Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Michael P. POUND"'
Autor:
Marcus GRIFFITHS, Jonathan A. ATKINSON, Laura-Jayne GARDINER, Ranjan SWARUP, Michael P. POUND, Michael H. WILSON, Malcolm J. BENNETT, Darren M. WELLS
Publikováno v:
Journal of Integrative Agriculture, Vol 21, Iss 4, Pp 917-932 (2022)
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.
Externí odkaz:
https://doaj.org/article/777cb8c6902a4909bd8161e9822d0651
Deep convolutional neural networks for image-based Convolvulus sepium detection in sugar beet fields
Publikováno v:
Plant Methods, Vol 16, Iss 1, Pp 1-12 (2020)
Abstract Background Convolvulus sepium (hedge bindweed) detection in sugar beet fields remains a challenging problem due to variation in appearance of plants, illumination changes, foliage occlusions, and different growth stages under field condition
Externí odkaz:
https://doaj.org/article/1198d051b9f241db97686af4af88cb10
Autor:
Marcus Griffiths, Nathan Mellor, Craig J. Sturrock, Brian S. Atkinson, James Johnson, Stefan Mairhofer, Larry M. York, Jonathan A. Atkinson, Mohammadreza Soltaninejad, John F. Foulkes, Michael P. Pound, Sacha J. Mooney, Tony P. Pridmore, Malcolm J. Bennett, Darren M. Wells
Publikováno v:
Plant Phenome Journal, Vol 5, Iss 1, Pp n/a-n/a (2022)
Abstract 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 o
Externí odkaz:
https://doaj.org/article/0f6e558d8eee43f3ab0e7dcc7e93516d
Publikováno v:
Frontiers in Plant Science, Vol 11 (2020)
Understanding plant growth processes is important for many aspects of biology and food security. Automating the observations of plant development—a process referred to as plant phenotyping—is increasingly important in the plant sciences, and is o
Externí odkaz:
https://doaj.org/article/3cd38c3375a54f03ace6ee6a094ffc6b
Publikováno v:
Fermentation, Vol 7, Iss 4, p 253 (2021)
Beer fermentation processes are traditionally monitored through sampling and off-line wort density measurements. In-line and on-line sensors would provide real-time data on the fermentation progress whilst minimising human involvement, enabling ident
Externí odkaz:
https://doaj.org/article/2d14e26688ab433a9b3bdb53ef24702b
Publikováno v:
Remote Sensing, Vol 13, Iss 3, p 331 (2021)
Phenotyping involves the quantitative assessment of the anatomical, biochemical, and physiological plant traits. Natural plant growth cycles can be extremely slow, hindering the experimental processes of phenotyping. Deep learning offers a great deal
Externí odkaz:
https://doaj.org/article/d6025be440d741cc8403852254d053a9
Autor:
Michael P. Pound, Laura-Jayne Gardiner, Michael Wilson, Darren M. Wells, Marcus Griffiths, Malcolm J. Bennett, Jonathan A. Atkinson, Ranjan Swarup
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 aestivumL.)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef7b954ae470001002b588fd7ab48d48
Publikováno v:
Ultrasonics. 124
Supervised machine learning techniques are increasingly being combined with ultrasonic sensor measurements owing to their strong performance. These techniques also offer advantages over calibration procedures of more complex fitting, improved general
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b4d92d7c6f7612fb8889bb742b5f16f
https://pubmed.ncbi.nlm.nih.gov/35653984
https://pubmed.ncbi.nlm.nih.gov/35653984
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::174049118d8004dc3346e0f92c8cac18
https://doi.org/10.1109/iccvw54120.2021.00186
https://doi.org/10.1109/iccvw54120.2021.00186
Autor:
Michael P. Pound, Robail Yasrab
In this work we propose an extension to recent methods for the reconstruction of root architectures in 2-dimensions. Recent methods for the automatic root analysis have proposed deep learned segmentation of root images followed by path finding such a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b0bf54c6da15bb9ba83dc4cd30e2cc6
https://doi.org/10.1101/2021.08.17.456626
https://doi.org/10.1101/2021.08.17.456626