Modeling the Main Fungal Diseases of Winter Wheat: Constraints and Possible Solutions

The first step in the formulation of disease management strategy for any cropping system is to identify the most important risk factors. This is facilitated by basic epidemiological studies of pathogen life cycles, and an understanding of the way in which weather and cropping factors affect the quantity of initial inoculum and the rate at which the epidemic develops. Weather conditions are important factors in the development of fungal diseases in winter wheat, and constitute the main inputs of the decision support systems used to forecast disease and thus determine the timing for efficacious fungicide application. Crop protection often relies on preventive fungicide applications. Considering the slim cost−revenue ratio for winter wheat and the negative environmental impacts of fungicide overuse, necessity for applying only sprays that are critical for disease control becomes paramount for a sustainable and environmentally friendly crop production. Thus, fungicides should only be applied at critical stages for disease development, and only after the pathogen has been correctly identified. This chapter provides an overview of different weather-based disease models developed for assessing the real-time risk of epidemic development of the major fungal diseases (Septoria leaf blotch, leaf rusts and Fusarium head blight) of winter wheat in Luxembourg

Performance of leaf wetness sensor used in winter wheat disease management

Wetness on crop leaves has particular epidemiological significance because many fungal diseases affect plants only when free moisture is present on leaves. The leaf wetness sensor detects the presence of wetness on a leaf’s surface, enabling researchers and producers to forecast disease and protect plant canopies, and consequently to optimize fungicide application and often reduce environmental load. This research project aimed at better understanding the leaf wetness duration and its influence in winter wheat disease. Measurement of surface wetness duration by three electronic flat-plate sensors (Model 237-Campbell Scientific, Inc) in wheat fields were compared with tactile and visual observations in replicated field experiments at the site of Arlon (Belgium) during the period May-July 2006 and April-July 2007. Performances of the sensor were evaluated against SWEB model outputs and visual observations of disease symptoms. On the field, dew-onset and dry-off of wetness on leaves were observed visually (with a flash light for dew-onset) at 15-minute intervals. Each sensor was placed close the flag leaf. For the three sensors, the two dew-onset and dry-off times measured in both 2006 and 2007 crop seasons gave a leaf wetness duration (LWD) which was on average one hour less than visual observations. In order to establish a relationship between the surface wetness periods and wheat foliar diseases, LWD was compared with the Septoria leaf blotch (SLB) development risk (main winter wheat disease). A minimal surface wetness duration favourable to infection for SLB was established.Weather-radar data ; Rainfall ; Septoria tritici ; Forecasting system ; Winter wheat ; Epidemiological model ; Surface wetness duration ; Spatializatio

Rouille brune du blé, un modèle pour évaluer les risques

peer reviewedL’article présente un outil de prévision de la rouille brune au G.-D. de Luxembourg. De 2000 à 2003, cette maladie apparaissait à la fin de l’épiaison, mais depuis 2003, elle apparaît de plus en plus tôt (GS45 stade gonflement). Cette apparition précoce est probablement liée à des températures printanières supérieures par rapport à la normale 1971-2000. Une analyse des données météorologiques nocturnes et des données d’observation de la maladie sur quatre sites expérimentaux (Everlange, Christnach, Burmerange et Reuler) entre 2000 et 2003 a révélé une forte corrélation positive entre la prédiction de la maladie basée sur le critère d’au moins 12 heures consécutives avec une température comprise entre 8 et 16°C et une humidité supérieure à 60% et la maladie observée sur la F1 (R = 0.93 ; P < 0.05) et sur la F2 (R = 0.87 ; P < 0.05). Les sorties de ce modèle qui a été développé sur base d’une approche stochastique ont été utilisées dans les bulletins d’avertissements diffusés conjointement par le Centre de Recherche Public – Gabriel Lippmann et l’Université de Liège-Campus d’Arlon à partir de 2004. La mise en application de ce modèle a montré un taux de réussite oscillant entre 80 et 85% pour la simulation de la rouille brune au G.-D. de Luxembourg. L’effort se poursuit pour spatialiser les sorties du modèle sur tout le territoire luxembourgeois et faciliter son utilisation par tous les vulgarisateurs agricoles

Ergeben sich Anhaltspunkte für einen Verlust von Biodiversität in der langjährigen Überwachung von Schaderregern?

Die Krefelder Studie zeigte 2017 einen Rückgang der Masse von fliegenden Insekten um etwa 75% innerhalb von 27 Jahren in einem geschützten Gebiet (HALLMANN et al. 2017). Um die Rolle der Landwirtschaft besser zu verstehen, wären Vergleichsdaten von ungeschützten landwirtschaftlichen Flächen hilfreich. Die Richtlinie 2009/128/EH des Europäischen Parlamentes und des Rates verlangt die Überwachung der Schaderreger in den wichtigsten Kulturpflanzen der Mitgliedsstaaten. Diese oft langjährigen Monitoringdaten von Agrarflächen können für Trendanalysen inklusive Tests auf einen potentiellen Verlust von Biodiversität im Bereich der Schädlinge und Krankheiten genutzt werden. Das Luxemburger Monitoring zeigte im Zeitraum 2007-2017 eine zunehmende Rolle von Gelbrost und eine abnehmende Rolle von Braunrost im Winterweizen. Bei Fusarium-Symptomen und Mehltau im Winterweizen sowie der Anzahl von Stängelrüsslern (gefangen mittels Gelbschalen im Winterraps) wurden sehr starke Schwankungen zwischen den Jahren beobachtet, ohne dass ein Trend in Richtung Aussterben einer Art gezeigt werden konnte. Septoria Blattdürre wurde in allen Jahren in hoher Dichte spätestens gegen Ende der Weizensaison gefunden. Die höchste pro Jahr in Luxemburg gefundene Anzahl von Rapsglanzkäfern pro Haupttrieb am Winterraps nahm zwischen 2007 und 2017 geringfügig aber statistisch absicherbar zu. Es wurde eine hohe Dynamik der Schaderreger zwischen den Jahren beobachtet ohne dass ein Verschwinden einer oder mehrerer der überwachten Arten auf den beobachteten Agrarflächen nachgewiesen werden konnte (DAM et al. 2020). Literatur DAM D, PALLEZ-BARTHEL M, EL JARROUDI M, EICKERMANN M, BEYER M (2020): The debate on a loss of biodiversity: can we derive evidence from the monitoring of major plant pests and diseases in major crops? Journal of Plant Diseases and Protection 127: 811-819. https://doi.org/10.1007/s41348-020-00351-9. HALLMANN CA, SORG M, JONGEJANS E, SIEPEL H, HOFLAND N, SCHWAN H, STENMANS W, MÜLLER A, SUMSER H, HÖRREN T, GOULSON D, DE KROON H (2017): More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS One 12:e0185809. https://doi.org/10.1371/journal.pone.0185809

Assessing the Interplay between Weather and Septoria Leaf Blotch Severity on Lower Leaves on the Disease Risk on Upper Leaves in Winter Wheat

peer reviewedSeptoria leaf blotch (SLB) is among the most damaging foliar diseases of wheat worldwide. In this study, data for seven cropping seasons (2003–2009) at four representative wheat-growing sites in the Grand-Duchy of Luxembourg (GDL) were used to assess SLB risk on the three upper leaves (L3 to L1, L1 being the flag leaf) based on the combination of conducive weather conditions, simulated potential daily infection events by Zymoseptoria tritici, and SLB severity on lower leaves between stem elongation and mid-flowering. Results indicated that the variability in SLB severity on L3 to L1 at soft dough was significantly (p < 0.05) influenced by the disease severity on the lower leaf L5 at L3 emergence and the sum of daily mean air temperature between stem elongation and mid-flowering. Moreover, analyzing the predictive power of these variables through multiple linear regression indicated that the disease severity on L5 at L3 emergence and mild weather conditions between stem elongation and mid-flowering critically influenced the progress of SLB later in the season. Such results can help fine tune weather-based SLB risk models to guide optimal timing of fungicide application in winter wheat fields and ensure economic and ecological benefits

Development of an Integrated Model to Assess the Impact of Agricultural Practices and Land Use on Agricultural Production in Morocco under Climate Stress over the Next Twenty Years

peer reviewedClimate change is one of the major risks facing developing countries in Africa for which agriculture is a predominant part in the economy. Alterations in rainfall patterns and increasing temperatures projected by the Intergovernmental Panel on Climate Change (IPCC) could lead to a decline in agricultural production in many areas requiring significant changes in agricultural practices and land distribution. The study provided estimates of the economic impacts of climate change, compared these with historical impacts of drought spells, and estimated the extent to which the current Moroccan agricultural development and investment strategy, the Plan Maroc Vert, helps in agricultural adaptation to climate change and uncertainty. The aim of this study was to quantify the effects of climate change on the overall economy by using an integrated framework incorporating a computable general equilibrium model. A concomitant factor to climate change will be the increase in population and its distribution and level of consumption, which will also influence agricultural production strategies, the conversion of agricultural land, the type of irrigation, and technological development. We demonstrated how changes in cereal production and area, affluence, and climate (rainfall and temperature) can be acquired for 12 regions of Morocco and used to develop and validate an earth system model in relation to the environment and socio-economic level, which projects their impact on current and potential land use over the next 20 years. We used different mathematical equations based on cereal area and production, population, consumption (kg/person), and change in climate (temperature and rainfall) in bour and irrigated areas for the growing season of 2014 in 12 regions to project agricultural land use over the next 20 years. Therefore, several possible scenarios were investigated to explore how variations in climate change, socio-economic level, and technological development will affect the future of agricultural land use over the next 20 years, which in turn could have important implications for human well-being. Among the 12 Moroccan regions, only 4 had a surplus of cereal production compared to their local consumption. The increase in population will generate a cereal deficit in 2024 and 2034, thus lowering the average annual quantity available per capita of cereals from 204.75 to 160.61 kg/p in 2014 and 2034, respectively. Therefore, it is necessary to reduce the amount of cereals per person by 5 kg/p and 25 kg/p so that the 2014 production could satisfy the population projected in 2024 and 2034. We found that cereal production will decrease with increasing temperature and decreasing precipitation according to the simulated scenarios, which might not satisfy the growing population in 2024 and 2034. This study provides a practical tool that can be used to provide policy makers with advice on food security assurance policy based on our current knowledge of the impending onset of climate change, including socio-economic statistics and the agricultural constraints of cereals in the 12 regions of Morocco

Weather-based predictive modeling of Cercospora beticola infection events in sugar beet in Belgium

Cercospora leaf spot (CLS; caused by Cercospora beticola Sacc.) is the most widespread and damaging foliar disease of sugar beet. Early assessments of CLS risk are thus pivotal to the success of disease management and farm profitability. In this study, we propose a weather-based modelling approach for predicting infection by C. beticola in sugar beet fields in Belgium. Based on reported weather conditions favoring CLS epidemics and the climate patterns across Belgian sugar beet-growing regions during the critical infection period (June to August), optimum weather conditions conducive to CLS were first identified. Subsequently, 14 models differing according to the combined thresholds of air temperature (T), relative humidity (RH), and rainfall (R) being met simultaneously over uninterrupted hours were evaluated using data collected during the 2018 to 2020 cropping seasons at 13 different sites. Individual model performance was based on the probability of detection (POD), the critical success index (CSI), and the false alarm ratio (FAR). Three models (i.e., M1, M2 and M3) were outstanding in the testing phase of all models. They exhibited similar performance in predicting CLS infection events at the study sites in the independent validation phase; in most cases, the POD, CSI, and FAR values were ≥84%, ≥78%, and ≤15%, respectively. Thus, a combination of uninterrupted rainy conditions during the four hours preceding a likely start of an infection event, RH &gt; 90% during the first four hours and RH &gt; 60% during the following 9 h, daytime T &gt; 16 °C and nighttime T &gt; 10 °C, were the most conducive to CLS development. Integrating such weather-based models within a decision support tool determining fungicide spray application can be a sound basis to protect sugar beet plants against C. beticola, while ensuring fungicides are applied only when needed throughout the season

Spatial heterogeneity of leaf wetness duration in winter wheat canopy and its influence on plant disease epidemiology

Leaf wetness duration (LWD) is an important factor influencing the occurrence of plant disease epidemiology. Despite considerable efforts to determine LWD, little attention has been given to study its variability within the canopy. The objective of this study was to evaluate its spatiotemporal variability in wheat fields in a heterogeneous landscape. The spatiotemporal variability of LWD was evaluated in a site close to Arlon (Belgium) during the period May to July 2006 and 2007. LWD measurements were made using a set of flat plate sensors deployed at five different distances from a 18 m high hedge (5, 10, 20, 50, 100 m). Each set of two sensors was placed horizontally close the flag leaf. In addition, we collected the amount of dew water that deposited on rigid epoxy plates placed next to each sensors. Experimental results showed that LWD measurements revealed substantial heterogeneity among sensor positions. LWD is longer for sensors closer to the hedge mainly because of its shadowing effect. 3 to 4 hours of difference was observed between sensors located at 5 m and those located at 100 m, and besides, a significant quantitative difference (p < 0.0001) of dew deposit was observed between area beside hedge and those placed at 100 m. In summary, this study provides new information on how wetness is distributed on wheat leaves according to the distance from a hedge. This leads to local microclimate conditions that will contribute to the disease spatial heterogeneity

Unleashing the Potential of Bacterial Isolates from Apple Tree Rhizosphere for Biocontrol of Monilinia laxa: A Promising Approach for Combatting Brown Rot Disease.

peer reviewedMonilinia laxa, a notorious fungal pathogen responsible for the devastating brown rot disease afflicting apples, wreaks havoc in both orchards and storage facilities, precipitating substantial economic losses. Currently, chemical methods represent the primary means of controlling this pathogen in warehouses. However, this study sought to explore an alternative approach by harnessing the biocontrol potential of bacterial isolates against brown rot in apple trees. A total of 72 bacterial isolates were successfully obtained from the apple tree rhizosphere and subjected to initial screening via co-cultivation with the pathogen. Notably, eight bacterial isolates demonstrated remarkable efficacy, reducing the mycelial growth of the pathogen from 68.75 to 9.25%. These isolates were subsequently characterized based on phenotypic traits, biochemical properties, and 16S rRNA gene amplification. Furthermore, we investigated these isolates' production capacity with respect to two enzymes, namely, protease and chitinase, and evaluated their efficacy in disease control. Through phenotypic, biochemical, and 16S rRNA gene-sequencing analyses, the bacterial isolates were identified as Serratia marcescens, Bacillus cereus, Bacillus sp., Staphylococcus succinus, and Pseudomonas baetica. In dual culture assays incorporating M. laxa, S. marcescens and S. succinus exhibited the most potent degree of mycelial growth inhibition, achieving 68.75 and 9.25% reductions, respectively. All the bacterial isolates displayed significant chitinase and protease activities. Quantitative assessment of chitinase activity revealed the highest levels in strains AP5 and AP13, with values of 1.47 and 1.36 U/mL, respectively. Similarly, AP13 and AP6 exhibited the highest protease activity, with maximal enzyme production levels reaching 1.3 and 1.2 U/mL, respectively. In apple disease control assays, S. marcescens and S. succinus strains exhibited disease severity values of 12.34% and 61.66% (DS), respectively, highlighting their contrasting efficacy in mitigating disease infecting apple fruits. These findings underscore the immense potential of the selected bacterial strains with regard to serving as biocontrol agents for combatting brown rot disease in apple trees, thus paving the way for sustainable and eco-friendly alternatives to chemical interventions