Pandora cacopsyllae Eilenberg, Keller & Humber (Entomophthorales: Entomophthoraceae), a new species infecting pear psyllid Cacopsylla pyri L. (Hemiptera: Psyllidae).

The new species Pandora cacopsyllae Eilenberg, Keller & Humber (Entomophthorales) is described. The fungus was found on infected pear psyllids Cacopsylla pyri (Hemiptera: Psyllidae) in a pear orchard in Zealand, Denmark. Morphological structures (conidia, rhizoids, cystidia) were described on the designated type host C. pyri. In addition, conidia from an in vitro culture were described. Pandora cacopsyllae differs from other Pandora species by a) C. pyri is the natural host; b) conidia are different from other Pandora species infecting Psylloidea; c) ITS differs from other Pandora species infecting Hemiptera. The fungus has a high potential for future use in biological control of Cacopsylla pest species as well as other psyllids.

Encapsulation of the psyllid-pathogenic fungus Pandora sp. nov. inedit. and experimental infection of target insects.

BACKGROUND: Pandora sp. nov. inedit. (Entomophthorales: Entomophthoraceae) (ARSEF 13372) is a recently isolated entomophthoralean fungus with potential for psyllid pest control. This study aimed to develop a formulation based on biocompatible hydrogel beads in order to transfer the fungus into an easily applicable form and to test the effects on psyllids. RESULTS: After encapsulation in calcium alginate beads, Pandora sp. nov. grew from the beads and discharged conidia over 12 days under optimal humidity conditions at 18 °C. Conidial number was increased 2.95-fold by the addition of skimmed milk as nutritional formulation adjuvant to the beads. The virulence of the encapsulated fungus was assessed with the two target psyllid species; the summer apple psyllid, Cacopsylla picta and the pear psyllid, Cacopsylla pyri. Beads containing skimmed milk as nutritional adjuvant led to the highest mortalities (48.3% on C. picta and 75.0% on C. pyri). In a second bioassay, survival time of C. pyri exposed to beads containing different concentration (10%, 20% or 40%) of Pandora sp. nov. was tested. The survival time of C. pyri was significantly reduced when exposed to beads containing 10% or 20% Pandora sp. nov. The median survival time was reached after 5-6 days past inoculation and the cumulative mortality for C. pyri treated with Pandora sp. nov. beads showed up to 89% mortality. CONCLUSION: The promising results of this study will ease the way for large-scale field application of a novel Pandora species in biological psyllid pest control.

Image analysis-based quantification of fungal sporulation by automatic conidia counting and gray value correlation.

The present work describes a new computer-assisted image analysis method for the rapid, simple, objective and reproducible quantification of actively discharged fungal spores which can serve as a manual for laboratories working in this context. The method can be used with conventional laboratory equipment by using bright field microscopes, standard scanners and the open-source software ImageJ. Compared to other conidia quantification methods by computer-assisted image analysis, the presented method bears a higher potential to be applied for large-scale sample quantities. The key to make quantification faster is the calculation of the linear relationship between the gray value and the automatically counted number of conidia that has only to be performed once in the beginning of analysis. Afterwards, the gray value is used as single parameter for quantification. The fast, easy and objective determination of sporulation capacity enables facilitated quality control of fungal formulations designed for biological pest control.•Rapid, simple, objective and reproducible quantification of fungal sporulation suitable for large-scale sample quantities.•Requires conventional laboratory equipment and open-source software without technical or computational expertise.•The number of automatically counted conidia can be correlated with the gray value and after initial calculation of a linear fit, the gray value can be applied as single quantification parameter.