Deep Learning for Plant Phenotyping
Plant Phenotyping is an emerging science which provides us the knowledge to better understand plants. Indeed, the study of the link between genetic background and environment in which plants develop can help us to determine cures for plants’ sicknesses and new ways to improve yields using limited re...
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2016
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| Online Access: | https://eprints.nottingham.ac.uk/39172/ |
| _version_ | 1848795779671523328 |
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| author | Mori, Matteo |
| author_facet | Mori, Matteo |
| author_sort | Mori, Matteo |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Plant Phenotyping is an emerging science which provides us the knowledge to better understand plants. Indeed, the study of the link between genetic background and environment in which plants develop can help us to determine cures for plants’ sicknesses and new ways to improve yields using limited resources. In this regard, one of the main aspects of Plant Phenotyping that were studied in the past, was Root Phenotyping, which is based on the study of the root architectures. In particular, today with great technology innovations, it was possible to focus the research on non-invasive approaches which allow to study the root development belowground without altering the natural plants’ environment. One of the most common practices, is to make use of X-ray microcomputed tomography ( |
| first_indexed | 2025-11-14T19:37:31Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-39172 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T19:37:31Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-391722017-10-12T21:57:53Z https://eprints.nottingham.ac.uk/39172/ Deep Learning for Plant Phenotyping Mori, Matteo Plant Phenotyping is an emerging science which provides us the knowledge to better understand plants. Indeed, the study of the link between genetic background and environment in which plants develop can help us to determine cures for plants’ sicknesses and new ways to improve yields using limited resources. In this regard, one of the main aspects of Plant Phenotyping that were studied in the past, was Root Phenotyping, which is based on the study of the root architectures. In particular, today with great technology innovations, it was possible to focus the research on non-invasive approaches which allow to study the root development belowground without altering the natural plants’ environment. One of the most common practices, is to make use of X-ray microcomputed tomography ( 2016-12-14 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/39172/1/Matteo%20Mori%204262811.pdf Mori, Matteo (2016) Deep Learning for Plant Phenotyping. [Dissertation (University of Nottingham only)] Plant phenotyping root phenotyping roots X-ray microcomputed tomography uCT Deep learning convolutional neural networks CNN classification segmentation. |
| spellingShingle | Plant phenotyping root phenotyping roots X-ray microcomputed tomography uCT Deep learning convolutional neural networks CNN classification segmentation. Mori, Matteo Deep Learning for Plant Phenotyping |
| title | Deep Learning for Plant Phenotyping |
| title_full | Deep Learning for Plant Phenotyping |
| title_fullStr | Deep Learning for Plant Phenotyping |
| title_full_unstemmed | Deep Learning for Plant Phenotyping |
| title_short | Deep Learning for Plant Phenotyping |
| title_sort | deep learning for plant phenotyping |
| topic | Plant phenotyping root phenotyping roots X-ray microcomputed tomography uCT Deep learning convolutional neural networks CNN classification segmentation. |
| url | https://eprints.nottingham.ac.uk/39172/ |