Search Results (2,076)

Old vines represent long-lived viticultural systems in which genetic resources, environmental adaptation, traditional management, territorial identity, and cultural heritage have developed over time. Old vineyards preserve historical germplasm and traditional production systems and may provide valuable material for future climate adaptation. However, their viticultural and enological value cannot be attributed directly to chronological age because vineyard history, site, genotype, vine health, rooting conditions, and management frequently interact. This review evaluates old-vine systems across the Southern Hemisphere. Scientific evidence on genetic diversity, epigenetics, physiology, water relations, vine longevity, grape and wine composition, sensory identity, heritage, and conservation was reviewed. Current evidence is insufficient to attribute greater stress resilience or superior wine quality to vine age alone. Reliable comparisons between young and old vines require accounting for vineyard heterogeneity, vine replacement, pruning history, and uncertainty in planting dates. Resolution OIV-VITI 703-2024 provides a useful framework for classification and traceability. The value of old vines value is multidimensional and emerges from the interaction between biological longevity, terroir, genetic resources, and human management. Conservation should therefore integrate heritage recognition with rigorous characterization of age-related, environmental, genetic, and management effects. Full article

Excessive fertilization in grape production reduces profitability and harms the environment. A five-year field experiment and household survey in Xiangyun County, Yunnan, evaluated a whole-process optimized fertilization plan for Vitis vinifera ‘Red Globe’ (hereafter abbreviated as Red Globe Grapes) and its spatial diffusion. The optimized plan reduced N, P₂O₅, and K₂O inputs by 385.28, 298.65, and 154.02 kg ha⁻¹, increased yield by 18.4%, and raised net income by 41,574 RMB ha⁻¹. After five years, partial factor productivity of nitrogen (PFPN, an indicator of nutrient management performance used here to assess adoption at the farmer level)—a proxy for technical readiness—was highest in the core demonstration area and declined with distance. Spatial Durbin modeling showed that spillover effects attenuated beyond roughly 30 km, with an optimal promotion radius near 10 km and an effective promotion radius of 17.5 km. Farmer education generated positive indirect spillovers. Promotion intensity had a negative local effect but net positive spatial feedback. In the development area, adoption remained unstable without sustained support. Scaling optimized fertilization therefore requires differentiated extension strategies that leverage social learning among neighboring farmers. Full article

Brain tumour segmentation from magnetic resonance imaging requires the accurate delineation of the sub-regions under clinical constraints on computational resources. Deploying deep segmentation networks on edge hardware demands model optimisation that preserves accuracy while reducing complexity. This paper presents the deployment of a pruned RAAGR2-Net brain tumour segmentation model on the Xilinx ZCU104 FPGA using the Vitis AI 3.0 toolchain. The model was optimised through sensitivity-guided channel pruning, which suppresses the channels identified as redundant while maintaining segmentation stability. The pruned model was trained and evaluated on the BraTS 2019 dataset. At a pruning ratio of 0.1, the pruned model achieved Dice scores of 0.8578, 0.8131, and 0.8635 for tumour core, enhancing tumour, and whole tumour, respectively, compared to the scores of 0.8169, 0.7896, and 0.8424 achieved by the base model. The deployment further serves as a verification step, confirming that the optimised model successfully completed quantisation, compilation, and FPGA inference using the Vitis AI toolchain. Following INT8 post-training quantisation and compilation for the DPUCZDX8G accelerator, inference on the ZCU104 produced an average latency of 69.16 ms per sample and a throughput of 14.46 frames per second. These results demonstrate that sensitivity-guided channel pruning is compatible with FPGA deployment without requiring network restructuring. Full article

Polyphenols are plant secondary metabolites widely recognized for their antioxidant properties and potential health benefits. Grapevine leaves are a rich yet underexplored source of these bioactive compounds. In this study, caftaric acid, and predominant flavonol glycosides were characterized in leaves of seventeen grapevine genotypes by high-performance liquid chromatography, while total phenolic content (TPC) was determined using the Folin–Ciocalteu assay. In addition, the growth-promoting effect of a polyphenol-rich Vitis amurensis leaf extract on Lactiplantibacillus plantarum and its protective effect under H₂O₂-induced oxidative stress were evaluated. Both TPC and phenolic composition were strongly genotype-dependent, with TPC ranging from approximately 20 to 100 mg gallic acid equivalents (GAE) g⁻¹ dry weight (DW). Quercetin and kaempferol glycosides were the predominant flavonols, and quercetin-3-O-glucuronide, one of the most abundant derivatives, varied nearly tenfold among genotypes (approximately 2100–20,000 mg kg⁻¹ DW). The leaf extract of V. amurensis, the genotype with the highest TPC, significantly promoted the in vitro growth of L. plantarum in a dose-dependent manner, resulting in higher viable cell counts after 24 h. The extract also markedly enhanced bacterial survival under H₂O₂-induced oxidative stress. At 2 mM H₂O₂, no bacterial growth was detected in the absence of the extract, whereas extract-supplemented cultures maintained substantial growth and reached a viable cell count of 1.8 × 10⁸ colony-forming units (CFU) mL⁻¹ after 24 h. The phenolic patterns identified across the investigated genotypes provide a basis for selecting Vitis genotypes as sources of specific flavonol glycosides. Furthermore, our microbiological results provide preliminary evidence of the beneficial effects of V. amurensis leaf extract on L. plantarum and warrant further investigation of its potential functional applications. Full article

The increasing demand for sustainable and phytochemically enriched foods has encouraged the valorization of agricultural by-products as ingredients for beverage formulation. This study investigated the enrichment of grape juice with Vitis vinifera leaf extract and characterized the resulting phytochemical, antioxidant, volatile, and sensory profiles. The fortified juice was compared with non-enriched grape juice and a commercial sample. Samples were analyzed at production (t₀) and after 30 days of refrigerated storage (4 °C) for polyphenols, flavonoids, anthocyanins, carotenoids, tocopherols, and antioxidant capacity (ABTS, DPPH, and CUPRAC assays). Volatile organic compounds (VOCs), sensory properties, and microbiological stability were also evaluated. The fortified preparation showed higher concentrations of polyphenols, flavonoids, and anthocyanins than the non-fortified preparation. α-Tocopherol, γ-tocopherol, β-carotene, and lutein were detected exclusively in fortified samples. ABTS and CUPRAC assays showed comparatively high antioxidant activity values in the fortified preparation. Lower concentrations of anthocyanins, carotenoids, and tocopherols were observed at t₃₀ than at t₀, although substantial levels remained detectable after 30 days. HS-SPME/GC-MS detected 63 VOCs, with the fortified beverage showing a distinct volatile profile after 30 days of refrigerated storage, including comparatively high analytical responses for several monoterpenes and C6 alcohols. Sensory analysis revealed a distinctive profile characterized by greater sourness, bitterness, astringency, density, and aromatic complexity, together with lower overall sensory quality. Microbial counts remained below the respective detection limits under the investigated conditions. Overall, the investigated fortified preparation was characterized by a phytochemically enriched profile and by differences in antioxidant capacity, volatile composition, and sensory characteristics compared with the non-fortified preparation. These findings provide preliminary evidence of the compositional potential of grapevine leaf extract as an ingredient for phytochemically enriched grape-based beverages, while also identifying sensory constraints requiring formulation optimization. Full article

Urban vineyards are expanding worldwide, driven by cultural and environmental motivations and their potential contribution to sustainable food systems. This study assessed grapevine (Vitis vinifera L.) responses to urban atmospheric conditions and explored traits relevant to cultivar selection and particulate matter (PM) interception. Research was conducted during the 2025 growing season in a highly biodiverse urban vineyard comprising 170 cultivars at the Botanical Garden of Rome (Italy), a city where grapevine has been documented since antiquity. Digital phenotyping was used to screen 54 cultivars based on leaf micromorphological traits, followed by detailed assessment of five selected cultivars. Measurements also included leaf anatomical traits, chlorophyll content, spectral reflectance-derived indices related to vigor and water status, and PM interception by scanning electron microscopy. Cultivars differed in micromorphological traits and ecophysiological proxies, suggesting different responses to urban environmental conditions. Total leaf-surface PM accumulation after an approximately 20-day accumulation period following the last intense rainfall event (>10 mm h⁻¹) ranged from 52,024 particles mm⁻² in cv. Barbera to 77,462 particles mm⁻² in cv. Maturano, values broadly comparable to those reported for some urban forest species. Deposition on the adaxial surface was more than twice that measured on the abaxial surface. These findings highlight the potential of digital phenotyping to integrate morphological and physiological traits, supporting plant material selection for urban viticulture, PM interception, and, more broadly, for urban landscape design. Full article

Hotter, drier and less predictable conditions are changing Mediterranean viticulture and renewing interest in local grapevine diversity. Regional persistence can identify candidates but does not demonstrate climatic adaptation. We asked when published evidence can support an adaptation claim and movement towards deployment. In this critical integrative review, indexed searches, complementary retrieval, retrospective validation and a bibliographic update produced a non-exhaustive corpus of 105 publications from January 2000 to September 2026. Studies were retained when they informed candidate identity, climatic response, comparative performance, robustness or possible use. Variation was reported in phenology, water relations, berry composition and responses to drought and heat. Much of the evidence stopped early. Identity or discovery was the main contribution of 24 publications; 16 examined mechanisms and 29 compared performance. Only four tested robustness across years or environments. Nine reached deployment-related questions, but none monitored later performance within a defined adaptation domain. Recovery, carry-over, compound or sequential stress and long-term productive stability remained poorly documented. These breaks informed an eight-gate framework, numbered zero to seven. A retrospective reading of Monastrell, Xynisteri and Greco showed that evidence stopped at different points and for different reasons. It demonstrated how the gates could be used, not that the framework was validated. Local diversity may widen adaptation choices, but recommendations require stronger evidence. Prospective testing across contrasting Mediterranean production systems is now needed. Full article

Efficient deployment of neural-network detectors on field-programmable gate array (FPGA) accelerators depends not only on model complexity but also on compiler-visible graph structure. On deep learning processing unit (DPU) platforms, unsupported operators can fragment execution between accelerator and host execution domains. We present C2fDeploy, a training-free rewrite for the YOLOv8 C2f block that moves channel splitting from the activation graph to an offline partition of the trained projection and batch-normalization parameters. The transformed block preserves the 32-bit floating-point (FP32) function without retraining or additional parameters. On the GRAZPEDWRI-DX fracture-detection task, the original and rewritten graphs produced identical FP32 test metrics and comparable 8-bit integer (INT8) accuracy. Direct tensor-level FP32 comparison at the outputs of all eight rewritten C2f blocks yielded an aggregate mean absolute error of $9.73\times {10}^{-8}$ and a relative $L_2$ error of $1.97\times {10}^{-7}$, providing numerical verification beyond detection-level metrics. Compilation for the Kria KV260 consolidated nine DPU subgraphs into one and removed the C2f-related host-side slicing operations. In a same-checkpoint whole-XModel benchmark, C2fDeploy improved whole-XModel graph execution throughput by $95.2\times$ and reduced energy per execution on the 5 V system-on-module (SOM) rail by 98.2%. Direct runtime profiling further showed that DPU compute-unit busy-time utilization increased from 0.36% to 90.75%, while system-wide CPU utilization decreased by 89.5%. Aggregate APM-observed external-memory bandwidth increased from 40.20 to 3250.56 MB/s as accelerator execution became more continuous, whereas normalized APM-observed traffic decreased by 14.8% per graph execution. These results show that compiler-aware graph rewriting can remove deployment bottlenecks without changing the trained detector. Full article

Rootstock selection is associated with differences in grapevine mineral nutrition, vegetative performance, grape composition and potentially wine characteristics. This study comparatively assessed Malvasia di Candia Aromatica (Vitis vinifera L.) grafted onto 1103 Paulsen (1103 P), 420 A, Teleki 5BB and SO4 in a rainfed commercial vineyard in Crete. The evaluation integrated field measurements, petiole mineral analysis, grape composition, standardized microvinification, basic wine analysis and GC-MS volatile profiling. Petiole mineral composition showed the clearest differentiation among graft combinations, with eight of nine measured elements remaining significant after false-discovery-rate correction. 1103 P was characterized by the highest P and Mg concentrations, 420 A by the highest Ca and comparatively low Na and K, Teleki 5BB by comparatively high Zn, and SO4 by the highest K and Mn and the lowest Mg, Cu and Zn. At harvest, must pH was the most robust response (3.75 in 1103 P compared with 3.27–3.42 in the other rootstocks), whereas soluble solids and titratable acidity did not differ significantly. Three independent grape lots per rootstock were microvinified under a common protocol. Wines from Teleki 5BB and SO4 showed higher alcoholic strength (12.10 and 12.21% vol, respectively) than those from 1103 P and 420 A (11.51 and 11.47% vol). Three volatile compounds showed nominal differences among rootstocks, but none remained significant after multiple-testing correction, and PERMANOVA did not detect significant overall separation of volatile profiles. Overall, rootstock-associated differences were biggest for mineral nutrition and must pH, intermediate for selected basic wine characteristics, and weak for wine volatile composition. These findings highlight distinct vine-to-wine response profiles among graft combinations while supporting cautious, cultivar- and site-specific interpretation under Mediterranean rainfed conditions. Full article

Viticulture currently faces major environmental challenges, mainly due to the intensive use of plant protection products to control downy and powdery mildew diseases, which are being intensified by climate change. To promote more sustainable production, cryptogamic disease-tolerant grape varieties have been developed through crosses between fungus-resistant Vitis varieties and traditional Vitis vinifera varieties. The cryptogamic disease-tolerant grape varieties can reduce the use of plant protection products by up to eighty percent, lowering both the carbon footprint and environmental impact. Nevertheless, knowledge of their oenological potential, especially regarding volatile composition, remains limited. This study aims to characterise and compare the volatile composition of cryptogamic disease-tolerant grape varieties with their progenitor varieties from the 2024 and 2025 vintages, using headspace solid-phase microextraction coupled with comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry (HS-SPME–GC×GC–TOFMS). The results show that cryptogamic disease-tolerant grape varieties showed a volatile composition more closely aligned with that of traditional Vitis vinifera varieties than with those of fungus-resistant Vitis varieties. Additionally, cryptogamic disease-tolerant grapes contain a large amount of varietal compounds. These findings expand current knowledge of the volatile composition of disease-tolerant grapevines and may inform future research on their potential suitability for sustainable viticulture. Full article

Grapevine (Vitis vinifera L.) hosts a diverse range of viruses and viroids that differ in genome type, abundance, and distribution, creating challenges for reliable detection. High-throughput sequencing (HTS) is a powerful non-targeted tool for pathogen diagnostics, but its routine implementation requires validated workflows and objective interpretation criteria. Here, we present a validation framework for HTS-based plant virus and viroid diagnostics and demonstrate its application using an in-house grapevine pathogen detection workflow. Ten composite reference samples containing 85 virus and viroid occurrences were analyzed across a dilution series to evaluate diagnostic accuracy, detection limits, repeatability, reproducibility, and contamination risk. Results showed that sequencing quality metrics alone were insufficient for diagnostic interpretation. Additional indicators, including mapped reads and internal control depth, were necessary to assess sample suitability and define minimum performance requirements. Viral detection was evaluated using genome coverage and relative abundance (weight) metrics. A positive relationship between these parameters enabled the establishment of quantitative detection thresholds and a three-tier classification system: positive, likely positive, and likely negative. Diagnostic accuracy decreased with dilution because of reduced sensitivity for low-abundance pathogens, whereas repeatability and within-laboratory reproducibility remained high and contamination signals stayed below detection thresholds. Although the performance metrics are workflow-specific, this study provides a practical framework for laboratory validation of HTS-based plant virus and viroid diagnostics. Full article

This study evaluated the efficacy of basil essential oil (BEO), extracted from basil plants irrigated with ozonated water, as a sustainable strategy to control grey mould (Botrytis cinerea, Bc) in grapevine, Vitis vinifera cv. Sangiovese. Bunches were treated with water (control) or BEO and, after Bc inoculation, disease progression (AUDPC), berry biometric traits and biochemical parameters were assessed. Treatment with BEO significantly reduced disease severity, lowering AUDPC values at 168 h post inoculation compared with untreated infected grapes, while limiting visible mycelial emergence. Anthocyanins and total phenols decreased following infection (−36 and −38%, respectively, in comparison to the control). By contrast, BEO-treated and infected grapes showed a more than 2-fold increase in resveratrol and condensed tannins, suggesting the activation of defence-related secondary metabolism. Lastly, glucose and fructose contents declined by 56% only in untreated infected berries, confirming active pathogen colonisation. These findings demonstrate that BEO significantly reduced grey mould development with enhanced defence-related metabolic responses, supporting its potential as an eco-friendly alternative to synthetic fungicides in sustainable viticulture. Full article

Gray mold (Botrytis cinerea Pers.) is a primary yield-limiting disease in European viticulture. Here we report a field evaluation of two chitosan oligomer (COS)-based nanocarrier (NC) systems loaded with Rubia tinctorum (NC-Rt) and Uncaria tomentosa (NC-Ut) extracts for B. cinerea management in ‘Tempranillo’ vineyards (D.O.P. Ribera del Duero, 2024 season). In vitro, nanoencapsulation reduced the effective extract concentration required for complete inhibition of B. cinerea mycelial growth by 1.8–6.7-fold relative to free extracts. Ex situ, both NC formulations at MIC×3 significantly reduced gray mold severity on inoculated ‘Tempranillo’ bunches at days 5 and 7, but not on ‘Verdejo’ bunches. In a field trial under commercial-vineyard conditions, NC-Ut and NC-Rt reduced mean gray mold severity from 80% in the untreated control to 18–25%, compared with 35–40% for the free extracts and commercial chitosan, an effectiveness of 69–78%. No visual symptoms of acute phytotoxicity were observed during the trial, and cluster weight and cluster number did not differ significantly among treatments. A preliminary, exploratory sensory screening of the wines produced from the treated grapevines detected no significant treatment-related differences in off-flavor or Botrytis-related defect scores. These single-season results support further evaluation of COS-based NCs as delivery systems for plant-derived antifungals in viticulture. Full article

The increasing use of unmanned aerial vehicles (UAVs) and other moving objects in civilian environments has created a growing need for reliable radar-based object classification systems, while deep learning (DL) models achieve high classification accuracy on range–Doppler (RD) radar data, their deployment on resource-constrained embedded platforms remains challenging due to computational and latency constraints. This work addresses that gap as a hardware–software co-design problem: the contribution is the system-level optimization and characterization of the deployment rather than the design of a new network architecture. This paper presents the deployment and system-level characterization of an adopted multiscale decision fusion convolutional neural network (MDF-CNN) for radar-based object classification on the Xilinx Kria KR260 platform. The network processes preprocessed stacked RD frames of size $11\times 61\times 3$ and classifies targets into cars, drones, and people using the publicly available RDRD dataset. The Floating-Point (FP32) reference model achieves 97.06% classification accuracy. For efficient embedded deployment, the model is quantized to 8-bit integer (INT8) precision using the Vitis AI framework and executed on the deep learning processing unit (DPU). The INT8 FPGA (DPU) implementation achieves 96.88% accuracy with an average classifier-stage latency of 9.24 ms per preprocessed input tensor and a throughput of 108.21 inferences per second, corresponding to a $6.2\times$ latency reduction relative to the FP32 central processing unit (CPU) baseline. The measured interval includes DPU execution and the tensor transfers between double data rate (DDR) memory and the DPU, but excludes radar acquisition, RD-map generation, target-centered cropping, temporal stacking, per-sample z-score normalization, and ARM-side INT8 input scaling. At fixed INT8 precision, the INT8 CPU implementation achieved a lower raw latency of 7.957 ms per preprocessed input tensor compared with 9.24 ms for the DPU. Power measurements show an average consumption of 4.14 W, resulting in an energy cost of 38.25 mJ per classifier inference. These figures compare two deployment configurations that differ in hardware, numerical precision, software runtime, and power-measurement boundary, and are therefore reported as a system-level comparison rather than as an attribution to any single factor. These results characterize low-latency and energy-efficient deployed MDF-CNN classifier execution on the KR260 using preprocessed radar tensors; investigation of the implementation and timing of the complete online radar-to-classification pipeline remain directions for future work. Full article

Improving stem cutting propagation of grapevine species (Vitis sp.) is important for supporting growing interest in southern grapevine production, particularly for lesser-known cultivars. More efficient and reliable propagation techniques can help nurseries increase the availability of grapevine plants for local growers and support development of the southern U.S. wine industry. Hardwood and semi-hardwood cuttings of four winegrape cultivars, ‘Mamont Noir’, ‘MidSouth’, ‘Miss Blanc’, and ‘Norton’, were subjected to 10 hormone treatments consisting of indole-3-butyric acid (IBA) alone or in combination with ascorbic acid (ASC). Treatments were applied as a three-second basal quick dip. Sixty days after treatment, total shoot and root number, average shoot and root length, rooting percentage, and cutting and root quality were evaluated. Based on the results, semi-hardwood or hardwood ‘Mamont Noir’ cuttings can be propagated using 50 ppm ASC or 50 ppm ASC + 500 ppm IBA. For nurseries where hardwood cuttings better fit the production schedule, ‘Miss Blanc’ cuttings rooted well regardless of hormone treatment. Additional research is needed to optimize hormone treatments for ‘MidSouth’ and ‘Norton’. Full article