Apple blotch (AB) is a major disease of apple in Asia and recently emerged in Europe and the United States. It is caused by the fungus Diplocarpon coronariae (formerly Marssonina coronaria; teleomorph: Diplocarpon mali) and leads to severe defoliation of apple trees in late summer, resulting in reduced yield and fruit quality. To develop effective disease management strategies, a sound knowledge of the pathogen's biology is crucial. Data on the early phase of disease development are scarce: No data on spore dispersal in Europe are available. We developed a highly sensitive TaqMan qPCR method to quantify D. coronariae conidia in spore trap samples. We monitored temporal and spatial dispersal of conidia of D. coronariae and the progress of AB in spring and early summer in an extensively managed apple orchard in Switzerland in 2019 and 2020. Our results show that D. coronariae overwinters in leaf litter, and spore dispersal and primary infections occur in late April and early May. We provide the first results describing early-season dispersal of conidia of D. coronariae, which, combined with the observed disease progress, helps to understand the disease dynamics and will be a basis for improved disease forecast models. Using the new qPCR method, we detected D. coronariae in buds, on bark, and on fruit mummies, suggesting that several apple tissues might serve as overwintering habitats for the fungus, in addition to fallen leaves. [ ] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

The analysis of soil nematode communities provides information on their impact on soil quality and the health of different agricultural cropping systems and soil management practices, which is necessary to evaluate their sustainability. Here, we evaluated the status of nematode communities and trophic groups’ abundance in fifteen fields hosting different cropping systems and managed according to organic or conventional practices. The nematode population densities differed significantly across cropping systems and management types covering various European climatic zones (spanning 121 to 799 individuals per sample). Population density was affected by the duration of the cropping system, with the lowest value in the vegetable cropping system (on average about 300 individuals) and the highest in the long-term fruiting system (on average more than 500 individuals). The occurrence and abundance of the different trophic groups was partly dependent on the cropping system or the management method, particularly for the bacteria, fungal and plant feeders. The taxonomical classification of a subset of samples allowed us to identify 22 genera and one family (Dorylaimidae) within the five trophic groups. Few taxa were observed in all fields and samples (i.e., Rhabditis and Cephalobus), while Aphelenchoides or Pratylenchus were present in the majority of samples. Phosphorus content was the only soil chemical parameter showing a positive correlation with total nematode population and bacterial feeders’ absolute abundance. Based on the nematological ecological indices, all three cropping systems were characterized by disturbed soil conditions, conductive and dominated by bacterivorous nematodes. This knowledge could lead to a choice of soil management practices that sustain a transition toward healthy soils.

Background: Self-organizing maps (SOMs) are a class of neural network algorithms able to visually describe a high-dimensional dataset onto a two-dimensional grid. SOMs were explored to classify soils based on an array of physical, chemical, and biological parameters. Methods: The SOM analysis was performed considering soil physical, chemical, and microbial data gathered from an array of apple orchards and strawberry plantations managed by organic or conventional methods and located in different European climatic zones. Results: The SOM analysis considering the “climatic zone” categorical variables was able to discriminate the samples from the three zones for both crops. The zones were associated with different soil textures and chemical characteristics, and for both crops, the Continental zone was associated with microbial parameters—including biodiversity indices derived from the NGS data analysis. However, the SOM analysis based on the “management method” categorical variables was not able to discriminate the soils between organic and integrated management. Conclusions: This study allowed for the discrimination of soils of medium- and long-term fruit crops based on their pedo-climatic characteristics and associating these characteristics to some indicators of the soil biome, pointing to the possibility of better understanding the interactions among diverse variables, which could support unraveling the intricate web of relationships that define soil quality.