In a series of laboratory experiments, acclimated pupae of Tuta absoluta were exposed to various constant low temperatures in order to estimate their maximum survival times (Kaplan–Meier, Lt99.99). A Weibull function was fitted to the data points, describing maximum survival time as a function of temperature. In another experiment at −6°C, the progress of mortality increasing with exposure time was identified. These values were fitted by a sigmoidal function converging asymptotically to 100% mortality for very long exposure times. Analysing mortality data from the maximum survival experiment by a generalized linear model showed a significant common slope parameter (p < .001) that reveals parallelism of the survival curves at each temperature if a log time axis is used. These curves appear stretched (time scaled) if plotted with a nonlogarithmic time axis. By combining these mathematical relations, it was possible to calculate a species‐specific ‘mortality surface’ which exhibits mortalities, depending on temperature and duration of exposure. In order to accumulate hourly mortalities for courses of varying temperatures, an algorithm was developed which yields mortality values from that surface taking into account the attained mortality level. In validation experiments, recorded mortalities were compared against modelled mortalities. Prediction of mortality was partially supported by the model, but pupae experiencing intensely fluctuating temperatures showed decreased mortality, probably caused by rapid cold hardening during exposure. Despite this observation, mortality data converged to distinct levels very close to 100% depending on the intensity of temperature fluctuations that were characteristic for different types of experiments. The highest mortality limit occurred at intensely fluctuating temperatures in laboratory experiments. This constituted a benchmark that was not reached under various field conditions. Thus, it was possible to identify temperature limits for the extinction of field populations of Tuta absoluta pupae.

The Nearctic eastern cherry fruit fly species Rhagoletis cingulata (Loew) (Dipt., Tephritidae) has been detected several times in different European countries during the last decades. This species as well as Rhagoletis indifferens (Curran) are major pests of cultivated cherries in North America and are classified as quarantine pests in Europe. The introduction and establishment of both species could result in severe problems for Austrian cherry production due to additional infestation pressure caused by overlapping developmental cycles of American and native cherry fruit flies. A survey of both non‐European cherry fruit fly species was carried out during the growing seasons of 2007 and 2008 at eleven sampling sites in the eastern part of Austria. Pherocon® AM yellow sticky traps were installed in cherry trees and replaced at weekly or fortnightly intervals. Identification of the cherry fruit flies caught was based on morphological characteristics. Two specimens of R. cingulata were caught in 2007 in different weeks and at different locations while none were caught in 2008. R. indifferens was not detected at all. While it is possible that these specimens originate from established populations with low densities, it is more likely that the catches derived from accidental introductions.

Fruit fly species (Diptera: Tephritidae) of the genus Bactrocera are among the most serious orchard pests worldwide but are not native to Austria. The unexpected finding of one Bactrocera zonata adult in Vienna in 2011 initiated increasing survey efforts in Austria since 2012. Traps with male attracting lures were employed at several sites during the fruiting periods and catches were analysed. At sites in Vienna (urban area) Bactrocera specimens were trapped between 2012 and 2018, whereas no Bactrocera specimens were caught in agricultural areas or commercial orchards outside the city. Twelve specimens were identified as B. zonata and nine specimens as B. dorsalis sensu lato, though for the latter it was not possible to distinguish between B. dorsalis s.l. and B. carambolae using molecular analysis (ITS1). Molecular sequencing showed that the specimens caught were genetically different (with only a few exceptions), indicating genetically different origins. It is evident that the repeated findings of Bactrocera specimens in Vienna, where winter temperatures do not allow the establishment of tropical fruit flies, are linked to repeated entries of juveniles with infested fruits (in luggage or consignments). The results of our study reveal the need to strengthen phytosanitary import requirements for fruit commodities and travellers' luggage in order to protect fruit production in Austria and probably in other countries.

Bactrocera dorsalis is considered among the most destructive and economically important invasive fruit flies worldwide. Native to Southeast Asia, in just a few years, it has spread almost throughout all of sub-Saharan Africa, causing fruit loss in several commercially grown crops. In Europe, it is frequently intercepted as larva on imported fruits during phytosanitary inspections. In recent years, adult specimens have been caught in traps in Austria, Italy, and France, increasing the level of attention to this species. Rapid and unambiguous identification by European plant health laboratories is important to effectively prevent its introduction and establishment in Europe. The harmonized use of validated diagnostic protocols is essential. However, in entomology, unlike other disciplines, diagnostic protocols often lack validation data to support their suitability as adequate identification tools. In this study, tests from two international diagnostic protocols for the identification of B. dorsalis underwent a thorough validation process to assess their performance characteristics (analytical and diagnostic sensitivity, specificity, accuracy, repeatability, and reproducibility). A novel process of a joint validation of morphological and molecular identification protocols is reported. The novelty of this approach arises from the fact that morphological and molecular tests are validated in the same study, based on the same panel of samples, also allowing a two-way control on the assigned values of samples. Potential critical issues that could represent weaknesses of the protocols are also discussed in detail. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Timely detection of an invasion event, or a pest outbreak, is an extremely challenging operation of major importance for implementing management action toward eradication and/or containment. Fruit flies—FF—(Diptera: Tephritidae) comprise important invasive and quarantine species that threaten the world fruit and vegetables production. The current manuscript introduces a recently developed McPhail-type electronic trap (e-trap) and provides data on its field performance to surveil three major invasive FF (Ceratitis capitata, Bactrocera dorsalis and B. zonata). Using FF male lures, the e-trap attracts the flies and retains them on a sticky surface placed in the internal part of the trap. The e-trap captures frames of the trapped adults and automatically uploads the images to the remote server for identification conducted on a novel algorithm involving deep learning. Both the e-trap and the developed code were tested in the field in Greece, Austria, Italy, South Africa and Israel. The FF classification code was initially trained using a machine-learning algorithm and FF images derived from laboratory colonies of two of the species (C. capitata and B. zonata). Field tests were then conducted to investigate the electronic, communication and attractive performance of the e-trap, and the model accuracy to classify FFs. Our results demonstrated a relatively good communication, electronic performance and trapping efficacy of the e-trap. The classification model provided average precision results (93–95%) for the three target FFs from images uploaded remotely from e-traps deployed in field conditions. The developed and field tested e-trap system complies with the suggested attributes required for an advanced camera-based smart-trap.