/978-1-4939-1902-4_11

© Springer Science+Business Media New York 2015. Fluorescent reporters are powerful tools for plant research. Many studies require accurate determination of fluorescence intensity and localization. Here, we describe protocols for the quantification o... Read More about Quantification of Fluorescent Reporters in Plant Cells.