In the viticulture sector, robots are being employed more frequently to increase productivity and accuracy in operations such as vineyard mapping, pruning, and harvesting, especially in locations where human labor is in short supply or expensive. This paper presents the development of an algorithm for grape maturity estimation in the framework of vineyard management. An object detection algorithm is proposed based on You Only Look Once (YOLO) v7 and its extensions in order to detect grape maturity in a white variety of grape (Assyrtiko grape variety). The proposed algorithm was trained using images received over a period of six weeks from grapevines in Drama, Greece. Tests on high-quality images have demonstrated that the detection of five grape maturity stages is possible. Furthermore, the proposed approach has been compared against alternative object detection algorithms. The results showed that YOLO v7 outperforms other architectures both in precision and accuracy. This work paves the way for the development of an autonomous robot for grapevine management.

The increased cost of labor in modern viticulture stemming from the nature of operations that require physical strength and precision, coupled with labor shortages, poses a significant constraint in facilitating and scheduling seasonal activities. Therefore, autonomous collaborative robots present a potential solution for achieving sustainable development objectives and decreasing operational expenditures in agricultural operations. The current paper presents an economic assessment of collaborative robots (or cobots for short) in comparison to conventional labor for four different cultivars in Greece in a lifecycle costing methodological framework. The selected cultivars are Asyrtiko, Cabernet Sauvignon, Merlot and Tempranillo, which are cultivated by two private wineries in the area of interest. All the relevant expenses of their annual production were distributed to agricultural operations, and eight scenarios were developed to compare conventional and cobot practices. The results indicate the great potential of cobots regarding specific viticultural operations such as weed control, pruning, herbiciding and topping. The adoption of cobots in these operations has the potential to contribute to sustainable agriculture by reducing labor costs and addressing labor shortages, while also increasing the efficiency and precision of these tasks. Nevertheless, the defoliation and tying operations appeared to be inefficient in most cases in comparison to conventional labor practices. Overall, the annual equivalent costs could be reduced by up to 11.53% using cobots, even though the projected lifetime of the cobots plays a significant role in the cost-effectiveness of autonomous robotic labor in viticulture. In conclusion, cobots could be instrumental in the Greek viticulture, integrating innovation and high-quality products toward sustainable agricultural development.

Grape harvesting based on estimated in-field maturity indices can reduce the costs of pre-harvest exhaustive sampling and chemical analysis, as well as the costs of post-harvest storage and waste across the production chain due to the non-climacteric nature of grapes, meaning that they are not able to reach desired maturity levels after being removed from the vine. Color imaging is used extensively for intact maturity estimation of fruits. In this study, color imaging is combined with Intervals’ Numbers (INs) technique to associate grape cluster images to maturity-related indices such as the total soluble solids (TSSs), titratable acidity (TA), and pH. A neural network regressor is employed to estimate the three indices for a given input of an IN representation of CIELAB color space. The model is tested on one hundred Tempranillo cultivar images, and the mean-square error (MSE) is calculated for the performance evaluation of the model. Results reveal the potential use of the Ins’ NN regressor for TSS, TA, and pH assessment as a non-destructive, efficient, fast, and cost-effective tool able to be integrated into an autonomous harvesting robot.

Greek wines excel in quality and exports, but the viticultural sector faces significant challenges from complex supply chains, shifting European policies, and the growing need for sustainability amidst climate change and economic pressures. External environmental costs could affect significantly the decision-making process of farmers, reflecting a broader evaluation of sustainability in viticulture. This study evaluates the economic and environmental impacts of organic, integrated, and conventional viticulture management systems in Drama, Greece using a life cycle (LC) approach and data envelopment analysis (DEA) to determine efficiency, quantify environmental impacts in monetary terms, and incorporate these costs into the analysis. Organic management systems have lower energy consumption and emissions compared to integrated and conventional systems, with organic systems ranging from 4546 to 6573 kWh/ha in energy use and 1358 to 1795 kg CO₂ eq./ha in emissions, while integrated and conventional systems range from 9157 to 12,109 kWh/ha and 2961 to 3661 kg CO₂ eq./ha. The DEA analysis reveals that most organic systems perform efficiently when accounting for environmental costs, whereas conventional systems face significant efficiency declines, with only a few maintaining optimal performance. Policy-supported transitions based on the provider gets principle are crucial for balancing economic and environmental goals in viticulture, as the integration of shadow prices significantly impacts efficiency.

Drama is a wine region in northern Greece with a local economy based on agricultural production. Despite its historical and geographical setting, the wine tourism industry is not very well developed in the wine-growing region of Drama. Although the sustainability of territorial development is often linked to local food and wine heritage, it seems that the implicated parties are not totally convinced. For this qualitative case study, we first conducted interviews with the management of the local wineries to determine the reason behind the low number of wine tourists in the area. Then, a workshop was organized, and all relevant parties were invited to increase awareness through education while also attempting to find mutually agreeable solutions through working group table discussions and the presentation of findings. Taking advantage of and preserving the cultural heritage through the cooperation of the related regional businesses, regional/central authorities, and non-governmental organizations (NGOs) was concluded to be an important tool for organizing new initiatives that will boost wine tourism.

Besides the other factors, the microclimate (terroir) influences the quality characteristics of wine. The Assyrtiko variety has adapted to the volcanic soil of Santorini but under climate change, finding an ideal location for full grape ripening represents a challenge in preserving the PDO quality of Santorini wines. Thus, this study aims to evaluate the effect of location and harvesting time on the quality of Assyrtiko wine. It assessed the location effect (three distant plots of land in three distant areas of the island) on the composition of grapes (water uptake, pH, sugar, and organic acid accumulation) during the ripening. The grapes were vinified using the same procedure. The aromatic volatile profile of the wines was evaluated with GC-MS. A two-way ANOVA revealed that besides location and harvest time, their interaction is also significant for the parameters studied, except for the interaction effect involving sugar content. The analysis of volatile aromatic compounds revealed that the wine from grapes harvested at a later date had a higher aromatic intensity with notes of citrus, white-fleshed, and tropical fruits. This wine surpasses the levels of 2-phenylethanol, isoamyl acetate, linalool, and 2-phenylethyl ester with 17.8%, 7.7%, 21.1%, and 15.6%, respectively, compared to the immediate next in descending order. Results suggest that the grape variety is better suited to the local climatic conditions when full grape ripeness is reached by the end of the growing season.