Grape Harvest Research Articles

Additions/removals of seeds before fermentation alters Cabernet Sauvignon wine color via modulating anthocyanins and derivatives

The advance of the grape harvest caused by global warming has to some extent resulted in poor or unstable wine color, this study investigated the potential benefits of grape seeds on wine color to mitigate this negative effect. Anthocyanins and their derivatives, and chromatic characteristics were measured by targeted UHPLC-QqQ-MS/MS and CIELab methods, respectively. The addition of seeds was beneficial to the formation of polymeric pigments and flavanyl-pyranoanthocyanins, while decreased the accumulation of other yranoanthocyanins, monomeric anthocyanins, and acylated anthocyanins during fermentation. All pigment levels in seed wine can be better maintained over time. Compared with the removal of seeds during fermentation, the addition of seeds significantly enhanced the color intensity, bluish hues, and Chroma, while an appropriate amount of seeds favored wine red hue. PLSR showed that the addition/removal of seeds during fermentation could alter red wine chromatic characteristics via modulating anthocyanin profiles. These results can be used as reference to further explore the technological applications of seeds during fermentation for optimizing the potential benefits on red wine color.

Jet stream controls on European climate and agriculture since 1300 ce

The jet stream is an important dynamic driver of climate variability in the Northern Hemisphere mid-latitudes1–3. Modern variability in the position of summer jet stream latitude in the North Atlantic–European sector (EU JSL) promotes dipole patterns in air pressure, temperature, precipitation and drought between northwestern and southeastern Europe. EU JSL variability and its impacts on regional climatic extremes and societal events are poorly understood, particularly before anthropogenic warming. Based on three temperature-sensitive European tree-ring records, we develop a reconstruction of interannual summer EU JSL variability over the period 1300–2004 ce (R2 = 38.5%) and compare it to independent historical documented climatic and societal records, such as grape harvest, grain prices, plagues and human mortality. Here we show contrasting summer climate extremes associated with EU JSL variability back to 1300 ce as well as biophysical, economic and human demographic impacts, including wildfires and epidemics. In light of projections for altered jet stream behaviour and intensified climate extremes, our findings underscore the importance of considering EU JSL variability when evaluating amplified future climate risk.

Navigating discreetly: Spatial ecology of urban wild boar in Bordeaux City's landscape of fear, France

An exemplary urban adapter, the wild boar (Sus scrofa) has successfully colonized urban ecological niches worldwide. Improvement of strategies for optimal management of urban wild boar need to gather more empirical evidence of their spatial ecology. This study is based on GPS tracking and capture-mark-recapture (CMR) of 10 and 59 wild boar, respectively, captured in Bordeaux Metropolis (France). It shows that wild boar have become urban dwellers, with intra-urban home ranges varying from 1.3 to 64.6 km2 (MCP 100 %) and from 0.5 to 9.6 km2 (KDE 95 %), depending on urban conditions. CMR results confirm the low propensity to move away from urban areas (with a mean distance of 2 km between capture and recapture sites), despite a relatively low one-year survival rate since capture (47.5 %), primarily attributable to removal efforts. Wild boar strongly depended on urban woods, mostly during daytime resting, and highly frequented urban meadows during night foraging. Their use of urban agricultural areas was minimal, but they were mostly monitored following corn and grape harvests. Wild boar mitigated the risk associated with close proximity to humans by: a nocturnal activity (72.2 % of active locations registered from sunset to sunrise), which could also be partially attributed to their sensitivity to heat; a strong use of covered habitats, especially during daytime resting and when close to buildings and roads; and a low mobility during night-time foraging (1974 m average daily distance travelled). Moreover, we demonstrate high inter- and intra-individual variability in the spatio-temporal behaviour of urban wild boar. Finally, we discuss the gap between these results and the narratives surrounding the spatial ecology of urban wild boar. Our results not only confirm the species' ability to adapt to urban environments, but also highlight their behavioural flexibility, underscoring the relevance of significant changes in representations and management activities to mitigate human-urban wild boar conflicts.

The humic acids influence on the quantity and quality of table grape varieties under the Absheron peninsula conditions

Humates are widely used in viticulture, including ecological viticulture. Humic stuffs benefit the qualitative and quantitative indicators of the grape harvest and can reduce the use of synthetic fertilizers and pesticides. This article presents the results of tests on the foliar application of various doses of the “Rostok” fertilizer in the conditions of the Absheron zone of Azerbaijan on local varieties of table grapes – traditional Tabrizi and a selection variety of Scientific Research Institute of Viticulture and Wine-making Ganjavi, grown in the Ampelographic collection of the institute, located on the Absheron peninsula. Fertilizer was applied in three doses – 0.5; 1.0 and 1.5 liter per hectar. Under the influence of the fertilizer, such elements of yield as the vigor of shoot growth, the number of opened buds, fruitful shoots, the number of berries in a bunch, the weight of a bunch, as well as the sugar content of berry juice increased. Fertilizer application had a positive effect on eliminating signs of leaf chlorosis. No toxic effect on the vegetative organs of the grape plant, on its development, or on the beneficial insect fauna of the vineyard was noted. Based on the data obtained, as well as calculations of economic efficiency, a four-fold application of fertilizer (twice before flowering, once after, once during veraison) at the rate of 1 liter per hectare was recommended for widespread use in wine-growing farms.

Brassinosteroids enhance the tolerance, production, and fruit quality of covered table grape vines

ABSTRACT Plastic covering (PC) is used to speed up the ripening and harvesting of grapes while also shielding grapevines from unfavourable climatic conditions. This study aimed to determine how PC induced abiotic stress on covered vines and assess the role of brassinosteroids (Brs) in alleviating these impacts. The results showed that PC caused a substantial rise in soluble sugar, MDA, proline, total phenol, and antioxidant enzymes (catalase and ascorbate peroxidase) and decreased insoluble sugars and carbohydrates in ‘Superior' seedless grape leaves. Applying Brs at concentrations of 0, 1, 2, and 3 mg/l twice during the berry development stages (pea and veraison) enhanced the plants’ ability to withstand PC-induced stress. The concentration of 3 mg/l Brs elevated some metabolic activities, including insoluble sugar, total carbohydrates, proline, and total phenol. Additionally, it increased the antioxidant enzyme activity. Meanwhile, 2 mg/l appeared to be the most effective concentration in achieving the highest cluster and berry weight, enhanced total soluble solids (TSS) and firmness, and reduced weight loss over shelf life. In conclusion, applying Brs could be a promising strategy to alleviate the adverse effect of abiotic stress on table grapes.

Research on a Trellis Grape Stem Recognition Method Based on YOLOv8n-GP

Grapes are an important cash crop that contributes to the rapid development of the agricultural economy. The harvesting of ripe fruits is one of the crucial steps in the grape production process. However, at present, the picking methods are mainly manual, resulting in wasted time and high costs. Therefore, it is particularly important to implement intelligent grape picking, in which the accurate detection of grape stems is a key step to achieve intelligent harvesting. In this study, a trellis grape stem detection model, YOLOv8n-GP, was proposed by combining the SENetV2 attention module and CARAFE upsampling operator with YOLOv8n-pose. Specifically, this study first embedded the SENetV2 attention module at the bottom of the backbone network to enhance the model’s ability to extract key feature information. Then, we utilized the CARAFE upsampling operator to replace the upsampling modules in the neck network, expanding the sensory field of the model without increasing its parameters. Finally, to validate the detection performance of YOLOv8n-GP, we examined the effectiveness of the various keypoint detection models constructed with YOLOv8n-pose, YOLOv5-pose, YOLOv7-pose, and YOLOv7-Tiny-pose. Experimental results show that the precision, recall, mAP, and mAP-kp of YOLOv8n-GP reached 91.6%, 91.3%, 97.1%, and 95.4%, which improved by 3.7%, 3.6%, 4.6%, and 4.0%, respectively, compared to YOLOv8n-pose. Furthermore, YOLOv8n-GP exhibits superior detection performance compared with the other keypoint detection models in terms of each evaluation indicator. The experimental results demonstrate that YOLOv8n-GP can detect trellis grape stems efficiently and accurately, providing technical support for advancing intelligent grape harvesting.

Fruit flexible collecting trajectory planning based on manual skill imitation for grape harvesting robot

The flexible collection is vital for the intelligent grape-picking robot. In view of the reliable operation method obtained by long-term training of human prior skill, a fruit flexible collecting trajectory planning method based on manual skill imitation for grape harvesting robot is proposed. The method involves capturing manual teaching trajectory data using a motion capture system, preprocessing the data, extracting features from multiple teaching trajectories, and forming a probability distribution through Gaussian mixture model – Gaussian mixture regression (GMM-GMR). And combined with the key point of manual operation trajectory, the general trajectory generated by GMR is segmented and further imitated by kernelized movement primitives (KMP) to obtain the reference trajectory, respectively. An optimization method for hyperparameter adaptation KMP (O-KMP) was proposed to meet the trajectory fitting effect of multiple key points. Mean square error (MSE) was used to evaluate the deviation of the trajectory from the reference trajectory. The partial optimal trajectory is selected and integrated into a single trajectory. Two experiments were conducted to investigate imitation: For the same starting and ending points task, the MSE of the trajectory generated by O-KMP decreased by 15.274% compared to the original fixed hyperparameter KMP. For different placement tasks, the MSE of the trajectory generated by the O-KMP decreased by 7.296% compared to the original KMP. Finally, the robot arm of the actuator visually presents different task states for the compliant placement of fresh grapes.

Low-Alcohol and Nonalcoholic Wines: From Production to Cardiovascular Health, along with Their Economic Effects

This review aims to create a communication tool for low-alcohol and nonalcoholic wine production, catering to scientists, educators, students, and wine producers in the field. With health concerns regarding alcohol consumption, the need for information on low-alcohol wines is essential. This paper outlines the methods for the pre-fermentation (leaf area reduction, early grape harvest, grape must dilution, filtration of grape juice and addition of glucose oxidase), mid-fermentation (employing non-saccharomyces yeasts, using genetically modified yeasts through metabolic engineering, and controlling yeast nutrition), and post-fermentation (nanofiltration and reverse osmosis, osmotic distillation, pervaporation, spinning cone column, vacuum distillation, and multi-stage membrane-based systems) stages and their effects on wine quality. It also presents evidence of the impact of alcoholic, low-alcohol, and nonalcoholic wines on cardiovascular health. Finally, the potential market for low-alcohol and nonalcoholic wines is discussed. Key findings indicate a shift toward low-alcohol alternatives due to health, economic, and social factors and consumer interest in healthier lifestyles. Low-alcohol and nonalcoholic wines offer health benefits, particularly cardiovascular health, presenting an opportunity for winemakers to cater to a health-conscious market. From an economic perspective, the low-alcohol and nonalcoholic wine market is poised to grow and diversify its revenue streams. The development of high-quality low-alcohol and nonalcoholic wines, which can command premium prices, enhances profitability. The changing regulatory landscape in Europe, with a focus on transparency in alcohol labeling and nutritional information, aligns with the new consumer preferences and regulatory standards.

Hand Gesture Controlled Robot for Smart Agriculture Monitoring System

Harvesting presents a significant obstacle in the agricultural sector. Workers face hazards and hardships as they visit each plant to harvest fruits. Combining robotic systems with modern technology is becoming more common in order to automate or semi-automate labor-intensive tasks, including grape harvesting. To improve output per worker hour, we provide a semi-automatic system to help in fruit harvesting. The user can remotely control a robotic arm attached to a rover as it roams the orchard using a hand glove equipped with multiple sensors. The robotic arm may be remotely positioned to gather the fruits thanks to these sensors. The design of a four-degree-of-freedom robotic arm, a wireless control interface, and a sensor-equipped hand glove are all covered in this study. This project also includes the system setup as well as the testing and assessment that was conducted in a controlled laboratory environment. Keywords— Hand Gesture Robot, Agriculture Monitoring, Controlled Robot.

MONITORING OF PESTICIDE RESIDUES IN GRAPEVINE LEAVES UNDER VARIANT FUNGAL DISEASE MANAGEMENT

Food contamination is the result of over-reliance on fungicides in crop production. The presence of pesticide residues in agricultural commodities needs to be strategically solved by applying gentle agrotechnical procedures. The research aimed to evaluate the effect of the treatment of grapevine with fungicides on the content and mobility of 4 active substances in the leaves of the variety Hibernal. The experiment included a control variant treated with fungicides and an untreated variant. We focused on monitoring the active substances of fungicides used in the first half of the vegetation: azoxystrobin, cyflufenamid, difenoconazole, myclobutanil, and another 25 active substances, in terms of multi-residue analysis methodologies. Grape leaves for analysis were collected on two dates: in the phenological phase of berry development BBCH 73 and 14 days after grape harvest – BBCH 91. Samples were prepared according to STN EN 15662. For qualitative analyzes of residues, we used the QuEChERS method in combination with liquid (LC-MS/MS) and gas (GC-MS/MS) chromatography with tandem mass spectrometry. In the untreated variant, the contents of residues from both leaves collection were in undetectable values. In the leaf samples of the treated variant collected in BBCH 73, we established higher values of residues than the MRL determines, namely for azoxystrobin 0.083 mg/kg (MRL – 0.01 mg/kg). Azoxystrobin is the active substance of the Quadris max fungicide, and we applied this preparation 41 days before the first collection of leaves. In the analyzes of leaf sampling from the treated variant after grape harvest in BBCH 91, we found a decrease in the content of all monitored residues below detectable values. We consider the gradual degradation of residues in biological materials to be a very favorable result from the point of view of their impact on consumer health and the environment. Through visual observations of the vegetation, we found out that even the untreated variant had a perfect state of health. Hibernal is a variety suitable for biological production systems, and we assume that even in vintages with high pressure of fungal diseases, it is possible to maintain the health of the grapevine with ecological products. Using the appropriate grape variety combined with the right agrotechnical interventions makes it possible to use safer ecological practices to produce healthy food, maintaining sustainability and a healthy natural environment. The research will continue in the early Table grape varieties, where the vegetation period is shorter, and space for breaking down the residues is more difficult.

THE IMPACT OF CLIMATE CHANGE ON THE SUSTAINABILITY OF WINE PRODUCTION AND THE STRUCTURE OF WINE CONSUMPTION IN THE NORTHEAST REGION OF ROMANIA

This study was carried out with the aim of investigating and analysing different aspects related to viticulture and wine production in the northeast region of Romania. The methodology focused on the use of statistical data and field research, with an emphasis on the impact of potential climate change on wine production and consumer preferences. The analysis of the evolution of vine cultivation in the northeast region of Romania was carried out using statistical data on grape harvest, area planted to vines and wine production. The results showed significant changes in these indicators over the period analysed (2013-2022), reflecting the dynamics of the wine industry in the region. A survey of a sample of 50 respondents provided relevant data on their preferences. Analysis of this data revealed information on preferred wine types, consumption habits and purchasing preferences. Although the population‘s preference for white wine is evident, climate change may pose a challenge for the region, and in the future, it may be necessary to adapt vineyard locations and cultivate vine varieties more suitable for red wine production. These issues have important implications for planning and developing the future of the wine industry in the northeast region.

Unveiling the transformations in phytochemicals and grape features: a thorough examination of 'Italia' and 'Bronx Seedless' cultivars throughout multiple berry development stages

Understanding the physical and phytochemical characteristics of grape cultivars across different berry development stages is crucial for optimizing grape production and quality in the agricultural and viticultural industries. The study, therefore, investigated the physical characteristics and phytochemical composition of 'Italia' and 'Bronx Seedless' grape cultivars harvested across six distinct periods. In grape cultivars displayed an intriguing journey in terms of resveratrol, ranging from 5.96 mg/kg in Period I to 11.59 mg/kg in Period VI. These vital compounds known for contributing to grape color and potential health benefits showed substantial variation across the grape cultivars and harvest periods. In addition, significant variations in phytochemical compositions were observed between 'Italia' and 'Bronx Seedless' grape cultivars, with 'Italia' generally exhibiting higher concentrations of key compounds such as resveratrol, pterostilbene, anthocyanidins, and flavonoids. The longitudinal analysis across six berry developmental periods highlighted a progressive increase in the concentrations of these phytochemicals in cultivar, indicating a dynamic evolution of grape biochemistry over time. Particularly, delphinidin-3-O-glycoside, cyanidin-3-O-glycoside, and petunidin-3-O-glycoside showed marked increases, indicating significant growth in anthocyanin content from Period I to Period VI. Utilizing PCA biplots and a hierarchical clustering heatmap, the study visually represented the relationships and variances among various phytochemical components. The insights revealed how certain compounds clustered together, suggesting similarities and dissimilarities. The positioning of compounds on these plots indicated their significance in characterizing grape cultivars and their maturation over time. In summary, the data underlined the strong influence of berry development time on phytochemical composition, emphasizing the importance of strategic grape harvesting to attain desired phytochemical profiles for wine or other grape products. The findings provide valuable insights for grape growers, winemakers, and researchers aiming to exploit the full potential of these compounds in grape-based products and for those interested in understanding the dynamics of grape phytochemistry.

ВИНОГРАДАРСТВО ЧЕЧЕНСКОЙ РЕСПУБЛИКИ В СОВЕТСКОЕ ВРЕМЯ (1954−1991), УСПЕХИ И ПРОБЛЕМЫ

The article discusses issues related to the unsuccessful introduction of viticulture in the administrative regions of the Chechen Autonomous Soviet Socialist Republic, where grapevine culture was new or non-traditional. These regions are Malgobeksky, Kurchaloevsky, Shalinsky, Grozny-Selsky districts. It has been established that the main reason for the spread of viticulture was the state’s desire to employ unemployed population and the high profitability of the industry. For this purpose, collective and state farms, which previously specialized in the cultivation of grain crops, feed production and livestock breeding, were restructured. The state allocated sufficient funds and material resources for the formation and functioning of a new sub-sector of the agro-industrial complex of the republic in these areas. However, hopes were not justified. The reasons that contributed to attempts to accelerate the introduction of grapevine culture in the “new” regions of the republic, as well as the failure of work in this direction, have been identified. An analysis of the activities of farms involved in the development of viticulture in these areas was carried out. Excesses of higher authorities have been established in planning for wine state farms the volume of new plantings of vineyards, achieving the planned yield and gross grape harvest, as well as planned targets for financial and economic indicators, and in the absence of proper consideration of soil and climatic factors and their compliance with the economic and biological characteristics of the grape culture. As a result, it was revealed that this crop was not adaptable to local conditions, which was reflected in the low survival rate of plantings, the high sparsity of plantings and their unprofitability for further exploitation. All wine farms were unprofitable. The factor of psychological incompatibility of the local population to this culture also had a certain influence. At the same time, all these undesirable phenomena intensified due to the fact that they coincided with the time of the weakening of the foundations of the state under the slogans of perestroika, the fight against alcoholism and drunkenness, and later − with the tragic events of the collapse of the USSR and their negative consequences. It is concluded that the widespread involvement of “new” regions in the development of viticulture was not a fully thought-out campaign. This led, in particular, to disastrous results: the vineyards were written off before they reached productive age. In the future, introducing grapevine culture here is not economically feasible.

Fusion deep learning with pre-post harvest quality management of grapes within the realm of supply chain management

It is becoming increasingly vital in supply chain management to use different algorithms, particularly when it comes to pre and post-harvesting of grapes. This is especially true in the wine industry. Grapes must be processed both before and after harvesting as part of the management process for supply chains in the food industry. The grape bunch identification in vineyards was performed using machine learning at various stages of growth, including early stages immediately after flowering and intermediate stages when the grape bunch reached intermediate developmental stages. The machine learning method can predict annual grape output and also identify grape harvesting. The impressive performance of the pre-trained model shows that architecture training using different algorithms differs in the performance of grape predictions. We achieved 100% accuracy in grape prediction using LR, DT, RF, NUSVC, Adaboost and gradient algorithms, while KNN and SVC lag behind with an accuracy of 83.33% each. Our model includes the color and size of the grapes to differ in grape quality using a variety of grape images as a reference. It is capable of predicting the maturity stage of grapes by predicting Brix, TA and pH values (ranging between 18.20–25.70, 5.67–9.83 and 2.93–3.77) according to the size and color of grapes.We compared different algorithms and their performances by evaluating grape quality prediction accuracy, processing time and memory consumption.

Morning Glory Flower Detection in Aerial Images Using Semi-Supervised Segmentation with Gaussian Mixture Models

The invasive morning glory, Ipomoea purpurea (Convolvulaceae), poses a mounting challenge in vineyards by hindering grape harvest and as a secondary host of disease pathogens, necessitating advanced detection and control strategies. This study introduces a novel automated image analysis framework using aerial images obtained from a small fixed-wing unmanned aircraft system (UAS) and an RGB camera for the large-scale detection of I. purpurea flowers. This study aimed to assess the sampling fidelity of aerial detection in comparison with the actual infestation measured by ground validation surveys. The UAS was systematically operated over 16 vineyard plots infested with I. purpurea and another 16 plots without I. purpurea infestation. We used a semi-supervised segmentation model incorporating a Gaussian Mixture Model (GMM) with the Expectation-Maximization algorithm to detect and count I. purpurea flowers. The flower detectability of the GMM was compared with that of conventional K-means methods. The results of this study showed that the GMM detected the presence of I. purpurea flowers in all 16 infested plots with 0% for both type I and type II errors, while the K-means method had 0% and 6.3% for type I and type II errors, respectively. The GMM and K-means methods detected 76% and 65% of the flowers, respectively. These results underscore the effectiveness of the GMM-based segmentation model in accurately detecting and quantifying I. purpurea flowers compared with a conventional approach. This study demonstrated the efficiency of a fixed-wing UAS coupled with automated image analysis for I. purpurea flower detection in vineyards, achieving success without relying on data-driven deep-learning models.

An Unstructured Orchard Grape Detection Method Utilizing YOLOv5s

Rising labor costs and a workforce shortage have impeded the development and economic benefits of the global grape industry. Research and development of intelligent grape harvesting technologies is desperately needed. Therefore, rapid and accurate identification of grapes is crucial for intelligent grape harvesting. However, object detection algorithms encounter multiple challenges in unstructured vineyards, such as similar background colors, light obstruction from greenhouses and leaves, and fruit occlusion. All of these factors contribute to the difficulty of correctly identifying grapes. The GrapeDetectNet (GDN), based on the YOLO (You Only Look Once) v5s, is proposed to improve grape detection accuracy and recall in unstructured vineyards. dual-channel feature extraction attention (DCFE) is a new attention structure introduced in GDN. We also use dynamic snake convolution (DS-Conv) in the backbone network. We collected an independent dataset of 1280 images after a strict selection process to evaluate GDN’s performance. The dataset encompasses examples of Shine Muscat and unripe Kyoho grapes, covering a range of complex outdoor situations. The results of the experiment demonstrate that GDN performed outstandingly on this dataset. Compared to YOLOv5s, this model increased metrics such as 2.02% of mAP0.5:0.95, 2.5% of mAP0.5, 1.4% of precision, 1.6% of recall, and 1.5% of F1 score. Finally, we test the method on a grape-picking robot, and the results show that our algorithm works remarkably well in harvesting experiments. The results indicate that the GDN grape detection model in this study exhibits high detection accuracy. It is proficient in identifying grapes and demonstrates good robustness in unstructured vineyards, providing a valuable empirical reference for the practical application of intelligent grape harvesting technology.

A lightweight grape detection model in natural environments based on an enhanced YOLOv8 framework.

Grapefruit and stem detection play a crucial role in automated grape harvesting. However, the dense arrangement of fruits in vineyards and the similarity in color between grape stems and branches pose challenges, often leading to missed or false detections in most existing models. Furthermore, these models' substantial parameters and computational demands result in slow detection speeds and difficulty deploying them on mobile devices. Therefore, we propose a lightweight TiGra-YOLOv8 model based on YOLOv8n. Initially, we integrated the Attentional Scale Fusion (ASF) module into the Neck, enhancing the network's ability to extract grape features in dense orchards. Subsequently, we employed Adaptive Training Sample Selection (ATSS) as the label-matching strategy to improve the quality of positive samples and address the challenge of detecting grape stems with similar colors. We then utilized the Weighted Interpolation of Sequential Evidence for Intersection over Union (Wise-IoU) loss function to overcome the limitations of CIoU, which does not consider the geometric attributes of targets, thereby enhancing detection efficiency. Finally, the model's size was reduced through channel pruning. The results indicate that the TiGra-YOLOv8 model's mAP(0.5) increased by 3.33% compared to YOLOv8n, with a 7.49% improvement in detection speed (FPS), a 52.19% reduction in parameter count, and a 51.72% decrease in computational demand, while also reducing the model size by 45.76%. The TiGra-YOLOv8 model not only improves the detection accuracy for dense and challenging targets but also reduces model parameters and speeds up detection, offering significant benefits for grape detection.

The Wisdom of Bacchus: Emblematic, Iconographic and Literary Allusions in the Hermitage Painting by P. P. Rubens

The painting “Bacchus” by Peter Paul Rubens (State Hermitage Museum, St Petersburg) has frequently attracted the attention of both local and foreign researchers. In this article, we question the interpretation of the painting as a simple allegory of the autumn grape harvest and the celebration of production of young wine. Bacchanalian subjects since Antiquity have been loaded with additional meanings associated with regeneration and creative potentials. The latter aspect was picked up and developed by Renaissance artists. Rubens followed often that tradition. L. D. Davis saw in the Hermitage painting a metaphor of the creative method of the Flemish painter, who trusted intuitive impulses more than rigid rules. We share partially this point of view, but we propose to consider the named work in a broader sense than that scholar did. It seems to us that Rubens presented in “Bacchus” his allegorical self-portrait, emphasizing his love of life and his philosophical emancipation. Thus, the Flemish artist expressed his opposition to moralizing and short-sighted opinions in contemporary culture and his desire to return to the breadth of the Renaissance vision. As a consequence, the allusions contained in his painting to “The Andrians” by Titian, some emblems by Andrea Alciato, as well as the new Rubens interpretation of Comus, an ancient character, which John Milton used in his didactic mask a few years before the creation of Hermitage work, — don’t seem accidental. The portly Bacchus in the painting is presented as the lord of earthly diversity and boundless abundance, at the same time he is a wise mentor-judge, indicating how to properly handle all this wealth open to human race. The concept of the boon as the right disposal of freedom and desires, reflected in iconographic system of the Hermitage painting, fits with the ideas of Plato’s dialogue “Feast”.

A fully automatic grape harvesting robot

A fully automatic grape harvesting robot

Effects of Climate Change and Phenological Monitoring of the Indigenous Godello Variety in a Territory of Heroic Viticulture and Biosphere Reserve

In the year 2023, the phenological behaviour of the indigenous Godello variety of vineyard was evaluated at Souto Chao, located in the north-west of the Iberian Peninsula, which is a wine-growing region and considered as the place of Designation of Origin (Ribeira Sacra DO). In 2017 and 2018, a similar study was carried out on the same plants of Godello variety, but this latest study aimed to ascertain the nature and extent of changes in the crop’s phenology within the timeframe between the initial two years analysed (2017 and 2018) and the present year, 2023. The scale used for study was the one proposed by the BBCH of Lorenz. The average length of the vegetative cycle in the initial two years was 167 days (161 and 174 days in 2017 and 2018, respectively), while in 2023 it was 164 days. The results obtained show a longer vegetative cycle in 2018, with significant differences between the beginning and end of the different phenological phases. Of the three years analysed, 2018 stands out showing a significant deviation from the average. Moreover, there is a close relationship between the phenological behaviour of the Godello variety and certain climatic parameters. Temperature is the most decisive factor, specifically the average annual minimum temperature, which was lower in 2018. In addition, the highest thermal requirements were observed in that same year, with figures slightly above 5200 GDD. As for the historical harvest dates, there are only two recorded years in which the grape harvest took place in August, namely in 2017 and 2023. In this geographical region, the grape harvest, with the exception of the two years mentioned above, usually takes place in September, as was the case in 2018. The vulnerability of viticulture to climate change depends on the magnitude of the impacts. Global warming is the great challenge for the wine business and will force changes in vineyard management to curb its most damaging effects. Its most obvious effects, such as the rise in average global temperature or the decrease and redistribution of rainfall, increasingly in the form of occasional and intense storms, have gone from perception to certainty.