Search Results (1,880)

Mediterranean organic viticulture requires sustainable pest management strategies that leverage local soil biodiversity. This study isolated endemic entomopathogenic fungi from vineyard soils in Nemea, Greece, using a dual-insect baiting system with Tribolium confusum and Sitophilus spp. The recovered isolates caused complete mortality in bait insects, with mycelial emergence from 93.75% of cadavers. DNA sequencing of the ITS1 region identified the recovered isolates as Purpureocillium lilacinum. Phylogenetic analysis revealed that Nemea isolates (TD and TM series) form a monophyletic clade with 100% bootstrap support, showing distinct genetic divergence from the reference strain P. lilacinum NRRL 895—evidence of a unique “microbial terroir.” Virulence assays demonstrated species-dependent mortality against stored-product pests: Sitophilus granarius was the most susceptible (76.7% mortality; LT₅₀ = 1.9 days), followed by Sitophilus zeamais (61.1%; LT₅₀ = 2.7 days), Tribolium confusum (56.7%; LT₅₀ = 2.8 days), and Sitophilus oryzae (50.0%; LT₅₀ = 3.3 days). Mycosis confirmation (65–83%) and 0% control mortality confirmed pathogenicity. As locally adapted biological control agents, these endemic P. lilacinum strains are highly suitable for protecting crops from major insect pests. Full article

Alfalfa (Medicago sativa L.) is widely recognized as a major forage crop, yet its role as a multifunctional biological input in sustainable horticultural production remains underexplored. This review evaluates alfalfa as a biological nitrogen source, organic fertilization resource, and biofertilizer-supporting crop within vegetable, medicinal, and perennial horticultural systems. Due to its high capacity for biological nitrogen fixation, alfalfa can supply substantial amounts of plant-available nitrogen, reducing dependency on synthetic fertilizers and supporting environmentally sound nutrient management. When used as green manure, cover crop, intercrop, mulch source, compost feedstock, or processed organic fertilizer, alfalfa enhances the soil organic carbon (SOC), improves soil structure, and increases the water-holding capacity properties particularly critical in intensive horticultural production. Higher SOC levels also contribute to the improved tolerance of horticultural crops to drought and heat stress through enhanced soil moisture retention and rhizosphere buffering. Alfalfa-based organic inputs stimulate rhizosphere microbial biomass, enzymatic activity, and functional genes associated with nitrogen cycling, strengthening plant–microbe interactions that underpin biofertilizer effectiveness. Evidence from vegetable and perennial systems indicates that alfalfa-derived amendments and rotations increase soil nitrogen availability, support yield stability, and improve soil health over the long-term. In orchards and vineyards, alfalfa cover cropping contributes to carbon sequestration, erosion control, and enhanced soil biological functioning. Overall, alfalfa emerges as a strategic species for integrating organic fertilization and biofertilizer-based approaches into modern horticultural systems, supporting reduced mineral fertilizer inputs while sustaining productivity, soil health, and environmental quality. Full article

Autonomous navigation in agricultural environments remains a key challenge for the deployment of mobile robots in precision viticulture. In this paper, we present the numerical and experimental validation of a LiDAR–inertial navigation and mapping framework for mobile robots operating in vineyard-like scenarios. A realistic vineyard simulation environment reproducing the geometric structure of vine rows is first developed to evaluate the performance of the proposed framework, considering multiple metrics including mapping time, speed stability, path tracking error, and point cloud reconstruction density. Then, the proposed approach is tested in a real vineyard using a Scout 2.0 mobile robot. Numerical and experimental results demonstrate the feasibility of the navigation and mapping strategy and its robustness during extensive repeated tests in the field. Full article

Viticulture and wine production uses approximately 30% of the land occupied with permanent crops in the EU. In countries in the southern part of the EU, this share is even higher, reaching up to about 80% in France and 55% in Romania. In recent years, the development of grape and wine production has been under pressure from climate and market changes. Competitiveness and value creation capacity are among the key factors in the sustainability of national production and the viability of wine regions. This study examines wine production competitiveness in the countries of the southern EU region within the European Single Market, comparing Bulgaria with leading producers—France, Italy, and Spain—and neighboring Romania. A set of production and trade indicators was applied, and the overall assessment was derived through a composite competitiveness index that simultaneously captures market performance and value creation potential. The results indicate a high level of competitiveness in the three leading European wine-producing countries, albeit with differences in the realization of their value creation potential. Bulgaria and Romania exhibit relatively low levels of competitive positioning, which could be improved through investments in technology and innovation, the implementation of collective marketing strategies, and the development of a national sectoral brand. Full article

Invasive leafhopper species Arboridia kakogawana, Tautoneura polymitusa and Erasmoneura vulnerata were investigated for distribution, routes of introduction and population genetics in the viticultural regions of Serbia. Surveillance traps were set up in vineyards and natural habitats across 26 administrative districts between 2017 and 2025. The mitochondrial cytochrome oxidase subunit I (COX1) and a nuclear wingless gene (Wg) were used in phylogenetic analysis. Arboridia kakogawana showed a significant invasive potential with its populations sampled from 19 districts. A single COX1 haplotype detected was identical with specimens from Bulgaria and Georgia suggesting a shared origin and probable invasion route via the Black Sea region. Tautoneura polymitusa expressed limited invasiveness, predominantly with northern distribution and very low population density. One detected COX1 haplotype shared identity with samples from Hungary, indicating their joint origin. Erasmoneura vulnerata has the greatest invasive potential, detected in all inspected districts. Eighteen COX1 haplotypes clustered into a monophyletic group. Three lineages were separated but morphologically indistinguishable, with a 7.5 to 9.5% average divergence between the groups. Analysis of Wg sequences led to the discovery of only two haplotypes, confirming their common ancestry. Diversity of Serbian COX1 haplotypes entirely reflected genetic variability in the native range, indicating a complex scenario of E. vulnerata introduction from multiple sources with admixed genotypes, including co-introduction of uncovered cryptic lineages. Full article

Climate change is progressively altering the thermal environment of European agriculture, with direct consequences for high-value perennial crops such as olive (Olea europaea L.) and grapevine (Vitis vinifera L.). Although the Growing Degree Days (GDD) index is widely applied to characterize crop thermal requirements, no systematic evidence exists on the actual GDD values accumulated at the locations where these crops are currently grown across Europe. This study introduces a “reverse agroclimatology” approach that anchors GDD calculations exclusively to olive grove and vineyard areas identified in the Corine Land Cover (CLC) dataset for five reference years (1990, 2000, 2006, 2012, and 2018), using ERA5-Land reanalysis daily temperature data as the climatological input. For each CLC reference year, GDD was computed for olive cultivation (T_base = 7 °C, January–May) and viticulture (T_base = 10 °C, April–October) exclusively over registered cultivation pixels, and per-country means were subjected to linear regression trend analysis (p < 0.05). For olive cultivation across 11 Mediterranean countries, statistically significant positive GDD trends were detected in 7 countries, with long-term (1985–2023) country means ranging from 476.2 GDD in France to 1214.3 in Cyprus, indicating that we can revise the known GDD thresholds. The first appearance of olive cultivation in Slovenia’s 2012 CLC dataset, with a median of 546.5 GDD, provides land use-mapped evidence of a spatial displacement of cultivation boundaries. For vineyard cultivation across 22 European countries, significant positive trends were identified in 18 countries, with warming rates reaching 19.25 GDD yr⁻¹ in Turkey, 15.83 GDD yr⁻¹ in Albania, and 14.89 GDD yr⁻¹ in Bosnia and Herzegovina. Mediterranean and Balkan vineyards already exceed the classical 2000 GDD threshold of viticultural suitability across all reference years. In contrast, central and northern European registered vineyards operate below it, though their warmest sites are increasingly approaching or crossing it in the most recent periods. The cultivation-anchored GDD framework, built on openly available data and a fully reproducible R-based pipeline, provides a practical and updatable tool for monitoring the evolving thermal conditions of European olive and wine production under ongoing climate change. Full article

A virtual training environment offers clear advantages for agricultural robotics. It provides a safe setting in which perception, navigation, and control algorithms can be evaluated without risking damage to either the robot or the crop. It also supports efficient data generation: large volumes of training data can be collected under diverse environmental conditions that would be costly, slow, and often season-dependent in real-world deployments. This broader variability improves model adaptability, reduces the risk of overfitting, and leads to more robust operation. In this paper, we argue that digital twin technology should therefore be understood not merely as a passive mirror of a physical robot, but as an active training environment in which multiple sensor-related subprocesses can be developed, tested, validated, and refined jointly. This paper is based on our experiences with digital twin technology used in the development of a vineyard robot, including a self-driving rover, sensor simulation, procedural map generation, and agriculture-specific movement models. Our contribution is threefold: we reinterpret the digital twin as a training space, propose a layered framework for training agricultural robots in virtual environments, and explain why agriculture is a particularly strong use case, given variable field conditions, expensive real-world experimentation, and persistent labor scarcity. To validate this framework, we present the simulation-based evaluation of an autonomous reinforcement learning agent. The agent has been trained entirely in this virtual environment, which successfully navigated to 155 out of 161 target points in a simulated vineyard demonstration environment. Full article

Smart technologies and artificial intelligence (AI) are increasingly reshaping viticulture by improving vineyard monitoring, supporting data interpretation, and enabling more targeted management decisions. This review examines how sensor networks, remote sensing, machine learning, deep learning, and decision-support systems contribute to more sustainable vineyard management and the production of high-quality grapes. Particular attention is paid to applications in grapevine stress monitoring, disease and pest detection, irrigation and nutrient management, yield estimation, grape quality prediction, and emerging automation. The review also highlights the main barriers that still limit broader adoption in commercial vineyards, including data quality issues, limited transferability across sites and seasons, interoperability gaps, vendor lock-in, and concerns related to governance, privacy, and cybersecurity. Although these constraints remain significant, the available evidence shows that smart viticulture can improve resource-use efficiency, support more precise interventions, and help growers respond more effectively to environmental variability. Future progress will depend on stronger validation under field conditions, better integration into practical vineyard workflows, interoperable digital infrastructures, and decision-support tools that are transparent, reliable, and useful for end users. Full article

Botryosphaeria dieback, caused by species of Botryosphaeriaceae, causes significant economic losses by infecting pruning wounds in vineyards and fruit trees. Previous studies have shown that pruning wounds constitute the main entry point for Botryosphaeriaceae and that isolates from different fruit hosts can infect these tissues regardless of origin. This study assessed the temporal susceptibility of Vitis vinifera pruning wounds in four cultivars (Cabernet Sauvignon, Malbec, Merlot, and Sauvignon Blanc) to six Botryosphaeriaceae isolates from different fruit hosts (grapevine, apple, blueberry, and walnut) under greenhouse and field conditions in central Chile. Pruning wounds were inoculated at 1, 15, 30, 45, and 60 d after pruning, and lesion length and wound infection (%) were evaluated. Both variables decreased with increasing wound age in greenhouse and field trials. Wounds were most susceptible during the first 15 d after pruning, with a marked reduction thereafter, although susceptibility persisted up to 60 d. Neofusicoccum parvum and N. arbuti showed the highest aggressiveness. All isolates were able to infect pruning wounds regardless of host of origin. These results indicate that pruning wounds remain susceptible for an extended period and highlight the importance of considering both wound age and cross-host inoculum sources in disease management strategies. Full article

Phenolic compounds, essential for grape quality, are affected by environmental factors, including abiotic stressors such as hail. This study examined the impact of varying levels of natural hail damage on the physicochemical parameters, phenolic composition, and antioxidant capacity of Thompson seedless grapevines (Vitis vinifera L.) under Mediterranean climatic conditions. The research was carried out in a commercial vineyard in Greece during the 2015 growing season, following a major hailstorm. Three treatments were implemented: control (undamaged), moderate hail damage, and total hail damage. The results showed that pH levels and specific physiological parameters, including proline concentration, were significantly influenced across treatments. Detailed analysis revealed that the concentrations of phenolic compounds generally increased with greater hail damage, indicating enhanced antioxidant capacity and metabolic adaptation to natural hail-induced mechanical stress. Additionally, individual phenolic compounds, such as flavanols, hydroxybenzoic acids, and stilbenes, responded differently to hail damage, demonstrating complex regulatory mechanisms in grape metabolism. These findings underscore the importance of understanding grapevine biochemical responses to extreme weather events in the context of climate change, as changes in phenolic composition can directly affect grape quality. Full article

Soil surface moisture (SSM) is a critical indicator of agricultural drought, yet high-resolution projections under climate change remain scarce. This study develops a machine learning framework to predict and project SSM at 1 km resolution across five European Living Labs (LLs), encompassing vineyards, olive groves, and fruit tree systems. Historical Sentinel-1 SSM observations (2014–2024) were used to train ensemble models (Random Forest, XGBoost, ExtraTrees, LightGBM) incorporating climate variables, soil texture, topography, and land use. Tree-based models achieved R² values of 0.63–0.87. Vineyards showed the highest predictability (R² ≈ 0.87), reflecting their sensitivity to short-term atmospheric demand and surface water availability, whereas olive groves were the least predictable (R² ≈ 0.63–0.68), consistent with deeper rooting systems and greater drought buffering capacity. When forced with bias-corrected CMIP6 projections under SSP1-2.6 and SSP5-8.5 for 2041–2070, models indicate minimal changes under SSP1-2.6 but pronounced SSM declines of 8–24% under SSP5-8.5, with historically wetter regions experiencing the largest absolute losses. SHAP analysis confirmed precipitation and potential evapotranspiration as dominant predictors across all crops. This framework provides spatially explicit, crop-relevant SSM projections to support climate adaptation in European agricultural landscapes. Full article

The La Mancha region (a semi-arid area of southeast Spain) hosts the world’s highest concentration of vineyards and is also one of the regions with the largest areas devoted to almond tree cultivation. Viticulture and nut fruit trees (mainly almonds) are one of the region’s principal sources of economic revenue. The Two-Source Energy Balance (TSEB) model can assist management of water resources. A simplified version of the TSEB approach (STSEB) was previously tested in a vineyard and almonds to estimate sensible heat (H) and latent heat (LE) fluxes using a parallel scheme method based on the Monin–Obukov similarity theory (MOST). This study introduces a method based on Surface Renewal (SR) theory to partition the sensible heat flux using low-frequency measurements as input. The latter was friendlier than the parallel MOST method under unstable conditions and than the series SR and MOST methods. The objective was to compare the MOST and SR models within a parallel scheme method. During the 2014 and 2015 growing season, measurements were collected in a 4 ha row crop drip-irrigated Tempranillo vineyard. Hourly sensible heat flux measured by an eddy covariance (EC) system and evapotranspiration (ET) registered by a 9 m² monolithic large weighting lysimeter were used as a reference. ET estimates were obtained as a residual of the energy balance equation (known as the residual method) using three methods for estimating sensible heat flux, H_SR, H_MOST and H_EC, yielding ET_SR-RE, ET_MOST-RE and ET_EC-RE, respectively. For sensible heat flux, the index of agreement (IA expressed in %) for 2014 and 2015 was 93% and 83%, respectively, using SR, and 84% and 78%, respectively, for MOST. This represents a 6–10% improvement using SR. For evapotranspiration, the ET_SR-RE and ET_MOST-RE IA showed similar performance in both years (around 88%), while ET_EC-RE yielded the best results (92% and 89% for 2014 and 2015, respectively). In addition, half-hourly EC fluxes, during the growing season of 2017, were used as a reference in an almond orchard. The SR sensible heat flux performed better (IA = 93%) than MOST (IA = 86%) in this case, whereas for the latent heat flux, the residual method performed the best, resulting in an IA of 81% for SR and of 78% for MOST. Overall, SR performed better than MOST, particularly under unstable conditions with wind speeds above 1 ms⁻¹. Full article

Berry thinning is a fundamental operation in modern vineyard management, and future robotic thinning systems have the potential to reduce labor intensity and improve operational consistency. However, automated berry thinning under field conditions is still constrained by insufficient berry-level segmentation accuracy, difficulty in recognizing occluded berries, and high missed-detection rates for small berries. These limitations mainly arise from dense berry arrangements, severe mutual occlusion, and the subtle visual features of small targets. To address these challenges, this study developed a lightweight grape berry instance segmentation and thinning decision-support method based on YOLOv8n-seg. A two-stage knowledge distillation strategy, using Mask R-CNN and YOLOv8l-seg as teacher models, was combined with 30% backbone pruning to improve the recognition of occluded and small berries while maintaining model efficiency. Subsequently, the DBSCAN clustering algorithm was used to analyze berry centroid coordinates and equivalent diameters extracted from instance segmentation masks, thereby generating preliminary thinning-target recommendations based on local berry density and berry size. The model was trained and evaluated on a self-constructed dataset containing 330 valid grape bunch images collected in 2025 from Yongming Vineyard, Lin’an District, Hangzhou, Zhejiang Province, China. The results showed that the optimized YOLOv8n-seg model achieved a box $mAP50\text{-}95$ of 0.8945 and a mask $mAP50\text{-}95$ of 0.7910, with an inference speed of 119.19 $FPS$ and 3.26 M parameters on an NVIDIA RTX 3060 Laptop GPU. Compared with the original YOLOv8n-seg model, the optimized model improved mask $mAP50\text{-}95$ by 1.20 percentage points, increased inference speed by 71.79 $FPS$, and reduced the number of parameters by 2.38 M. These results indicate that the proposed method improves grape berry instance segmentation performance while achieving a favorable balance among segmentation accuracy, lightweight characteristics, and inference efficiency. The proposed framework provides an offline RGB-based visual perception and preliminary thinning decision-support method for future grape berry thinning robots. However, because the current dataset was collected from Shine Muscat grape bunches at the berry enlargement stage in a single vineyard using the same imaging setup, the results should be interpreted as preliminary evidence under the specific cultivar, growth stage, vineyard, and imaging conditions of this study. Further validation across different grape cultivars, growth stages, vineyards, production seasons, camera systems, embedded platforms, and real robotic thinning operations is still required. Full article

The valorization of agro-industrial residues and sewage sludge into value-added products through vermicomposting represents a promising strategy for nutrient recycling and waste reduction. This study evaluated the effects of aqueous extracts obtained from five vermicomposts (VC1-VC5) produced from different mixtures of vineyard and winery residues and sewage sludge on cucumber (Cucumis sativus L.) seedlings grown under in vitro conditions. The aqueous extracts (10%, w/v) were characterized in terms of pH, electrical conductivity, and total polyphenolic content, and applied to cucumber seedlings cultivated for 30 days under sterile and controlled in vitro conditions using commercially available peat pellets (Jiffy-7^®). Seedling development was monitored throughout the experiment, and morphological and biochemical parameters were assessed at the end of the 30-day assay. All extracts supported seedling development, with no evidence of phytotoxicity. The application of VC2 and VC4 extracts resulted in significant increases in fresh and dry weight, while VC2 led to higher chlorophyll and carotenoid contents. Conversely, VC3 and VC5 extracts were associated with slight reductions in growth parameters and photosynthetic pigment content. Correlation analysis suggested positive associations between biomass accumulation and chlorophyll content, and negative association between total polyphenolic content and stem growth. Overall, the results indicate that aqueous vermicompost extracts were not phytotoxic under the tested conditions, although their effects appear to depend on extract composition, highlighting the importance of feedstock selection for sustainable horticultural applications. Full article

This narrative review develops fermentation-oriented viticulture as an agronomic-oenological framework linking vineyard environment, management and must ecology to fermentation performance. The literature from 2010 to April 2026 was synthesized through structured searches in PubMed and Google Scholar, complemented by targeted searches in MDPI, Frontiers, Nature, ScienceDirect, OENO One, PNAS and European Union regulatory sources, with emphasis on 2020–2026 publications and retention of older foundational sources. Current evidence indicates that must microbiota is not a linear derivative of soil or berry surfaces, but a network outcome of connected habitats spanning the viticultural biotope and grapevine-associated biocenosis (soil, rhizosphere, phyllosphere, berry, insect, atmospheric and winery). Climate warming, drought, altered phenology, soil fertility, nitrogen nutrition, crop-protection programs and bio-based inputs jointly modify berry chemistry, yeast-assimilable nitrogen (YAN), microbial inocula and pre-fermentative selection pressures. The review distinguishes fermentation-oriented viticulture from descriptive microbial terroir by defining practical endpoints: fermentation onset and completion, sluggish or stuck fermentation risk, microbial stability, spoilage taxa, volatilome development and wine typicity. It also proposes operational indicators and a decision matrix for integrating vineyard and winery management. The framework supports future multi-vintage studies combining climate, soil, agronomic metadata, YAN, microbiome profiling and microvinification outcomes. Full article