Search

In this study hyperspectral imaging (380–1020 nm) and machine learning were utilised to develop a technique for detecting different disease development stages (asymptomatic, early, intermediate, and late disease stage) of powdery mildew (PM) in squash. Data were collected in the laboratory as well as in the field using an unmanned aerial vehicle (UAV). Radial basis function (RBF) was used to discriminate between healthy and diseased plants, and to classify the severity level (disease stage) of a plant; the most significant bands to differentiate between healthy and different stages of disease development were selected (388 nm, 591 nm, 646 nm, 975 nm, and 1012 nm). Furthermore, 29 spectral vegetation indices (VIs) were tested and evaluated for their ability to detect and classify healthy and PM-infected plants; the M value was used to evaluate the VIs. The water index (WI) and the photochemical reflectance index (PRI) were able to accurately detect and classify PM in asymptomatic, early, and late development stages under laboratory conditions. Under field conditions (UAV-based), the spectral ratio of 761 (SR761) accurately detected PM in early stages, and the chlorophyll index green (CI green), the normalised difference of 750/705 (ND 750/705), the green normalised difference vegetation index (GNDVI), and the spectral ratio of 850 (SR850) in late stages. The classification results, by using RBF, in laboratory conditions for the asymptomatic and late stage was 82% and 99% respectively, while in field conditions it was 89% and 96% in early and late disease development stages, respectively. • A lab- and UAV-based powdery mildew (PM) disease detection system was developed. • Spectral reflectance analysis of PM-infected squash leaves was performed. • The most significant wavelengths and vegetation indices were selected. • The technique was able to detect different stages of PM progress in squash. [ABSTRACT FROM AUTHOR]

Thermotherapy, as a non-chemical method to treat pests, has many advantages over the conventional chemical methods for treating some plant diseases. However, applying this method in the field, especially in orchards, can be difficult due to technical complications with regards to total coverage of large trees. In this work, a mobile thermotherapy system was designed and developed to provide heat treatment to individual citrus trees infected with Huanglongbing (HLB) disease. Based on previous studies, the system was designed to produce heat inside a canopy cover that covered a whole citrus tree, raising the internal temperature to 54 °C and treating the tree for 90 s. The system was able to increase the heat inside the canopy cover using different heat sources by either releasing steam or a combination of steam and hot water. A series of experiments were conducted to assess the uniformity of heat distribution within the tree canopy and the time to reach an appropriate temperature utilising two treatment types: Steam Treatment (ST) and Hot Water & Steam Treatment (HWST). Results indicated that the uniformity of heat is similar with both treatment types, while the average time for the entire treating process was 63% shorter when using HWST compared to ST. Furthermore, HWST reduced energy consumption by 52% compared to ST. The present study focuses on the technical evaluation of an thermotherapy system and does not evaluate the treatment efficiency and tree condition after treatment, which will be the subject of future experimental work. • A mobile thermotherapy technology was developed for citrus trees. • Steam Treatment (ST) and Hot water & Steam Treatment (HWST) were examined. • Heat distribution is similar in both treatments. • HWST reduced the treatment time by 63% and energy consumption by 52%. • Both treatment did not irreversibly harm trees. [ABSTRACT FROM AUTHOR]