In the present study, the detection and mapping of Silybum marianum (L.) Gaertn. weed using novelty detection classifiers is reported. A multispectral camera (green-red-NIR) on board a fixed wing unmanned aerial vehicle (UAV) was employed for obtaining high-resolution images. Four novelty detection classifiers were used to identify S. marianum between other vegetation in a field. The classifiers were One Class Support Vector Machine (OC-SVM), One Class Self-Organizing Maps (OC-SOM), Autoencoders and One Class Principal Component Analysis (OC-PCA). As input features to the novelty detection classifiers, the three spectral bands and texture were used. The S. marianum identification accuracy using OC-SVM reached an overall accuracy of 96%. The results show the feasibility of effective S. marianum mapping by means of novelty detection classifiers acting on multispectral UAV imagery.

Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery.

Tree of heaven (Ailanthus altissima) is a fast-growing deciduous tree native to China, considered a serious invasive species worldwide, with several socio-economic and ecological impacts attributed to it. Chemical and mechanical methods have limited efficacy in its management, and biological controls may offer a suitable and sustainable option. Aculus mosoniensis (Ripka) is an eriophyid mite that has been recorded to attack tree of heaven in 13 European countries. This study aims to explore the host range of this mite by exposing 13 plant species, selected either for their phylogenetic and ecological similarity to the target weed or their economic importance. Shortly after inoculation with the mite, we recorded a quick decrease in mite number on all nontarget species and no sign of mite reproduction. Whereas, after just one month, the population of mites on tree of heaven numbered in the thousands, irrespective of the starting population, and included both adults and juveniles. Significantly, we observed evidence of damage due to the mite only on target plants. Due to the specificity, strong impact on the target, and the ability to increase its population to high levels in a relatively short amount of time, we find A. mosoniensis to be a very promising candidate for the biological control of tree of heaven.

Summary: In May 2020, populations of Eriophyid mites were detected on tree of heaven,AilanthusaltissimaMill., in a recreative park in the city of Colombes, near Paris, and later in August and September in four locations, in Southern France. Morphological examination supplemented with sequencing data for the cytochrome c oxidase subunit I (COI) assigned all collected mites to a single species,Aculusmosoniensis(Ripka) (Acari; Prostigmata; Eriophyoidea). This is the first record of this species in France and the first insights into its intraspecific variability based on a barcode dataset. In Europe, this species is considered one of the most promising biological control agents of tree of heaven. This new record provides encouraging evidence that the geographic occurrence of this species is expanding in Europe which may be indicative of its dispersal and establishment abilities, two key factors for a future biological control program.

The larvae of Lasioptera donacis Coutin feed on fungal communities lining galleries within the mesophyll of leaf sheaths of Arundo donax in an aggregative manner. It has been stated that L. donacis could have established a fundamental symbiotic relationship with one fungus, although the fungal composition of these communities remains unsettled. Using a culture-dependent approach and ITS sequencing, the present work characterizes and compares the fungal communities associated with L. donacis in Eurasia with the endophytes of A. donax in Texas where L. donacis is absent. The 65 cultivable isolates obtained from L. donacis fungal communities were sorted into 15 MOTUs, among which Fusarium and Sarocladium predominated. No particular MOTU was systematically recovered from these communities regardless of the sites. The 19 isolates obtained in Texas were sorted into 11 MOTUs. Sarocladium and Fusarium were commonly found in Texas and Eurasia. Our finding indicate that the communities were composed of a diverse assemblage of non-systemic endophytes, rather than an exclusive fungal symbiont. From ovipositors and ovarioles of L. donacis emerging from plants in France, we opportunistically isolated the endophyte Apiospora arundinis, which lies at the origin of further research pertaining to its role in the feeding and oviposition of L. donacis.