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Impedance of the grape berry cuticle as a novel phenotypic trait to estimate resistance to Botrytis cinerea.

Herzog K, Wind R, Töpfer R - Sensors (Basel) (2015)

Bottom Line: Statistical experiments revealed highly significant correlations between relative impedance of CW and the resistance of grapevines to B. cinerea.An ordinal logistic regression analysis revealed a R2McFadden of 0.37 and confirmed the application of Zrel of CW for the prediction of bunch infection and in this way as novel phenotyping trait.Applying the I-sensor, a preliminary QTL region was identified indicating that the novel phenotypic trait is as well a valuable tool for genetic analyses.

View Article: PubMed Central - PubMed

Affiliation: Julius Kühn-Institut-Federal Research Centre of Cultivated Plants, Institute for Grapevine Breeding Geilweilerhof, Siebeldingen 76833, Germany. Katja.herzog@jki.bund.de.

ABSTRACT
Warm and moist weather conditions during berry ripening provoke Botrytis cinerea (B. cinerea) causing notable bunch rot on susceptible grapevines with the effect of reduced yield and wine quality. Resistance donors of genetic loci to increase B. cinerea resistance are widely unknown. Promising traits of resistance are represented by physical features like the thickness and permeability of the grape berry cuticle. Sensor-based phenotyping methods or genetic markers are rare for such traits. In the present study, the simple-to-handle I-sensor was developed. The sensor enables the fast and reliable measurement of electrical impedance of the grape berry cuticles and its epicuticular waxes (CW). Statistical experiments revealed highly significant correlations between relative impedance of CW and the resistance of grapevines to B. cinerea. Thus, the relative impedance Zrel of CW was identified as the most important phenotypic factor with regard to the prediction of grapevine resistance to B. cinerea. An ordinal logistic regression analysis revealed a R2McFadden of 0.37 and confirmed the application of Zrel of CW for the prediction of bunch infection and in this way as novel phenotyping trait. Applying the I-sensor, a preliminary QTL region was identified indicating that the novel phenotypic trait is as well a valuable tool for genetic analyses.

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Prediction the probability of B. cinerea infection. Relative impedance Zrel of CW was applied in an ordinal logistic regression model. The data set including all genotypes (except genotypes with loose bunch compactness). Maximum Likelihood estimation was used and R2McFadden = 0.37 was calculated. CW: intact cuticle with epicuticular waxes.
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sensors-15-12498-f007: Prediction the probability of B. cinerea infection. Relative impedance Zrel of CW was applied in an ordinal logistic regression model. The data set including all genotypes (except genotypes with loose bunch compactness). Maximum Likelihood estimation was used and R2McFadden = 0.37 was calculated. CW: intact cuticle with epicuticular waxes.

Mentions: Logistic regression analysis was carried out in order to predict the probability of B. cinerea infection by using the relative impedance Zrel of CW (Figure 7).


Impedance of the grape berry cuticle as a novel phenotypic trait to estimate resistance to Botrytis cinerea.

Herzog K, Wind R, Töpfer R - Sensors (Basel) (2015)

Prediction the probability of B. cinerea infection. Relative impedance Zrel of CW was applied in an ordinal logistic regression model. The data set including all genotypes (except genotypes with loose bunch compactness). Maximum Likelihood estimation was used and R2McFadden = 0.37 was calculated. CW: intact cuticle with epicuticular waxes.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507599&req=5

sensors-15-12498-f007: Prediction the probability of B. cinerea infection. Relative impedance Zrel of CW was applied in an ordinal logistic regression model. The data set including all genotypes (except genotypes with loose bunch compactness). Maximum Likelihood estimation was used and R2McFadden = 0.37 was calculated. CW: intact cuticle with epicuticular waxes.
Mentions: Logistic regression analysis was carried out in order to predict the probability of B. cinerea infection by using the relative impedance Zrel of CW (Figure 7).

Bottom Line: Statistical experiments revealed highly significant correlations between relative impedance of CW and the resistance of grapevines to B. cinerea.An ordinal logistic regression analysis revealed a R2McFadden of 0.37 and confirmed the application of Zrel of CW for the prediction of bunch infection and in this way as novel phenotyping trait.Applying the I-sensor, a preliminary QTL region was identified indicating that the novel phenotypic trait is as well a valuable tool for genetic analyses.

View Article: PubMed Central - PubMed

Affiliation: Julius Kühn-Institut-Federal Research Centre of Cultivated Plants, Institute for Grapevine Breeding Geilweilerhof, Siebeldingen 76833, Germany. Katja.herzog@jki.bund.de.

ABSTRACT
Warm and moist weather conditions during berry ripening provoke Botrytis cinerea (B. cinerea) causing notable bunch rot on susceptible grapevines with the effect of reduced yield and wine quality. Resistance donors of genetic loci to increase B. cinerea resistance are widely unknown. Promising traits of resistance are represented by physical features like the thickness and permeability of the grape berry cuticle. Sensor-based phenotyping methods or genetic markers are rare for such traits. In the present study, the simple-to-handle I-sensor was developed. The sensor enables the fast and reliable measurement of electrical impedance of the grape berry cuticles and its epicuticular waxes (CW). Statistical experiments revealed highly significant correlations between relative impedance of CW and the resistance of grapevines to B. cinerea. Thus, the relative impedance Zrel of CW was identified as the most important phenotypic factor with regard to the prediction of grapevine resistance to B. cinerea. An ordinal logistic regression analysis revealed a R2McFadden of 0.37 and confirmed the application of Zrel of CW for the prediction of bunch infection and in this way as novel phenotyping trait. Applying the I-sensor, a preliminary QTL region was identified indicating that the novel phenotypic trait is as well a valuable tool for genetic analyses.

Show MeSH
Related in: MedlinePlus