The Variability of Berry Parameters Could Be an Indicator of the Potential Quality of the Vineyard.

BACKGROUND: Berry quality potential from a single vineyard is mainly defined based on some physicochemical parameters and subjective assessments. In this way, berry maturity variability would be a key factor affecting berry quality. METHODS: This trial aimed to study the effects of the maturity variability of berries harvested from plots of low (~37,080 kg ha-1), middle (~12,545 kg ha-1), and high (~1476 kg ha-1) quality potential on berry and wine physicochemical parameters of Cabernet Sauvignon in two consecutive seasons. The quality potential of the plots was defined by the winemakers considering mostly yield per hectare and the final price of their wines. RESULTS: The berry heterogeneous maturity of soluble solids and berry weight in Cabernet Sauvignon was confirmed. The coefficient of variability (CV) of berry weight of high-quality plots was high at véraison and decreased as ripening progressed, reaching CV of 19.9% at harvest. Low-quality plots showed the lowest CV of berry weight in all the studied dates, whereas high-quality plots presented the lowest CV in soluble solids content of berries, reaching a 5.1% of variability at harvest. The physicochemical parameters showed that high-quality plots were characterized by high levels of soluble solids and phenolic maturity parameters, whereas samples from low-quality plots reached high berry weight and malic acid content. Berry differences among the physicochemical parameters determined wine quality, which allowed for plots to be classified by their potential quality at harvest. CONCLUSIONS: Studying maturity variability of soluble solids and berry weight will allow for sampling to be sectorized within a vineyard to reduce the extremes of maturity that would affect wine quality and productive goals of winemakers.

Preliminary Evaluation of New Wearable Sensors to Study Incongruous Postures Held by Employees in Viticulture.

Musculoskeletal Disorders (MSDs) stand as a prominent cause of injuries in modern agriculture. Scientific research has highlighted a causal link between MSDs and awkward working postures. Several methods for the evaluation of working postures, and related risks, have been developed such as the Rapid Upper Limb Assessment (RULA). Nevertheless, these methods are generally applied with manual measurements on pictures or videos. As a consequence, their applicability could be scarce, and their effectiveness could be limited. The use of wearable sensors to collect kinetic data could facilitate the use of these methods for risk assessment. Nevertheless, the existing system may not be usable in the agricultural and vine sectors because of its cost, robustness and versatility to the various anthropometric characteristics of workers. The aim of this study was to develop a technology capable of collecting accurate data about uncomfortable postures and repetitive movements typical of vine workers. Specific objectives of the project were the development of a low-cost, robust, and wearable device, which could measure data about wrist angles and workers' hand positions during possible viticultural operations. Furthermore, the project was meant to test its use to evaluate incongruous postures and repetitive movements of workers' hand positions during pruning operations in vineyard. The developed sensor had 3-axis accelerometers and a gyroscope, and it could monitor the positions of the hand-wrist-forearm musculoskeletal system when moving. When such a sensor was applied to the study of a real case, such as the pruning of a vines, it permitted the evaluation of a simulated sequence of pruning and the quantification of the levels of risk induced by this type of agricultural activity.

Transcriptome analysis reveals activation of detoxification and defense mechanisms in smoke-exposed Merlot grape (Vitis vinifera) berries.

A significant consequence of climate change is the rising incidence of wildfires. When wildfires occur close to wine grape (Vitis vinifera) production areas, smoke-derived volatile phenolic compounds can be taken up by the grape berries, negatively affecting the flavor and aroma profile of the resulting wine and compromising the production value of entire vineyards. Evidence for the permeation of smoke-associated compounds into grape berries has been provided through metabolomics; however, the basis for grapevines' response to smoke at the gene expression level has not been investigated in detail. To address this knowledge gap, we employed time-course RNA sequencing to observe gene expression-level changes in grape berries in response to smoke exposure. Significant increases in gene expression (and enrichment of gene ontologies) associated with detoxification of reactive compounds, maintenance of redox homeostasis, and cell wall fortification were observed in response to smoke. These findings suggest that the accumulation of volatile phenols from smoke exposure activates mechanisms that render smoke-derived compounds less reactive while simultaneously fortifying intracellular defense mechanisms. The results of this work lend a better understanding of the molecular basis for grapevines' response to smoke and provide insight into the origins of smoke-taint-associated flavor and aroma attributes in wine produced from smoke-exposed grapes.

Strategies to Increase the Phosphorus Content in the Soil Profile of Vineyards Grown in Subtropical Climates.

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.

Integrative genomics reveals the polygenic basis of seedlessness in grapevine.

Seedlessness is a crucial quality trait in table grape (Vitis vinifera L.) breeding. However, the development of seeds involved intricate regulations, and the polygenic basis of seed abortion remains unclear. Here, we combine comparative genomics, population genetics, quantitative genetics, and integrative genomics to unravel the evolution and polygenic basis of seedlessness in grapes. We generated the haplotype-resolved genomes for two seedless grape cultivars, "Thompson Seedless" (TS, syn. "Sultania") and "Black Monukka" (BM). Comparative genomics identified a ∼4.25 Mb hemizygous inversion on Chr10 specific in seedless cultivars, with seedless-associated genes VvTT16 and VvSUS2 located at breakpoints. Population genomic analyses of 548 grapevine accessions revealed two distinct clusters of seedless cultivars, and the identity-by-descent (IBD) results indicated that the origin of the seedlessness trait could be traced back to "Sultania." Introgression, rather than convergent selection, shaped the evolutionary history of seedlessness in grape improvement. Genome-wide association study (GWAS) analysis identified 110 quantitative trait loci (QTLs) associated with 634 candidate genes, including previously unidentified candidate genes, such as three 11S GLOBULIN SEED STORAGE PROTEIN and two CYTOCHROME P450 genes, and well-known genes like VviAGL11. Integrative genomic analyses resulted in 339 core candidate genes categorized into 13 functional categories related to seed development. Machine learning-based genomic selection achieved a remarkable prediction accuracy of 97% for seedlessness in grapevines. Our findings highlight the polygenic nature of seedlessness and provide candidate genes for molecular genetics and an effective prediction for seedlessness in grape genomic breeding.

Comparative Analysis of TLS and UAV Sensors for Estimation of Grapevine Geometric Parameters.

Understanding geometric and biophysical characteristics is essential for determining grapevine vigor and improving input management and automation in viticulture. This study compares point cloud data obtained from a Terrestrial Laser Scanner (TLS) and various UAV sensors including multispectral, panchromatic, Thermal Infrared (TIR), RGB, and LiDAR data, to estimate geometric parameters of grapevines. Descriptive statistics, linear correlations, significance using the F-test of overall significance, and box plots were used for analysis. The results indicate that 3D point clouds from these sensors can accurately estimate maximum grapevine height, projected area, and volume, though with varying degrees of accuracy. The TLS data showed the highest correlation with grapevine height (r = 0.95, p < 0.001; R2 = 0.90; RMSE = 0.027 m), while point cloud data from panchromatic, RGB, and multispectral sensors also performed well, closely matching TLS and measured values (r > 0.83, p < 0.001; R2 > 0.70; RMSE < 0.084 m). In contrast, TIR point cloud data performed poorly in estimating grapevine height (r = 0.76, p < 0.001; R2 = 0.58; RMSE = 0.147 m) and projected area (r = 0.82, p < 0.001; R2 = 0.66; RMSE = 0.165 m). The greater variability observed in projected area and volume from UAV sensors is related to the low point density associated with spatial resolution. These findings are valuable for both researchers and winegrowers, as they support the optimization of TLS and UAV sensors for precision viticulture, providing a basis for further research and helping farmers select appropriate technologies for crop monitoring.

Rootstock Effects on Fruit Yield and Quality of 'BRS Tainá' Seedless Table Grape in Semi-Arid Tropical Conditions.

In viticulture, choosing the most suitable rootstock for a specific scion cultivar is an efficient and cost-effective way to increase yield and enhance the physicochemical characteristics of the fruit. The objective of this study was to evaluate the agronomic performance of the 'BRS Tainá' grapevine on different rootstocks under the conditions of the Sub-Middle São Francisco Valley. The main experimental factor consisted of eight rootstocks (IAC 313, IAC 572, IAC 766, 101-14 MgT, Paulsen 1103, Ramsey, SO4, and Teleki 5C), arranged in randomized blocks with four replicates. The experiment was conducted over four production cycles, from 2021 to 2023, in a commercial crop area in Petrolina, PE, Brazil. There were significant effects of rootstocks for the yield and number of bunches per plant, as well as berry length and firmness. 'BRS Tainá' achieved the highest yield (22.2 kg per plant) when grafted onto the Paulsen 1103 rootstock, which was superior to the yield on 101-14 MgT, IAC 313, and IAC 572 rootstocks. The highest number of bunches (88) was obtained with 'BRS Tainá' grafted on Paulsen 1103, while the lowest number (63) was obtained on IAC 572; both these rootstocks were not significantly different from the other rootstocks. For all scion-rootstock combinations, the mean values for soluble solid (SS) content, titratable acidity (TA), and the SS/TA ratio were similar to those previously described for 'BRS Tainá', meeting the commercialization standard. The results for the yield and number of bunches per plant indicate the suitability of grafting 'BRS Tainá' on Paulsen 1103 under the semi-arid tropical conditions of the São Francisco Valley.

Unearthing Grape Heritage: Morphological Relationships between Late Bronze-Iron Age Grape Pips and Modern Cultivars.

The grapevine was one of the earliest domesticated fruit crops and has been cultivated since ancient times. It is considered one of the most important fruit crops worldwide for wine and table grape production. The current grape varieties are the outcome of prolonged selection initiated during the domestication process of their wild relative. Recent genetic studies have shed light on the origins of the modern domestic grapevine in western Europe, suggesting that its origin stems from the introgression between eastern domestic grapes and western wild grapes. However, the origin of ancient grapevines remains largely unexplored. In this study, we conducted an extensive analysis of 2228 well-preserved waterlogged archaeological grape pips from two sites in Sardinia (Italy), dated to the Late Bronze Age (ca. 1300-1100 BC) and the Iron Age (4th and 3rd centuries BC). Using morphometrics and linear discriminant analyses, we compared the archaeological grape pips with modern reference collections to differentiate between wild and domestic grape types and to investigate similarities with 330 modern cultivars. Grape pips from the Late Bronze Age displayed a high percentage of similarity with domesticated grapevines, with a small percentage assigned to wild ones, while the majority of grape pips from the Iron Age were classified as domestic. Discriminant analyses revealed that both white and red grape varieties were cultivated during the Late Bronze and Iron Ages, suggesting a high level of diversification in grape cultivation. Furthermore, a high percentage of archaeological grape pips from both periods showed strong similarities with modern cultivars from the Caucasus and Balkans. This suggests that the great diversity of grapevines present in Sardinia could result from interbreeding between western Asian cultivars and local grapevines that began in the Late Bronze Age. Additionally, a substantial proportion of archaeological grape pips exhibited similar morphometric characteristics to two important Mediterranean grape cultivars: "Muscat à petits grains blancs" and "Garnacha".

Non-destructive quantification of key quality characteristics in individual grapevine berries using near-infrared spectroscopy.

It is crucial for winegrowers to make informed decisions about the optimum time to harvest the grapes to ensure the production of premium wines. Global warming contributes to decreasing acidity and increasing sugar levels in grapes, resulting in bland wines with high contents of alcohol. Predicting quality in viticulture is thus pivotal. To assess the average ripeness, typically a sample of one hundred berries representative for the entire vineyard is collected. However, this process, along with the subsequent detailed must analysis, is time consuming and expensive. This study focusses on predicting essential quality parameters like sugar and acid content in Vitis vinifera (L.) varieties 'Chardonnay', 'Riesling', 'Dornfelder', and 'Pinot Noir'. A small near-infrared spectrometer was used measuring non-destructively in the wavelength range from 1 100 nm to 1 350 nm while the reference contents were measured using high-performance liquid chromatography. Chemometric models were developed employing partial least squares regression and using spectra of all four grapevine varieties, spectra gained from berries of the same colour, or from the individual varieties. The models exhibited high accuracy in predicting main quality-determining parameters in independent test sets. On average, the model regression coefficients exceeded 93% for the sugars fructose and glucose, 86% for malic acid, and 73% for tartaric acid. Using these models, prediction accuracies revealed the ability to forecast individual sugar contents within an range of ± 6.97 g/L to ± 10.08 g/L, and malic acid within ± 2.01 g/L to ± 3.69 g/L. This approach indicates the potential to develop robust models by incorporating spectra from diverse grape varieties and berries of different colours. Such insight is crucial for the potential widespread adoption of a handheld near-infrared sensor, possibly integrated into devices used in everyday life, like smartphones. A server-side and cloud-based solution for pre-processing and modelling could thus avoid pitfalls of using near-infrared sensors on unknown varieties and in diverse wine-producing regions.

Site-Independent Mapping of Clay Content in Vineyard Soils via Mobile Proximal Gamma-Ray Spectrometry and Machine Learning Calibrations.

Vineyards hold considerable soil variability between regions and plots, and there is frequently large soil heterogeneity within plots. Clay content in vineyard soils is of interest with respect to soil management, environmental monitoring, and wine quality. However, spatially resolved clay mapping is laborious and expensive. Gamma-ray spectrometry (GS) is a suitable tool for predicting clay content in precision agriculture when locally calibrated, but it has scarcely been tested site-independently and in vineyards. This study evaluated GS to predict clay content with a site-independent calibration and four machine learning algorithms (Support Vector Machines, Random Forest, k-Nearest Neighbors, and Bayesian regulated neuronal networks) in eight vineyards from four German vine-growing regions. Clay content in the studied soils ranged from 62 to 647 g kg-1. The Random Forest calibration was most suitable. Test set evaluation revealed good model performance for the entire dataset with RPIQ = 4.64, RMSEP = 56.7 g kg-1, and R2 = 0.87; however, prediction quality varied between the sites. Overall, GS with the Random Forest model calibration was appropriate to predict the clay content and its spatial distribution, even for heterogeneous geopedological settings and in individual plots. Therefore, GS is considered a valuable tool for soil mapping in vineyards, where clay content and product quality are closely linked.

Microplastics in vineyard soils: First insights from plastic-intensive viticulture systems.

In the terrestrial environment, microplastics in specialty cropping systems have not been studied so far. Viticulture as a potential plastic-intensive management form and a land use with high erosion risks, plays an important role in transport and distribution of material to other terrestrial and aquatic systems. This paper is a first investigation of microplastics in vineyard soils, assessing the spatial distribution and composition of microplastics in organically and conventionally managed viticulture, and relates it to the macroplastic collected at the vineyards. Topsoils (0-10, 10-30 cm) and plastic particles on soil surfaces from eight vineyard lots were sampled. Four of the vineyards were under organic and four underconventional management and they were all located in the Moselle and Saar Wine Region (Rhineland-Palatinate, Germany). Microplastic analysis was performed via µFTIR chemical imaging after wet-chemical microplastic extraction from soil samples. The mean microplastic concentration was 4200 ± 2800 p kg-1 (mean ± SD), with detected mean sizes of 230 µm ± 300 µm. Most abundant polymers were PP (35.2 %), PA (25.3 %) and PE (15.5 %). The distribution pattern showed higher microplastic concentration in topsoil, at middle and bottom slope position. The smallest particle sizes were found in subsoil samples and bottom position. Thus, erosion is assumed to be a potential downhill transport pathway. According to our dataset, management seems to have no significant influence on microplastic abundance, but affects polymer composition. Polymer composition of micro- and macroplastics partly coincide, thus in-situ fragmentation, is considered the major input source. Based on our findings, we recommend further investigation of plastic pathways in speciality crop systems like viticulture.

Potential to take root in viticulture? An evaluation of mycorrhizal inoculants on the growth and nutrient uptake of young wine grapes planted in live field soil.

AIMS: Incorporating biofertilizers, such as arbuscular mycorrhizal fungal (AM) fungal inoculants, into vineyard management practices may enhance vine growth and reduce environmental impact. Here, we evaluate the effects of commercially available and local AM fungal inoculants on the growth, root colonization, and nutrient uptake of wine grapes (Vitis vinifera) when planted in a field soil substrate. METHODS AND RESULTS: In a greenhouse experiment, young wine grapes were planted in a field soil substrate and inoculated with one of three commercially available mycorrhizal inoculant products, or one of two locally collected whole soil inoculants. After 4 months of growth, inoculated vines showed no differences in plant biomass, colonization of roots by AM fungi, or foliar macronutrient concentrations compared to uninoculated field soil substrate. However, vines grown with local inoculants had greater shoot biomass than vines grown with mycorrhizal inoculant products. CONCLUSIONS: Although effects from inoculations with AM fungi varied by inoculant type and source, inoculations may not improve young vine performance in field soils with a resident microbial community.

French low-input winegrowing demonstration farms: A dataset of their operations traceability and sustainability performances.

This article presents data on farming operations traceability and associated performances, for winegrowing systems with low phytosanitary inputs. 343 farms were sampled from the DEPHY network: a governmental initiative to produce references on phytosanitary-efficient cropping systems under real conditions of production. Data were collected every campaign between 2017 and 2020, by multiple extensionists who provide support to the voluntarily enlisted growers, in exchange for traceability of their practices and their commitment to reducing pesticide use. The dataset includes raw data of farming operations (date, machinery, inputs, products and doses, etc.), and performance indicators computed at farm level (Treatment Frequency Index, workload, expenses, greenhouse gas emissions, etc.). This information could be useful to researchers, policymakers and agricultural consultants. It provides leads to understand how winegrowers manage to successfully reduce their pesticide consumption, as well as assessing the triggers and entailments of such transitions.

GrapeMOTS: UAV vineyard dataset with MOTS grape bunch annotations recorded from multiple perspectives for enhanced object detection and tracking.

Object Detection and Tracking have provided a valuable tool for many tasks, mostly time-consuming and prone-to-error jobs, including fruit counting while in the field, among others. Fruit counting can be a challenging assignment for humans due to the large quantity of fruit available, which turns it into a mentally-taxing operation. Hence, it is relevant to use technology to ease the task of farmers by implementing Object Detection and Tracking algorithms to facilitate fruit counting. However, those algorithms suffer undercounting due to occlusion, which means that the fruit is hidden behind a leaf or a branch, complicating the detection task. Consequently, gathering the datasets from multiple viewing angles is essential to boost the likelihood of recording the images and videos from the most visible point of view. Furthermore, the most critical open-source datasets do not include labels for certain fruits, such as grape bunches. This study aims to unravel the scarcity of public datasets, including labels, to train algorithms for grape bunch Detection and Tracking by considering multiple angles acquired with a UAV to overcome fruit occlusion challenges.

EscaYard: Precision viticulture multimodal dataset of vineyards affected by Esca disease consisting of geotagged smartphone images, phytosanitary status, UAV 3D point clouds and Orthomosaics.

The "EscaYard" dataset comprises multimodal data collected from vineyards to support agricultural research, specifically focusing on vine health and productivity. Data collection involved two primary methods: (1) unmanned aerial vehicle (UAV) for capturing multispectral images and 3D point clouds, and (2) smartphones for detailed ground-level photography. The UAV used was DJI Matrice 210 V2 RTK, equipped with a Micasense Altum sensor, flying at 30 m above ground level to ensure detailed coverage. Ground-level data were collected using smartphones (iPhone X and Xiaomi Poco X3 Pro), which provided high-resolution images of individual plants. These images were geotagged, enabling location mapping, and included data on the phytosanitary status and number of grape clusters per plant. Additionally, the dataset contains RTK GNSS data, offering high-precision location information for each vine, enhancing the dataset's value for spatial analysis. Moreover, the dataset is structured to support various research applications, including agronomy, remote sensing, and machine learning. It is particularly suited for studying disease detection, yield estimation, and vineyard management strategies. The high-resolution and multispectral nature of the data allows for a detailed analysis of vineyard conditions. Potential reuse of the dataset spans multiple disciplines, enabling studies on environmental monitoring, geographic information systems (GIS), and precision agriculture. Its comprehensive nature makes it a valuable resource for developing and testing algorithms for disease classification, yield prediction, and plant phenotyping. For instance, the images of bunches and grape leaves can be used to train object detection algorithms for accurate disease detection and consequent precise spraying. Moreover, yield prediction algorithms can be trained by extracting the phenotypic traits of the grape bunches. The "EscaYard" dataset provides a foundation for advancing research in sustainable farming practices, optimising crop health, and improving productivity through precise agricultural technologies.

Developing a simple and efficient modeling solution for predicting key phenological stages of table grapes in a non-traditional viticulture zone in south Asia.

Phenological shifts are one of the most visible signs of climatic variability and change in the biosphere. However, modeling plant phenological responses has always been a key challenge due to climatic variability and plant adaptation. Grapevine is a phenologically sensitive crop and, thus, its developmental stages are affected by the increase in temperature. The goal of this study was to develop a temperature-based grapevine phenology model (GPM) for predicting key developmental stages for different table grape cultivars for a non-traditional viticulture zone in south Asia. Experiments were conducted in two vineyards at two locations (Chakwal and Islamabad) in the Pothawar region of Pakistan during the 2019 and 2020 growing seasons for four cultivars including Perlette, King's Ruby, Sugraone and NARC Black. Detailed phenological observations were obtained starting in January until harvest of the grapes. The Mitscherlich monomolecular equation was used to develop the phenology model for table grapes. There was a strong non-linear correlation between the Eichhorn and Lorenz phenological (ELP) scale and growing degree days (GDD) for all cultivars with coefficient of determinations (R2) ranging from 0.90 to 0.94. The results for model development indicated that GPM was able to predict phenological stages with high skill scores, i.e., a root mean square (RMSE) of 2.14 to 2.78 and mean absolute error (MAE) of 1.86 to 2.26 days. The prediction variability of the model for the onset timings of phenological stages was up to 3 days. The results also reveal that the phenology model based on GDD approach provides an efficient planning tool for viticulture industry in different grape growing regions. The proposed methodology, being a simpler one, can be easily applied to other regions and cultivars as a predictor for grapevine phenology.

Adverse effects of the Bordeaux mixture copper-based fungicide on the non-target vineyard pest Lobesia botrana.

BACKGROUND: Bordeaux mixture is a copper-based fungicide commonly used in vineyards to prevent fungal and bacterial infections in grapevines. However, this fungicide may adversely affect the entomological component, including insect pests. Understanding the impacts of Bordeaux mixture on the vineyard pest Lobesia botrana is an increasing concern in the viticultural production. RESULTS: Bordeaux mixture had detrimental effects on the development and reproductive performance of L. botrana. Several physiological traits were adversely affected by copper-based fungicide exposure, including a decrease in larval survival and a delayed larval development to moth emergence, as well as a reduced reproductive performance through a decrease in female fecundity and fertility and male sperm quality. However, we did not detect any effect of Bordeaux mixture on the measured reproductive behaviors (mating success, pre-mating latency and mating duration). CONCLUSION: Ingestion by larvae of food contaminated with Bordeaux mixture had a negative effect on the reproductive performance of the pest L. botrana, which could affect its population dynamics in vineyards. Although this study highlighted collateral damage of Bordeaux mixture on L. botrana, the potential impact of copper-based fungicides on vineyard diversity, including natural predators is discussed and needs to be taken in consideration in integrated pest management. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Estimation of Intercepted Solar Radiation and Stem Water Potential in a Table Grape Vineyard Covered by Plastic Film Using Sentinel-2 Data: A Comparison of OLS-, MLR-, and ML-Based Methods.

In the framework of precision viticulture, satellite data have been demonstrated to significantly support many tasks. Specifically, they enable the rapid, large-scale estimation of some viticultural parameters like vine stem water potential (Ψstem) and intercepted solar radiation (ISR) that traditionally require time-consuming ground surveys. The practice of covering table grape vineyards with plastic films introduces an additional challenge for estimation, potentially affecting vine spectral responses and, consequently, the accuracy of estimations from satellites. This study aimed to address these challenges with a special focus on the exploitation of Sentinel-2 Level 2A and meteorological data to monitor a plastic-covered vineyard in Southern Italy. Estimates of Ψstem and ISR were obtained using different algorithms, namely, Ordinary Least Square (OLS), Multivariate Linear Regression (MLR), and machine learning (ML) techniques, which rely on Random Forest Regression, Support Vector Regression, and Partial Least Squares. The results proved that, despite the potential spectral interference from the plastic coverings, ISR and Ψstem can be locally estimated with a satisfying accuracy. In particular, (i) the OLS regression-based approach showed a good performance in providing accurate ISR estimates using the near-infrared spectral bands (RMSE < 8%), and (ii) the MLR and ML algorithms could estimate both the ISR and vine water status with a higher accuracy (RMSE < 7 for ISR and RMSE < 0.14 MPa for Ψstem). These results encourage the adoption of medium-high resolution multispectral satellite imagery for deriving satisfying estimates of key crop parameters even in anomalous situations like the ones where plastic films cover the monitored vineyard, thus marking a significant advancement in precision viticulture.

Bacterial Community Structure Responds to Soil Management in the Rhizosphere of Vine Grape Vineyards.

The microbial communities of the rhizospheres of vineyards have been subject to a considerable body of research, but it is still unclear how the applied soil cultivation methods are able to change the structure, composition, and level of diversity of their communities. Rhizosphere samples were collected from three neighbouring vineyards with the same time of planting and planting material (rootstock: Teleki 5C; Vitis vinifera: Müller Thurgau). Our objective was to examine the diversity occurring in bacterial community structures in vineyards that differ only in the methods of tillage procedure applied, namely intensive (INT), extensive (EXT), and abandoned (AB). For that we took samples from two depths (10-30 cm (shallow = S) and 30-50 cm (deep = D) of the grape rhizosphere in each vineyard and the laboratory and immediately prepared the slices of the roots for DNA-based analysis of the bacterial communities. Bacterial community structure was assessed by means of PCR-DGGE analysis carried out on the v3 region of 16S rRNA gene. Based on the band composition of the DGGE profiles thus obtained, the diversity of the microbial communities was evaluated and determined by the Shannon-Weaver index (H'). Between the AB and EXT vineyards at the S depth, the similarity of the community structure was 55%; however, the similarity of the D samples was more than 80%, while the difference between the INT samples and the other two was also higher than 80%. Based on our results, we can conclude that intensive cultivation strongly affects the structure and diversity of the bacterial community.

Use of an automatic fruit-zone cooling system to cope with multiple summer stresses in Sangiovese and Montepulciano grapes.

Grapevines are frequently subjected to heatwaves and limited water availability during ripening. These conditions can have consequences for the physiological health of the vines. Moreover, the situation is often exacerbated by intense solar radiation, resulting in reduced yield due to sunburn and a decline in quality. In light of these challenges, our study aimed to develop a fruit-zone cooling system designed to mitigate grape sunburn damage and improve the microclimate conditions within the vineyard. The system comprises a network of proximal sensors that collect microclimate data from the vineyard and an actuator that activates nebulizers when the temperature exceeds the threshold of 35°C. The research was conducted over two years (2022 and 2023) in Bologna (Italy) using potted Sangiovese and Montepulciano vines. These two vintages were characterized by high temperatures, with varying amounts of rainfall during the test period, significantly impacting the evaporative demand, which was notably higher in 2023. Starting from the veraison stage we compared three treatments: Irrigated control vines (WW); Control vines subjected to 50% water restriction during the month of August (WS); WS vines treated with nebulized water in the bunch area during the stress period (WS+FOG). The application of nebulized water effectively reduced the temperature of both the air around the clusters and the clusters themselves. As we expected, Montepulciano showed better single leaf assimilation rate and stomatal conductance under non-limiting water conditions than Sangiovese while their behavior was unaffected under water-scarce conditions. Importantly, for the first time, we demonstrated that nebulized water positively affected gas exchange in both grape varieties. In addition to this, the vines treated with the misting system exhibited higher productivity compared to WS vines without affecting technological maturity. In the 2023 vintage, the activation of the system prevented the ripening blockage that occurred in Montepulciano under water stress. Regarding the concentration of total anthocyanins, a significant increase in color was observed in WS+FOG treatment, suggesting a predominant role of microclimate on anthocyanin biosynthesis and reduction of oxidative phenomena. In conclusion, the fruit-zone cooling system proved to be an invaluable tool for mitigating the adverse effects of multiple summer stresses.