Fungus-resistant grape cultivars, commonly referred to as PIWIs (an abbreviation of the German term pilzwiderstandsfähig), are hybrids of Vitis vinifera with other Vitis species that exhibit low susceptibility to powdery mildew (Erysiphe necator) and downy mildew (Plasmopara viticola), the major fungal diseases in viticulture. In contrast, traditional grape cultivars are highly susceptible and require frequent fungicide applications during the growing season. The reduced number of fungicide treatments required by PIWIs lead to significant environmental and economic advantages, including fewer tractor passes, lower fuel and water consumption, and reduced pesticide-related waste. However, these benefits are rarely quantified.This study compares two fungus-resistant cultivars (Cabaret noir and Sauvignac) with two traditional ones (Pinot noir and Rivaner), using data from an experimental vineyard in Luxembourg. Environmental impacts are assessed using Life Cycle Assessment (LCA), and economic costs analysed both from a private and social perspective, accounting for direct production costs and environmental externalities.Results show that fungus-resistant cultivars can reduce environmental impacts by up to a factor of three, particularly in the climate change and freshwater ecotoxicity categories. Economically, growing PIWI cultivars allowed average savings of €685/ha/year at the level of the winery (mostly driven by lower fungicides use) compared to traditional cultivars. The estimated environmental costs in PIWI systems were €157/ha, compared to €406/ha for traditional systems. Sensitivity analyses confirmed the robustness of these findings across variations in disease pressure, yield and input prices, while showing that additional fertilizer inputs can reduce the relative magnitude of the environmental advantage.Altogether, the findings highlight the strong potential of fungus-resistant cultivars to lower both the environmental and economic burden of viticulture, supporting their broader adoption as a sustainable alternative.

Remote sensing of crop diseases has traditionally focused on detecting visible symptoms, often limiting intervention to advanced stages of epidemic development. This study investigates whether high-resolution unmanned aerial vehicles (UAV)-based red–green–blue (RGB) imagery can reveal earlier physiological destabilization preceding visible symptoms of wheat stripe rust and wheat leaf rust. UAV imagery was acquired at four winter wheat-growing sites in Luxembourg during the 2018/2019 season. Temporal dynamics of green–red spectral slopes were analyzed and compared with ground-based disease severity observations to identify potential pre-symptomatic spectral signals. A consistent flattening of the green–red spectral slope was detected prior to a rapid increase in visually assessed severity for both diseases. However, the length of this pre-symptomatic window varied between the two diseases: it lasted 7 to 14 days for wheat stripe rust and 5 to 10 days for wheat leaf rust. Likewise, the reduction in spectral slope magnitude was slightly greater for wheat stripe rust (65–80%) than for wheat leaf rust (60–75%), indicating that the temporal lead time and intensity of the spectral response were disease-dependent. During the pre-symptomatic phase, the spectral dynamics reflected latent physiological changes rather than visible disease severity. Strong correlations emerged only after the epidemic transition. These findings demonstrate that UAV-based RGB imagery could capture a distinct pre-symptomatic phase of stripe rust and leaf rust epidemics in winter wheat. Interpreting RGB spectral dynamics as early-warning indicators rather than merely as static severity proxies can guide proactive disease monitoring and precision agriculture.

BACKGROUND:Integrated pest management (IPM) aims to control crop pests while balancing environmental sustainability and farm profitability. Under IPM, pesticides are applied only when pest or disease pressure surpasses economic thresholds, even after the implementation of non-chemical control strategies, thus implying that reducing pesticide use below IPM standards entails economic losses. In response, some European Union member states have introduced compensation schemes for farms adopting pesticide reduction strategies, such as zero-fungicide approaches. However, it remains critical to determine under which conditions these financial incentives sufficiently offset economic losses and support fungicide reduction. RESULTS:Using commodity prices and fungicide application costs observed between 2018 and 2023, IPM-based fungicide use across 25 winter wheat trials generated an average net return of €67 ha-1 if disease monitoring was provided free of charge and €41 ha-1 if the farms had to bear the costs of disease monitoring themselves. The economic viability of compensation schemes depended on several key market factors: higher commodity prices, increased fungicide efficacy and low fungicide application costs enhanced the profitability of fungicide use, while low commodity prices and fungicide efficacy and high fungicide application costs made compensation schemes more attractive. CONCLUSION:The success of financial incentives for fungicide reduction is challenged by high commodity prices, highly effective fungicides and low-cost application services. Given the strong influence of commodity prices on fungicide profitability, reductions are most likely to occur in lower-value market segments (e.g. grain for animal feed production), where compensation schemes gain economic leverage more easily. © 2026 Society of Chemical Industry.

Unmanned aerial vehicle UAV-based RGB imaging is increasingly used to track crop diseases and assess fungicide performance. However, standard disease severity measures may miss an important factor: fungicide-induced changes in canopy structure that modulate disease observability. Here we analyse a multi-site dataset of wheat yellow and leaf rust, integrating UAV-derived canopy cover and disease severity, and rater-based disease severity assessments. Results indicate that between visual and UAV imagery-based disease severity was high but fundamentally non-stationary, governed by canopy cover and epidemic intensity. Measurement error followed structured, canopy-dependent regimes. The canopy-normalized disease area, a metric that harmonizes severity with structural and spatial context, revealed ranking shifts in fungicide efficacy that are not captured through traditional metrics. This suggests that severity-based comparisons may combine true disease suppression with treatment-related changes in how visible symptoms are. Framing plant disease quantification as a measurement challenge, rather than only a detection, may support a more accurate assessment of treatment effects. Modelling the influence of canopy structure on symptom expression could provide a scalable and robust basis for disease monitoring and decision-making in precision agriculture.

Fusarium graminearum is the main causal agent of Fusarium head blight (FHB) disease in wheat in Europe. To reveal population structure and to pinpoint genetic targets of selection we studied genomes of 96 strains of F. graminearum using population genomics. Bayesian and phylogenomic analyses indicated that the F. graminearum emergence in Europe could be linked to two independently evolving populations termed here as East European (EE) and West European (WE) population. The EE strains are primarily prevalent in Eastern Europe, but to a lesser extent also in western and southern areas. In contrast, the WE population appears to be endemic to Western Europe. Both populations evolved in response to population-specific selection forces, resulting in distinct localized adaptations that allowed them to migrate into their environmental niche. The detection of positive selection in genes with protein/zinc ion binding domains, transcription factors and in genes encoding proteins involved in transmembrane transport highlights their important role in driving evolutionary novelty that allow F. graminearum to increase adaptation to the host and/or environment. F. graminearum also maintained distinct sets of accessory genes showing population-specific conservation. Among them, genes involved in host invasion and virulence such as those encoding proteins with high homology to tannase/feruloyl esterase and genes encoding proteins with functions related to oxidation-reduction were mostly found in the WE population. Our findings shed light on genetic features related to microevolutionary divergence of F. graminearum and reveal relevant genes for further functional research aiming at better control of this pathogen.

The file contains the raw data of the manuscript " Overrepresentation of Alopecurus myosuroides with high levels of resistance towards herbicides applied in spring on heavy clay soils" by Treer S, Scherer K, Pallez-Barthel M, Dam D, Beyer M

Bunch rot caused by Botrytis cinerea is a major fungal disease in grapevines. Under humid climatic conditions, bunch rot development on grapes cannot be completely suppressed and bunch rot control strategies mainly aim to delay the epidemic. In the present study, we investigated the potential of the innovative cultural practice “partial double-pruning after bloom (PDP)” to delay the bunch rot epidemic on Pinot gris and Riesling cultivars over five consecutive seasons (2016-2020) in Remich/Luxembourg. Control vines were pruned at winter to one 10-node fruiting cane per vine, while in PDP, two 10-node fruiting canes per vine were kept; one of the two canes was removed at BBCH 73 (2-3 weeks after bloom). In all the 10 cultivar*year combinations, the bunch rot disease severity at the final assessment date (shortly before harvest) was lower in PDP than in the control. This reduction was significant (P £ 0.05) in 7 of the 10 cultivar*year combinations. PDP significantly delayed the date when 5 % disease severity was reached; in data pooled over the five years this delay ranged between 10.3 (Pinot gris) and 8.3 days (Riesling). The proportion of non-marketable fruit was significantly reduced by 41 % (Pinot gris) and 53 % (Riesling). Total yield per plant was reduced by 10 % (Pinot gris) and 19 % (Riesling), with a significant increase in total soluble solids at harvest in the case of Riesling. An additional evaluation in the year 2020 revealed reduced cluster compactness in PDP for both cultivars. PDP turned out to be an innovative, efficient, reliable and relatively cost-efficient cultural practice to delay the bunch rot epidemic in grapes. It can be integrated as one module into the best practice strategy to control bunch rot and contributes to pesticide reduction in viticulture.

Recent improvements in microbiology and molecular epidemiology were largely stimulated by whole- genome sequencing (WGS), which provides an unprecedented resolution in discriminating highly related genetic backgrounds. WGS is becoming the method of choice in epidemiology of fungal diseases, but its application is still in a pioneer stage, mainly due to the limited number of available genomes. Fungal pathogens often belong to complexes composed of numerous cryptic species. Detecting cryptic diversity is fundamental to understand the dynamics and the evolutionary relationships underlying disease outbreaks. In this study, we explore the value of whole-genome SNP analyses in identification of the pandemic pathogen Fusarium graminearum sensu stricto (F.g.). This species is responsible for cereal diseases and negatively impacts grain production worldwide. The fungus belongs to the monophyletic fungal complex referred to as F. graminearum species complex including at least sixteen cryptic species, a few among them may be involved in cereal diseases in certain agricultural areas. We analyzed WGS data from a collection of 99 F.g. strains and 33 strains representing all known cryptic species belonging to the FGSC complex. As a first step, we performed a phylogenomic analysis to reveal species-specific clustering. A RAxML maximum likelihood tree grouped all analyzed strains of F.g. into a single clade, supporting the clustering-based identification approach. Although, phylogenetic reconstructions are essential in detecting cryptic species, a phylogenomic tree does not fulfill the criteria for rapid and cost-effective approach for identification of fungi, due to the time-consuming nature of the analysis. As an alternative, analysis of WGS information by mapping sequence data from individual strains against reference genomes may provide useful markers for the rapid identification of fungi. We provide a robust framework for typing F.g. through the web-based PhaME workflow available at EDGE bioinformatics. The method was validated through multiple comparisons of assembly genomes to F.g. reference strain PH-1. We showed that the difference between intra- and interspecies variability was at least two times higher than intraspecific variation facilitating successful typing of F.g. This is the first study which employs WGS data for typing plant pathogenic fusaria.

The invasive pest Drosophila suzukii is threatening berry production. It is mainly managed via chemical control, which is associated with consumer and environmental concerns. Here, we tested the efficacy of mineral dusts under field and laboratory conditions in 2019 and 2020. Furthermore, population dynamics were studied in a vineyard and its surroundings. The kaolin products Cutisan and Surround®, as well as the CaCO3 product Carboliq, had neither insecticidal nor repellent effects on Drosophila suzukii adults in laboratory choice tests with grapes at concentrations of up to 2% (w/v). Cutisan and Surround® significantly reduced the number of deposited eggs (−41.9% and −49.3% respectively) while Carboliq had no effect on the oviposition under laboratory conditions. The Surround® treatment significantly reduced the number of flies trapped on 09 September 2020 at a test vineyard. Depending on the assessment date and treatment, between 59% and 84% of the flies in the bait traps were females. The number of eggs found in fruit treated with Carboliq in the field was higher at each assessment date than in the control but this difference was not statistically significant. Fruit treated with Cutisan or Surround® in the field showed an equivalent or lower average number of eggs compared with the control, but this difference was only significant on 24 September 2020. Between May 2015 and October 2020, the highest number of D. suzukii adults was observed around September in the field and a decline of the population occurred in the winter months until July. In epidemic years, temperature – humidity – combinations prior to population peaks were quite stable with low humidity being associated with a high temperature and vice versa. In non‐epidemic years, humidity fluctuated more than in epidemic years and temperatures were lower before population peaks. The effect of global radiation on population maxima seemed to be minor.

Viticulture is exposed and vulnerable to extreme weather and climate change. In Europe, owing to the high socio-economic value of the winemaking sector, the development of adaptation strategies to mitigate climate change impacts will be of foremost relevance for its future sustainability and competitiveness. Some guidelines on feasible short-term adaptation strategies are provided here (Figure 1), collected by the Clim4Vitis action (https://clim4vitis.eu/). Long-term adapation startegies are described in an accompanying technical review.

Climate change is a major challenge to viticulture worldwide. The adaptation potential of the different strategies to cope with climate change still embraces many uncertainties (e.g., unpredictable social-economic developments and land-use changes), particularly in the long-term. However, adaptation strategies adjusted to local terroirs and regional climate change projections will contribute to the sustainable development of the winemaking sector. The Clim4Vitis action (https://clim4vitis.eu/) recommends some guidelines for long-term adaptation (Figure 1).

Mycotoxins such as deoxynivalenol (DON) in wheat grain pose a threat to food and feed safety. Models predicting DON levels mostly require field specific input data that in turn allow predictions for individual fields. To obtain predictions for entire regions, model results from fields commonly have to be aggregated, requiring many model runs and the integration of field specific information. Here, we present a novel approach for predicting the percentage of winter wheat samples with DON levels above the EU maximum legal limit (ML) based on freely available agricultural summary statistics and meteorological data for an entire region using case study data from Luxembourg and Switzerland. The coefficient of variation of the rainfall data recorded ±7 days around wheat anthesis and the percentage of fields with a previous crop of maize were used to predict the countrywide percentage of winter wheat grain samples with DON levels > ML. The relationships found in the present study allow for a better assessment of the risk of obtaining winter wheat samples with DON contaminations > ML for an entire region based on predictors that are freely available in agricultural summary statistics and meteorological data.

In integrated pest management (IPM), pests are controlled when the costs of control correspond with the damage caused by a pest on a monetary scale, implying that low pest levels are left uncontrolled. Several forecast models have been developed in plant pathology to warn farmers before an epidemic occurs to allow timely control. Most of these models do not predict a control threshold (pest level at which action needs to be taken to prevent economic losses at the farm level) directly making an application in precision agriculture where pesticides and other inputs shall be used precisely where and when they are needed, difficult. Here, we quantified the temporal distance between critical rainfall periods and the breaking of the control threshold of Z. tritici on winter wheat, as affected by temperature based on data from 52 field experiments carried out in Luxembourg between 2005 and 2016. The highest frequency of hours with rain (≥ 0.1 mm/h) was observed approximately at 300 h before epidemic outbreaks at about 13 °C, at 350 h at 11.5 °C and at about 475 h at about 7.5 °C. A Q10 value of 2.8 was estimated. The knowledge generated here will be used to construct a model that directly forecasts the time at which the control threshold will be reached and thus, when fungicide use is needed according to the standards of IPM with direct applicability in precision agriculture.

In precision agriculture, pesticides and other inputs shall be used precisely when (and where) they are needed. European Directive 2009/128/EC calls for respecting the principles of integrated pest management (IPM) in the member states. To clarify the question, when, for instance, fungicide use is needed, the well-established economic principle of IPM may be used. This principle says that pests shall be controlled when the costs of control correspond with the damage the pests will cause. Disease levels corresponding with the costs of control are referred to as control thresholds in IPM. Several models have been developed in plant pathology to predict when epidemics will occur, but hardly any of these models predicts a control threshold directly limiting their usefulness for answering the question when pest control is needed according to the principles of IPM. Previously, we quantified the temporal distance between critical rainfall periods and the breaking of the control threshold of Zymoseptoria tritici on winter wheat as being affected by temperature, based on data from 52 field experiments carried out in Luxembourg from 2005 to 2016. This knowledge was used to construct the ShIFT (SeptorIa ForecasT, https://shift.list.lu/ ) model, which has been validated using external data recorded between 2017 and 2019. Within the efficacy period of a systemic fungicide, the model allowed correct predictions in 84.6% of the cases, while 15.4% of the cases were predicted falsely. The average deviation between the observed and predicted dates of epidemic outbreaks was 0.62 ± 2.4 days with a maximum deviation of 19 days. The observed and predicted dates were closely correlated (r = 0.92, P < 0.0001). Apart from outliers, the forecast model tested here was reliable within the period of efficacy of current commercial fungicides.

Demethylase inhibitors (DMIs) also referred to as azoles or triazoles are currently the main fungicides used for controlling Fusarium diseases and associated toxins in cereals. DMIs also represent an important class of fungicides used in the medical domain. The level of sensitivity of a set of F. graminearum strains (n = 23), collected over the period 1994-2010 in Luxembourg, Germany, Canada, USA, Italy and Belgium against three DMIs (cyproconazole, propiconazole, tebuconazole) used in agriculture and one DMI used in medicine (tioconazole) was assessed using a microplate test. Median molar EC50 values varied 113-fold among DMIs and on average 11-fold within DMIs with cyproconazole and tebuconazole being the least and the most effective ones, respectively. The EC50 values of the two DMIs registered for use against Fusarium species on cereals (propiconazole and tebuconazole) were significantly correlated (r = 0.597**), while no evidence for cross-resistance was obtained for other fungicide combinations. Haplotypes for CYP51A and CYP51C were defined based on snps determining amino acid variations in the two genes. EC50 values of strains with the CYP51A haplotype A0 and the CYP51C haplotype D1 varied greatly for the agricultural DMIs tebuconazole, propiconazole and cyproconazole, but not for the medical DMI tioconazole. None of the mutations and snps that were previously reported to be associated with resistance towards propiconazole was unambiguously related with resistance to tioconazole, because the mutations and snps were found in strains with low as well as with high EC50 values. Our results show that (1) DMI sensitivity of F. graminearum mycelium has been largely stable between 1994 and 2010, (2) effects of snps on sensitivity towards one DMI detected in one set of strains cannot be extrapolated to other DMIs and sets of strains and (3) F. graminearum strains responded differently to DMIs used in agriculture and to a representative of a medical DMI with no evidence for cross-resistance.

Much of the mitogenome variation observed in fungal lineages seems driven by mobile genetic elements (MGEs), which have invaded their genomes throughout evolution. The variation in the distribution and nucleotide diversity of these elements appears to be the main distinction between different fungal taxa, making them promising candidates for diagnostic purposes. Fungi of the genus Fusarium display a high variation in MGE content, from MGE-poor (Fusarium oxysporum and Fusarium fujikuroi species complex) to MGE-rich mitogenomes found in the important cereal pathogens F. culmorum and F. graminearum sensu stricto. In this study, we investigated the MGE variation in these latter two species by mitogenome analysis of geographically diverse strains. In addition, a smaller set of F. cerealis and F. pseudograminearum strains was included for comparison. Forty-seven introns harboring from 0 to 3 endonucleases (HEGs) were identified in the standard set of mitochondrial protein-coding genes. Most of them belonged to the group I intron family and harbored either LAGLIDADG or GIY-YIG HEGs. Among a total of 53 HEGs, 27 were shared by all fungal strains. Most of the optional HEGs were irregularly distributed among fungal strains/species indicating ancestral mosaicism in MGEs. However, among optional MGEs, one exhibited species-specific conservation in F. culmorum. While in F. graminearum s.s. MGE patterns in cox3 and in the intergenic spacer between cox2 and nad4L may facilitate the identification of this species. Thus, our results demonstrate distinctive traits of mitogenomes for diagnostic purposes of Fusaria.

The European commission directive EC 128/2009 calls for monitoring pests and pathogens of major crops. The monitoring data may be analysed for trends over time, including tests for a potential loss of biodiversity in the domain of plant pests and pathogens. The monitoring programs carried out in Luxembourg since 2007 provided evidence for an increasing role of yellow rust and a decreasing role of brown rust on winter wheat. Vast inter-annual variability was observed at the level of Fusarium head blight and mildew symptoms on winter wheat as well as at the level of Ceutorhynchus counts in oilseed rape, but no trend towards extinction could be demonstrated. Septoria leaf blotch was present in winter wheat at high levels towards the end of all seasons. The maximum number of Brassicogethes aeneus individuals found per main stem and season on oilseed rape increased slightly but significantly between 2007 and 2017. Substantial evidence for highly dynamic changes in the pest populations was found, but no evidence for the vanishing of the monitored species could be demonstrated.

During the past decade, imagery data acquired from unmanned aerial vehicles (UAVs), thanks to their high spatial, spectral, and temporal resolutions, have attracted increasing attention for discriminating healthy from diseased plants and monitoring the progress of such plant diseases in fields. Despite the well-documented usage of UAV-based hyperspectral remote sensing for discriminating healthy and diseased plant areas, employing red-green-blue (RGB) imagery for a similar purpose has yet to be fully investigated. This study aims at evaluating UAV-based RGB imagery to discriminate healthy plants from those infected by stripe and wheat leaf rusts in winter wheat (Triticum aestivum L.), with a focus on implementing an expert system to assist growers in improved disease management. RGB images were acquired at four representative wheat-producing sites in the Grand Duchy of Luxembourg. Diseased leaf areas were determined based on the digital numbers (DNs) of green and red spectral bands for wheat stripe rust (WSR), and the combination of DNs of green, red, and blue spectral bands for wheat leaf rust (WLR). WSR and WLR caused alterations in the typical reflectance spectra of wheat plants between the green and red spectral channels. Overall, good agreements between UAV-based estimates and observations were found for canopy cover, WSR, and WLR severities, with statistically significant correlations (p-value (Kendall) < 0.0001). Correlation coefficients were 0.92, 0.96, and 0.86 for WSR severity, WLR severity, and canopy cover, respectively. While the estimation of canopy cover was most often less accurate (correlation coefficients < 0.20), WSR and WLR infected leaf areas were identified satisfactorily using the RGB imagery-derived indices during the critical period (i.e., stem elongation and booting stages) for efficacious fungicide application, while disease severities were also quantified accurately over the same period. Using such a UAV-based RGB imagery method for monitoring fungal foliar diseases throughout the cropping season can help to identify any new disease outbreak and efficaciously control its spread.