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Statements

Subject Item
n2:RIV%2F25328859%3A_____%2F11%3A%230000576%21RIV12-MZE-25328859
rdf:type
n11:Vysledek skos:Concept
rdfs:seeAlso
http://www.mendelu.cz/dok_server/slozka.pl?id=51329;download=82059
dcterms:description
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. 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.
dcterms:title
IDENTIFICATION OF FUSARIUM DAMAGED WHEAT KERNELS USING IMAGE ANALYSIS IDENTIFICATION OF FUSARIUM DAMAGED WHEAT KERNELS USING IMAGE ANALYSIS
skos:prefLabel
IDENTIFICATION OF FUSARIUM DAMAGED WHEAT KERNELS USING IMAGE ANALYSIS IDENTIFICATION OF FUSARIUM DAMAGED WHEAT KERNELS USING IMAGE ANALYSIS
skos:notation
RIV/25328859:_____/11:#0000576!RIV12-MZE-25328859
n11:predkladatel
n18:ico%3A25328859
n3:aktivita
n9:P
n3:aktivity
P(GP525/09/P647), P(QG60047)
n3:cisloPeriodika
5
n3:dodaniDat
n13:2012
n3:domaciTvurceVysledku
n14:2962039 n14:4686845
n3:druhVysledku
n8:J
n3:duvernostUdaju
n15:S
n3:entitaPredkladatele
n19:predkladatel
n3:idSjednocenehoVysledku
203351
n3:idVysledku
RIV/25328859:_____/11:#0000576
n3:jazykVysledku
n6:eng
n3:klicovaSlova
Fusarium; mycotoxin DON; deoxynivalenol; image analysis; wheat
n3:klicoveSlovo
n7:wheat n7:image%20analysis n7:mycotoxin%20DON n7:deoxynivalenol n7:Fusarium
n3:kodStatuVydavatele
CZ - Česká republika
n3:kontrolniKodProRIV
[8114A05F4DE8]
n3:nazevZdroje
ACTA UNIVERSITATIS AGRICULTURAE ET SILVICULTURAE MENDELIANAE BRUNENSIS
n3:obor
n17:GM
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n4:QG60047 n4:GP525%2F09%2FP647
n3:rokUplatneniVysledku
n13:2011
n3:svazekPeriodika
59
n3:tvurceVysledku
Polišenská, Ivana Jirsa, Ondřej
s:issn
1211-8516
s:numberOfPages
6