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| Hauptseite > Publikationsdatenbank > Detection of plant stress responses in aphid-infested lettuce using non-invasive detection methods |
| Hauptseite > Publikationsdatenbank > Detection of plant stress responses in aphid-infested lettuce using non-invasive detection methods |
| Conference Presentation (After Call) | FZJ-2017-07607 |
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2017
Abstract: Lettuce cultures are prone to aphid infestations, but consumer tolerance for aphids in fresh lettuce is close to zero. To avoid losses of harvest due to aphids, lettuce plants are routinely sprayed with pesticides, which is costly and leads to high levels of pesticide residues in lettuce. Typically, early aphid infestation of lettuce cultures is not uniform, but shows a heterogeneous distribution. An early identification of aphid-infested lettuce plants prior to widespread infestation of whole fields would allow for selective spraying which reduces the use of pesticides. Although aphids have been shown to trigger physiological adjustments in plants, optical detection methods for aphid-infested lettuce plants have yet to be developed. For other crop plants, aphid infestation has been shown to change the optical properties of leaves and canopies. Spectral reflectance measurements of wheat and soybean revealed an increased reflectance in the visible spectrum, but decreased reflectance in the near-infrared (NIR) due to changed chlorophyll content and structural characteristics of leaves. We will compare different non-invasive detection techniques to determine suitable indicators for the biotic stress response of lettuce plants. As a first possible method, spectral reflectance measurements will be explored, followed by chlorophyll fluorescence measurements and thermal imaging. We will use image-based approaches in the laboratory as well as point measurements of field-grown plants with different infestation intensities to identify suitable indicators for the biotic stress response of plants to aphid infestation. Ideally, we can determine specific spectral signatures that are characteristic for aphid-infested plants. Our results will be used in the interdisciplinary project “Optimization of lettuce cultivation by high precision detection and selective pesticide treatment of aphid-infested plants” to select suitable sensors for the detection of aphid-infested plants, which can be mounted on a tractor and combined with a custom designed spraying installation for small-scale application of pesticides. We propose, that the early detection of aphid infestation and selective spraying of infested plants contribute to a reduced use of pesticides. On the long term, the developed setup will contribute to reduce the costs and environmental impact of pesticide treatments in lettuce cultivation.
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