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
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