It is accepted that irrigation water is a potential carrier of enteric pathogens, such as Salmonella and E. coli O157:H7 and, therefore, a source for contamination of fresh produce. We tested this by comparing irrigation water samples taken from five different greenhouses in Belgium. The water samples were inoculated with four zoonotic strains, two Salmonella and two E. coli O157:H7 strains, and pathogen survival and growth in the water were monitored up till 14 days. The influence of water temperature and chemical water quality was evaluated, and the survival tests were also performed in water samples from which the resident aquatic microbiota had previously been eliminated by filter sterilization. The pathogen’s survival differed greatly in the different irrigation waters. Three water samples contained nutrients to support important growth of the pathogens, and another enabled weaker growth. However, for all, growth was only observed in the samples that did not contain the resident aquatic microbiota. In the original waters with their specific water biota, pathogen levels declined. The same survival tendencies existed in water of 4 °C and 20 °C, although always more expressed at 20 °C. Low water temperatures resulted in longer pathogen survival. Remarkably, the survival capacity of two E. coli 0157:H7 strains differed, while Salmonella Thompson and Salmonella Typhimurium behaved similarly. The pathogens were also transferred to detached lettuce leaves, while suspended in two of the water samples or in a buffer. The effect of the water sample on the pathogen’s fitness was also reproduced on the leaves when stored at 100% relative humidity. Inoculation of the suspension in buffer or in one of the water samples enabled epiphytic growth and survival, while the pathogen level in the other water sample decreased once loaded on the leaves. Our results show that irrigation waters from different origin may have a different capacity to transmit enteric pathogens and an important impact on the fitness of the pathogens to sustain and even grow on the leaf surface.

This study introduces a geospatial comprehensive methodological system aimed at evaluating the suitability and need for agricultural digital solutions (ADSs) across Europe. This system integrates a diverse range of factors, including geophysical characteristics, climate patterns, and socioeconomic conditions, evaluated at regional- and farm-specific levels. By leveraging open-source Earth observations and socioeconomic data, we develop multiple performance, environmental, and socioeconomic similarity indexes that compare regions based on shared characteristics, such as soil quality, climate, and socioeconomic factors. Using advanced statistical and multi-criteria analysis tools, these indexes are tailored to different stages of agricultural production, enabling region-specific assessments that identify and prioritize the needs for digital solutions across Europe. The results indicate that the developed indexes effectively categorize regions based on comparable characteristics, facilitating the targeted recommendation of ADSs. Additionally, a connectivity performance index is created to assess the local deployment model of agricultural digital solutions (cloud, edge, or mixed), ensuring that the recommendations for technological implementation are feasible and effective given the local connectivity conditions.

Retrieval of soil organic carbon (SOC) from uncrewed aerial vehicle (UAV) hyperspectral imagery depends on how laboratory measurements are linked to pixels at centimetre resolution. This study presents a quality-controlled workflow in which radiometric calibration, harmonisation against proximal spectroradiometer measurements, pixel-level screening, spectral support definition and model validation are treated as interdependent components of a single procedure. Imagery was acquired with a tunable Fabry–Pérot interferometer camera in six bands between 670 and 1100~nm over eight bare soil fields in Flanders, Belgium (85 topsoil samples) and five fields in Central Macedonia, Greece (42 samples). Single pixel spectra, neighbourhood aggregation and local pixel augmentation were compared at radii of 0.25, 0.50 and 1.00~m using Random Forest, XGBoost, a 1D convolutional neural network and TabPFN, with all pixels from a given sampling location assigned to the same cross-validation fold. In Flanders, 23 of 24 neighbourhood configurations reduced RMSE relative to single pixel extraction, the best reaching $R^2 = 0.784$ and RMSE =0.155% SOC. In Central Macedonia, adverse acquisition conditions and a narrow target range prevented a usable SOC model, although electrical conductivity, CaCO₃ and pH reached $R^2$ between 0.61 and 0.69. These results indicate that the spectral support should be defined to match the field sampling support, and that this correspondence belongs alongside radiometric calibration, pixel screening and validation in a reproducible workflow for field-scale soil mapping.

Monitoring regulated quarantine plant pathogens and, when relevant, their vectors is compulsory in the European Union. Local Monochamus species (Coleoptera, Cerambycidae) vector the pine wood nematode, Bursaphelenchus xylophilus , a non-native pest already established in most of Portugal. Only 29 M. galloprovincialis individuals were trapped in Belgium in ten years (2013–2022), despite a dense coverage of pheromone-baited traps, suggesting absence or a very rare local occurrence in the country. In the northern neighbouring countries, only one single established population is known in The Netherlands and one in Denmark. A species distribution model based on pheromone-trap catches (negative and positive) of M. galloprovincialis from 4,914 traps in 29 European countries between 2008 and 2019 was developed, using the overall climate conditions and the distribution of seven pine tree species as explanatory variables. The effect of spatial scale was tested with a multi-scale approach. With a 225*225 km spatial grain, the major explanatory variables were the mean diurnal temperature range and, to a lesser extent, the presence of Pinus spp. The model predicted a low probability of presence in Belgium, the Netherlands, Great Britain and north-western Germany compared to southern Europe. Genotyping allowed to conclude that at least some of the beetles caught in Belgium originated from foreign locations. All catches were located close to entry points, suggesting introduction with imported material. The small size of most of the Belgian pine stands may also explain the absence or apparently transient status, or rareness of Monochamus spp. This study thus suggests that surveys in Belgium should privilege entry points rather than local forest stands.