The assessment of soil functions and ecosystem services requires reliable eco-physiological indicators that capture the complexity of soil processes across scales. Long-term field experiment provides unique insights into soil carbon dynamic and functions under varying agricultural management practices and environmental conditions. In this study, we plan to conduct a meta-analysis of self-obtained field data from several long-term field experiments in Bad Lauchstädt, central Germany, to evaluate the applicability of both basic and novel eco-indicators in assessing soil health and carbon sequestration.
Our analysis includes traditional indicators such as metabolic quintet (qCO2) and microbial biomass carbon to soil organic carbon ratio (MBC:SOC), alongside some potential novel indicators like active microbial fractions, particulate organic matter to soil organic matter ratio (POM/SOM), soil pore characteristics, and soil fauna. These long-term field experiments represent varying land use practices, climatic conditions, and management strategies, offering a robust dataset for testing indicator sensitivity and effectiveness.
The primary objective of this research is to identify which indicators are most responsive to land use, climate variability, and seasonality at the field scale, and to explore their potential for evaluating soil functions and ecosystem services. While our data analysis is ongoing, we hypothesize that integrating basic and novel indicators will provide a comprehensive framework for soil assessment, enabling better predictions of ecosystem resilience and carbon storage potential. We look forward to presenting our findings and discussing the implications of eco-indicator-based assessments for sustainable soil management and climate change mitigation at the conference.
How to cite: Wang, S. and Blagodatskaya, E.: Meta-analysis of soil eco-indicators to assess soil functions and ecosystem services in long-term field experiments in Bad Lauchstädt, Central Germany, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7372, https://doi.org/10.5194/egusphere-egu25-7372, 2025.
Due to expected climate change effects, and with the aim of improving the resilience of the region of Navarra (N Spain), the Life Nadapta project has developed different studies on diverse knowledge fields. One of them is related to agriculture, more specifically to soil heath and the capability of improving its resilience through different agricultural managements.
These managements are conservation agriculture, organic amendments and crop rotation and the goal of this work was to assess the effect of these practices on three previously defined soil quality indicators (bulk density, water holding capacity and organic carbon storage).
To measure the effect of this practices over the agricultural soils of Navarra, previously a zonification process took place, considering the agroclimatic distribution and different bioregions. As result of this, the region of Navarra was split into 12 zones. Subsequently, for each zone, the more representative agricultural soil managements were selected in a network of more than 150 agricultural plots. On these, paired comparisons on plots with on the same soil unit and contrasting management were conducted to determine the effect of the selected management strategies on soil health.
Result of an extensive plot selection, 11 plots were chosen out of the 150 in the network to continue the study several years after the first assessment, comparing the effect of a conventional management with the adaptative ones on soil health indicators.
In addition, to account for all aspects of the sustainability of these managements in real life, the study took into consideration the economic yield and cost of each management strategy in these 11 plots.
The groups of plots that showed significant differences in bulk density between adaptive and conventional management were those located in study zone 3 (semi-arid transition area). The plot under conservation agriculture management displayed higher values than the conventional one and the plot with organic amendments obtained a lower density.
Regarding carbon concentration, the same plot under conservation agriculture mentioned above performed worse than its conventional equivalent. On the other hand, in study area 1 (arid Mediterranean), the plot with organic amendments achieved a higher concentration than the conventional plot.
Finally, no differences were observed in any of the groups of plots studied, in terms of the water retention capacity indicator.
The economical balances showed that not all situations leading to improved soil quality resulted in a better economical behavior, which suggests that improving soil resilience may induce additional costs to producers.
Our results offer a first approximation of actual changes in agricultural fields when adaptive strategies are adopted at the regional level.
How to cite: Itarte, M., Antón, R., Enrique, A., de Soto, I., and Virto, I.: Assessment of soil health indicators in a regional strategy for climate change adaptation in agricultural land in Navarre (Spain)., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10094, https://doi.org/10.5194/egusphere-egu25-10094, 2025.
Agricultural conservation practices (e.g. conservation tillage, cover crops) are critical measures to mitigate nutrient loss and greenhouse gas emissions, enhance soil organic carbon (SOC), and maintain crop yield. Despite these benefits, recent studies indicate that switching to conservation tillage (e.g. no-till) can inadvertently increase nitrate leaching, thereby degrading water quality. This study presents a meta-analysis of field experiments to elucidate the conflicting outcomes of conservation tillage—increasing SOC levels but simultaneously exacerbating nitrate loss. For instance, SOC in the top 30 cm of soil under no-till (NT) was 14.2% and 4.7% higher than under high-intensity tillage (HT) and intermediate-intensity tillage (IT), respectively. In contrast, nitrate leaching under NT exceeded that under HT and IT by 4.9% and 0.6%, respectively.
By leveraging high-resolution datasets of soil characteristics, weather, water quality, land use, and topography, we utilized a comprehensive watershed model, the Terrestrial-Aquatic Sciences Convergence (TASC) to evaluate the combined effects of tillage and cover crops (e.g., winter wheat, rye, and oats) on SOC sequestration, nitrate loading, and crop yield in the Upper Mississippi River Basin (492,000km2). We found that conservation tillage and cover crops could complement each other. The combined adoption significantly affects water availability, nitrate leaching, SOC, and crop yield. While the integration of cover crops enhances biomass production and SOC, their ability to absorb soil inorganic nitrogen during the non-growing season helps mitigate nitrate leaching. Notably, crop yield under scenarios combining tillage and cover crops surpasses those involving only tillage. However, cover crops can also enhance evapotranspiration, which could potentially aggravate the water availability issues for crop production under future climate conditions. These results underscore the critical need for careful evaluation of the trade-offs between conservation tillage and cover crops when developing policies to address environmental challenges in agricultural ecosystems over the coming decades.
How to cite: Liang, K., Zhang, X., and Zhao, K.: Trade-offs of Conservation Practices in the US Corn-belt: Balancing Soil Organic Carbon, Water Quality, and Crop Yield, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12605, https://doi.org/10.5194/egusphere-egu25-12605, 2025.
Agriculture represents the most water-demanding sector in the Mediterranean, constituting 72% of total water demand, but exceeding 80% in most Southern Mediterranean countries. Moreover, climate change is expected to threaten water resources, by increasing evapotranspiration rates and changing precipitation regimes, with more heavy rains and prolonged long-term droughts. For these reasons, improving irrigation efficiency through policies like the Integrated Water Resource Management (IWRM) is critical for sustainable development. The digitalization of the irrigation sector can constitute a strategic solution to overcome the issue of water scarcity, as it integrates the latest technological advancements (Internet of Things – IoT, innovative water and weather sensors and actuators) in conventional irrigation systems. For this purpose, this work aims to develop and implement a real-time irrigation model, which acts as a decision-support tool for accurate irrigation management in Mediterranean environments. By integrating sensor-based data (soil moisture sensors, water meters and weather stations), weather forecasts (from meteorological models) and user inputs (crop, soil and irrigation management indications), the irrigation model provides accurate scheduling of irrigation events, according to crop water needs. The model runs at hourly scale, performing a soil water balance over the soil profile of the field and assessing the irrigation requirements, given the inputs (precipitation and irrigation) and outputs (deep percolation and crop evapotranspiration) of the system. The model schedules the days and volumes of future irrigation events, considering the scenarios of optimal irrigation (Early), moderate (Late) and high (Limit) water stress, in the case of full and deficit irrigation. One of the key features of the presented irrigation model is its ability to calibrate future irrigation events by analyzing the performance of past irrigations and checking the presence of deep percolation or water deficit in the lowest level of the soil profile. This model can constitute a powerful tool for the support of farmers in precision irrigation, considering the real-time monitoring of crop water needs and the scheduling of future irrigation events. Moreover, its user-friendly interface, with a very limited and easy-to-get set of input data allows an accessible management and visualization of the model’s outputs. This work is part of the PRIMA-founded ACQUAOUNT (Adapting to Climate change by QUantifying optimal Allocation of water resOUrces and socio-ecoNomic inTerlinkages - https://www.acquaount.eu/ ) project, which aims to apply innovative tools, smart water services and digital solutions, to improve sustainable irrigation and contribute to climate resilience in agriculture.
How to cite: Borgo, A., Debolini, M., Rianna, G., and Mereu, S.: Integrated digital solutions for sustainable farm-scale water allocation in Mediterranean environments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9410, https://doi.org/10.5194/egusphere-egu25-9410, 2025.
Across Europe sugar beet farmers are experiencing unsustainable losses due the yield impact of beet virus yellows (VY). In 2020 losses of £43 M were experienced by UK growers, with some individual losses of more than £0.5 M. High forecasts of over 67% VY incidence without control measures, triggered the use of environmentally damaging neonicotinoid seed treatment in the UK for 2022 and 2023. Sustainable management of VY requires a better understanding the risk of virus transmission from adjacent fields and field margins into sugar beet crops by the aphids that are the main vector.
A time sequence of images of sugar beet fields were collected over several weeks using a multispectral drone camera, from which several spectral indices were calculated, including mNDblue. In the 2022 season, a sample of plants within a field were inoculated with disease. In 2023, two fields were allowed to become naturally infected, with additional field sampling to directly measure the rate of infection, the presence of aphids and plant species at locations in the crop and the field margin.
2022 was a high disease pressure year where the natural infection arrived soon after inoculation and spread rapidly throughout the whole field. The frequency of observations was such that it was impossible to temporally separate the introduced and natural infections, by remote sensing, through some differences were seen on one image date for some vegetation indices, but surprisingly not in the mean value of mNDblue, between the areas around the inoculation and control sites. However, the standard deviation of mNDblue index was found to be correlated with infection rate as measured by ground sampling (R2 ≈ 0.5). This finding was confirmed in 2023 – a low disease pressure year -at Morley (R2 ≈ 0.4).
The images, ground sampling and disease testing showed that there was no reservoir of infection in the field margins and that the aphid numbers and infection rates were lower near the field margins. The presence of oilseed rape adjacent to one field did not result in any clear difference in infection rate or pattern.
How to cite: Waine, T., Beale, J., Bell, J., Garrett, D., Wright, A., Mead, A., and Takahashi, T.: Tracking in-field progression of beet virus yellows using UAS remote sensing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18188, https://doi.org/10.5194/egusphere-egu25-18188, 2025.
With climate change, both drought and heavy precipitation are becoming more frequent. The EJPSOIL project SoilX investigated the possibilities to mitigate impacts of such extremes on crop productivity through improved soil management practices. To do that, we applied a multidisciplinaryresearch framework. Three methodological approaches were applied to derive complementary findings on the possibilities to alleviate impacts of increasingly frequent precipitation extremes on cropping systems in Europe through adaptations in soil and crop management: (1) sampling and measurement campaigns in long-term field experiments (LTE’s) along a north-south gradient through Europe, (2) simulation experiments with an ensemble of four agro-hydrological models and the development of a new model for dynamically simulating soil structural changes, and finally (3) socio-economic interviews within regional farming communities.
From the compiled results of this project, we conclude that while soil structural improvements have potential to buffer the effects of short-term droughts on crop productivity according to hypothetical agrohydrological simulation experiments. However, the adaptation benefits realized in the contrasting field treatments of LTE’s studied in this project (i.e. organic amendments / no-till vs. conventional management) are likely to be small under current and future climatic conditions as measured differences in physical, mechanical and hydraulic properties were mostly small. This can be explained by the fact that treatments implemented in current LTE’s are often conservative (i.e. relatively small differences between contrasting treatments; often only single and not combined measures are tested). This finding calls for the introduction of new LTE treatments with greater emphasis on soil health and climate resilience. The need for more efficient management strategies to maintain and improve these soil functionalities is clearly highlighted by the results from model-based studies of climate change impacts in SoilX: climate warming contributed to the degradation of soil organic carbon resources, potentially also leading to a deterioration of the soils’ ability to infiltrate water and to retain water in the crop root zone.
Based on analyses of farmer interviews across different LTE regions in Europe, we can say that, since viewpoints on and priorities in the selection of soil management choices differ, diverse strategies to promote the uptake of soil management improvements are likely to be most successful: farmers with a strong intrinsic motivation to maintain and improve soil functionalities are most likely to respond positively to educational measures and can best be supported by regulatory frameworks supporting flexibility in the choice of measures. Farmers with a stronger focus on economic and production targets, however, may better be addressed by information campaigns highlighting possibilities for reducing production cost and increasing yield benefits in combination with regulatory frameworks that buffer against economic risks and possible additional costs.
How to cite: Holzkämper, A., ten Damme, L., D'Hose, T., Mehdi-Schulz, B., Pullens, J., Leonhard, H., and Meurer, K. and the SoilX researchers: Soil management to mitigate climate change-related precipitation eXtremes - SoilX, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16532, https://doi.org/10.5194/egusphere-egu25-16532, 2025.
Climate change-driven drought events are becoming increasingly common across Europe. These events can dramatically affect crop production, leading to significant yield losses and an overall deterioration of yield quality. Furthermore, irrigation is often not possible or allowed during long drought periods due to water scarcity. This problem requires crop management adaptations that provide more stable yields during challenging environmental conditions. To this end, organic mulch materials are being used as an agroecological solution. However, the effects of this management practice are not always straightforward, which has led to contradictory observations regarding their effect on crop yield. Here, we investigate the effect of applying an organic grass-clover mulch layer on the soil-water relations of celery (Apium graveolens Tango L.) during an extreme drought event. A full-factorial setup was used with (i) plants growing on a rainfed field with supplementary irrigation and plants subjected to drought using a movable rainout shelter and (ii) soil with and without organic mulch. Based on soil moisture and soil water potential sensors, and below-ground ERT (Electrical Resistivity Tomography) measurements, it was observed that the soil below mulched areas maintained a higher soil water content for a longer period of time compared to the soil in areas without mulch. Plant growth was monitored over time by combining manual measurements and drone data. Plants subjected to drought with mulch were significantly larger compared to plants without mulch, resulting in yields comparable to rainfed fields without mulch. Furthermore, the stomatal conductance and leaf water content of plants in mulched fields tended to be higher compared to plants in fields with no mulch. However, rainfed fields with mulch provided an even higher yield, indicating that the positive effects of the organic mulch were probably also mediated by a buffered soil temperature and an additional nitrogen input. Overall, organic mulch appears to buffer the soil-plant water relations of celery during drought, providing more stable yields under a changing climate.
How to cite: Schreel, J., Willemet, R., Blanchy, G., Deroo, W., Garré, S., Lootens, P., Roldán-Ruiz, I., De Boever, M., and De Swaef, T.: Mulching improves soil-plant water status and yield in experimental drought conditions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1694, https://doi.org/10.5194/egusphere-egu25-1694, 2025.
Many precision farming applications rely increasingly on the near-real time provisioning of accurate root zone soil moisture measurements to enable the efficient and economical use of limited freshwater resources. Besides the established sensor manufacturers who have been around for decades, new companies are entering the market, often with a portfolio of sensors especially designed for agricultural applications. These so-called soil moisture profile sensors (SMPS) exhibit a high potential for agricultural use. Their elongated shape and the ability to measure simultaneously in different depths make them especially suitable for frequent changes of location as required during cultivation of field crops. These sensors measure the volumetric soil water content (VWC) by exploiting the highly different dielectric permittivity of the solid and liquid soil compounds.
I this study we use a sandbox experiment to determine the measurement accuracy of different SMPS under controlled moisture conditions. The sandbox is a 2 x 2 x 1.5 m container filled with well-characterized fine sand which is sealed watertight to all sides. The sandbox is equipped with a 20 cm drainage layer and the water level inside the sandbox can be controlled by pumping water in or out using piezometer tubes, which are open at the bottom in the drainage layer. The SMPS were installed into the sandbox and the measurements were compared against reference measurements using CS610 TDR probes connected to a TDR100 (Campbell Scientific) and SMT100 (TRUEBNER) measurements installed in triplicate at six different depths. The measurement accuracy of 10 different sensors were evaluated, with each sensor being tested in triplicate. Most SMPS performed with reasonable accuracy under very dry and very wet conditions. However, strong variation was observed with respect to slope, offset and spread of the measurements and non-linear behavior was observed with some SMPS in the intermediate soil moisture range. The high variability of the measurement accuracy (RMSE: 1.2 – 6.5 vol. %) highlights the importance of choosing a suitable sensor, especially for precision farming applications, where it is crucial to have accurate field data to make the best management decisions without the need for soil specific calibration.
How to cite: Nieberding, F., Huisman, J. A., and Bogena, H. R.: How accurate are soil moisture profile sensors? – Results from a multi-sensor evaluation using a sandbox experiment , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17079, https://doi.org/10.5194/egusphere-egu25-17079, 2025.
Climate change impacts agricultural production globally, affecting food security and economic development at all scales. The Climate and Agriculture risk Visualization and Assessment (CAVA) framework has been co-designed by the University of Cantabria, Predictia Intelligent Data Solutions and the Food and Agriculture Organization (FAO) of the United Nations in response to the need for evidence-based climate information in formulating climate change adaptation projects (e.g. Green Climate Fund) and investment plans in the agriculture sector.
Within this framework, CAVA Platform has been designed as a climate service which provides users with an easy access to state-of-the-art climate information through a web portal, with the aim to facilitate the assessment of risks in the agricultural sector at regional, national, and sub-national scales. In particular, this is done based on global gridded observations, reanalysis, and the ensemble of CORDEX-CORE simulations covering the period up to 2100. The tool provides immediate access to essential climate variables (temperatures, precipitation, wind, humidity, radiation), and a series of pre-computed climate-derived indices relevant to agriculture (e.g., number of days below/above temperature thresholds, number and length of dry/wet spells, frequency and intensity of heat waves, etc.), allowing the user to select his/her region, period and season of interest. Moreover, users are also allowed to conduct more sophisticated analyses on demand; e.g. by modifying the thresholds that define the aforementioned indicators, focusing on specific crops, etc. In addition, all this information can be downloaded via automatic reports.
Concurrently to the CAVA Platform, CAVA Analytics is a cloud-based service that allows users with basic programming skills to access, process, and visualize most of the data CAVA Platform builds on. This computing environment, which is available via a web browser, relies on a Jupyter hub with a pre-installed version of the R package CAVAanalytics (https://github.com/Risk-Team/CAVAanalytics), which internally builds on the climate4R (https://github.com/SantanderMetGroup/climate4R) suite.
How to cite: Manzanas, R., Soldan, R., Kanamaru, H., San Martín, D., Tuni, M., Sánchez, I., Cimadevilla, E., Milovac, J., and Gutiérrez, J. M.: CAVA: a user-driven climate service for the assessment of risks in the agriculture sector, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21391, https://doi.org/10.5194/egusphere-egu25-21391, 2025.
Extreme heat is a growing threat to global agricultural production. Compound climate extremes, such as co-occurring hot and dry conditions driven by interactions between land and atmosphere, further exacerbate yield loss. Given the projected increase in such extremes, crop adaptation is becoming increasingly crucial to mitigate yield shocks and ensure food security.
The US Midwest, responsible for about a third of global corn production, is a key region of focus. In this study, we find that the regional sensitivity of corn yields to extreme heat has shown an increasing trend over the past 6 decades. While this finding aligns with other studies indicating limited adaptation in the region, the spatial variations in sensitivity changes suggest more localized influences on crop yields. Using data from the USDA and ERA5, we explore the basis for this observed variability in sensitivity, with a particular focus on two management strategies—crop diversity and tillage practices—at the county scale to assess potential adaptation.
How to cite: Raghuram, A. and Coffel, E.: Drivers of Spatial Variability in Corn Yield Sensitivity to Heat in the US Midwest, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12701, https://doi.org/10.5194/egusphere-egu25-12701, 2025.
Potatoes, with their small, shallow roots, are one of the most drought-sensitive crops. Silicon (Si) fertilizers have the potential to increase the drought tolerance of potatoes by modulating soil and plant properties. We investigated the effect of Si fertilizers on potato production and greenhouse gas emissions (N2O and CH4) under drought stress. The experiment was conducted on 2 soils (orthic haplohumod-sand and typical Agrudalf-clay) with drought intensity as main plot (acute drought and severe drought) and Si fertilizers as split plots (amorphous silica-ASi, diatomaceous earth-DE and no-Si addition-Control). For drought intensity treatments, acute drought had higher total yields compared to severe drought, while Si fertilizer treatments (ASi and DE) had higher total yields as well as higher soil moisture and leaf P content compared to the Control in both soils. Overall, Si-based fertilizers (ASi and DE) significantly reduced cumulative N₂O emissions in both sand and clay soils compared to Control treatments. More specifically Si-based fertilizers recorded an average reduction of 31% in N₂O emissions compared to Control. For CH₄ emissions, Si-based fertilizers led to an 8% increase in CH₄ uptake in clay soils and a 3% increase in sand soils (with DE) compared to Control, although these values were not significant. Our results indicate that, at field scale, Si fertilization has the potential to be a sustainable solution for maintaining potato production while reducing agricultural N2O emissions under drought stress in Denmark.
How to cite: Madegwa, Y., Hu, Y., Schaller, J., and Butterbach-Bahl, K.: Silicon fertilizer increased potato drought tolerance and reduced soil N2O emissions in two Danish soils at field scale , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8877, https://doi.org/10.5194/egusphere-egu25-8877, 2025.
Europe's commitment to sustainability drives the need for agricultural practices that are more environmentally friendly. This transition emphasizes the protection of biodiversity, reduction of environmental harm, efficient use of resources, and the simultaneous preservation of farming profitability and food security. To support this shift, various agroecological strategies are being examined for their impact on both productivity and environmental sustainability.
The presentation will show the results of a systematic review of existing research on multicropping (MC) to evaluate its potential to enhance the environmental sustainability of agro-ecosystems while maintaining or even increasing food production. MC is defined as the sequential cultivation of more than one crop on the same field within approximately 12 months.
While MC is widely practiced in developing countries, in the European region agriculture largely relies on single-cropping, with some exceptions in the Mediterranean region. Climate change will likely allow a future expansion of MC systems in Europe. As a result, MC practices are expected to play a more prominent role in future European agriculture, necessitating an evaluation of their broader implications. The review analyses the current knowledge on the impacts of MC system implementation for yields, soil water availability, soil properties and biodiversity.
How to cite: Fader, M.: Evaluation of multicropping systems (sequential cultivation) from an agroecological perspective, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12931, https://doi.org/10.5194/egusphere-egu25-12931, 2025.
Surface wetness (SW) is a particularly relevant variable for plant growers as it is related to the incidence of microbial and fungal diseases, as well as to fruit cracking, especially in susceptible species (e.g. Prunus avium). Although knowledge of SW quantity and duration is key to discern and predict its impact on plant health status, monitoring of this variable is still based on sensors of which the output is a simple electrical voltage, rather than a water amount. Furthermore, the intrinsic heterogeneity of canopy conditions seems to play a major role on leaf microclimate and SW.
The presented study analyzes i) the effects of radiative conditions (also affected by the presence of a rain exclusion covers) on the main structural factors affecting SW and SW duration on cherry leaves and ii) the ability of a Leaf Wetness capacitive Sensors (LWS) to represent SW on real leaves. Cherry leaves grown under 4 different environmental conditions (sunlit/shaded x covered/uncovered) were simultaneously artificially wetted to various degrees and their surface water content measured immediately or after variable drying times. The leaf growing conditions appeared to be strongly associated to some leaf structural properties, such as leaf angle, in turn influencing the SW amount and duration. Concerning the LWS, their output signal was first calibrated in respect to their actual SW. Following, the LWS ability to represent the nearby real leaves SW was analyzed. The ability of the LWS to represent real leaves largely depended on the growing conditions of the latter, highlighting the limitations related to using a single sensor type to represent canopy parts affected by intrinsic ecophysiological plasticity. The present analysis provides key findings to support assessments of microclimate, SW, SW duration and its variability on fruit trees, and in particular on cherry.
The study was funded by the PRIN CHOICE project (Optimizing CHerry physiOlogIcal performanCE through the correct choice of multifunctional covers).
How to cite: Reyes, F. and Destefanis, C.: Tree protection covers affects microclimate, leaf structural properties and the suitability of leaf wetness sensors to monitor surface wetness in cherry, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18958, https://doi.org/10.5194/egusphere-egu25-18958, 2025.
Viticulture is a key business for Italy, significantly contributing to the country's economy and cultural heritage. Italy is the largest world wine producer, with an estimated wine production of 41.0 mhL (2024 World Wine Production - OIV First Estimates). The relationship between climate variability and wine grape yield is a critical area of research, particularly considering ongoing climate change.
This study evaluates this relationship by employing ecoclimatic indices computed on key phenological periods that are crucial for grape development and specifically tailored to the life cycle of grapevines throughout the entire growing season. These periods have been identified using a validated phenological development model that accounts for various grape varieties. In addition to examining the effects of climate variability, this research also considers the risks posed by major cryptogamic diseases that can lead to significant crop losses.
To ensure the validity and relevance of the findings, the study actively engages with growers and obtains yield data from two prominent Italian wine consortia based in Lombardy and Tuscany. This localised approach allows the specific climatic and agronomic characteristics of each region to be considered, as well as the different grape varieties grown there.
The methodology developed correlates the ecoclimatic indices with the collected grape yield data through both single and multiple regression analyses, quantifying the proportion of total yield variability that can be explained by these predictors, both individually and in combination. The findings indicate that the ecoclimatic indices account for approximately 25% to 50% of the variance in grape yield.
By presenting a novel set of ecoclimatic indices derived from contemporary knowledge of climate impacts on grapevine development, this study contributes to filling a gap in the current research framework.
How to cite: Massano, L., Bois, B., Adrian, M., Fosser, G., and Gaetani, M.: From Vine to Wine: The Relationship Between Ecoclimatic Factors and Grape Yield in Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17505, https://doi.org/10.5194/egusphere-egu25-17505, 2025.
Studying volatile compounds emitted by plants is crucial in modern agriculture, providing insights into plant health, environmental interactions, and crop management. Plant volatile organic compounds (PVOCs) act as chemical signals, facilitating communication with pollinators, herbivores, and beneficial microorganisms. Understanding PVOC dynamics helps decode plant phenology events (e.g., flowering, fruit ripening), nutritional deficiencies, stress responses, and defence mechanisms. Terpenes are a class of PVOCs emitted during distinct growth stages as well as abiotic and biotic stresses.
Monitoring PVOCs (terpenes) allows for early detection of nutrient shortages, pest infestations, and disease outbreaks, enabling targeted interventions that reduce fertiliser and pesticide use, ultimately minimising crop losses. By leveraging PVOC monitoring, farmers can optimise resource allocation, enhance crop yield and quality, and reduce environmental impact, thus promoting sustainable agroecosystem management.
The MOSSA project integrated sensor technologies into IoT-based digital platforms for plant health monitoring. This project developed distinct interconnected units for each platform:
- TREE Unit – Tracks plant physiological parameters, including water consumption, biomass growth, and leaf stability.
- VOC Unit – Detects PVOC (terpene) emissions from lemon trees to monitor stress-related emission patterns.
- Power Unit – Powers the multi-sensing platform through energy harvesting.
Two different nanotechnological approaches were hired to achieve the VOC Unit goal. Electrospinning (ES) is a key nanotechnology for developing ultra-sensitive sensors, offering advantages in production efficiency and costs. The potential of ES technology to generate nanofibrous networks with various architectures featuring excellent specific surface area and remarkable porosity was combined with the exceptional selectivity of molecular imprinting technology (MIT) characterised by typical biological recognition mechanisms (e.g. enzyme-substrate, antibody-antigene, biological receptors) to developing highly sensitive and selective VOC (terpene) sensors, specifically for limonene, a key biomarker of plant biotic and abiotic stress. These sensors demonstrated extraordinary specificity, even distinguishing between stereoselective compounds. The VOC Unit, which incorporated MIT/ES sensors for limonene detection, allowed real-time monitoring of emission dynamics from lemon trees under simulated stress conditions, such as drought and pest injuries.
The Tree Unit monitored plant health by recording sap flow, tree growth, trunk temperature, air conditions, and incoming radiation under the canopy. Sap flow, a key indicator of transpiration and water status, was measured using heat transport as a tracer within xylem tissue. After laboratory evaluation, the HPV method was selected, using a 6-second heat pulse at ~4W power.
A 4-chip ASM Osram sensor spectrometer measured incoming radiation across 28 spectral bands. An infrared dendrometer tracked tree growth, while an improved radial increment sensor achieved 0.46 m resolution with an absolute error <10 µm. A hygrometer recorded air temperature and humidity.
The Power Unit utilised a solar energy module based on a 450 nm 3D perovskite light harvester (1.65 eV band gap)between ETL and HTL layers. The ETL, composed of compact and mesoporous TiO₂, supported crystal growth and enhanced charge extraction. This solar cell module efficiently harvested solar energy, ensuring a continuous power supply for the sensing platform.
These innovations open new possibilities for plant health monitoring, contributing to precision agriculture and enabling more sustainable and efficient agrosystem management.
How to cite: De Cesare, F., Molinari, F. N., Valentini, R., Agresti, A., and Macagnano, A.: Development of a selective molecularly imprinted polymer composite electrospun nanofiber sensor for a multifunctional platform for monitoring fruit tree health, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20724, https://doi.org/10.5194/egusphere-egu25-20724, 2025.
Climate change poses long-term risks to agriculture, driven by shifts in temperature, precipitation, and increased extreme weather events. Rising temperatures shift growing seasons, while altered precipitation affects water availability. Extreme weather, including intense rainfall, increases the risk of soil erosion and runoff. These changes are particularly important for vineyards, where grape ripening timing, crucial for wine quality, is affected. Vineyards, often located in hilly regions, also face soil degradation, impacting not only production but sectors like eno-tourism.
In this study - under the AGRITECH PNRR project - an experimental vineyard at Tenuta Donna Elvira in Montemiletto (AV), located in the Taurasi DOCG district (southern Italy), was used to assess the impact of climate change on soil and vineyard dynamics. The research included the following activities: i) identifying functional homogeneous zones (fHZs) in the vineyard using lidar-derived Digital Terrain Models (DTM), electromagnetic induction (EMI) sensor data, and vegetation indices derived from UAV flights; ii) Monitoring soil water content, agro-meteorological variables, leaf water potential, and leaf area index (LAI) over two years; iii) Conducting soil analysis on two distinct but adjacent soil types, evaluating their chemical, mechanical, and hydrological properties.
For both soils, the agro-hydrological model FLOWS was first calibrated and validated. Subsequently, simulations were conducted to assess conditions under the current climate (ACT: 2016–2023), near future (NEAR: 2025–2049), mid-future (MID: 2050–2074), and far future (FAR: 2075–2099) across three climate scenarios. These scenarios were derived from datasets provided by the 6th phase of the Coupled Model Intercomparison Project (CMIP6), utilizing three General Circulation Models (GCMs)—MPI-ESM1-2-LR, MRI-ESM2-0, and GFDL-ESM4—and three Representative Concentration Pathways (RCP2.6, RCP7.0, and RCP8.5). The models were locally validated against ground data (precipitation and mean temperature) for the period 2006–2023 and bias-corrected using a linear technique with 10 years of data (2014–2023) from a weather station located approximately 10 km from the study site in Luogosano (PZ).
The results indicated that under the RCP2.6 scenario, the ripening date remains stable, while under RCP7 and RCP8.5, ripening advances by up to 6 weeks. The increase in groundwater recharge due to climate change is minimal, with an increase of less than 6% in the far future for both soils. Soil 1 is, on average, 50% more effective at preventing runoff and flooding than Soil 2. Runoff increases from the RCP2.6 scenario to the RCP7 scenario and further under the RCP8.5 scenario.
Challenges with GCMs include inconsistencies in predicting climate variables, emphasizing the need for ensemble approaches. Despite these challenges, process-based models have proven reliable for predicting agricultural outcomes, especially in managing vineyard ecosystems under climate change.
How to cite: Basile, A., Albrizio, R., Bonfante, A., Buonanno, M., De Mascellis, R., and Bancheri, M.: Assessing the Impact of Climate Change on Vineyard Ripening and Water Dynamics: A Case Study from the Taurasi DOCG in Southern Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7215, https://doi.org/10.5194/egusphere-egu25-7215, 2025.
Grape downy mildew, caused by the pathogen Plasmopara viticola, is one of the most devastating diseases impacting grapevine cultivation globally. Its primary infection is highly influenced by weather conditions and the presence of airborne sporangia. Effective management of this disease relies on timely preventive fungicide applications, which depend on accurate forecasting. Traditional empirical forecasting methods often lack precision, leading to costly and less effective intervention decisions. Recently, the use of spore traps for monitoring airborne spores has shown promise in enhancing plant disease forecasting accuracy.
This study aims to enhance Rossi’s primary infection model and develop a spore data assimilation method to improve the forecasting of grapevine downy mildew infections. Additionally, we examine the impact of climate change on disease occurrence risks and evaluate adaptation strategies across different grape-growing regions in China. By integrating spore trap monitoring data with the mechanistic model, our data assimilation method improved primary infection predictions and disease management strategies.
From 2022 to 2024, we conducted multisite monitoring in Nanning, Hechi, Guilin, and Yangling to analyze sporangia splash patterns and concentration changes within orchards, as well as disease index variations across regions. The collected data were used for model verification and calibration. We employed data assimilation techniques and performed a model sensitivity analysis to determine relevant parameters. The enhanced model demonstrated high sensitivity, specificity, and accuracy across major grape-growing regions in China, correctly predicting primary infection dates with a coefficient of determination (R²) of 0.85 and a root mean square error (RMSE) of 8-16%. Notably, the model accurately forecasted infection dates across multiple years and sites, with only one instance of a 7-day delay. Furthermore, the model identified optimal fungicide spraying windows, potentially reducing management costs by 10-30% compared to traditional strategies used by farmers.
Our analysis of climate change scenarios revealed significant shifts in primary infection trends, with warmer and more humid conditions projected to increase the risk and frequency of downy mildew outbreaks in several key grape-growing regions. In response, we propose adaptation strategies including the adoption of resistant grapevine varieties, modification of irrigation practices to reduce humidity around plants, and the implementation of integrated pest management (IPM) approaches that combine biological control agents with optimized fungicide application schedules.
These results indicate that assimilating real-time spore counts allows the model to effectively simulate primary infection processes, enabling timely and informed decision-making to limit disease spread. Additionally, understanding the climate change-driven shifts in infection trends facilitates the development of robust adaptation strategies to sustain grapevine cultivation under evolving environmental conditions. This approach provides grape growers with location-specific, precise, and timely information essential for developing effective disease management and adaptation strategies, thereby enhancing the sustainability and productivity of grapevine cultivation in the face of climate variability.
How to cite: Yao, L., Zhao, G., Chen, B., and Yu, Q.: Optimizing Primary Infection Forecasting and Management of Grapevine Downy Mildew with Spore Trap Data Across Chinese Vineyards, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12159, https://doi.org/10.5194/egusphere-egu25-12159, 2025.
Sustainable farms must balance agronomic production, farm economics and environmental concerns. Nutrient losses from agriculture are known to degrade downstream water quality. Many practices and technologies have been used to minimize the impact agriculture has on water quality, but few studies have been able to demonstrate how precision agriculture can accomplish such benefits. This presentation will demonstrate how precision agriculture was used to improve runoff water quality and farm gate returns through the adoption of precision conservation. At a research farm near Riesel, Texas, USA, ten cropped fields were managed with various levels of conservation adoption. Precision agriculture technologies were adopted for planting, fertilizing, and harvesting equipment in 2017. A baseline of data was captured from 2018-2021 to determine crop yield stability for each field. Starting in crop year 2022, the crop yield stability was used to implement precision conservation on four fields: two fields received reduced inputs to 60-80% of recommended rates in unprofitable zones, while two fields eliminated production in unprofitable zones. Water quality monitoring occurs in six of the ten fields. Preliminary data indicated decreased in soluble P loads of 90% following adoption of precision conservation, due to lower or eliminated P applications. Precision conservation seems to be able to balance production, economics and environmental concerns greater than traditional agriculture.
How to cite: Smith, D., Adhikari, K., and Hajda, C.: Balancing agronomic production, farm economics and water quality with precision conservation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3287, https://doi.org/10.5194/egusphere-egu25-3287, 2025.
The application of novel organic fertilizers derived from secondary raw materials has emerged as a promising sustainable agricultural practice in recent years. This study investigates the potential of organic fertilizers produced from fishery waste to be applied as alternatives for synthetic nitrogen (N) fertilizers through comprehensive soil incubation and pot experiments. The N content of eight selected organic fertilizers ranged from 1.9% to 9.8%, in which some of them were rich in labile N such as protein fractions and amino acids. In a 120-day incubation trial, six of these labile N-rich organic fertilizers demonstrated a superior mineralization rate of 49-66% compared to 10-35% for the other fertilizing products, showcasing a high concentration of readily degradable N fractions. This increased mineralization led to enhanced N availability for crop, which is crucial for short-term agricultural productivity. Remarkably, when applied to spinach at a fertilization rate of 170 kg N ha⁻¹, the tested organic fertilizers performed comparably to the synthetic fertilizer, resulting in similar yields and statistically non-significant differences in N use efficiency over two months of spinach growth. Additionally, a follow-up experiment assessed greenhouse gas emissions, especially N₂O, from soils amended with the fertilizers under high-water condition. Notably, solid organic fertilizers exhibited lower N₂O emissions (0.5%-2.0%) compared to the liquid ones (2.6%-4.5%) even when soil moisture content reached 70% of water-filled pore space, which in line with the previous field studies (Aguilera et al., 2013), where solid organic fertilizers emitted less N2O than the liquid organic fertilizers ). Overall, these circular fertilizers matched the N-supplying efficacy of synthetic fertilizers, offering a sustainable alternative. Notably, solid organic fertilizers outperformed the liquid ones in terms of N2O emissions, highlighting their potential for more environmentally friendly agricultural practices.
Keywords: fishery waste; organic fertilizer; nitrogen mineralization; greenhouse gas emissions
Reference
Aguilera, E., Lassaletta, L., Sanz-Cobena, A., Garnier, J., Vallejo, A., 2013. The potential of organic fertilizers and water management to reduce N2O emissions in Mediterranean climate cropping systems. A review. Agriculture, Ecosystems & Environment 164, 32-52.https://doi.org/10.1016/j.agee.2012.09.006.
How to cite: Zhang, J., Akyol, Ç., Luo, H., De Neve, S., and Meers, E.: Agro-environmental Potential of Novel Organic Fertilizers Derived from Fishery Waste , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21543, https://doi.org/10.5194/egusphere-egu25-21543, 2025.
Viticulture in Trentino Alto Adige (northern Italy) mainly focuses on wine quality rather than quantity, and it is well known that wine quality can be improved by applying moderate water stress during fruit ripening. But with climate change extreme drought periods are becoming more and more frequent, and longer often coupled with high air temperatures. This is challenging for farmers, since prolonged periods of water scarcity negatively affect the physiological activity of the vines, the yield and the increase of water demand from irrigation reservoirs. On the other hand, summer extreme precipitations cause, as well, crop loss, plant diseases, nutrient leaching and soil erosion.
With appropriate precision irrigation practices the timing and the amount of water can be controlled to guarantee the optimal amount of water to the crops and ensure the best quality of the products, also avoiding water loss by runoff or deep percolation resulting from an excess of irrigation. In this perspective it is essential to accurately monitor the water status of the SPAC, which is the Soil-Plant-Atmosphere Continuum.
This study focuses on the comparison of two different irrigation regimes on a vineyard located in Mezzolombardo (Trentino Alto Adige, Italy), with the analysis of the water status of the field during the 2024 growing season and the comparison of the musts after harvest.
Four vines (Vitis vinifera L., Teroldego cv.) on the same vine row were chosen: two of them were kept without irrigation, and the others were treated as usual with irrigation scheduled by the irrigation consortia. The water state of the plant was monitored with microtensiometers (FloraPulse Co., Davis, USA) embedded in the trunk and measuring the stem water potential (Ψstem) allowing a continuous, non-invasive and remote monitoring of Ψstem. The amount of water in the soil was measured with tensiometers, located near each plant, and atmospheric parameters were given by a meteorological station nearby.
The start of the 2024 growing season has been extremely wet and limited the initial development of the vegetation, but August was characterized by almost no water income and particularly high temperatures. Despite the lack of water, the non irrigated plants never reached Ψstem values associated to water stress, whereas the irrigated plants were kept regularly irrigated even when the water in the soil was above field capacity, leading to a potential loss of water by deep percolation. The comparison of the musts between the two thesis highlighted no significant differences in the organoleptic properties and the Ravaz Index showed that the non irrigated vines were in a better vegetative-productive equilibrium with respect to the irrigated plants.
In order to adapt the agricultural production to the water imbalance given by the changing climate, it is more effective to provide irrigation only when needed, and not to rely on a scheduled calendar. It is confirmed that precision irrigation practices accurately support the crop needs and it should be one common practice to be developed and enhanced in the near future.
How to cite: Mattedi, C., Zottele, F., Centurioni, F., and Corradini, S.: Effects of deficit irrigation practices on the Soil-Plant-Atmosphere system: a case study on Vitis vinifera L. (Teroldego cv.) from Trentino Alto Adige, Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10812, https://doi.org/10.5194/egusphere-egu25-10812, 2025.
Posters on site: Wed, 30 Apr, 08:30–10:15 | Hall X3
Tea is a globally important crop, that is highly sensitive to variations in climate. While the UK has traditionally imported tea from regions such as China, India, and Sri Lanka, there are now several tea producers established across the UK. However, the potential impacts of future climate change on the suitability of different regions of the UK for tea cultivation is currently poorly understood.
This study evaluates the future climate suitability for tea cultivation across the UK. Comparing the current climate from various continental European tea growing regions with UKCP climate projections under the four representative concentration pathway (RCP) scenarios, we analyse where in the UK European cultivars could feasibly be grown over the century. A ranking approach was employed, incorporating closeness between European current, and UK future climates, including temperature (Tmin and Tmax), precipitation, and humidity projections, to identify regions most conducive to tea growth. Results indicate that the southeast of the UK may provide optimal growing conditions in the future, contrasting with the west, where current tea farms are predominantly located.
These findings have implications for the strategic planning of tea farming in the UK, particularly due to the long lifespan of tea plants, highlighting the need for potential adaptation to shifting climate conditions such as importing cultivars that are more suitable for the future UK climate. Furthermore, the methodology offers a framework that could be extended to assess the viability of tea gardens outside the UK, and other crops under changing climatic regimes, supporting resilient agricultural practices.
How to cite: Howard, H.: Exploring the suitability of European tea cultivar growth in future UK climates., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3253, https://doi.org/10.5194/egusphere-egu25-3253, 2025.
The repercussions of climate change on viticulture are a matter of increasing concern, particularly in Europe, where vineyards are intrinsic to both the economy and cultural heritage. In order to facilitate a more profound comprehension of the spatial change of the climate, the climate twin method [1] is employed to analyse the case of European vineyards. The methodology involves the use of a climate twin model, which matches future vineyard climates with those of other regions. This provides insights into how shifting climates may influence the suitability of current and potential vineyard regions. The approach enables an understanding of both current and future climate conditions in wine-producing regions, offering prospective insights into the potential shift of suitable vineyard locations. The employment of the climate twin method facilitates the identification of regions within Europe that will retain their suitability for viticulture under future climate conditions, whilst concomitantly enabling the discovery of new areas with wine-growing potential in the future.
We rely on several bioclimatic indices, that consider climate conditions in the context of vineyard growth and disease development. The Huglin index and the number of heat and frost days are employed to describe the optimal conditions required for vine growth. The Scaphoideus titanus, the vector of Flavescence dorée, as well as the downy and powdery mildew, which are the main threats to European vineyards, are also considered. The climate twins are computed using these bioclimatic indices, as well as the raw climate data, namely temperature, precipitation, humidity and solar radiation. Results show that using the bioclimatic indices yields consistent mappings region by region, with a specific region being reliably associated with another under future climate conditions.
Topography is a pivotal factor in viticulture, with vineyards frequently situated in hilly regions with south-facing slopes to maximise sunlight exposure. These topographic characteristics modify temperature, thereby influencing vine growth and disease dynamics. In this study, we analyse the impact of topography by calculating temperature corrections based on slope orientation and altitude. We show that the influence of these adjustments plays an important role on the identification of climate twins, and subsequent predictions for vineyard viability under future climate scenarios.
The findings of this study offer a more robust understanding of how European viticulture will need to adapt to climate change, with a particular focus on spatial shifts in suitable regions. This will assist winegrowers in making informed decisions regarding vineyard locations, culture management strategies, and future investments in viticulture. Our study underscores the significance of the climate twins approach to understanding climate impacts on viticulture, taking into account both bioclimatic variables and topographic factors. The overarching objective of this research is to provide a scientific foundation for the sustainable viticulture practices that will be required in the face of ongoing climate change, thereby safeguarding the future of European winemaking.
[1] G. Rohat, S. Goyette, J. Flacke, International Journal of Climate
Change Strategies and Management (2017)
How to cite: Allaman, H., Goyette, S., and Kasparian, J.: Climate Twin Methodology for Assessing the Future Viability of European Vineyards: A Bioclimatic and Topographic Approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3752, https://doi.org/10.5194/egusphere-egu25-3752, 2025.
In Europe, future summers are expected to bring both droughts and periods of excessive rainfall, highlighting the need for adaptable agronomic strategies across varying climatic scenarios. While mulch is well-documented for its ability to reduce soil evaporation and enhance tolerance against drought, its effects under wet conditions remain unclear.
In this study, we investigated the efficacy of three types of organic mulch - hay, miscanthus, and woodchips - for potato cultivation (Solanum tuberosum L.) during the wet summer of 2024 in the Flemish region of Belgium. Mulch was applied as a 6-cm layer on a sandy loam field. To gain insights into the impact of mulching on soil processes and crop development, we measured soil water content, matric potential, temperature, microbial activity, nitrogen in both soil and plant, and crop growth through a combination of manual and UAV measurements.
Our findings indicate that mulch biodegradability was the main factor affecting crop development during the wet 2024 growing season. At the final harvest, the average tuber yields under hay and miscanthus treatments were 33.2±3.0 t/ha and 29.2±4.5 t/ha, respectively, surpassing the control group yield of 28.1±3.3 t/ha. In contrast, the woodchip treatment resulted in a lower tuber yield of 24.4±4.4 t/ha. The best-performing mulch thus led to an 18% increase in tuber yield, while the worst-performing mulch induced a 13% decrease compared to the control treatment.
We assume that rapidly decomposing mulches provided a nitrogen boost mediated by soil microbial activity, thereby enhancing crop growth. In contrast, slowly decomposing materials might have caused nitrogen immobilization, reducing crop development and yield compared to the control group. The study underscores that the effectiveness of mulching is context-dependent and shaped by the interplay of mulch characteristics, environmental conditions, and crop-specific requirements.
How to cite: Willemet, R., Schreel, J., De Swaef, T., Cornelis, W., and De Boever, M.: Mulch Type Matters: The Impact of Mulch Biodegradability on Potato Crop Development Under Wet Conditions in Belgium, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6950, https://doi.org/10.5194/egusphere-egu25-6950, 2025.
In recent years, molecular biomarkers have emerged as important tools in modern agriculture, facilitating the monitoring of plant health and providing objective assessments of resistance and susceptibility to environmental factors. Within the realm of grapevines (Vitis vinifera L.), genomic biomarkers hold promise owing to their ability to integrate multifaceted, context-dependent information.
In this context, telomere length emerges as a promising, rapid, and cost-effective genomic biomarker, as observed in other species such as mammals and other plants. Telomeres, repetitive DNA sequences situated at chromosome ends, play a central role in safeguarding genetic material from damage and have been widely used in processes related to health, aging, and stress in mammalian models.
Quantitative real-time PCR (qPCR) enables precise quantification of telomere length relative to an internal reference gene specific to grapevines, ensuring stable measurements across diverse environmental conditions. Implementation of this novel protocol will facilitate the evaluation of telomere length dynamics in grapevines under varying conditions, thereby providing a valuable tool for assessing the vine's health status.
This contribution presents the first results on the Aglianico vine subjected to different levels of water stress (irrigated and non-irrigated) under the same soil in an area of southern Italy devoted to the production of high-quality wines (Taurasi DOCG area) in the Tenuta Donna Elvira winery (Montemiletto—AV).
The results were be achieved within the BeViteLo project.
How to cite: Iannuzzi, A., Erbaggio, A., Albrizio, R., Accomando, F., Vitale, A., and Pistucci, R.: Telomere Length as a genomic biomarker of well-being in grapevines: preliminary results in Aglianico grapevine, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7186, https://doi.org/10.5194/egusphere-egu25-7186, 2025.
Southeast Asia is a cornerstone of global rice security, contributing substantially to regional and international food supply chains. Accurate and timely information on rice yield is essential for effective agricultural planning, trade policy formulation, and food security management. However, conventional approaches to yield estimation, which often rely on historical trends or sparse in situ observations, are insufficient for capturing the complex interplay between climate variability, extreme weather events, and crop dynamics. The increasing frequency and intensity of climate shocks, including droughts, floods, and heatwaves, underscore the need for an advanced rice yield forecasting system. The development of a decision support system--RICE-MAP (Rice Information & Climate Evaluation- Monitoring And Prediction), integrates state-of-the-art climate forecasts with machine learning techniques to provide dynamic, high-resolution predictions of rice yield under current and future climate scenarios. RICE-MAP synthesizes satellite-derived datasets, global climate model outputs, and agricultural statistics to monitor and predict yield variability across rice-growing regions in Southeast Asia. By leveraging spatially and temporally resolved climate variables with machine learning models, the system provides lead-time-specific yield predictions, accompanied by rigorous evaluations of forecast performance using established metrics. The system’s capabilities are accessible through a user-friendly dashboard, designed to facilitate decision-making for policymakers, agricultural planners, and other stakeholders. Case studies in Southeast Asia demonstrate the system’s potential of integrating climate science and artificial intelligence to enhance climate resilience and adaptive capacity in the agricultural.
Keywords: Decision Support System; Rice yield forecast; climate shocks.
How to cite: Zhao, C., Wang, Y., Zhang, C., and He, X.: RICE-MAP: A Prototype Decision Support System for Climate-Informed Rice Security in Southeast Asia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7657, https://doi.org/10.5194/egusphere-egu25-7657, 2025.
The agricultural sector faces increasing pressure to meet global food demand due to population growth. Challenges such as climate change, resource scarcity, and environmental degradation will further increase this problem. These issues are particularly critical in the Mediterranean region, which is characterized by water-limited conditions and soils poor in organic matter and mineral nutrients. As a step toward ensuring food security, optimized resource utilization strategies and actionable plans for stakeholders are necessary. Reliable estimation of crop growth parameters and yield prediction under different climatic and agronomic scenarios have emerged as critical tools in driving these changes.
Various conventional crop growth parameter estimation and yield prediction methods have emerged as methods for optimizing resource utilization, identifying risks, and enabling effective decision-making. However, conventional methods, including empirical, statistical, and process-based models, often face limitations such as co-linearity among predictor variables, assumptions of stationarity, and the inability to capture complex biophysical and biochemical interactions at large scales. These shortcomings highlight the need for more robust and adaptable approaches. Advanced technologies, particularly Artificial Intelligence (AI) and Remote Sensing (RS) have revolutionized agriculture by uncovering hidden patterns, enabling large-scale monitoring, and improving prediction accuracy. This research evaluates the state-of-the-art in the synergized use of AI and RS for crop growth parameter estimation and yield prediction in Mediterranean agroecosystems.
A systematic literature review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Keywords and Boolean operators were used to search titles, abstracts, and keywords in selected databases, including Web of Science and Scopus. The review included English and French publications focusing on the Mediterranean region, encompassing Southern European, Middle Eastern, and North African countries bordering the Mediterranean Sea. Publications that were duplicated, unrelated to the study objectives, or outside the geographical focus were excluded. Out of 551 initial publications retrieved, 117 met the inclusion criteria and were selected for detailed review.
The findings reveal a rising interest in integrating AI and RS for estimating crop growth parameters and predicting yield. Multispectral RS products, such as Landsat-8 and Sentinel-2, are the most frequently utilized data sources. Additionally, Sentinel-1 microwave sensors and Unmanned Aerial Vehicle (UAV)-based imagery are increasingly employed alongside ground-based sensors. Among AI methodologies, Machine Learning (ML) algorithms like Random Forest (RF), Artificial Neural Networks (ANN), and Support Vector Machines (SVM) dominate, while Deep Learning (DL) techniques such as Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks have gained prominence since 2020. Most publications were produced between 2020 and 2024, with Italy, Spain, and France being the most studied regions.
The study underscores the transformative potential of integrating AI and RS for crop growth parameter estimation and yield prediction in Mediterranean agroecosystems. By leveraging diverse data sources, algorithms, and sensor technologies, these advancements address the limitations of traditional models, enhance scalability and accuracy, and support sustainable agriculture in resource-limited environments.
This research is performed in the framework of the PhD program in Agrobiosciences, Scuola Superiore Sant'Anna, scholarship: PNRR “Digital and environmental transitions” (M4C1, Inv. 3.4) ex MD 629/2024.
How to cite: Demissie, W., Sebastiani, L., and Rossetto, R.: Synergizing Artificial Intelligence and Remote Sensing for Enhanced Crop Growth Parameter Estimation and Yield Prediction in Mediterranean Agroecosystems: A Systematic Literature Review, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8207, https://doi.org/10.5194/egusphere-egu25-8207, 2025.
The Mediterranean region is experiencing severe environmental pressures due to climate change, population growth, agricultural intensification, and desertification. Impacts will be exacerbated in the coming decades and require adaptation strategies to increase the resilience of ecosystems and counteract land degradation. Throughout the Mediterranean, desertification combined with reduced freshwater availability will be the main factors limiting agricultural production, driving the need for alternative low-water demanding crops. Some Neglected and Underutilized Species (NUS), typical of the Mediterranean area and already used by rural populations, are adapted to grow under drought conditions, in combination with other soil limiting factors, such as high salinity, reduced nutrient inputs, and desertification. These species have the potential to ameliorate soil quality and to be a viable alternative for farmers, especially smallholders, to generate economic value.
The VENUS project (i.e. ConVErting marginal lands of the Mediterranean basin into productive and sustainable agroecosystems using low water demanding Neglected and Underutilized Species) aims to demonstrate the environmental potential of introducing NUS, known for their resilience under extreme conditions, and their economic potential as marketable products, including food, cosmetics, and energy applications. Specifically, 10 pilot sites have recently been established in 7 Mediterranean countries (Greece, Italy, Morocco, Tunisia, Egypt, Jordan and Algeria) to collect data on biotic and abiotic factors regulating the NUS production systems, to test the suitability and sustainability of NUS, and to assess the impact of their cultivation on soil health quality. The local results obtained at the pilot sites, combined with an analysis of the distribution of the most recent databases available in the literature of key abiotic/climatic factors across the Mediterranean, will be useful for the scalability and transferability assessment of NUS production systems to a wider scale. Furthermore, NUS production system at each site will be analysed to assess their quality for various market applications (i.e., food, cosmeceutical and pharmaceutical, and energy production), and social acceptance with the final aim of producing a set of commercially viable and sustainable business models at partners’ pilot regions and countries, providing alternatives to farmers struggling with water scarcity and other limiting factors.
Funding
This work was conducted in the framework of the project VENUS - “ConVErting marginal lands of the Mediterranean basin into productive and sustainable agroecosystems using low water demanding Neglected and Underutilized Species” funded by the PRIMA programme (Grant Agreement No. 2312) supported by the European Union’s Horizon 2020 research and innovation programme.
How to cite: Da Lio, C., Cosma, M., Al-Hadidi, L., Boufekane, A., Donnici, S., El-Din Abdin, A., ElRawy, A., Frison, L., Galeazzi, L., Hermassi, T., Lopez-Abelairas, M., Loudyi, D., Castaldi, S., Mastrocicco, M., Tosi, L., Maloupa, E., Grigoriadou, K., and Aschonitis, V.: Neglected and underutilized plant species to enhance productivity of marginal lands in the Mediterranean basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9409, https://doi.org/10.5194/egusphere-egu25-9409, 2025.
The plant pathogen Xylella fastidiosa (Xf) is a significant threat to various economically important tree cash crops. Although previously found only in the Americas, the bacterium responsible for olive quick decline syndrome was detected in Apulia, Italy, in 2013. The primary vector of Xf in Italy is the spittlebug Philaenus spumarius. Several studies suggested that vector mobility has been a critical factor influencing the epidemic, along with the insect population density and the pathogen transmission rate. Since then, it has spread to approximately 54,000 ha of olive trees in the region, causing dramatic concern throughout the Mediterranean basin. As a result, it is crucial to comprehend its distribution and forecast its potential diffusion. While a large contribution to the “olive quick decline syndrome” (OQSD) study has been focused on the insect-bacterium characteristics as well as on the climate, phenological and epidemiological Xf-driving factors, to date, the effect of the anthropogenic pressure on the distribution of OQDS has been neglected, notwithstanding some authors hinted to the importance of human mobility and settlements on the vector dissemination, and on the actual spread of insect pests over short and medium distances. To fill this research gap, we analyzed the spatiotemporal patterns of the OQDS epidemic in Apulia using an ecological niche model to identify how different land uses, used as proxies of different levels of human pressure across the Apulia territory, impacted the distribution of the Xf-infected olive trees in 2015–2021. Results demonstrated that the anthropogenic component significantly contributed to the epidemic, with the road system representing the main driver of diffusion and natural/seminatural areas hampering Xf spread at the landscape scale. This evidence highlighted the importance of explicitly considering the effects of the anthropogenic landscape when modelling Xf distribution and support the design of landscape-informed monitoring strategies to prevent Xf spread in Apulia and other Mediterranean countries.
How to cite: Raparelli, E., Bregaglio, S., and Bajocco, S.: Assessing the driving role of the anthropogenic landscape on the distribution of the Xylella fastidiosa-driven “olive quick decline syndrome” in Apulia (Italy), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10182, https://doi.org/10.5194/egusphere-egu25-10182, 2025.
With warming climate, the conditions north of the alps become more favorable for growing paddy rice as a niche product to diversify the crop production, while simultaneously utilizing wetlands with their benefits for high biodiversity and the prevention of greenhouse gas emissions. However, growing paddy rice in these climatic conditions remains challenging, and therefore, the Nitrogen availability might not be a dominant limiting factor to reach the relatively low yield objectives of Swiss growers (3-4 t / ha). Here, we assess the occurrence of N deficiencies in paddy rice fields across Switzerland and the relative importance of the two main fertilizations (basal at transplantation and at panicle initiation) to reach the yield objectives. To achieve these goals, we used proximal sensing (SPAD (soil plant analysis development) and a near-infrared leaf spectrometer) to estimate the nitrogen nutrition index (NNI) as a fast and affordable method as needed for precision agriculture and targeted fertilization. We calibrated the methodology to determine N and chlorophyl critical values at panicle initiation for the short duration rice variety (Loto) grown in Switzerland.
In nine paddy rice fields throughout Switzerland, proximal sensing measurements were done between transplantation and panicle initiation (determined as the best moment for the second application of fertilizer). In addition, in one paddy rice field we implemented an experiment consisting of four treatments: a standard practice, where the field was fertilized once at transplantation together with the plant (40 kg N/ha) and once before panicle initiation with a spreader (40 kg N/ha), zero fertilizer and two treatments of only one fertilizer application, namely one in which the fertilizer was applied with the transplantation, and one where the fertilizer was applied before panicle initiation.
Plant leaves were measured with two proximal sensing devices, (Hansatech SPAD meter and SpectraVue leaf spectrometer) before the second fertilization, and in the case of the experiment also one week after fertilizer application. In parallel, plant samples were collected to be analyzed for biomass, leaf N content and phenology.
Preliminary results of the SPAD values showed, that they tended to reach a maximum at ca. 18 ± 4 before panicle initiation, especially in the high yielding fields. In other fields, the SPAD values were much lower (ca. 9 ± 5), indicating the need for adapted fertilization even at low yield objectives.
In terms of yield, the experiment resulted in significantly different (p<0.05) grain yield differences between the treatment without fertilizer and with the two doses of fertilizer applied. The SPAD values showed significant differences after the second fertilizer application between the treatments that received the second fertilization and those who didn’t. No effect could be seen from the first fertilization in that case as the recent fertilization overrode the other differences.
This method could be used in the future to guide precision fertilization based on crop needs and to account for the high interannual variability.
How to cite: Metzger, K., Guillod, L., Fabian, Y., and Guillaume, T.: Rice N fertilization guided by plant nutritional status using proximal sensing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13048, https://doi.org/10.5194/egusphere-egu25-13048, 2025.
Anthropogenic soil degradation undermines essential ecosystem services such as food production, water purification, nutrient cycling and climate regulation. Unsustainable agricultural practices are among the main causes of soil degradation through pollution, soil loss and consequently lowering organic matter and nutrients. Adopting innovative solutions for agriculture soil management by adding low-decomposable organic amendments to the soil, such as hydrochar, can help reverse soil degradation. Hydrochar, derived from the hydrothermal carbonization of organic waste, may have the advantage of restoring the organic C stock in the soil, helping to mitigate climate change and improving soil health. Before using hydrochar at a large scale, a comprehensive assessment to exclude any potential adverse effects on the soil biotic community, playing a key role in the provisioning of ecosystem services, is needed.
This study, part of the interdisciplinary project ‘CHIMERA’ evaluating the impact of hydrochar on the soil-plant-atmosphere system, aims to investigate changes in the chemical and microbial properties of degraded agricultural soil following the application of hydrochar. Therefore, a controlled greenhouse experiment was conducted using pots (21 cm diameter, 16 cm height), each containing 1 kg of soil. Two types of hydrochar, produced by hydrothermal carbonization at 250 °C and 50 bar without oxygen, were tested: one derived from sewage sludge (HS) and the other from thistle (Cynara cardunculus L., HC) residues, respectively. Each hydrochar was applied at two doses (3 kg m-² and 6 kg m-²), and the resulting five treatments (four with hydrochar and one control) were assayed in five replicates. At different exposure times (from 18 to 517 days), the following soil properties were analysed: pH, total organic C (Corg) and its extractable fraction (Cext), microbial biomass (Cmic), activity (as respiration), the quotient of mineralization (qM) and genetic bacterial diversity (richness).
The results showed no toxicity to the soil microbial community; moreover, a general improvement of microbial biomass, activity and richness was observed, compared to control, at each exposure time, together with a significant decrease in qM, suggesting that C added as hydrochar was at least in part retained in soil. This ability highlights the positive hydrochar's role in improving soil structure and promoting resilience against erosion, drought and other climate-related challenges.
Our findings suggest that hydrochar could be a tool for sustainable agricultural practices in restoring degraded soils. However, the application of hydrochar on soils requires further studies to confirm these positive effects and whether these effects can be observed using hydrochar derived from other raw materials and for other soil types.
How to cite: Di Santo, T., Marzaioli, R., Coppola, E., Battipaglia, G., Castaldi, S., Zaccariello, L., Mastellone, M. L., and Rutigliano, F. A.: Hydrochar as an emerging solution for soil health improvement: Insights from a pot trial, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13091, https://doi.org/10.5194/egusphere-egu25-13091, 2025.
Abstract
Precision agriculture has become a critical approach for achieving efficient crop production while addressing the challenge of sustainable management of natural resources. A key component of precision agriculture is optimizing plant fertilization to maximize yields while minimizing environmental impact. Traditional methods of assessing plant nutritional status and fertilizer needs, such as soil and plant sampling, can be costly and time-consuming. Remote sensing techniques offer an alternative, reducing both the cost and time required for accurate fertilizer dose determination. Additionally, these methods provide more comprehensive information with higher spatial resolution.
This study aimed to investigate the potential of remote sensing techniques, specifically satellite imagery from Sentinel-2, to determine the nutritional needs of oats grown on highly heterogeneous soils. Field studies and satellite data analysis were conducted on an oats cultivation field situated on sandy soil with significant spatial heterogeneity in southwestern Poland. Observations and measurements were performed during the BBCH growth stages 12, 31, 49, 77, and 99.
Nitrogen uptake was calculated based on biomass yield and nitrogen content in crop samples taken at 40 designated points within the field. The AGRICOLUS software and Copernicus services were used for remote sensing monitoring of oats growth, while satellite images were processed at specific intervals to calculate selected remote sensing indices using QGIS software. Spectral data were used to determine indices such as NDVI, GNDVI, SAVI, EVI, NDMI, and MCARI.
The results demonstrated that soil heterogeneity had a significant impact on oats development and its nutritional requirements. Base on outcomes the linear model for N uptake was developed, where GNDVI and percentage content of sand in the soil where used for estimation of the nitrogen uptake. The study confirmed that remote sensing, particularly the GNDVI index, is a highly effective tool for managing fertilization during the early growth stages of oats on light soils with high spatial variability. Therefore remote sensing techniques can be used for real-time monitoring of spatial variability, facilitating precision management of the crops.
Research carried out as part of the OPUS-LAP project entitled "Sustainable nitrogen fertilization for agricultural crops based on open laboratory and field experiments with integrated near-real-time hydrological modeling" (grant number: 2022/47/I/ST10/02453)
How to cite: Franz, A., Sowiński, J., Głogowski, A., and Fiałkiewicz, W.: The use of remote sensing techniques to determine the nitrogen uptake by oats on highly variable sandy soils, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13590, https://doi.org/10.5194/egusphere-egu25-13590, 2025.
Modern agriculture faces an urgent challenge of optimizing the use of fertilizers, especially nitrogen, which is essential for healthy plant growth. However, overuse of nitrogen fertilizers can lead to severe environmental consequences, including surface and groundwater contamination, soil degradation, and the release of harmful greenhouse gases. This study aims to investigate how different fertilization and irrigation strategies affect oats growth, with a particular focus on nitrogen distribution in the soil, straw, and grain, as well as the overall performance of the crop. The research was conducted under controlled conditions, both in a vegetation hall that simulated real field conditions and in actual field settings at the Lubnów Agricultural Farm, located in the Ślęganiana catchment area near Wrocław, Poland. Various fertilization doses were tested, along with several irrigation schemes designed to replicate extreme rainfall events. The simulated rainfalls of 10 mm and 20 mm were applied at intervals of 2, 4, and 6 days, reflecting the unpredictability of real-world weather patterns. Additionally, the experiment incorporated four distinct soil types with different granulometric compositions to assess how soil texture and structure influence the effectiveness of nitrogen uptake by crops and irrigation practices. This approach allowed to better understand the interactions between soil characteristics, fertilization, and irrigation in real agricultural systems. The results of this study are critical for advancing sustainable farming practices concerning future climate changes and costs of fertilizer itself. By examining key crop parameters, such as stem length, biomass, and grain weight, it was possible to gain valuable insights into how different management strategies impact overall crop productivity and nitrogen use efficiency with regard to crop production. As climate change continues to disrupt agricultural systems worldwide, optimizing fertilization and irrigation techniques will be essential to ensure food security while minimizing the environmental impact. This research not only contributes to improving oats cultivation, but also offers a broader perspective on how precision agriculture can address pressing global challenges in agriculture.
Research carried out as part of the OPUS-LAP project entitled "Sustainable nitrogen fertilization for agricultural crops based on open laboratory and field experiments with integrated near-real-time hydrological modeling" (grant number: 2022/47/I/ST10/02453).
How to cite: Radzimska, J., Michalak, I., Głogowski, A., Fiałkiewicz, W., and Gałka, B.: Applying variable fertilization and irrigation to improve oats growth and reduce environmental impact, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13591, https://doi.org/10.5194/egusphere-egu25-13591, 2025.
The term 'carbon farming' is currently used as a synonym for 'regenerative agriculture', which is explicitly based on improving soil fertility and farm productivity (EU, 2021).
The final aim of the complementary agri-food plan AGROALNEXT is to favour the double transformation, digital and sustainable of the agri-food sector, in order to increase its competitiveness and achieve the climate and environmental objectives set out in the Green Pact, while guaranteeing the supply of healthy, safe, sustainable and accessible food to the population, as pursued by the EU Farm to Table Strategy. Specifically, line 4 'Circular Economy' is developed with the aim of reducing losses, emissions and waste generated by the agricultural sector, and of those that cannot be avoided, generating opportunities for exploitation and win-win processes in their management, which are technologically transformed into value for the sector, increasing the circularity of the sector.
The RECEC research project, which started on the 1st of September 2024, aims to enhance the resilience of agricultural production to the impacts of climate change through the promotion of efficient circularity. This project is founded on the POST LIFE plan of the LIFE AMDRYC4 project, which was led by the University of Murcia and concluded in 2022.
The objective of the RECEC project is to ensure, through a series of agricultural practices, that CO2 is absorbed from the atmosphere and stored in plant material and soil organic matter. In order to achieve these objectives, the present research project aims to evaluate and determine the suitability of new organic products, for which no data are available, such as plant biomass removed from the Mar Menor coast (Murcia, Spain), to improve soil structure, increase its fertility and evaluate its capacity as a CO2 sink for these marine by-products. Recent data from the Regional Ministry of Environment of the CARM reveals that between 2017 and 2022, a total of 32,920 tonnes of marine biomass were removed. Other vegetable waste (broccoli, cabbage, almond, olive, grapefruit and fig tree pruning waste) from agricultural activity in the Region of Murcia that can be used as by-products for soil regeneration have also been incorporated.
The results obtained from this research will be useful to collaborate in the governance of the implementation of the European 'Carbon Farming' Strategy. These solutions would provide a common framework for the entire national territory, and the rest of the European regulations, thereby demonstrating the potential of Mediterranean rainfed agriculture to play a significant role as a tool for climate change mitigation, as a carbon sink and as a supplier of ecosystem services. The benefits obtained from this project translate into agricultural tools for climate change mitigation and adaptation through, for example, the fight against desertification, biodiversity conservation and socio-economic benefits, which would curb rural depopulation, in line with meeting the demographic challenge.
This study formed part of the AGROALNEXT programme and was supported by MCIN with funding from European Union Next Generation EU (PRTR-C17.I1) and by Fundación Séneca with funding from Comunidad Autónoma Región de Murcia (CARM).
How to cite: Martínez-López, S., López-Torres, M., Motos-Alarcón, M. I., Baena-Navarro, N., Núñez-Gómez, V., Martínez-Sánchez, M. J., Esteban-Abad, M. D. L. Á., Tudela-Serrano, M. L., El-Jamaoui, I., Hernández-Cordoba, M., and Pérez-Sirvent, C.: Regenerative agriculture as a tool for combating climate change in semi-arid Mediterranean regions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13636, https://doi.org/10.5194/egusphere-egu25-13636, 2025.
AquaCrop is a relatively simple crop model with a wide range of applications at the point, field, and regional to continental scales. Its four main assets, distributed by FAO (https://www.fao.org/aquacrop/en/), are: (i) the standard program with a graphical user interface (GUI), (ii) the open-source version-controlled Fortran90 code available on GitHub, (iii) the stand-alone programs for Windows, macOS, and Linux, and (iv) its integration into systems for efficient regional-scale modeling, satellite-based data assimilation, and climate impact simulations. Specifically, a parallelized Python wrapper is available to run the stand-alone program, and the Fortran90 code is integrated into NASA’s Land Information System Framework (LISF).
This poster introduces AquaCrop's four assets and focuses on two regional-scale applications in Europe. First, we demonstrate the use of the parallelized Python wrapper in the context of a climate impact study, where we evaluated current and future maize yields. AquaCrop simulations were performed at a coarse spatial resolution (0.5°) to assess future changes in yields, and yield gaps (difference between actual and potential yield, without stresses). Second, the use of AquaCrop within NASA’s LISF is presented through a data assimilation experiment, in which AquaCrop simulations were performed at a 0.1° resolution. A generic type of C3 crop was used over the entire domain, and the crop stage lengths were parametrized using the VIIRS global land surface phenology. The uncertainty in simulations was assessed by perturbing meteorological inputs and soil moisture in the upper soil layers. To correct plant water stress, SMAP-enhanced surface soil moisture observations (9-km resolution) were assimilated using an ensemble Kalman filter. Results highlight (i) the need for careful mapping between AquaCrop-simulated and satellite-retrieved soil moisture and (ii) how small updates in soil moisture can propagate to significant changes in biomass development.
How to cite: Busschaert, L., De Lannoy, G., Raes, D., de Roos, S., Heyvaert, Z., Mortelmans, J., Scherrer, S., Van den Bossche, M., Kumar, S., Fereres, E., Garcia-Vila, M., Steduto, P., Hsiao, T., Heng, L., Salman, M., Eun, J., Deketelaere, V., and Bechtold, M.: AquaCrop assets and regional applications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16383, https://doi.org/10.5194/egusphere-egu25-16383, 2025.
Agricultural drainage systems have been widely implemented to enhance crop productivity by managing excess water. However, with increasing weather extremes, including prolonged droughts and heavy precipitation, drained areas face new challenges, including the need for irrigation and a critical reassessment of water retention capabilities. Despite the importance of these systems, the extent of drained agricultural land in Austria, particularly in Lower Austria, remains largely unknown. Therefore, quantitative knowledge about the agrohydrological potential of drainage water management in the complex landscapes of Austria are urgently demanded.
This study aims to estimate the volume of water discharged through existing drainage infrastructure in agricultural regions of Lower Austria. By providing a foundational dataset, we seek to quantify the scale of drainage and evaluate its impact on soil water retention. The approach involves a two-step process. First, potentially drained agricultural areas are being identified by using existing resources such as the Austrian soil survey, cadastral soil assessments which provide spatial information on slope data, soil types, and land use.
Secondly, a raster-based water balance model is employed, using meteorological data and literature-based assumptions that attribute certain fractions of total runoff to drainage discharge. The model produces monthly estimates of drainage, emphasizing water retention beyond the vegetation period. These results are then upscaled to the identified drained areas.
Future repetitions of the model will incorporate increasing complexity, including detailed soil parameters and refined hydrological modelling techniques, such as the SWAP model. However, even initial estimations provide critical insights and serve as a starting point for understanding the interplay between drainage systems, water retention, and potential management strategies. This research underscores the importance of rethinking water management practices in agricultural systems to adapt to climate-induced challenges and improve sustainability.
How to cite: Fischer, K., Weninger, T., Hussin, A., Brunner, T., and Strauss, P.: Assessing Water Retention Potential in Agricultural Drainage Systems in Lower Austria, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16434, https://doi.org/10.5194/egusphere-egu25-16434, 2025.
Full-Bayesian multi-level models for crop phenology in Germany
Friedrich Busch – Potsdam Institute for Climate Impact Research
Effective adaptation of agriculture to climate change requires detailed insights into all components of the agricultural system. Understanding the phenological development of crops is crucial not only for making informed management decisions, such as the timing of fertilizer or pesticide application and harvest but also for assessing future weather-related risks. With climate change, the timing and duration of phenological phases are expected to shift, and the likelihood of weather extremes during these phases may increase. Therefore, comprehensive phenological models with robust representations of uncertainties are essential.
Most current phenological models rely primarily on temperature-driven development units to predict crop phenology while neglecting other potential predictors. Since phenological observations are often limited, data is typically pooled to obtain seemingly robust parameter estimates. This structural decision, in combination with neglect of input data uncertainty, can lead to overconfidence in parameter estimates.
Hierarchical Bayesian models can address these issues. By employing a multi-level interpretation of the data (partial pooling), parameter estimates for varying groups within the data can be improved. In phenological data, one critical group level is the cultivar level, which is often omitted due to the limited availability of such data. For historical phenological observations of maize grown in Germany, cultivar data is partially available. To maximize the use of this data and minimize bias caused by missing information, a data imputation scheme is applied to reconstruct missing cultivar data. Subsequently, a full Bayesian statistical phenology model is calibrated, incorporating cultivar information and individual farm location as hierarchical levels.
Since phenological observations are typically collected by the local farmers, based on visual judgment, considerable uncertainty is inherent in the data. Incorporating this uncertainty into the model structure allows for more realistic parameter estimates. Furthermore, enhancing the development unit concept by incorporating additional predictors, such as radiation and soil moisture alongside temperature, has the potential to reduce unexplained variance in the data.
Model comparison and evaluation of the trade-off between predictive power and complexity are conducted using information criteria such as WAIC and Pareto-smoothed importance sampling. This work builds on recent advances in hierarchical Bayesian phenological modeling, providing new insights into key driving factors and relevant model structures. The models are developed using the Stan programming language, optimized for Bayesian analysis, and employ state-of-the-art Bayesian parameter sampling algorithms. In conjunction with climate scenarios these models can be used to estimate future changes in the phenological development of crops.
How to cite: Busch, F.: Full-Bayesian multi-level models for crop phenology in Germany, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18241, https://doi.org/10.5194/egusphere-egu25-18241, 2025.
In the Mediterranean region, viticulture is challenged by climate change which is increasing the frequency and severity of summer drought events. Under limited water availability conditions, controlling plant hydraulics and gas exchanges is crucial for crop productivity. Functional anatomical traits at the leaf and wood levels play a fundamental role in the capability of acclimation to environmental stresses. Thus, understanding how environmental factors and cultivation practices influence such traits is fundamental, given that they establish the limits of physiological acclimation capability.
Within this framework, this study aimed to evaluate if anatomical traits at the leaf and wood levels are differently harmonized when vines are cultivated under various treatments of soil and canopy management, with possible consequences on eco-physiological behavior, growth, and productivity. The study was conducted in a vineyard at the Feudi di San Gregorio winery premises (Southern Italy), where vines of the 'Greco' cultivar were cultivated under three treatments of soil management (cover crops, natural coverage, and soil tillage) and two types of canopy management (double guyot and double guyot flipped) over a period of three years. Leaf and wood anatomy were analyzed through light and epi-fluorescence microscopy to quantify functional anatomical traits linked with the efficiency of gas exchanges and water flow. To better interpret the relations among wood anatomical traits, inter- and intra-annual environmental variability, and cultivation management, the knowledge of the precise timing of wood formation is fundamental. Therefore, xylogenesis analysis was applied too, by collecting microcores biweekly from the main stem, in order to model wood growth dynamics and relate them to climate variables.
The overall data analysis showed the degree of plasticity of the ‘Greco’ cultivar at the structural level and suggested that the combination of traits at different organ levels may influence the vines’ response to climate change also mediated by pedo-climatic and cultivation conditions.
How to cite: De Micco, V., Petracca, F., Balzano, A., Damiano, N., Vitale, A., Erbaggio, A., Savo Valente, I., Amitrano, C., Merela, M., Cirillo, C., and Bonfante, A.: Harmonization of functional anatomical traits at the leaf and wood levels in grapevine in response to different soil and canopy management, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18905, https://doi.org/10.5194/egusphere-egu25-18905, 2025.
Precise soil spatial identification and characterization is crucial for optimizing vineyard management and enhancing grape quality. Various approaches exist for characterizing spatial soil variability, all aimed at zoning and identifying areas that, despite experiencing the same climate, exhibit different crop responses and therefore require differentiated management. However, the complexity of soil-plant interactions and the dynamic nature of soil properties over time necessitates the optimization of existing zoning methodologies. For instance, electrical conductivity (EC) mapping is a common technique, but relying on single-date measurements often fails to capture the full extent of spatial and temporal soil variability, even within a single growing season. Furthermore, commonly used electromagnetic induction (EMI) instruments operate at multiple frequencies to analyze different soil depths, making it challenging to directly relate these measurements to the specific soil volume explored by plant roots. Focusing on a well-defined soil depth, even if coarsely related to the root zone, would be more relevant for plant-soil interaction studies. Identifying the optimal period for characterizing soil spatial variability is therefore a key objective.
In this context, within the Agritech National Research Center project (https://agritechcenter.it/it/), we study the use of multi-temporal EC data, acquired with a GF Instruments CMD MiniExplorer 6L, for delineating functional homogeneous zones within an Aglianico DOC vineyard at Tenuta Donna Elvira, Grottoni (AV), Italy. The CMD MiniExplorer 6L, capable of measuring EC at up to nine depths within 2 meters by combining its horizontal and vertical dipole configurations, provided detailed soil information.
EC data were collected over five distinct days spanning from April to late August, capturing seasonal soil moisture variations. Concurrently, multi-spectral imagery was acquired using a DJI Phantom 4 RTK drone across a broader timeframe from April to late October. Normalized Difference Vegetation Index (NDVI) values were derived from the drone imagery to assess canopy vigor and variability.
A k-means clustering approach was applied to the daily EC datasets, exploring various depth combinations to generate 36 distinct clustering outputs for each acquisition date. This multi-depth approach allowed for a comprehensive assessment of soil variability at different scales. The resulting EC-derived clusters were then compared with the mean NDVI values extracted for each cluster. This comparison aimed to evaluate the relationship between soil electrical properties and vine vigor, as reflected by NDVI.
The analysis revealed a strong correlation between EC-derived clusters and NDVI, demonstrating the effectiveness of EMI measurements for differentiating soil properties relevant to vineyard performance. The study also highlighted the influence of acquisition timing on the efficacy of soil classification, identifying optimal periods and depth configurations for maximizing the differentiation of functional zones. This multi-temporal, multi-depth approach provides valuable insights for precision viticulture, enabling targeted management practices based on spatially explicit soil and canopy information. The results contribute to a better understanding of soil-vine interactions and offer a practical methodology for efficient vineyard zoning.
How to cite: Vitale, A., Accomando, F., Buonanno, M., Cascón, R. G., and Bonfante, A.: Multi-Temporal Electrical Conductivity and NDVI Analysis for Vineyard Functional Zone Mapping, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19576, https://doi.org/10.5194/egusphere-egu25-19576, 2025.
Climate change and urbanisation imposes substantial challenges on the agricultural sector, leading to various environmental and food security impacts. At the same time, there is a growing demand for high-quality, year-round, fresh vegetables which drives water and natural resources overexploitation. To mitigate these pressures, high-intensity cultivation strategies such as hydroponics and controlled environment farming systems are becoming more popular. In this context, given their substantial nutritional and culinary properties, wild edible vegetables are receiving renewed attention. Considering this background, here we investigate the impact of (a) photoperiod and (b) light intensity on yield performance of the wild edible green Scolymus hispanicus L (Asteraceae), wild relative of the domesticated globe artichoke (Cynara cardunculus var. scolymus), in indoor cultivation. Four treatments were applied including (a) a long photoperiod (16 hours of light and 8 dark), (b) short photoperiod (8 hours of light and 16 dark), (c) a low light intensity (40 μmol m-2 s-1) and (d) high light intensity (240 μmol m-2 s-1), using LEDs (Samsung SMD2835, Honglitronics) at a distance of one meter above the crop. Treatments were conducted in four growth chambers with adjustable photoperiod and light intensity regimes and constant temperature and air humidity levels. In each growth chamber, 15 Scolymus hispanicus L. plants were transplanted into 10 L pots and arranged on 3 gutters at a density of 9 plants m-2. Plants were fertigated daily (modified Hoagland nutrient solution), each with an individual emitter at a flow rate of 0.4 - 0.7 L plant-1 day-1. Results indicate that long photoperiod treatment was associated with increased rosette diameter (59.9±1.8 cm), and root fresh and dry weight (31.35±2.19 and 3.65±0.4 g, respectively) while high light intensity treatment increased shoot fresh and dry weight (118.58±6.34 and 7.55±0.38 g, respectively) and edible root hardness-firmness (1288.72±32.47 g), 90 days after transplant. Based on these results, we conclude that photoperiod and light intensity optimal management can increase marketable yield and quality traits of the wild crop Scolymus hispanicus L., in soilless indoor farming systems.
This work is supported by Optimus project [Grant Agreement ATTΡ4-0356837] with the co-funding of Greece and the European Union.
Reference
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Papadimitriou, Dimitrios M., et al. "Effect of moderate salinity on Golden Thistle (Scolymus hispanicus L.) grown in a soilless cropping system." Scientia Horticulturae 303 (2022): 111182.
Voutsinos-Frantzis, O.; Karavidas, I.; Liakopoulos, G.; Saitanis, C.; Savvas, D.; Ntatsi, G. Can Long Photoperiods Be Utilized to Integrate Cichorium spinosum L. into Vertical Farms? Biol. Life Sci. Forum 2023, 27, 8.
How to cite: Papadimitriou, D., Moschou, C., Louloudakis, I., Sabathianakis, M., Christoforakis, I., Livas, I., Daliakopoulos, I., and Manios, T.: Photoperiod and Light Intensity Impact on Wild Edible Vegetables Performance: From Controlled Environment Agriculture to Crop Resilience, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19862, https://doi.org/10.5194/egusphere-egu25-19862, 2025.
Sweet potato (Ipomoea batatas) is an important crop with moderate tolerance to water stress. Understanding its antioxidant properties and nutritional content under various environmental stressors is vital for optimizing their nutritional value and resilience. Antioxidants like carotenoids, anthocyanins, and polyphenols are health benefits of sweet potatoes. Although previous studies have examined the nutritional components of sweet potato leaves and roots, comparative analysis of antioxidant activity and nutritional content among different cultivars under environmental stress conditions remains limited. Our study examined the antioxidant properties and nutritional content of three sweet potato cultivars, Georgia Jet, Jasmin, and Line 11-88 (recently released by LSU AgCenter) under various environmental stresses including Control (100% Nitrogen +100% water), Nitrogen stress (60% Nitrogen + 100% water), Drought stress (100% Nitrogen + 60 water), and the Combined stress of nitrogen and water (60% Nitrogen + 60% water). Nutritional content was quantified across cultivars and treatments in the leaves. Anthocyanin content varied significantly across cultivars and treatments. Jasmin had the highest response under both nitrogen and combined stresses, Line 11-88 highest under control, and Georgia Jet remained relatively low and stable across all treatments. Flavonoid content was not significantly affected by stress treatments but was higher in Georgia Jet and Jasmin compared to Line 11-88. Polyphenol content was highest in Jasmin under Control and Combined stress but remained consistent across treatments for Georgia Jet and is generally lower content for Line 11-88. The results suggest that Jasmin is the most promising cultivar in terms of antioxidant properties, making it a potential source of nutritional and functional food in sweet potato leaves.
This study explores how nitrogen and water availability variations impact sweet potato leaves' nutritional quality. Our study shows that nitrogen and water as limiting factors can cause an increase in the nutritional content of sweet potato leaves.
How to cite: Mano, S., Issaka, D. S., Shibu, G., Rachmilevitch, S., and Tietel, Z.: Cultivar-Specific Responses of Sweet Potato Leaf Nutritional Quality to Nitrogen Application Rate and Water Availability, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20555, https://doi.org/10.5194/egusphere-egu25-20555, 2025.
Soil organic matter (SOM) plays a significant role in modulating soil water and therefore irrigation scheduling. This relationship is especially vital in arid regions like the Mediterranean, where both SOM and water resources are scarce and increasingly threatened by the climate crisis. Soil amendments based on agricultural biowaste (e.g., compost) or byproducts of pre-existing processes (e.g., biochar) offer a cost-effective solution to boost SOM levels. However, because of this less strictly managed production process, the variability in their properties and their long-term effects on soil hydraulic behaviour, particularly after weathering, remain poorly understood. Here we compare the effect of 3 soil amendment treatments to the hydraulic properties of clay loam soil: olive tree pruning compost at 1% (C1B0), biowaste-based biochar from at 1% (C0B1), and compost-biochar mix at 1% (C1B1) against a control treatment (C0B0). Amendments were incorporated in the soil at the prescribed rates to a depth of 15 cm. To quantify the impact of the amendments in hydraulic properties of soil such as clay loam we use a modification of the hydraulic property (HYPROP2, Meter, USA) analyser (Daliakopoulos et al., 2021) after application, and 6 months after application. The assessed van Genuchten parameters are used to estimate the movement of water soil in the soil profile with HYDRUS-1D (Kool & Van Genuchten, 1991) using two distinct profiles. Simulations were validated through irrigation experiments using in-situ soil moisture measurements at 2 depths (10 and 30 cm). As shown by changes Van Genuchten parameters, results show that, compared to compost applications, biochar had a more pronounced and lasting positive effect regarding soil porosity and structure, also decreasing hydraulic conductivity and increasing field capacity. These results highlight the potential of biochar and it’s mixes to improve soil water status and contribute to the reversal of desertification processes in arid Mediterranean soils.
Acknowledgements
This work has received funding from REACT4MED: Inclusive Outscaling of Agro-Ecosystem Restoration Actions for the Mediterranean. The REACT4MED Project (grant agreement 2122) is funded by PRIMA, a program supported by Horizon 2020. MP was supported by ERASMUS+ KA131 mobility (ID 1174266). Authors IND and AK thank MINERVA Ltd. and research project “Assessment of climate change impacts on olive oil production and implementation of sustainable agricultural adaptation practices in Greece” for its support.
References
Daliakopoulos, I., Papadimitriou, D., & Manios, T. (2021). Improving the efficiency of HYPROP by controlling temperature and air flow. EGU General Assembly Conference Abstracts, EGU21--13082.
Kool, J., & Van Genuchten, M. T. (1991). HYDRUS: One-dimensional Variably Saturated Flow and Transport Model, Including Hysteresis and Root Water Uptake, Version 3.31. US Salinity Laboratory.
How to cite: Daliakopoulos, I., Gaitanakis, M., Pietersen, M., Louloudakis, I., Papadimitriou, D., Galliou, F., Yang, X., and Koutroulis, A.: Assessing Biowaste-based Amendments for Enhancing Soil Hydraulic Properties in Arid Mediterranean Soils, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21214, https://doi.org/10.5194/egusphere-egu25-21214, 2025.
Posters virtual: Tue, 29 Apr, 14:00–15:45 | vPoster spot 3
EGU25-14160 | ECS | Posters virtual | VPS14
Integrating Proximal Sensing, high-resolution Imagery, and Machine Learning for Field-Scale Soil Salinity Mapping in Semi-Arid RegionTue, 29 Apr, 14:00–15:45 (CEST) | vP3.16
Soil salinity is a major environmental challenge that reduces agricultural productivity and degrades soil health, especially in arid and semi-arid regions. Conventional soil salinity assessment methods involve extensive manual labor and are time-consuming In this study, we explored alternative approaches by using a combination of proximal sensing data (i.e., electromagnetic (EM) induction instruments, EM 38-MK2) with two very high-resolution multi-spectral and -sources imagery (i.e., a UAV (Unnamed Aerial Vehicle) and PlanetScope (PS)), topographic attributes, and machine learning methods to achieve field-scale soil salinity mapping under data-scarce conditions. To do so, an initial set of 26 topsoil samples (0–5 cm) were collected from a saline field in the semi-arid area of Sehb El Masjoune in Southern Morocco. and their Electrical conductivity (EC, a proxy of salinity) was determined at the lab. Then, proximal sensed data from EM38 were collected along the same field and measured apparent soil electrical conductivity (ECa – dS/m) was correlated with measured topsoil EC. We used proximal sensing technology to generate 500 EC (electrical conductivity) observations for spatialization, thereby creating a robust dataset for training four machine learning models: partial least squares regression (PLSR), support vector machine (SVM), random forest (RF), and an ensemble (stacked) model. Among these models, the RF and ensemble approaches delivered the highest accuracy, with RF outperforming all others. Performance assessments indicated that PlanetScope data achieved R² = 0.91 and RMSE = 3.47, while UAV data showed R² = 0.89 and RMSE = 3.83. These findings underscore that integrating multisource data, even in data-scarce environments, enhances reliability and robustness in soil salinity mapping at the field scale. Our results highlight a cost-effective, high-precision strategy for characterizing saline and sodic soils, offering valuable insights for targeted reclamation and management interventions in arid and semi-arid regions. We conclude that the used approach not only contributes to the scientific understanding of soil salinity dynamics but also provides practical implications for sustainable land management and agricultural planning. The research highlights the potential of combining cutting-edge technology with environmental predictors to address critical global issues.
How to cite: Chindong, M. J., Ouzemou, J.-E., Laamrani, A., El Battay, A., and Chehbouni, A.: Integrating Proximal Sensing, high-resolution Imagery, and Machine Learning for Field-Scale Soil Salinity Mapping in Semi-Arid Region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14160, https://doi.org/10.5194/egusphere-egu25-14160, 2025.
EGU25-15982 | ECS | Posters virtual | VPS14
Meadow intensification, a biodiversity approachTue, 29 Apr, 14:00–15:45 (CEST) | vP3.17
Mountain livestock farming relies on meadows, by providing pasture in autumn and spring and providing hay for the winter. They are composed by different plant species from various botanical families, being a biodiverse ecosystem with high resilience.
We can classify them according to their intensification, depending on its fertilization strategy and livestock load. The most intensive meadows are fertilized by inorganic fertilizer and has high livestock load, semi extensive meadows are fertilized by manure and has lower livestock load, whereas extensive meadows are rarely fertilized and has low livestock load.
In this study, 12 meadows from the central Spanish Pyrenees where analysed, 4 meadows of each type for 2 years. Production was higher in semi extensive meadows, due to its organic fertilization, and extensive meadows had the lowest production. Looking at the quality of the hay, intensive and extensive meadows had similar protein content, being significantly higher than in semi extensive meadows. Fiber was higher in extensive meadows and the lowest was found in intensive meadows.
We used Sannon index to address biodiversity. There were significant differences between each meadow type, having extensive meadows the highest levels and intensive meadows the lowest.
High biodiversity can be kept even in high productive meadows, as it’s shown in semi extensive meadows, although they have lower protein content. Intensification practices are thought to increase productivity, with a cost of reducing biodiversity, but this study shows that lower intensive practices can have higher production.
How to cite: Jarne Casasús, A., Reiné Viñales, R., and Usón Murillo, A.: Meadow intensification, a biodiversity approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15982, https://doi.org/10.5194/egusphere-egu25-15982, 2025.
