Near infrared hyperspectral imaging : a rapid method for the differentiation of maize ear rot pathogens on growth media
[摘要] ENGLISH ABSTRACT: Maize grain is highly susceptible to the toxin-producing fungal pathogens Fusarium spp. and Stenocarpella spp. Infection of grain with these species leads to maize ear rots but of greater concern is their ability to produce mycotoxins, which can promote cancer, among other diseases, in humans and animals. By combining microbiology, plant pathology and chemistry disciplines to create rapid screening methods that can accurately distinguish fungal pathogens, an initial step in ensuring food safety can be achieved, which can potentially be applied to maize grain in future. This thesis aimed to distinguish between the most important maize ear rot pathogens namely Fusarium verticillioides, F. graminearum species complex (FGSC) and Stenocarpella maydis that cause Fusarium-, Gibberella- and Diplodia ear rot, respectively. Furthermore, pathogen isolates from the same species were also distinguished. This was done with near infrared (NIR) hyperspectral imaging, a technology that offers the ability for rapid sample measurement that provides data containing both spatial and spectral information. Through multivariate analysis such as principal component analysis, primarily used for data exploration, and partial least square discriminant analysis, hyperspectral images was used to build classification models that accurately distinguish between the maize ear rot pathogens. All the major ear rot pathogens were distinguished with reasonable accuracy on day 3 of growth, with the isolates from the same species showing higher accuracy on day 5 of growth.
[发布日期] [发布机构] Stellenbosch University
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