@article{masteling2020DiSCount,
	title = {{DiSCount}: computer vision for automated quantification of {Striga} seed germination},
	volume = {16},
	issn = {1746-4811},
	shorttitle = {{DiSCount}},
	url = {https://doi.org/10.1186/s13007-020-00602-8},
	doi = {10.1186/s13007-020-00602-8},
	abstract = {Plant parasitic weeds belonging to the genus Striga are a major threat for food production in Sub-Saharan Africa and Southeast Asia. The parasite’s life cycle starts with the induction of seed germination by host plant-derived signals, followed by parasite attachment, infection, outgrowth, flowering, reproduction, seed set and dispersal. Given the small seed size of the parasite ({\textless} 200 μm), quantification of the impact of new control measures that interfere with seed germination relies on manual, labour-intensive counting of seed batches under the microscope. Hence, there is a need for high-throughput assays that allow for large-scale screening of compounds or microorganisms that adversely affect Striga seed germination.},
	number = {1},
	urldate = {2020-05-05},
	journal = {Plant Methods},
	author = {Masteling, Raul and Voorhoeve, Lodewijk and IJsselmuiden, Joris and Dini-Andreote, Francisco and de Boer, Wietse and Raaijmakers, Jos M.},
	month = may,
	year = {2020},
	note = {ZSCC: 0000000},
	pages = {60}
}

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