Journal
MACHINE VISION AND APPLICATIONS
Volume 27, Issue 5, Pages 637-646Publisher
SPRINGER
DOI: 10.1007/s00138-015-0719-5
Keywords
Small grain cereals; Branching; Plant development; Computer vision
Categories
Funding
- Biotechnology and Biological Sciences Research Council (BBSRC) [BB/J004405/1, BB/J004464/1]
- European Union (EPPN, an Integrating Activity, Research Infrastructure project) - European Union under FP7 Capacities Programme [284443]
- Biosciences, Environment and Agriculture Alliance (BEAA)
- BBSRC [BB/E00721X/1, BBS/E/W/10961A01, BBS/E/W/10962A01D] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BBS/E/W/10961A01, BB/E00721X/1, BBS/E/W/10962A01D] Funding Source: researchfish
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The advent of high-throughput phenotyping installations signals a need for plant biology to use pattern analysis and recognition techniques, especially when analysis is done via digital images. Such installations also provide an opportunity to computer vision. We describe one such application at the UK National Plant Phenomics Centre, in which historically measurements have been made in a labour-intensive manual manner. We develop an estimator of tiller number in growing wheat which, when exploiting per-day averaging, temporal interpolation and dynamic programming, delivers measurements of finer-grain and no less accuracy than manually, and provides observations on plant treatments hitherto difficult or impossible to obtain. The approach developed lends itself to reuse for any similar imaging setup, and plants with tillering characteristics similar to wheat. We consider the work a useful exemplar for co-operation between biologists and computer scientists in such installations.
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