Abstract
Automatic methods for an early detection of plant diseases (i.e., visible symptoms at early stages of disease development) using remote sensing are critical for precision crop protection. Verticillium wilt (VW) of olive caused by Verticillium dahliae can be controlled only if detected at early stages of development. Linear discriminant analysis (LDA) and support vector machine (SVM) classification methods were applied to classify V. dahliae severity using remote sensing at large scale. High-resolution thermal and hyperspectral imagery were acquired with a manned platform which flew a 3000-ha commercial olive area. LDA reached an overall accuracy of 59.0% and a κ of 0.487 while SVM obtained a higher overall accuracy, 79.2% with a similar κ, 0.495. However, LDA better classified trees at initial and low severity levels, reaching accuracies of 71.4 and 75.0%, respectively, in comparison with the 14.3% and 40.6% obtained by SVM. Normalized canopy temperature, chlorophyll fluorescence, structural, xanthophyll, chlorophyll, carotenoid and disease indices were found to be the best indicators for early and advanced stage infection by VW. These results demonstrate that the methods developed in other studies at orchard scale are valid for flights in large areas comprising several olive orchards differing in soil and crop management characteristics.
Highlights
Olive (Olea europaea L.) is one of the most important crops in the Mediterranean Basin, representing 95% of the world production
linear discriminant analysis (LDA) reached an overall accuracy of 59.0% and a κ of 0.487 while support vector machine (SVM) showed a higher overall accuracy, 79.2%, and a slightly higher κ, 0.495
This study completed the one conducted by Calderón et al [12] at orchard scale, extrapolating the methods to larger areas comprising several olive orchards differing in soil and crop management characteristics
Summary
Olive (Olea europaea L.) is one of the most important crops in the Mediterranean Basin, representing 95% of the world production. In Spain, VW is of increasing concern for olive production because of its rapid spread and increasing severity associated with recent changes in cropping practices implemented to increase olive yields [2,3] These changes include use of self-rooted planting stocks to establish high-tree-density, drip irrigation, reduced or no tillage and high inputs of fertilizers in newly cultivated soils or fertile soils [4] previously grown with susceptible crops to V. dahliae, such as cotton [3]. Remote sensing for the detection of damage caused by soil-borne plant pathogens has proved to be the best-fit technology for optimization of integrated pest management These methods are rapid and reliable, allowing real-time plant disease monitoring for disease control and management [8,9]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
