Grapevines in cold regions are prone to frost damage in winter. Due to its adverse effects on soil structure, plant damage, high operational costs, and limited mechanization feasibility, buried soil overwintering has been gradually replaced by no-burial overwintering techniques, which are now the primary focus for mitigating frost damage in wine grapes. While current research focuses on the selection of thermal insulation materials, less attention has been paid to the insulation mechanism of covering materials and covering methods. In this study, we investigated the insulation performance of two covering materials (tarpaulin and insulation blanket) combined with six height treatments (5-30 cm) to analyze the effect of insulation space volume on no-buried-soil overwintering. The results show that the thermal insulation performance of the insulation blanket is significantly better than that of the tarpaulin. The 5 cm height treatment under the tarpaulin cover and the 25 cm height treatment under the insulation blanket cover exhibited the best thermal insulation performance. Using a neural network machine learning approach, we constructed a model related to the height of the insulation material and facilitate the model's accurate predictions, in which tarpaulin R2branches = 0.92, R220 cm = 0.99, and R240 cm = 0.99 and insulation blanket R2branches = 0.89, R220 cm = 0.98, and R240 cm = 0.99. The model predicted optimal insulation heights of 6 cm for the tarpaulin and 22 cm for the insulation blanket. Factors like solar radiation within the insulation space, ground radiation, airflow, and material thermal conductivity affect the optimal insulation height for different materials. This study used a neural network model to predict the optimal insulation heights for different materials, providing systematic theoretical guidance for the overwintering cultivation of wine grapes and aiding the safe development of the wine grape industry in cold regions.

Cold climate viticulture is challenged by climatic variability, including increased frost risk, shorter growing seasons, and unpredictable weather events that impact vine productivity and grape quality. Global warming is altering traditional viticulture zones, prompting the exploration of new regions for grape cultivation, the selection of climate-resilient cultivars, and the implementation of adaptive practices. This review synthesizes recent advances in adaptive viticulture practices and plant growth regulator applications, highlighting novel molecular and physiological insights on cold stress resilience and berry quality. Key strategies include delayed winter pruning to mitigate frost damage, osmoprotectant application to improve freeze tolerance, and canopy management techniques (cluster thinning and defoliation) to enhance berry ripening and wine composition. Their effectiveness depends on vineyard microclimate, soil properties and variety-specific physiological response. Cover cropping is examined for its role in vine vigor regulation, improving soil microbial diversity, and water retention, though its effectiveness depends on soil type, participation patterns, and vineyard management practices. Recent transcriptomic and metabolomic studies have provided new regulatory mechanisms in cold stress adaptation, highlighting the regulatory roles of abscisic acid, brassinosteroids, ethylene, and salicylic acid in dormancy induction, oxidative stress response, and osmotic regulation. Reflective mulch technologies are currently examined for their ability to enhance light interception, modulating secondary metabolite accumulation, improving technological maturity (soluble solids, pH, and titratable acidity) and enhancing phenolic compounds content. The effectiveness of these strategies remains highly site-specific, influenced by variety selection and pruning methods particularly due to their differences on sugar accumulation and berry weight. Future research should prioritize long-term vineyard trials to refine these adaptive strategies, integrate genetic and transcriptomic insights into breeding programs to improve cold hardiness, and develop precision viticulture tools tailored to cold climate vineyard management.

Grapevines are subjected to many physiological and environmental stresses that influence their vegetative and reproductive growth. Water stress, cold damage, and pathogen attacks are highly relevant stresses in many grape-growing regions. Precision viticulture can be used to determine and manage the spatial variation in grapevine health within a single vineyard block. Newer technologies such as remotely piloted aircraft systems (RPASs) with remote sensing capabilities can enhance the application of precision viticulture. The use of remote sensing for vineyard variation detection has been extensively investigated; however, there is still a dearth of literature regarding its potential for detecting key stresses such as winter hardiness, water status, and virus infection. The main objective of this research is to examine the performance of modern remote sensing technologies to determine if their application can enhance vineyard management by providing evidence-based stress detection. To accomplish the objective, remotely sensed data such as the normalized difference vegetation index (NDVI) and thermal imaging from RPAS flights were measured from six commercial vineyards in Niagara, ON, along with the manual measurement of key viticultural data including vine water stress, cold stress, vine size, and virus titre. This study verified that the NDVI could be a useful metric to detect variation across vineyards for agriculturally important variables including vine size and soil moisture. The red-edge and near-infrared regions of the electromagnetic reflectance spectra could also have a potential application in detecting virus infection in vineyards.

Phosphate fertilizers are applied to the soil surface, especially in vineyards in production in subtropical regions. Nowadays, phosphorus (P) is not incorporated into the soil to avoid mechanical damage to the root system in orchards. However, over the years, successive surface P applications can increase the P content only in the topsoil, maintaining low P levels in the subsurface, which can reduce its use by grapevines. For this reason, there is a need to propose strategies to increase the P content in the soil profile of established orchards. The study aimed to evaluate the effect of management strategies to (i) increase the P content in the soil profile; (ii) enhance the grape production; and (iii) maintain the grape must composition. An experiment on the 'Pinot Noir' grape in full production was carried out over three crop seasons. The treatments were without P application (C), P on the soil surface without incorporation (SP), P incorporated at 20 cm (IP20), P incorporated at 40 cm (IP40), and twice the P dose incorporated at 40 cm (2IP40). The P concentration in leaves at flowering and veraison, P content in the soil, grape production and its components, and chemical parameters of the grape must (total soluble solids, total polyphenols, total titratable acidity, total anthocyanins, and pH) were evaluated. The P concentration in leaves did not differ among the P application modes. The application of P associated with soil mobilization, especially at 20 cm depth, increased grape production. The P application modes did not affect the values of the chemical parameters of the grape must except for the total anthocyanins, which had the highest values when the vines were subjected to 2IP40. Finally, the P application and incorporation into the soil profile was an efficient strategy for increasing the grape production in full production vineyards.

In the context of increasing global food demand and the urgent need for production processes optimization, plant protection products play a key role in safeguarding crops from insects, pests, and fungi, responsible of plant diseases proliferation and yield losses. Despite the inaccurate distribution of conventional aerial spraying performed by airplanes and helicopters, Unmanned Aerial Spraying Systems (UASSs) offer low health risks and operational cost solutions, preserving crops and soil from physical damage. This study explores the impact of UASS flight height (2 m and 2.5 m above ground level), speed (1 m s-1 and 1.5 m s-1), and position (over the canopy and the inter-row) on vineyard aerial spraying efficiency by analysing Water Sensitive Papers droplet coverage, density, and Number Median Diameter using a MATLAB script. Flight position factor, more than others, influenced the application results. The specific configuration of 2 m altitude, 1.5 m s-1 cruising speed, and inter-row positioning yielded the best results in terms of canopy coverage, minimizing off-target and ground dispersion, and represented the best setting to facilitate droplets penetration, reaching the lowest parts generally more affected from disease. Further research is needed to assess UASS aerial PPP distribution effectiveness and environmental impact in agriculture, crucial for technology implementation, especially in countries where aerial treatments are not yet permitted.

The C & ocirc;a region in inner-northern Portugal heavily relies on viticulture, which is a cornerstone of its economy and cultural identity. Understanding the intricate relationship between climatic variables and wine production (WP) is crucial for adapting management practices to changing climatic conditions. This study employs machine learning (ML), specifically random forest (RF) regression, to predict grapevine yields in the C & ocirc;a region using high-resolution climate data for 2004-2020. SHAP (SHapley Additive exPlanations) values are used to potentially explain the non-linear relationships between climatic factors and WP. The results reveal a complex interplay between predictors and WP, with precipitation emerging as a key determinant. Higher precipitation levels in April positively impact WP by replenishing soil moisture ahead of flowering, while elevated precipitation and humidity levels in August have a negative effect, possibly due to late-season heavy rainfall damaging grapes or creating more favorable conditions for fungal pathogens. Moreover, warmer temperatures during the growing season and adequate solar radiation in winter months favor higher WP. However, excessive radiation during advanced growth stages can lead to negative effects, such as sunburn. This study underscores the importance of tailoring viticultural strategies to local climatic conditions and employing advanced analytical techniques such as SHAP values to interpret ML model predictions effectively. Furthermore, the research highlights the potential of ML models in climate change risk reduction associated with viticulture, specifically WP. By leveraging insights from ML and interpretability techniques, policymakers and stakeholders can develop adaptive strategies to safeguard viticultural livelihoods and stable WP in a changing climate, particularly in regions with a rich agrarian heritage, such as the C & ocirc;a region.

Precision agriculture (PA), also known as smart farming, has emerged as an innovative solution to address contemporary challenges in agricultural sustainability. A particular sector within PA, precision viticulture (PV), is specifically tailored for vineyards. The advent of the Internet of Things (IoT) has facilitated the acquisition of higher resolution meteorological and soil data obtained through in situ sensing. The integration of machine learning (ML) with IoT-enabled farm machinery stands at the forefront of the forthcoming agricultural revolution. These data allow ML-based forecasting as an alternative to conventional approaches, providing agronomists with predictive tools essential for improved land productivity and crop quality. This study conducts a thorough examination of vineyards with a specific focus on three key aspects of PV: mitigating frost damage, analyzing soil moisture levels, and addressing grapevine diseases. In this context, several ML-based models are proposed in a real-world scenario involving a vineyard located in Southern Italy. The test results affirm the feasibility and efficacy of the ML models, demonstrating their potential to revolutionize vineyard management and contribute to sustainable agricultural practices.

The wine sector, among the most profitable agricultural segments, has been markedly affected by the ongoing climate change impacts, such as warmer climate conditions with higher frequency of extreme temperatures and a trend of decreasing precipitation. All this results in higher evaporative demand and therefore higher occurrence of water stress events leading to advancement of temperature-sensitive phenological stages (e.g., budburst and ripening). Such negative effects eventually affect berry development and quality, especially in historically valuable viticultural areas, forcing winegrowers to work within a compressed harvest period to maintain wine typicity. In this work we examined the relationship between environmental variables (air and soil temperature, relative humidity, precipitation, and solar radiation), phenology, berry, and wine quality for the two varieties (Chardonnay and Teroldego) in Trentino Alto-Adige/South Tyrol (Italy) over 36 years. Huglin Index (a bioclimatic heat index), growing degree days (measure of heat accumulation), and overall mean temperature showed linear increase (p < 0.001) in the last years, while no variations were recorded for precipitations. Despite no major effects being observed for phenological interval lengths, the onset of most of the phenological stages for both varieties had significantly (p < 0.001) advanced. However, i) early budburst pushed the budburst-flowering interphase by-1.2 days every two years toward putative colder periods with increased late frost probability and potential slower phenological progression towards flowering, and ii) early veraison shifted the veraison-ripening interphase by 0.25 day per year into warmer periods that oppositely impose faster phenological advancement. Hence, a substantial equilibrium in the seasonal growing length over years was maintained. Potential carry-over effects from the previous season were observed, particularly associated with heat requirements to unlock early phenological events, raising additional concerns on the additive effects of climate change to viticulture. Generally, white wine quality increased (p < 0.05) over the years, while red and sparkling wines remained unaffected. This was putatively related to accurate harvest date decision-making dictated by berry quality parameters: sugar-to-acidity ratio for Chardonnay and bunch sanitary status for Teroldego. Overall, this work provides evidence of the dynamics involved in climate change, and, to our knowledge, its overlooked effects on viticulture, thus providing new insights that can contribute to further developing adaptive strategies.