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Dr DARREN WELLS's Outputs (21)

Root metaxylem area influences drought tolerance and transpiration in pearl millet in a soil texture dependent manner (2024)
Preprint / Working Paper
Affortit, P., Faye, A., Jones, D. H., Benson, E., Sine, B., Burridge, J., Ndoye, M. S., Barry, L., Moukouanga, D., Barnard, S., Bhosale, R., Pridmore, T., Gantet, P., Vadez, V., Cubry, P., Kane, N., Bennett, M., Atkinson, J. A., Laplaze, L., Wells, D. M., & Grondin, A. (2024). Root metaxylem area influences drought tolerance and transpiration in pearl millet in a soil texture dependent manner

Pearl millet is a key cereal for food security in drylands but its yield is strongly impacted by drought. We investigated how root anatomical traits contribute to mitigating the effects of vegetative drought stress in pearl millet.

We examined ass... Read More about Root metaxylem area influences drought tolerance and transpiration in pearl millet in a soil texture dependent manner.

Root architecture and leaf photosynthesis traits and associations with nitrogen-use efficiency in landrace-derived lines in wheat (2022)
Journal Article
Kareem, S. H., Hawkesford, M. J., DeSilva, J., Weerasinghe, M., Wells, D. M., Pound, M. P., Atkinson, J. A., & Foulkes, M. J. (2022). Root architecture and leaf photosynthesis traits and associations with nitrogen-use efficiency in landrace-derived lines in wheat. European Journal of Agronomy, 140, Article 126603. https://doi.org/10.1016/j.eja.2022.126603

Root system architecture (RSA) is important in optimizing the use of nitrogen. High-throughput phenotyping techniques may be used to study root system architecture traits under controlled environments. A root phenotyping platform, consisting of germi... Read More about Root architecture and leaf photosynthesis traits and associations with nitrogen-use efficiency in landrace-derived lines in wheat.

Identification of QTL and underlying genes for root system architecture associated with nitrate nutrition in hexaploid wheat (2022)
Journal Article
GRIFFITHS, M., ATKINSON, J. A., Gardiner, L. J., SWARUP, R., POUND, M. P., WILSON, M. H., BENNETT, M. J., & WELLS, D. M. (2022). Identification of QTL and underlying genes for root system architecture associated with nitrate nutrition in hexaploid wheat. Journal of Integrative Agriculture, 21(4), 917-932. https://doi.org/10.1016/s2095-3119%2821%2963700-0

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 adaptive responses in wheat (Triticum aestivum L.... Read More about Identification of QTL and underlying genes for root system architecture associated with nitrate nutrition in hexaploid wheat.

Data and statistical analysis scripts for manuscript on wheat root response to nitrate using X-ray CT and OpenSimRoot (2022)
Data
(2022). Data and statistical analysis scripts for manuscript on wheat root response to nitrate using X-ray CT and OpenSimRoot. [Data]. https://doi.org/10.5281/zenodo.5504299

Data and statistical analysis scripts for manuscript on wheat root response to nitrate using X-ray CT and OpenSimRoot

X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil - [https://doi.org/10.1002/ppj2.20036]... Read More about Data and statistical analysis scripts for manuscript on wheat root response to nitrate using X-ray CT and OpenSimRoot.

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), Article giz123. https://doi.org/10.1093/gigascience/giz123

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 a plant's ability to take up water and nutrients. Segmentat... Read More about RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures.

Supporting data for "RootNav 2.0: Deep Learning for Automatic Navigation of Complex Plant Root Architectures" (2019)
Data
French, A., Wells, D. M., Atkinson, J., Pound, M., Yasrab, R., & Pridmore, T. (2019). Supporting data for "RootNav 2.0: Deep Learning for Automatic Navigation of Complex Plant Root Architectures". [Data]. https://doi.org/10.5524/100651

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 Supporting data for "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. (2020). Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(6), 1907-1917. 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.

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

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.

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.

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.

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".

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.

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.

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.

Mechanical modelling quantifies the functional importance of outer tissue layers during root elongation and bending (2014)
Journal Article
Dyson, R. J., Vizcay-Barrena, G., Band, L. R., Fernandes, A. N., French, A. P., Fozard, J. A., Hodgman, T. C., Kenobi, K., Pridmore, T. P., Stout, M., Wells, D. M., Wilson, M. H., Bennett, M. J., & Jensen, O. E. (2014). Mechanical modelling quantifies the functional importance of outer tissue layers during root elongation and bending. New Phytologist, 202(4), 1212-1222. https://doi.org/10.1111/nph.12764

Root elongation and bending require the coordinated expansion of multiple cells of different types. These processes are regulated by the action of hormones that can target distinct cell layers. We use a mathematical model to characterise the influenc... Read More about Mechanical modelling quantifies the functional importance of outer tissue layers during root elongation and bending.