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Near-infrared (NIR) hyperspectral imaging and multivariate image analysis to study growth characteristics and differences between species and strains of members of the genus Fusarium

机译:近红外(NIR)高光谱成像和多元图像分析以研究镰刀菌属成员的生长特征以及物种和品系之间的差异

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摘要

Near-infrared (NIR) hyperspectral imaging was used to study three strains of each of three Fusarium spp. (Fusarium subglutinans, Fusarium proliferatum and Fusarium verticillioides) inoculated on potato dextrose agar in Petri dishes after either 72 or 96 h of incubation. Multivariate image analysis was used for cleaning the images and for making principal component analysis (PCA) score plots and score images and local partial least squares discriminant analysis (PLS-DA) models. The score images, including all strains, showed how different the strains were from each other. Using classification gradients, it was possible to show the change in mycelium growth over time. Loading line plots for principal component (PC) 1 and PC2 explained variation between the different Fusarium spp. as scattering and chemical differences (protein production), respectively. PLS-DA prediction results (including only the most important strain of each species) showed that it was possible to discriminate between species with F. verticillioides the least correctly predicted (between 16 and 47 % pixels correctly predicted). For F. subglutinans, 78–100 % pixels were correctly predicted depending on the training and test sets used. Similarly, the percentage correctly predicted values of F. proliferatum were 60–80 %. Visualisation of the mycelium radial growth in the PCA score images was made possible due to the use of NIR hyperspectral imaging. This is not possible with bulk spectroscopy in the visible or NIR regions.>FigurePrincipal component 1 score image showing differences between colonies. F. subglutinans (MRC 0115) are top left followed by F. proliferatum (MRC 2301) and F. verticillioides (MRC 0826).
机译:近红外(NIR)高光谱成像用于研究三个镰刀菌属中每个菌株的三个菌株。孵育72或96小时后,在陪替氏培养皿中的马铃薯葡萄糖琼脂上接种(次谷氨酸镰刀菌,枯萎镰刀菌和verticillioides镰刀菌)。多变量图像分析用于清洁图像并制作主成分分析(PCA)得分图和得分图像以及局部偏最小二乘判别分析(PLS-DA)模型。评分图像(包括所有菌株)显示了菌株之间的差异。使用分类梯度,可以显示菌丝体生长随时间的变化。主成分(PC)1和PC2的加载线图说明了不同镰刀菌属之间的差异。分别为散射和化学差异(蛋白质产生)。 PLS-DA预测结果(仅包括每个物种中最重要的菌株)表明,可以区分具有最不正确预测的拟南芥(在正确预测的16%到47%像素之间)的物种。对于谷粉镰刀菌,取决于所使用的训练和测试集,可以正确预测78-100%的像素。同样,正确预测的F. proliferatum值的百分比为60-80%。由于使用了NIR高光谱成像,因此PCA评分图像中菌丝体径向生长的可视化成为可能。使用可见光谱或NIR区域中的体光谱法是不可能的。<!-fig ft0-> <!-fig @ position =“ anchor” mode = article f4-> <!-fig mode =“ anchored “ f5-> > Figure <!-fig / graphic | fig / alternatives / graphic mode =” anchored“ m1-> <!-标题a7->主成分1得分图像,显示菌落之间的差异。谷胶镰刀菌(MRC 0115)在左上角,然后是增殖镰刀菌(MRC 2301)和网状镰刀菌(MRC 0826)。

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