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 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 (C_org) and its extractable fraction (C_ext), microbial biomass (C_mic), 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

Appolloni, Elisa, et al. "Beyond vegetables: effects of indoor LED light on specialized metabolite biosynthesis in medicinal and aromatic plants, edible flowers, and microgreens." Journal of the Science of Food and Agriculture 102.2 (2022): 472-487.

Bantis, F. Light Spectrum Differentially Affects the Yield and Phytochemical Content of Microgreen Vegetables in a Plant Factory. Plants 2021, 10, 2182.

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.