Search Results (279)

The genus Diaporthe consists of saprobes, endophytes, and important plant pathogens. Members of this genus are widely distributed and have a broad host range, including grapevines. This study aimed to establish a baseline survey to assess the diversity of Diaporthe species infecting propagation material and to explore their dynamics in disease development. Initially, a survey was conducted in a nursery field, and isolations were carried out from 2-month-old symptomatic grafted vines of cv. Agiorgitiko grafted onto rootstock Richter 110. The initial molecular identification of the isolated mycobiome at the genus level was carried out by sequencing the universal internal transcribed spacer (ITS) locus, while subsequent species-level identification of the Diaporthe isolates was performed through phylogenetic approaches coupled with morphological characterization. Based on the combined analysis, five phylogenetically distinct Diaporthe spp. were identified in this study, taxonomically assigned to D. ampelina, D. eres, D. foeniculina, D. serafiniae, and D. novem. Pathogenicity trials demonstrated that the most aggressive species were D. ampelina followed by D. eres, while the remaining species were classified as opportunistic or weak pathogens of grapevine. Overall, accurate identification and monitoring of Diaporthe species involved in propagation material infections are important in order to develop species-specific effective management strategies in grapevine nurseries. Full article

Predicting road crash severity remains a major challenge in transportation safety research, requiring models that combine predictive accuracy, interpretability, and computational efficiency. This study introduces a Multi-Risk Index based on Copula Integration (MRI-Copula)—a hybrid framework that integrates Categorical Boosting (CatBoost) with SHapley Additive exPlanations (SHAP) and Vine Copula dependence modeling to assess and predict crash severity. The approach leverages CatBoost–SHAP to quantify the marginal contribution of each risk factor while maintaining model transparency and employs copula-based tail dependence to capture the joint escalation of risk under extreme crash conditions. Using a dataset of 877 police-reported crashes from Jeddah, Saudi Arabia, the framework constructs three interpretable sub-indices—Environmental Risk Index (ERI), Behavioural Risk Index (BRI), and Systemic Risk Index (SRI)—representing distinct domains of crash causation. These indices are combined through a convex weighting parameter (α), optimized via cross-validation (optimal α = 0.80), ensuring a balanced integration of predictive and dependence-based information. Comparative evaluation across multiple classifiers—CatBoost, Light Gradient Boosting Machine (LightGBM), Histogram-based Gradient Boosting (HistGB), and Logistic Regression—demonstrated the robustness of the framework. The CatBoost + MRI-Copula configuration achieved the highest predictive performance (AUC = 0.986; F1 = 0.904), while LightGBM and HistGB offered comparable accuracy (AUC ≈ 0.958; F1 ≈ 0.89) at a fraction of the computational time (≤1 s versus 32 s for CatBoost), highlighting a trade-off between analytical precision and scalability. Consequently, the MRI-Copula framework provides a transparent and theoretically grounded foundation for data-driven road safety management. It bridges predictive analytics and decision support offering a scalable, interpretable, and policy-relevant tool for proactive crash risk mitigation. Full article

Selecting an appropriate rootstock for a specific scion cultivar is an efficient way to improve both yield and berry quality in viticulture. This study aimed to provide practical guidance for rootstock selection in the cultivation of the table grape cultivar ‘Fengguang’. The mature scions of this cultivar were grafted onto hardwood cuttings of eight different resistant rootstocks, which included 101-14M, 110R, 188-08, 3309C, 5BB, 5C, SO4, and Beta, with the own-rooted vines as control. Graft compatibility, growth vigor, yield performance, and fruit quality were compared and analyzed among the different grafting combinations. The results suggested that vines on 101-14M, 5BB, and Beta obtained higher germination rates of scions, better healing rates of the mating interface, and greater generation rates of root callus. Among these, vines on 5BB exhibited the largest scion trunk cross-sectional diameter. Furthermore, SO4 demonstrated the most significant improvement in yield, with an average increase of 13.54% compared to the control. Regarding berry quality, 101-14M significantly enhanced berry mass, pressure resistance, and flesh firmness relative to the controls, with average improvements of 7.67%, 11.34%, and 29.86%, respectively. Based on a comprehensive evaluation of yield and fruit quality indicators, 101-14M gained the highest value. In conclusion, 101-14M is preferentially recommended for grafting cultivation of ‘Fengguang’ vines. These findings could provide practical guidance for the cultivation of table grape cultivars. Full article

In response to the dust pollution issue during the harvesting operations of peanut pickup combines, this study involved conducting bench tests to explore the variation patterns of dust emission parameters and harvesting operation indicators under diverse working parameter conditions of the combine’s working components. A multi-factor mathematical model was established to predict both the dust emission rate of peanut pickup combines and the quality of harvesting operations. The model was utilized to identify the optimal combination of operation parameters for achieving high-quality and low-emission performance. The optimal parameter combination was determined as follows: a pod threshing roller speed of 313 r/min, a cleaning fan speed of 2535 r/min, a vine crushing roller speed of 1970 r/min, and a lifting fan speed of 1604 r/min. Under these conditions, the theoretical dust emission rate was calculated to be 10,603 mg/s, with a pod loss rate of 4.73% and a pod impurity rate of 5.21%. Compared to previous settings, the optimized operation parameters effectively reduced the combine’s dust emissions by 9.95%. Notably, the harvesting operation quality still complies with the industry standards for peanut harvesters. These research findings offer theoretical insights and robust technical support for minimizing dust pollution during the whole-feed harvesting of peanuts, contributing to more environmentally friendly and efficient peanut harvesting practices. Full article

Recent climatic extremes, characterized by hot and dry summers, threaten grape yield and berry composition, increasing the need for sustainable mitigation strategies. In this study, a fruit-zone cooling system was tested to reduce sunburn damage and improve vine performance. The system integrates proximal sensors and an automatic misting actuator, triggered when the air temperature exceeds 35 °C. Over two seasons (2022–2023), trials were conducted on Pignoletto vines subjected to four treatments: control (C), misted without defoliation (C + FOG), defoliated (DEF), and defoliated plus misted (DEF + FOG). The effects on microclimate, yield, berry sunburn, and berry composition were evaluated. Misting consistently reduced both air and berry temperature. Treated vines showed increased yield, mainly due to reduced sunburn and higher cluster weight. Although no clear differences in technological maturity were observed, misted vines tended to retain higher acidity under extreme heat. Flavonol synthesis was unaffected by cooling but stimulated by increased light exposure, being higher in defoliated vines. Volatile compounds analysis highlighted misting’s moderating effect on oxidative stress and aroma profile shifts, particularly during the hotter season. Overall, the cooling system proved effective in mitigating summer stress, offering a promising tool for preserving yield and berry composition in white cultivars under climate change. Full article

AI-driven agricultural automation increasingly demands efficient data generation methods for training deep learning models in autonomous robotic systems. Traditional bounding box annotation methods for agricultural objects present significant challenges including subjective boundary determination, inconsistent labeling across annotators, and physical strain from extensive mouse movements required for elongated objects. This study proposes a novel base-width standardized annotation method that utilizes the base width of a vine trunk and a support post as a reference parameter for automated bounding box generation. The method requires annotators to specify only the left and right endpoints of object bases, from which the system automatically generates standardized bounding boxes with predefined aspect ratios. Performance assessment utilized Precision, Recall, F1-score, and Average Precision metrics across vine trunks and support posts. The study reveals that vertically elongated rectangular bounding boxes outperform square configurations for agricultural object detection. The proposed method is expected to reduce time consumption from subjective boundary determination and minimize physical strain during bounding box annotation for AI-based autonomous navigation models in agricultural environments. This will ultimately enhance dataset consistency and improve the efficiency of artificial intelligence learning. Full article

This study develops an integrated risk modeling framework to assess capital adequacy and optimize portfolio performance for Thai life and non-life insurers. Leveraging ARMA–GJR–GARCH models with skewed Student-t innovations, extreme value theory, and dynamic R-vine copulas, the framework effectively captures volatility, tail risks, and evolving asset interdependencies. Utilizing daily data from 2014 to 2024, the models generate value-at-risk forecasts consistent with international standards such as Basel III’s 10-day 99% VaR and rolling Sharpe ratios for portfolios integrating green bonds compared to traditional asset allocations. The results demonstrate that green bonds, fixedincome instruments funding renewable energy and other environmental projects, significantly improve risk-adjusted returns and have the potential to reduce capital requirements, particularly for life insurers with long-term sustainability mandates. These findings underscore the importance of portfolio-level capital assessment and support the proactive integration of ESG considerations into supervisory investment guidelines to enhance financial resilience and align the insurance sector with Thailand’s sustainable finance agenda. Full article

Selecting appropriate rootstocks can enhance the adaptability and fruit quality of grafted grapevines. However, grafting studies on ‘Red Globe’, one of the major cultivated cultivars, remain limited, particularly those involving long-term and comprehensive evaluations. The present research grafted ‘Red Globe’ onto four rootstocks—‘101-14’, ‘188-08’, ‘110R’, and ‘3309C’—and systematically compared graft union healing following hardwood grafting, field performance of grafted vines, vegetative growth of mature vines, and fruit phenotypic and quality traits across multiple years. The results showed that ‘101-14’ promoted the accumulation of organic acids, which reached 1.1% in 2023, and caused an increased tendency for berry detachment from the peduncle. The RG/110R combination exhibited a higher CFI, 0.8 on average, at the basal section, and promoted shoot thickening. RG/3309C was found to have a larger shoot length exceeding 600 cm, and a significant increase in fruit weight to nearly 13 g. The grafts on ‘188-08’ showed the highest survival rate of 74% among the graft combinations, and enhanced fruit quality, as evidenced by elevated TSS (16 °Brix) and firmer pulp texture, indicating that ‘188-08’ may serve as a valuable rootstock for enhancing the local adaptability and fruit quality of ‘Red Globe’ grapevines. Full article

Contextual multi-armed bandits (CMABs) are vital for sequential decision-making in areas such as recommendation systems, clinical trials, and finance. We propose a simulation framework integrating Gaussian Process (GP)-based CMABs with vine copulas to model dependent contexts and GARCH processes to capture reward volatility. Rewards are generated via copula-transformed Beta distributions to reflect complex joint dependencies and skewness. We evaluate four policies—ensemble, Epsilon-greedy, Thompson, and Upper Confidence Bound (UCB)—over 10,000 replications, assessing cumulative regret, observed reward, and cumulative reward. While Thompson sampling and LLM-guided policies consistently minimize regret and maximize rewards under varied reward distributions, Epsilon-greedy shows instability, and UCB exhibits moderate performance. Enhancing the ensemble with copula features, GP models, and dynamic policy selection driven by a large language model (LLM) yields superior adaptability and performance. Our results highlight the effectiveness of combining structured probabilistic models with LLM-based guidance for robust, adaptive decision-making in skewed, high-variance environments. Full article

Climbing vines have recently induced increasing threats to forest growth under favourable environmental changes. In mangrove forests, the native vine Derris trifoliata became invasive and is now one of the main threats. Yet current management relies on manual removal with low efficiency. Exploring an alternative, cost-effective method is required. To assess the potential of a proposed biological control method, this study performed a pot-plant experiment using Cuscuta japonica to infect D. trifoliata and three common mangrove species in Beihai, China. Results showed that D. trifoliata had a higher infection rate and high host mortality (90%) than mangrove (0%). It also had significantly decreased moisture by 4%, nitrogen by 14%, phosphorus by 27%, potassium by 49% and increased soluble sugar by 49% and protein by 20%, whereas only moisture (2% reduction) and one or two minerals of Excoecaria agallocha and Aegiceras corniculatum were influenced. Only Kandelia obovata had neither effective haustoria nor any nutrients impact from the infection. This study indicated that C. japonica can cause more damage to D. trifoliata than to mangrove species and has the potential to be used as a biological control agent for the threatened mangrove forests of A. corniculatum and K. obovata with monitoring and control. Further field tests are required to bring this method into practice. Full article

Grafting compatibility between rootstocks and scions is a critical factor influencing the success of vine propagation and the long-term productivity of vineyards. This study aimed to evaluate the compatibility, sapling quality characteristics, and survival rates of grafted vines produced by combining ten local grape cultivars from Yozgat Province with four rootstocks: ‘5 BB’, ‘41 B’, ‘1103 P’, and ‘Fercal’. Grafted vines were assessed based on callus formation, graft union success, root development, and overall sapling quality. The results revealed that the ‘Fercal’ rootstock exhibited superior compatibility with several cultivars, notably achieving 100% graft success with ‘Siyah Üzüm’ and a high sapling rate of 93.4% with ‘Gelinparmağı’. Strong performance was also observed in the ‘Fercal/Köledoyuran’ and ‘Fercal/Horoz Üzümü’ combinations, which produced sapling rates of 95.4%. While ‘5 BB’ performed well with ‘Parmak Üzümü’ (100% graft success), ‘Karagevrek’ (94.4%), and ‘Mor Bulut’, it showed poor results with ‘Gelinparmağı’ (66.5% sapling rate). The ‘1103 P’ rootstock demonstrated good compatibility with ‘Şahmuratlı’ (94.3% graft success) and ‘Kirpi Üzümü’. In contrast, although ‘41 B’ reached up to 100% graft success in some combinations, it exhibited variable sapling development potential, ranging from 46.2% to 80.0%. Among the cultivars, ‘Siyah Üzüm’ achieved 100% compatibility with three rootstocks (‘41 B’, ‘1103 P’, and ‘Fercal’), followed by ‘Köledoyuran’, which consistently showed high success rates ranging from 96.9% to 100%. These findings offer practical guidance for selecting optimal rootstock–scion combinations to improve the efficiency of grafted vine production and reduce losses, particularly for local grape cultivars. Full article

The petiole nitrate–nitrogen concentration (PNNC) has been an industry standard indicator for in-season potato (Solanum tuberosum L.) nitrogen (N) status diagnosis. Leaf sensors can be used to predict the PNNC and other N status indicators non-destructively. The SPAD meter is a common leaf chlorophyll (Chl) meter, while the Dualex is a newer leaf fluorescence sensor. Limited research has been conducted to compare the two leaf sensors for potato N status assessment. Therefore, the objectives of this study were to (1) compare SPAD and Dualex for predicting potato N status indicators, and (2) evaluate the potential prediction improvement using multi-source data fusion. The plot-scale experiments were conducted in Becker, Minnesota, USA, in 2018, 2019, 2021, and 2023, involving different cultivars, N treatments, and irrigation rates. The results indicated that Dualex’s N balance index (NBI; Chl/Flav) always outperformed Dualex Chl but did not consistently perform better than the SPAD meter. All N status indicators were predicted with significantly higher accuracy with multi-source data fusion using machine learning models. A practical strategy was developed using a linear support vector regression model with SPAD, cultivar information, accumulated growing degree days, accumulated total moisture, and an as-applied N rate to predict the vine or whole-plant N nutrition index (NNI), achieving an R² of 0.80–0.82, accuracy of 0.75–0.77, and Kappa statistic of 0.57–0.58 (near-substantial). Further research is needed to develop an easy-to-use application and corresponding in-season N recommendation strategy to facilitate practical on-farm applications. Full article

Water status is a key determinant of physiological performance and vineyard productivity. However, its assessment through field measurements is time-consuming and labour-intensive. Remote sensing offers a fast and reliable alternative to traditional in situ methods for the monitoring of the water status in vineyards. This study aimed to assess the potential of high-resolution multispectral imagery acquired by UAVs to estimate the vine water status. The research was conducted over two growing seasons (2021 and 2022) in a commercial Merlot vineyard in Yepes (Toledo, Central Spain), under five irrigation regimes designed to generate a range of water statuses. UAV flights were performed at two times of day (09:00 and 12:00 solar time), coinciding with in-field measurements of physiological parameters. Stem water potential (SWP), chlorophyll content, and photosynthesis data were collected. The SWP consistently showed the strongest and most stable associations with vegetation indices (VIs) and the red spectral band at 12:00. A simple linear regression model using the NDVI explained up to 58% of the SWP variability regardless of the time of day or year. Multiple linear regression models incorporating the red and NIR bands yielded even higher predictive power (R² = 0.62). Stronger correlations were observed at 12:00, especially when combining data from both years, highlighting the importance of midday measurements in capturing water stress effects. These findings demonstrate the potential of UAV-based multispectral imagery as a non-destructive and scalable tool for the monitoring of the vine water status under field conditions. Full article

Anaerobic digestion for biogas production represents a crucial approach to achieving the high-value utilization of agricultural solid waste. The adoption of multi-material co-digestion offers a viable solution to overcome the inherent constraints associated with single-substrate digestion, thereby significantly enhancing the efficiency of resource utilization. This study explored a co-digestion system using dairy manure and cucumber vines as substrates, uncovering how total solids (TS) influence the methane yield and microbial community characteristics. All treatments exhibited swift methane fermentation, with daily production initially increasing before declining. Cumulative methane production increased with the increasing TS contents. These results may be linked to pH value and the concentration of volatile fatty acids (VFAs). Except for the 6% TS treatment, digesters across different TS levels maintained a favorable final pH of 7.4–8.4, while VFA concentrations exhibited a downward trend as TS contents increased. The treatment with the highest TS concentration (25%) demonstrated superior performance, achieving the maximum volumetric methane yield. This yield was 1.6 to 9.1 times higher than those obtained at low (6–10%) and medium (12–18%) TS concentrations. Microbial community analysis revealed that during the peak methane production phase, Firmicutes and Methanoculleus were the predominant bacterial and archaeal phyla, respectively. The microbial community structure changed with different TS levels. This study offers valuable scientific insights for enhancing biogas production efficiency in co-digestion systems. Full article

Soil management in vineyards is a crucial component of sustainable viticulture. Weed control under the row has traditionally been addressed using mechanical, physical, and chemical techniques, but herbicides pose environmental and health risks. The circular economy offers an alternative approach by converting organic waste into a resource, such as compost. This study explores the effectiveness of compost derived from the organic fraction of municipal solid waste (MSW) not only as a mulching technique but also as a potential biological agent for weed control through allelopathic mechanisms in vineyards. Experiments were conducted both in the field and under controlled conditions. In the field, compost was applied under the vine row as mulch and incorporated into the soil. Under controlled conditions, germination tests were performed to assess weed inhibition at different compost concentrations. Field results demonstrated that compost applications, both as mulch and incorporated into the soil, significantly inhibited weed growth during the first period after application compared to the tilled control without compost. Thus, this inhibition is not limited to physical mulching; it also applies to the release of allelopathic compounds from compost. Controlled condition experiments showed strong inhibition of germination in Cichorium intybus and Foeniculum vulgare seeds, confirming the anti-germinative effects of compost, particularly on small-seeded weed species. Compost is a promising tool for sustainable vineyard management, offering fertilization and weed-suppression benefits while reducing herbicide use. Full article