נגישות
menu      
Advanced Search

Sandovsky, T.; Edan, Y.; Gad, S.; Etzioni, A.

This work presents a non-destructive methodology for early detection of Fusarium infection, by spectral analysis in the 350-2,500 nm range. Corn plants in greenhouse conditions were analysed using spectral analysis. The Lasso model was used to differentiate infected from non-infected plants based on the first derivative of leaf spectral reflectance. Fusarium infection was successfully recognized in plants at V2 growth stage with 74% success rate. This result enables infection detection at a stage which currently is not possible without destroying the plant, which can be further applied to map the disease in field scale. © Wageningen Academic Publishers 2019

Powered by ClearMash Solutions Ltd -
Volcani treasures
About
Terms of use
Early detection of Fusarium infection in corn using spectral analysis

Sandovsky, T.; Edan, Y.; Gad, S.; Etzioni, A.

Early detection of Fusarium infection in corn using spectral analysis

This work presents a non-destructive methodology for early detection of Fusarium infection, by spectral analysis in the 350-2,500 nm range. Corn plants in greenhouse conditions were analysed using spectral analysis. The Lasso model was used to differentiate infected from non-infected plants based on the first derivative of leaf spectral reflectance. Fusarium infection was successfully recognized in plants at V2 growth stage with 74% success rate. This result enables infection detection at a stage which currently is not possible without destroying the plant, which can be further applied to map the disease in field scale. © Wageningen Academic Publishers 2019

Scientific Publication
You may also be interested in