All Outputs (40)

X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil (2022)
Journal Article
Griffiths, M., Mellor, N., Sturrock, C. J., Atkinson, B. S., Johnson, J., Mairhofer, S., …Wells, D. M. (2022). X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil. Plant Phenome Journal, 5(1), Article e20036. https://doi.org/10.1002/ppj2.20036

The spatial arrangement of the root system, termed root system architecture, is important for resource acquisition as it directly affects the soil zone explored. Methods for phenotyping roots are mostly destructive, which prevents analysis of roots o... Read More about X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil.

Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models (2021)
Journal Article
Bellos, D., Basham, M., Pridmore, T., & French, A. P. (2021). Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models. Scientific Reports, 11(1), Article 23279. https://doi.org/10.1038/s41598-021-02466-x

Recently, several convolutional neural networks have been proposed not only for 2D images, but also for 3D and 4D volume segmentation. Nevertheless, due to the large data size of the latter, acquiring a sufficient amount of training annotations is mu... Read More about Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models.

A stacked dense denoising–segmentation network for undersampled tomograms and knowledge transfer using synthetic tomograms (2021)
Journal Article
Bellos, D., Basham, M., Pridmore, T., & French, A. P. (2021). A stacked dense denoising–segmentation network for undersampled tomograms and knowledge transfer using synthetic tomograms. Machine Vision and Applications, 32(3), Article 75. https://doi.org/10.1007/s00138-021-01196-4

Over recent years, many approaches have been proposed for the denoising or semantic segmentation of X-ray computed tomography (CT) scans. In most cases, high-quality CT reconstructions are used; however, such reconstructions are not always available.... Read More about A stacked dense denoising–segmentation network for undersampled tomograms and knowledge transfer using synthetic tomograms.

Hydrodynamic characterization of soil compaction using integrated electrical resistivity and X-ray computed tomography (2021)
Journal Article
Cimpoiasu, M. O., Kuras, O., Wilkinson, P., Pridmore, T., & Mooney, S. J. (2021). Hydrodynamic characterization of soil compaction using integrated electrical resistivity and X-ray computed tomography. Vadose Zone Journal, 20(4), Article e20109. https://doi.org/10.1002/vzj2.20109

© 2020 The Authors. Vadose Zone Journal published by Wiley Periodicals LLC on behalf of Soil Science Society of America Modern agricultural practices can cause significant stress on soil, which ultimately has degrading effects, such as compaction. Th... Read More about Hydrodynamic characterization of soil compaction using integrated electrical resistivity and X-ray computed tomography.

Low-cost automated vectors and modular environmental sensors for plant phenotyping (2020)
Journal Article
Bagley, S. A., Atkinson, J. A., Hunt, H., Wilson, M. H., Pridmore, T. P., & Wells, D. M. (2020). Low-cost automated vectors and modular environmental sensors for plant phenotyping. Sensors, 20(11), https://doi.org/10.3390/s20113319

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. High-throughput plant phenotyping in controlled environments (growth chambers and glasshouses) is often delivered via large, expensive installations, leading to limited access and the increase... Read More about Low-cost automated vectors and modular environmental sensors for plant phenotyping.

Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks (2020)
Journal Article
Soltaninejad, M., Sturrock, C. J., Griffiths, M., Pridmore, T. P., & Pound, M. P. (2020). Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks. IEEE Transactions on Image Processing, 29, 6667-6679. https://doi.org/10.1109/TIP.2020.2992893

© 1992-2012 IEEE. We address the complex problem of reliably segmenting root structure from soil in X-ray Computed Tomography (CT) images. We utilise a deep learning approach, and propose a state-of-the-art multi-resolution architecture based on enco... Read More about Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks.

Potential of geoelectrical methods to monitor root zone processes and structure: A review (2020)
Journal Article
Cimpoia?u, M. O., Cimpoiasu, M. O., Kuras, O., Pridmore, T., & Mooney, S. J. (2020). Potential of geoelectrical methods to monitor root zone processes and structure: A review. Geoderma, 365, 114232. https://doi.org/10.1016/j.geoderma.2020.114232

© 2020 Understanding the processes that control mass and energy exchanges between soil, plants and the atmosphere plays a critical role for understanding the root zone system, but it is also beneficial for practical applications such as sustainable a... Read More about Potential of geoelectrical methods to monitor root zone processes and structure: A review.

Towards infield, live plant phenotyping using a reduced-parameter CNN (2019)
Journal Article
Atanbori, J., French, A. P., & Pridmore, T. P. (2020). Towards infield, live plant phenotyping using a reduced-parameter CNN. Machine Vision and Applications, 31, Article 2. https://doi.org/10.1007/s00138-019-01051-7

There is an increase in consumption of agricultural produce as a result of the rapidly growing human population, particularly in developing nations. This has triggered high-quality plant phenotyping re- search to help with the breeding of high yieldi... Read More about Towards infield, live plant phenotyping using a reduced-parameter CNN.

CNN-Based Cassava Storage Root Counting Using Real and Synthetic Images (2019)
Journal Article
Atanbori, J., Montoya, M., Selvaraj, M., French, A. P., & Pridmore, T. P. (2019). CNN-Based Cassava Storage Root Counting Using Real and Synthetic Images. Frontiers in Plant Science, 10, https://doi.org/10.3389/fpls.2019.01516

Cassava roots are complex structures comprising several distinct types of root. The number and size of the storage roots are two potential phenotypic traits reflecting crop yield and quality. Counting and measuring the size of cassava storage roots a... Read More about CNN-Based Cassava Storage Root Counting Using Real and Synthetic Images.

A low-cost aeroponic phenotyping system for storage root development: Unravelling the below-ground secrets of cassava (Manihot esculenta) (2019)
Journal Article
Selvaraj, M. G., Montoya-P, M. E., Atanbori, J., French, A. P., & Pridmore, T. (2019). A low-cost aeroponic phenotyping system for storage root development: Unravelling the below-ground secrets of cassava (Manihot esculenta). Plant Methods, 15(1), https://doi.org/10.1186/s13007-019-0517-6

© 2019 The Author(s). Background: Root and tuber crops are becoming more important for their high source of carbohydrates, next to cereals. Despite their commercial impact, there are significant knowledge gaps about the environmental and inherent reg... Read More about A low-cost aeroponic phenotyping system for storage root development: Unravelling the below-ground secrets of cassava (Manihot esculenta).

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.

Recovering Wind-induced Plant motion in Dense Field Environments via Deep Learning and Multiple Object Tracking (2019)
Journal Article
Gibbs, J. A., Burgess, A. J., Pound, M. P., Pridmore, T. P., & Murchie, E. H. (2019). Recovering Wind-induced Plant motion in Dense Field Environments via Deep Learning and Multiple Object Tracking. Plant Physiology, 181, 28-42. https://doi.org/10.1104/pp.19.00141

Understanding the relationships between local environmental conditions and plant structure and function is critical for both fundamental science and for improving the performance of crops in field settings. Wind-induced plant motion is important in m... Read More about Recovering Wind-induced Plant motion in Dense Field Environments via Deep Learning and Multiple Object Tracking.

A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram (2019)
Journal Article
Bellos, D., Basham, M., Pridmore, T., & French, A. P. (2019). A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram. Journal of Synchrotron Radiation, 26(3), 839-853. https://doi.org/10.1107/s1600577519003448

We designed a convolutional neural network to quickly and accurately upscale the sinograms of x-ray tomograms captured with a low number of projections; effectively increasing the number of projections. This is particularly useful for tomograms that... Read More about A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram.

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.

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.

Erratum: Author Correction: Rice auxin influx carrier OsAUX1 facilitates root hair elongation in response to low external phosphate (Nature communications (2018) 9 1 (1408)) (2018)
Journal Article
Giri, J., Bhosale, R., Huang, G., Pandey, B. K., Parker, H., Zappala, S., …Bennett, M. J. (2018). Erratum: Author Correction: Rice auxin influx carrier OsAUX1 facilitates root hair elongation in response to low external phosphate (Nature communications (2018) 9 1 (1408)). Nature Communications, 9(1), Article 1810. https://doi.org/10.1038/s41467-018-04280-y

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.

Rice auxin influx carrier OsAUX1 facilitates root hair elongation in response to low external phosphate (2018)
Journal Article
Giri, J., Bhosale, R., Huang, G., Pandey, B. K., Parker, H., Zappala, S., …Bennett, M. J. (2018). Rice auxin influx carrier OsAUX1 facilitates root hair elongation in response to low external phosphate. Nature Communications, 9(1), https://doi.org/10.1038/s41467-018-03850-4

Root traits such as root angle and hair length influence resource acquisition particularly for immobile nutrients like phosphorus (P). Here, we attempted to modify root angle in rice by disrupting the OsAUX1 auxin influx transporter gene in an effort... Read More about Rice auxin influx carrier OsAUX1 facilitates root hair elongation in response to low external phosphate.

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.

Plant phenomics, from sensors to knowledge (2017)
Journal Article
Tardieu, F., Cabrera-Bosquet, L., Pridmore, T. P., & Bennett, M. J. (2017). Plant phenomics, from sensors to knowledge. Current Biology, 27(15), R770-R783. https://doi.org/10.1016/j.cub.2017.05.055

Major improvements in crop yield are needed to keep pace with population growth and climate change. While plant breeding efforts have greatly benefited from advances in genomics, profiling the crop phenome (i.e., the structure and function of plants)... Read More about Plant phenomics, from sensors to knowledge.

Quantification of root water uptake in soil using X-ray computed tomography and image-based modelling: Quantification of root water uptake in soil (2017)
Journal Article
Daly, K. R., Tracy, S. R., Crout, N. M., Mairhofer, S., Pridmore, T. P., Mooney, S. J., & Roose, T. (2018). Quantification of root water uptake in soil using X-ray computed tomography and image-based modelling: Quantification of root water uptake in soil. Plant, Cell and Environment, 41(1), 121-133. https://doi.org/10.1111/pce.12983

Spatially averaged models of root-soil interactions are often used to calculate plant water uptake. Using a combination of X-ray Computed Tomography (CT) and image based modelling we tested the accuracy of this spatial averaging by directly calculati... Read More about Quantification of root water uptake in soil using X-ray computed tomography and image-based modelling: Quantification of root water uptake in soil.