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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. In Annual Plant Reviews OnlineWiley. 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

Demystifying roots: a need for clarification and extended concepts in root phenotyping (2018)
Journal Article
Lobet, G., Paez-Garcia, A., Schneider, H., Junker, A., Atkinson, J. A., & Tracy, S. (2018). Demystifying roots: a need for clarification and extended concepts in root phenotyping. Plant Science, doi:10.1016/j.plantsci.2018.09.015

Plant roots have major roles in plant anchorage, resource acquisition and offer environmental benefits including carbon sequestration and soil erosion mitigation. As such, the study of root system architecture, anatomy and functional properties is of... Read More

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. ISSN 0958-1669

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

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, doi:10.3389/fpls.2017.01721. ISSN 1664-462X

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

Deep machine learning provides state-of-the-art performance in image-based plant phenotyping (2017)
Journal Article
Murchie, E. H., Wells, D. M., Jackson, A. S., Wilson, M. H., Townsend, A. J., Atkinson, J. A., …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

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

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, doi:10.3389/fpls.2016.00829. ISSN 1664-462X

Pearl millet plays an important role for food security in arid regions of Africa and India. Nevertheless, it is considered an orphan crop as it lags far behind other cereals in terms of genetic improvement efforts. Breeding pearl millet varieties wit... Read More

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

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, J., …Wells, D. M. (2015). Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat. Journal of Experimental Botany, 66(8), doi:10.1093/jxb/erv006. ISSN 0022-0957

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

Branching out in roots: uncovering form, function, and regulation (2014)
Journal Article
Atkinson, J. A., Rasmussen, A., Traini, R., Voss, U., Sturrock, C., Mooney, S. J., …Bennett, M. J. (2014). Branching out in roots: uncovering form, function, and regulation. Plant Physiology, 166(2), doi:10.1104/pp.114.245423. ISSN 0032-0889

Root branching is critical for plants to secure anchorage and ensure the supply of water, minerals, and nutrients. To date, research on root branching has focused on lateral root development in young seedlings. However, many other programs of postemb... Read More

RootNav: navigating images of complex root architectures (2013)
Journal Article
Pound, M. P., French, A. P., Atkinson, J. A., Wells, D. M., Bennett, M. J., & Pridmore, T. (2013). RootNav: navigating images of complex root architectures. Plant Physiology, 162(4), 1802-1814. doi:10.1104/pp.113.221531

We present a novel image analysis tool that allows the semiautomated quantification of complex root system architectures in a range of plant species grown and imaged in a variety of ways. The automatic component of RootNav takes a top-down approach,... Read More