. "IDENTIFICATION OF FUSARIUM DAMAGED WHEAT KERNELS USING IMAGE ANALYSIS"@en . . . . . "2"^^ . "Visual evaluation of kernels damaged by Fusarium spp. pathogens is labour intensive and due to a subjective approach, it can lead to inconsistencies. Digital imaging technology combined with appropriate statistical methods can provide much faster and more accurate ev aluation of the visually scabby kernels proportion. The aim of the present study was to develop a discrimination model to identify wheat kernels infected by Fusarium spp. using digital image analysis and statistical methods. Winter wheat kernels from fi eld experiments were evaluated visually as healthy or damaged. Deoxynivalenol (DON) content was determined in individual kernels using an ELISA method. Images of individual kernels were produced using a digital camera on dark background. Colour and shape descriptors were obtained by image analysis from the area representing the kernel. Healthy and damaged kernels diff ered signifi cantly in DON content and kernel weight. Various combinations of individual shape and colour descriptors were examined during the development of the model using linear discriminant analysis. In addition to basic descriptors of the RGB colour model (red, green, blue), very good classifi cation was also obtained using hue from the HSL colour model (hue, saturation, luminance). The accuracy of classifi cation using the developed discrimination model based on RGBH descriptors was 85 %. The shape descriptors themselves were not specifi c enough to distinguish individual kernels."@en . "RIV/25328859:_____/11:#0000576" . "Poli\u0161ensk\u00E1, Ivana" . "59" . . "1211-8516" . "2"^^ . . "IDENTIFICATION OF FUSARIUM DAMAGED WHEAT KERNELS USING IMAGE ANALYSIS" . . "Fusarium; mycotoxin DON; deoxynivalenol; image analysis; wheat"@en . . "[8114A05F4DE8]" . "203351" . "IDENTIFICATION OF FUSARIUM DAMAGED WHEAT KERNELS USING IMAGE ANALYSIS"@en . . "http://www.mendelu.cz/dok_server/slozka.pl?id=51329;download=82059" . "ACTA UNIVERSITATIS AGRICULTURAE ET SILVICULTURAE MENDELIANAE BRUNENSIS" . "5" . . . . "CZ - \u010Cesk\u00E1 republika" . . . . "P(GP525/09/P647), P(QG60047)" . . "6"^^ . . "IDENTIFICATION OF FUSARIUM DAMAGED WHEAT KERNELS USING IMAGE ANALYSIS" . "RIV/25328859:_____/11:#0000576!RIV12-MZE-25328859" . "Visual evaluation of kernels damaged by Fusarium spp. pathogens is labour intensive and due to a subjective approach, it can lead to inconsistencies. Digital imaging technology combined with appropriate statistical methods can provide much faster and more accurate ev aluation of the visually scabby kernels proportion. The aim of the present study was to develop a discrimination model to identify wheat kernels infected by Fusarium spp. using digital image analysis and statistical methods. Winter wheat kernels from fi eld experiments were evaluated visually as healthy or damaged. Deoxynivalenol (DON) content was determined in individual kernels using an ELISA method. Images of individual kernels were produced using a digital camera on dark background. Colour and shape descriptors were obtained by image analysis from the area representing the kernel. Healthy and damaged kernels diff ered signifi cantly in DON content and kernel weight. Various combinations of individual shape and colour descriptors were examined during the development of the model using linear discriminant analysis. In addition to basic descriptors of the RGB colour model (red, green, blue), very good classifi cation was also obtained using hue from the HSL colour model (hue, saturation, luminance). The accuracy of classifi cation using the developed discrimination model based on RGBH descriptors was 85 %. The shape descriptors themselves were not specifi c enough to distinguish individual kernels." . . "Jirsa, Ond\u0159ej" . .