Pinot Noir Vineyards Research Articles

Contributions of Hanseniaspora species to Pinot Noir microbial terroir in Oregon's Willamette Valley wine region.

Hanseniaspora yeasts are frequently found in uninoculated wine fermentations, and depending upon the species present, their contributions to the wine may be positive or negative. We found that in Oregon's Willamette Valley, the most common species of Hanseniaspora in Pinot Noir vineyards was the known spoilage organism, H. uvarum. This species was one of the strongest contributors to differences in fungal communities between different vineyards and was enriched during typical Pinot Noir processing. These results support Hanseniaspora as an integral and functional component of vineyard "microbial terroir" within Oregon.

Effect of the Shadow Pixels on Evapotranspiration Inversion of Vineyard: A High-Resolution UAV-Based and Ground-Based Remote Sensing Measurements

Due to the proliferation of precision agriculture, the obstacle of estimating evapotranspiration (ET) and its components from shadow pixels acquired from remote sensing technology should not be neglected. To accurately detect shaded soil and leaf pixels and quantify the implications of shadow pixels on ET inversion, a two-year field-scale observation was carried out in the growing season for a pinot noir vineyard. Based on high-resolution remote sensing sensors covering visible light, thermal infrared, and multispectral light, the supervised classification was applied to detect shadow pixels. Then, we innovatively combined the normalized difference vegetation index with the three-temperature model to quantify the proportion of plant transpiration (T) and soil evaporation (E) in the vineyard ecosystem. Finally, evaluated with the eddy covariance system, we clarified the implications of the shadow pixels on the ET estimation and the spatiotemporal patterns of ET in a vineyard system by considering where shadow pixels were presented. Results indicated that the shadow detection process significantly improved reliable assessment of ET and its components. (1) The shaded soil pixels misled the land cover classification, with the mean canopy cover ignoring shadows 1.68–1.70 times more often than that of shaded area removal; the estimation accuracy of ET can be improved by 4.59–6.82% after considering the effect of shaded soil pixels; and the accuracy can be improved by 0.28–0.89% after multispectral correction. (2) There was a 2 °C canopy temperature discrepancy between sunlit leaves and shaded leaves, meaning that the estimation accuracy of T can be improved by 1.38–7.16% after considering the effect of shaded canopy pixels. (3) Simultaneously, the characteristics showed that there was heterogeneity of ET in the vineyard spatially and that E and T fluxes accounted for 238.05 and 208.79 W·m−2, respectively; the diurnal variation represented a single-peak curve, with a mean of 0.26 mm/h. Our findings provide a better understanding of the influences of shadow pixels on ET estimation using remote sensing techniques.

Irrigation Improves Vine Physiology and Fruit Composition in Grapevine Red Blotch Virus-Infected Vitis vinifera L.

Grapevine red blotch virus (GRBV) negatively impacts vine physiology and fruit quality in <i>Vitis vinifera</i> L. by reducing photosynthetic rate, total soluble solids (TSS), and berry anthocyanin concentration. Currently, growers have few management strategies beyond removal of infected vines, which may be particularly costly in vineyards with high disease incidence. The present study was established in 2018 in a GRBV-infected Pinot noir vineyard in southern Oregon to investigate whether reducing vine stress with cultural practices could dampen the impact of the disease on vine physiology and fruit quality. The effects of control and supplemental levels of irrigation and fertilizer on vine growth and physiology, disease severity, and fruit composition were observed over three years. Supplemental irrigation affected vine physiology and fruit composition in 2019 and 2020, but fertilization had no significant effect over three years. Photosynthetic rate, vegetative growth, vine yield, berry weight, TSS, and titratable acidity were increased with supplemental irrigation while disease severity (symptomatic leaves per vine) was reduced. Supplemental irrigation did not have consistent effects on secondary metabolites, though an increase in anthocyanin concentration was observed in 2020 despite an increase in berry size. Irrespective of applied water amounts, maintaining a higher vine water status effectively increased photosynthesis and canopy size, which resulted in greater sugar accumulation. Ultimately, these results suggest that maintaining a high vine water status (Ψ_stem &gt; -0.8 MPa) may mitigate some of the negative effects of GRBV on vine physiology and fruit composition.

Characterization of Sub-Regional Variation in Saccharomyces Populations and Grape Phenolic Composition in Pinot Noir Vineyards of a Canadian Wine Region.

Wine is a product of grape juice fermentation by yeast. Terroir is a term that encompasses all environmental factors and interactions at a specific geographical site, resulting in the development of regional-specific microbial strains and grape metabolites. In this study we determine the distribution of vineyard-associated wine yeast strains and characterize the flavonoid profile of Pinot Noir grapes among 3 sub-regions in the Okanagan Valley (OV), a major wine region in British Columbia, Canada. Pinot Noir grape samples were collected from 13 vineyards among 3 sub-regions of the OV, namely Kelowna (KE), Naramata-Penticton (NP) and Oliver-Osoyoos (OO), within a week prior to the winery harvesting date in 2016 and 2017. A total of 156 spontaneous Pinot Noir fermentations were conducted and vineyard-associated Saccharomyces strains were isolated from fermentations that reached two-thirds sugar depletion. Using microsatellite genotyping, we identified 103 Saccharomyces cerevisiae strains and 9 Saccharomyces uvarum strains. We also identified Saccharomyces paradoxus in one vineyard using ITS sequencing. We developed a microsatellite database of 160 commercial S. cerevisiae strains to determine the identity of the isolated strains and we include the database herein. Commercial strains were widely distributed across the three sub-regions. Forty-two of our 103 S. cerevisiae strains were equivalent or highly similar to commercial strains whereas the remaining 61 were considered as ‘unknown’ strains. Two S. uvarum strains were previously isolated in other OV studies and none matched the S. uvarum commercial strain BMV58. S. cerevisiae population structure was driven by sub-region, although S. cerevisiae populations did not differ significantly across vintages. S. uvarum and S. paradoxus were only identified in the 2017 vintage, demonstrating dynamic wine yeast populations between vintages. We found that the flavonoid profile of Pinot Noir grapes from the same 13 vineyards was also affected by sub-regional terroir. The anthocyanin content was lower and the proportion of methoxylated anthocyanins and flavonols was higher in Pinot Noir grapes from OO, the warmer sub-region as compared to KE, the cooler sub-region. Our study demonstrates that both yeast populations and metabolites associated with the Pinot Noir variety have sub-regional variation within a viticultural area.

Using Satellite Thermal-Based Evapotranspiration Time Series for Defining Management Zones and Spatial Association to Local Attributes in a Vineyard

A well-planned irrigation management strategy is crucial for successful wine grape production and is highly dependent on accurate assessments of water stress. Precision irrigation practices may benefit from the quantification of within-field spatial variability and temporal patterns of evapotranspiration (ET). A spatiotemporal modeling framework is proposed to delineate the vineyard into homogeneous areas (i.e., management zones) according to their ET patterns. The dataset for this study relied on ET retrievals from multiple satellite platforms, generating estimates at high spatial (30 m) and temporal (daily) resolutions for a Vitis vinifera Pinot noir vineyard in the Central Valley of California during the growing seasons of 2015-2018. Time-series decomposition was used to deconstruct the time series of each pixel into three components: long-term trend, seasonality, and remainder, which indicates daily fluctuations. For each time-series component, a time-series clustering (TSC) algorithm was applied to partition the time series of all pixels into homogeneous groups and generate TSC maps. The TSC maps were compared for spatial similarities using the V-measure statistic. A random forest (RF) classification algorithm was used for each TSC map against six environmental variables (elevation, slope, northness, lithology, topographic wetness index, and soil type) to check for spatial association between ET-TSC maps and the local characteristics in the vineyard. Finally, the TSC maps were used as independent variables against yield (ton ha-1) using analysis of variance (ANOVA) to assess whether the TSC maps explained yield variability. The trend and seasonality TSC maps had a moderate spatial association (V = 0.49), while the remainder showed dissimilar spatial patterns to seasonality and trend. The RF model showed high error matrix-based prediction accuracy levels ranging between 86% and 90%. For the trend and seasonality models, the most important predictor was soil type, followed by elevation, while the remainder TSC was strongly linked with northness spatial variability. The yield levels corresponding to the two clusters in all TSC were significantly different. These findings enabled spatial quantification of ET time series at different temporal scales that may benefit within-season decision-making regarding the amounts, timing, intervals, and location of irrigation. The proposed framework may be applicable to other cases in both agricultural systems and environmental modeling.

Relationships between soil water content, evapotranspiration, and irrigation measurements in a California drip-irrigated Pinot noir vineyard

The Central Valley of California relies on irrigation for crop production, but water resources, particularly groundwater, have reached a critical state due to extended drought periods and overuse by irrigated agriculture. The purpose of the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project is to improve efficiency in vineyard irrigation through field measurements and modeling efforts using remote sensing. In this study, we analyze multi-year timeseries of ground-based soil moisture and evapotranspiration (ET) measurements collected during GRAPEX to identify patterns that may inform future irrigation recommendations based on remotely sensed ET. The study focuses on field data collected in two adjacent Pinot noir vineyards near Lodi, CA from 2013 to 2017. The data used for this analysis are reference evapotranspiration (ETref), actual evapotranspiration (ETa), mean daytime soil water content (SWC) measured to a depth of 90 cm, precipitation, and irrigation. The relationship between SWC and the ratio of ETa/ETref (used as a soil moisture proxy indicator) changes throughout the spring and summer months due to advancing phenological stages and management practices. In early spring, when the interrow cover crop is the primary source of ET, ETa is strongly correlated with SWC. As the vine canopy grows in, the strong correlation breaks down as the vines begin to access to water beyond the depth of the soil moisture sensors. As the soil profile dries out during the summer, the correlation between ETa and SWC once again emerges as the vines become strongly dependent on irrigation. The dynamic interaction between the upper and lower root zone profile and evaporative demand means that the key to understanding vineyard water status using relatively shallow SWC observations is to use them in conjunction with ETa data, so that when both SWC and ETa timeseries are highly correlated vine water status is well defined. This suggests, delaying the initiation of irrigation during the period of rapid vine growth until a clear relationship between SWC and ETa emerges would both reduce the total amount of water used and give the grower more control over vine growth and grape quality affected by water status.

Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence.

Wine aroma profiles are determinant for the specific style and quality characteristics of final wines. These are dependent on the seasonality, mainly weather conditions, such as solar exposure and temperatures and water management strategies from veraison to harvest. This paper presents machine learning modeling strategies using weather and water management information from a Pinot noir vineyard from 2008 to 2016 vintages as inputs and aroma profiles from wines from the same vintages assessed using gas chromatography and chemometric analyses of wines as targets. The results showed that artificial neural network (ANN) models rendered the high accuracy in the prediction of aroma profiles (Model 1; R = 0.99) and chemometric wine parameters (Model 2; R = 0.94) with no indication of overfitting. These models could offer powerful tools to winemakers to assess the aroma profiles of wines before winemaking, which could help adjust some techniques to maintain/increase the quality of wines or wine styles that are characteristic of specific vineyards or regions. These models can be modified for different cultivars and regions by including more data from vertical vintages to implement artificial intelligence in winemaking.

Small scale fungal community differentiation in a vineyard system

Microbes influence the quality of agricultural commodities and contribute to their distinctive sensorial attributes. Increasingly studies have demonstrated not only differential geographic patterns in microbial communities and populations, but that these contribute to valuable regionally distinct agricultural product identities, the most well-known example being wine. However, little is understood about microbial geographic patterns at scales of less than 100 km. For wine, single vineyards are the smallest (and most valuable) scale at which wine is asserted to differ; however, it is unknown whether microbes play any role in agricultural produce differentiation at this scale. Here we investigate whether vineyard fungal communities and yeast populations driving the spontaneous fermentation of fruit from these same vineyards are differentiated using metagenomics and population genetics. Significant differentiation of fungal communities was revealed between four Central Otago (New Zealand) Pinot Noir vineyard sites. However, there was no vineyard demarcation between fermenting populations of S. cerevisiae. Overall, this provides evidence that vineyard microbiomes potentially contribute to vineyard specific attributes in wine. Understanding the scale at which microbial communities are differentiated, and how these communities influence food product attributes has direct economic implications for industry and could inform sustainable management practices that maintain and enhance microbial diversity.

An intercomparison of radiation partitioning models in vineyard canopies

Multiple radiation transfer models with unique clumping indices (a total of five approaches) were evaluated on two Pinot Noir vineyards in Central California over 3 years. In the first approach, a basic clumping index meant for heterogeneous randomly placed clumped canopies was combined with the Campbell and Norman transfer model (C&N–H). The other four approaches, namely, the Campbell and Norman with rectangular hedgerow clumping index (C&N–R), Campbell and Norman with a geometric elliptical hedgerow model (C&N–E), the 4-stream scattering by arbitrary inclined leaves model (4SAIL) with row-crop clumping index, and the discrete anisotropic radiative transfer (DART) models, account for the unique canopy coverage distribution of the vineyard row-structured canopies. Each modeling approach varied in its complexity to predict transmitted solar radiation at ground level and the outputs were compared to solar radiation observed at the surface with an array of pyranometers. All five modeling approaches showed good agreement with the observed values [correlation coefficients (r) ranged from 0.95 to 0.97]. Model performance varied throughout the season due to their sensitivity to canopy growth. Although r values showed good agreement among all approaches, the C&N–E and DART models showed a better “goodness of fit” with lower root mean squared and bias values.

Kaolin treatments on Pinot noir grapevines for the control of heat stress damages

The aim of the study was to verify if vineyard kaolin application during the 2017 hot summer could reduce the negative effects of high temperatures and heat stress on canopy physiological processes, yield and fruit quality. The kaolin was applied once at the beginning of August, at 3% concentration, in a Pinot Noir vineyard. The application was performed only to the west side of the rows, where the vines were more subjected to heat stress. The 2017 summer was very hot, with maximum air temperature higher than 35 °C for several consecutive days in June, July and August and with heat waves that reached 42.3 °C in August. The kaolin coating works by significantly reducing leaf temperatures in comparison to untreated vines, with an average of about − 4 °C and up to −6 °C. Moreover, it maintains high the photosynthetic activity preventing irreversible photoinhibition phenomena, whereas untreated vines exhibit a marked physiological damage with chlorotic and necrotic leaves, dehydrated berries and sunburn damages. At harvest, 30-35% of the untreated vines were affected by severe water stress symptoms and produced unmarketable fruits. In comparison to the untreated vines, those sprayed with kaolin showed a higher yield (+27%), higher anthocyanins (+35%) and higher concentration of organic acids (+11%)

Impact of delayed winter pruning on phenology and ripening kinetics of Pinot Noir grapevines

Climate change impacts viticulture with even stronger effects on sparkling wines. Innovative cultural practices represent effective short-term solutions. Among these, postponement of winter pruning later than budburst delayed both vegetative and reproductive cycles as well as technological maturity of several varieties from different wine regions. This research aims to assess the impact of delayed winter pruning on grapevine performance as a function of training system.The trial was carried out in a Pinot Noir vineyard sited at 385 m asl in Central Italy. Delayed winter pruning was performed when unpruned canes had shoots showing three unfolded leaves (BBCH 13) and compared to standard winter pruning within two separate experiments focused on: i) cane pruning, and ii) spur pruning. Grapevine phenology, vegetative growth, fruit ripening kinetics and productivity of selected vines were assessed over three years. Delayed winter pruning postponed budburst by 20 and 31 days in Guyot and spur pruned cordons, respectively; then, differences diminished over time showing a maximum delay of 17 days at bloom and 7–10 days at harvest. Despite a decrease in yield (ranging from −35 to −47% in cane and spur pruning, respectively), delayed winter pruning increased titratable acidity (40–89%) and reduced sugars (721%) as compared to control vines. Although effects of delayed pruning were stronger in spur pruned vines, delayed winter pruning was effective also on cane-pruned vines, therefore adapting to varieties marked by low basal-node fruitfulness

Bird Management in Blueberries and Grapes

Bird damage to fruit is a long-standing challenge for growers that imposes significant costs because of yield losses and grower efforts to manage birds. We measured bird damage in ‘Bluecrop’ blueberry fields and Pinot noir vineyards in 2012–2014 in Michigan to investigate how year, grower, and forest cover influenced the proportions of bird damage. We tested whether inflatable tubemen (2013–2014) and a methyl anthranilate spray (2015) reduced bird damage in blueberries, and tested the deterrent effect of inflatable tubemen in grapes (2014). Years when crop yield was lower tended to have a higher damage percentage; for blueberries, bird damage was highest in 2012, and in grapes, damage was highest in 2012 and 2014. Neither blueberry fields nor vineyards with inflatable tubemen showed significantly reduced bird damage, although the blueberry fields showed a non-significant trend toward lower damage in the tubemen blocks. Blueberry field halves treated with the methyl anthranilate spray had equivalent bird damage to untreated halves. Our results correspond to previous work showing that percent bird damage varies by year, which was likely because bird consumption of fruit is relatively constant over time, while fruit yield varies. Fruit growers should expect a higher proportion of bird damage in low-fruit contexts, such as low-yield years, and prepare to invest more in bird management at those times. Investigating patterns of bird damage and testing deterrent strategies remain challenges. Bird activity is spatially and temporally variable, and birds’ mobility necessitates tests at large scales.

Evapotranspiration estimates derived using thermal-based satellite remote sensing and data fusion for irrigation management in California vineyards

Irrigation in the Central Valley of California is essential for successful wine grape production. With reductions in water availability in much of California due to drought and competing water-use interests, it is important to optimize irrigation management strategies. In the current study, we investigate the utility of satellite-derived maps of evapotranspiration (ET) and the ratio of actual-to-reference ET (fRET) based on remotely sensed land-surface temperature (LST) imagery for monitoring crop water use and stress in vineyards. The Disaggregated Atmosphere Land EXchange Inverse (ALEXI/DisALEXI) surface-energy balance model, a multi-scale ET remote-sensing framework with operational capabilities, is evaluated over two Pinot noir vineyard sites in central California that are being monitored as part of the Grape Remote-Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). A data fusion approach is employed to combine ET time-series retrievals from multiple satellite platforms to generate estimates at both the high spatial (30 m) and temporal (daily) resolution required for field-scale irrigation management. Comparisons with micrometeorological data indicate reasonable model performance, with mean absolute errors of 0.6 mm day−1 in ET at the daily time step and minimal bias. Values of fRET agree well with tower observations and reflect known irrigation. Spatiotemporal analyses illustrate the ability of ALEXI/DisALEXI/data fusion package to characterize heterogeneity in ET and fRET both within a vineyard and over the surrounding landscape. These findings will inform the development of strategies for integrating ET mapping time series into operational irrigation management framework, providing actionable information regarding vineyard water use and crop stress at the field and regional scale and at daily to multi-annual time scales.

Utility of the two-source energy balance (TSEB) model in vine and interrow flux partitioning over the growing season

For monitoring water use in vineyards, it becomes important to evaluate the evapotranspiration (ET) contributions from the two distinct management zones: the vines and the interrow. Often the interrow is not completely bare soil but contains a cover crop that is senescent during the main growing season (nominally May–August), which in Central California is also the dry season. Drip irrigation systems running during the growing season supply water to the vine plant and re-wet some of the surrounding bare soil. However, most of the interrow cover crop is dry stubble by the end of May. This paper analyzes the utility of the thermal-based two-source energy balance (TSEB) model for estimating daytime ET using tower-based land surface temperature (LST) estimates over two Pinot Noir (Vitis vinifera) vineyards at different levels of maturity in the Central Valley of California near Lodi, CA. The data were collected as part of the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). Local eddy covariance (EC) flux tower measurements are used to evaluate the performance of the TSEB model output of the fluxes and the capability of partitioning the vine and cover crop transpiration (T) from the total ET or T/ET ratio. The results for the 2014–2016 growing seasons indicate that TSEB output of the energy balance components and ET, particularly, over the daytime period yield relative differences with flux tower measurements of less than 15%. However, the TSEB model in comparison with the correlation-based flux partitioning method overestimates T/ET during the winter and spring through bud break, but then underestimates during the growing season. A major factor that appears to affect this temporal behavior in T/ET is the daily LAI used as input to TSEB derived from a remote sensing product. An additional source of uncertainty is the use of local tower-based LST measurements, which are not representative of the flux tower measurement source area footprint.

THE GRAPE REMOTE SENSING ATMOSPHERIC PROFILE AND EVAPOTRANSPIRATION EXPERIMENT.

AbstractParticularly in light of California’s recent multiyear drought, there is a critical need for accurate and timely evapotranspiration (ET) and crop stress information to ensure long-term sustainability of high-value crops. Providing this information requires the development of tools applicable across the continuum from subfield scales to improve water management within individual fields up to watershed and regional scales to assess water resources at county and state levels. High-value perennial crops (vineyards and orchards) are major water users, and growers will need better tools to improve water-use efficiency to remain economically viable and sustainable during periods of prolonged drought. To develop these tools, government, university, and industry partners are evaluating a multiscale remote sensing–based modeling system for application over vineyards. During the 2013–17 growing seasons, the Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project has collected micrometeorological and biophysical data within adjacent pinot noir vineyards in the Central Valley of California. Additionally, each year ground, airborne, and satellite remote sensing data were collected during intensive observation periods (IOPs) representing different vine phenological stages. An overview of the measurements and some initial results regarding the impact of vine canopy architecture on modeling ET and plant stress are presented here. Refinements to the ET modeling system based on GRAPEX are being implemented initially at the field scale for validation and then will be integrated into the regional modeling toolkit for large area assessment.

Agronomical and Chemical Effects of the Timing of Cluster Thinning on Pinot Noir (Clone 115) Grapes and Wines

A two-year study was performed to evaluate the effects of the timing of cluster thinning on Pinot noir grapes and wines in the central coast of California. Vines were thinned to one cluster per shoot at three selected time-points during the growing season, and fruit was harvested and made into wine. No consistent effect of cluster thinning was found in wine phenolic profile or color across a cool (2016) and a warm (2017) growing season. The growing season had a more significant effect than the cluster thinning treatment for most parameters measured. There was no detectable overall sensory difference between the non-thinned control wines and any of the thinned treatment wines. Based on current results, Pinot noir vineyards on the central coast of California can support crop loads that result in Ravaz Index values from 3 to 6 without concern for impacting ripening potential or negatively affecting fruit composition.

Spur Pruning May Be a Viable Option for Oregon Pinot noir Producers Despite Industry Fears of Lower Productivity

Summary Goals: Winegrape production is more costly in Oregon than in other US growing regions, and industry faces rising production costs and labor concerns. Growers are considering ways to reduce labor and introduce mechanization. Spur pruning requires less labor and is more readily mechanized than cane pruning; however, the majority of Oregon growers use cane pruning. We conducted industry surveys and interviews to understand why cane pruning is preferred and determine potential barriers to adopting spur pruning. We conducted a vineyard case study to quantify fruitfulness and yield of cane- and spur-pruned vines to determine the potential for spur pruning in Pinot noir. Key Findings: The majority of survey respondents (76%) primarily used cane pruning on cool climate cultivars because they believe that spur pruning reduces yields and fruit quality and increases fungal and mite pests. A total of 35% believed that spur pruning reduces yield due to vines having unfruitful basal buds. Interviews of Pinot noir growers who use both spur and cane pruning revealed that spur pruning could achieve desired yields, while reducing production costs and labor dependency. Their observations did not support survey respondent concerns about severely reduced yields, fruit quality, and increased mites or diseases. The Pinot noir vineyard case study revealed that cane and spur pruning led to similar yields, cluster size, and fruit ripeness. Data from spur-pruned Pinot noir vines showed that shoots arising from basal, first, and second buds were fruitful. Impact and Significance: Industry perception and lack of experience with spur pruning is preventing adoption. Expectation of low yields is based on industry hearsay, not direct experience. Concerns that spur pruning lowers quality may be derived from mechanization research from regions that focus on quantity, not quality. However, grower interviews and field data show that Pinot noir is fruitful at basal nodes and can be spur pruned without limiting yield or quality based on Oregon standards. Converting to spur pruning reduced pruning cost, and research/demonstration projects are needed to help small, quality-focused industries make necessary adaptations to their production systems.

Daily Mapping of 30 m LAI and NDVI for Grape Yield Prediction in California Vineyards

Wine grape quality and quantity are affected by vine growing conditions during critical phenological stages. Field observations of vine growth stages are too sparse to fully capture the spatial variability of vine conditions. In addition, traditional grape yield prediction methods are time consuming and require large amount grape samples. Remote sensing data provide detailed spatial and temporal information regarding vine development that is useful for vineyard management. In this study, Landsat surface reflectance products from 2013 and 2014 were used to map satellite-based Normalized Difference Vegetation Index (NDVI) and leaf area index (LAI) over two Vitis vinifera L. cv. Pinot Noir vineyards in California, USA. The spatial correlation between grape yield maps and the interpolated daily time series (LAI and NDVI) was quantified. NDVI and LAI were found to have similar performance as a predictor of spatial yield variability, providing peak correlations of 0.8 at specific times during the growing season, and the timing of this peak correlation differed for the two years of study. In addition, correlations with maximum and seasonal-cumulative vegetation indices were also evaluated, and showed slightly lower correlations with the observed yield maps. Finally, the within-season grape yield predictability was examined using a simple strategy in which the relationship between grape yield and vegetation indices were calibrated with limited ground measurements. This strategy has a strong potential to improve the accuracy and efficiency of yield estimation in comparison with traditional approaches used in the wine grape growing industry.

Spatial Variability in Ontario Pinot noir Vineyards: Use of Geomatics and Implications for Precision Viticulture

Relationships among vine water status, soil texture, and vine size were observed in four Ontario Pinot noir vineyards in 2008 and 2009. The vineyards were divided into water status zones using geographic information systems to map the seasonal mean leaf water potential (Ψ) and cane pruning weight (vine size). Leaf Ψ zones were confirmed using k-means clustering. Both seasons were cooler and wetter than average and the range of leaf Ψ defining the water status zones was narrow (−0.59 to −0.95 MPa across all vineyards). Yield, vine size, crop load, anthocyanins, and phenols had the highest coefficients of variability. Higher yields, berry weights, titratable acidity, anthocyanins, and color were occasionally associated with low water status zones. There were no berry composition variables with differences between vine size zones in all four vineyards. Higher yields, cluster numbers, and berry weights were frequently associated with high vine size zones. Principal components analysis separated the vineyards but did not create clusters based on leaf Ψ or vine size. There were notable correlations between vineyard and grape composition variables, and spatial trends were qualitatively related for many of the variables. Significant r2 values that suggested inverse relationships were found in 2008 for leaf Ψ versus anthocyanins, color intensity, and phenols and for vine size versus anthocyanins, while in 2009 there were significant r2 values for soil moisture versus anthocyanins and color intensity that likewise suggested inverse relationships. This study showed that there is potential for using geomatic techniques to understand variability in vineyards, but that erratic weather in eastern North America presents a challenge for understanding the driving forces of such variability.

Impact of Commercial Strain Use on Saccharomyces cerevisiae Population Structure and Dynamics in Pinot Noir Vineyards and Spontaneous Fermentations of a Canadian Winery.

Wine is produced by one of two methods: inoculated fermentation, where a commercially-produced, single Saccharomyces cerevisiae (S. cerevisiae) yeast strain is used; or the traditional spontaneous fermentation, where yeast present on grape and winery surfaces carry out the fermentative process. Spontaneous fermentations are characterized by a diverse succession of yeast, ending with one or multiple strains of S. cerevisiae dominating the fermentation. In wineries using both fermentation methods, commercial strains may dominate spontaneous fermentations. We elucidate the impact of the winery environment and commercial strain use on S. cerevisiae population structure in spontaneous fermentations over two vintages by comparing S. cerevisiae populations in aseptically fermented grapes from a Canadian Pinot Noir vineyard to S. cerevisiae populations in winery-conducted fermentations of grapes from the same vineyard. We also characterize the vineyard-associated S. cerevisiae populations in two other geographically separate Pinot Noir vineyards farmed by the same winery. Winery fermentations were not dominated by commercial strains, but by a diverse number of strains with genotypes similar to commercial strains, suggesting that a population of S. cerevisiae derived from commercial strains is resident in the winery. Commercial and commercial-related yeast were also identified in the three vineyards examined, although at a lower frequency. There is low genetic differentiation and S. cerevisiae population structure between vineyards and between the vineyard and winery that persisted over both vintages, indicating commercial yeast are a driver of S. cerevisiae population structure. We also have evidence of distinct and persistent populations of winery and vineyard-associated S. cerevisiae populations unrelated to commercial strains. This study is the first to characterize S. cerevisiae populations in Canadian vineyards.