Rust mites can be a nuisance pest and require careful monitoring and assessment. Check out the post below written by Dr. Patty Skinkis, Viticulture Extension Specialist & Associate Professor, which provides information on how to deal with these pests.
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Monitoring Vineyards for Grape Rust Mites in Late Summer
Dr. Patty Skinkis, Viticulture Extension Specialist & Associate Professor
Grape rust mites have been a nuisance pest in vineyards of western Oregon for years. They can be found living on grape tissues from early spring through summer. During late summer and into fall, they retreat to overwintering sites in the bark and bud scales. The grape rust mite has been known to cause shoot deformity early in the growing season and stippling of leaves as they advance into the upper canopy in summer. If populations are very high (hundreds to thousands per fully expanded leaf), the leaf tissue can begin to discolor, starting to turn a dark green, then purplish and finally a bronzed color in late summer to early fall. This discoloration can lead to reduced photosynthetic ability of the vines if a large percentage of the vine’s leaf area is damaged.
Monitoring for signs and symptoms of rust mite infestation are important to do throughout the season. However, determining the presence of grape rust mites in your vineyard now (late August and early September) will help determine whether control methods are warranted the following season. We developed a user-friendly method by which to monitor grape rust mites on vine tissues, and this method has since been employed by growers in Oregon to determine presence of rust mites. The protocol for this method is available for use:
Grape tissue washing protocol (link to document)
Visual work flow of protocol (link to document)
Using this method, we were able to determine a strong correlation of stippling symptoms to rust mite presence on small shoots and leaves. The greater the stippling severity on the leaf, the greater the number of rust mites. The bronzing of leaves was also associated with high rust mite numbers, but the symptom was associated with feeding later in the summer on older leaf tissues. Now is your last chance to monitor your vineyards for these symptoms and verifying mite presence before the hustle of harvest. For examples of these symptoms, see the grape rust mite section of the PNW Insect Management Handbook.
If you find significant rust mite damage and presence, it is best to make note of those vineyard blocks that are most damaged and consider your management options for the future. In some cases, you may want to reevaluate your in-season fungicide program, as sulfur has been found to be effective at reducing or maintaining low rust mite populations. Also, it is best to know the infestation status of your vineyard now so that plans can be made to monitor and take action against rust mites shortly after bud break the following spring. Current recommendations exist for early season rust mite control, and those can be found in the pest management guide released by OSU Extension each spring.
For more information about monitoring for rust mites and management, see the following publications and resources:
Schreiner, R.P., P.A. Skinkis, and A.J. Dreves. 2014. A rapid method to assess grape rust mites on leaves and observations from case studies in Western Oregon vineyards. HortTechnology. 24: 38-47.
The grapevine has a certain capacity to buffer itself in a changing environment without disrupting normal developmental processes. How different cultivars of Vitis vinifera respond to changing environmental conditions and viticultural practices beyond their buffering capacity are interesting research questions. It is complicated to consider these effects during a multi-dimensional developmental process like ripening. One approach to describe grape berry ripening is to treat whole clusters as a unit, aggregating all the berries within a cluster together for measurements, resulting in data that represents the average contribution of genes or metabolites during berry ripening. This approach overlooks dimensions of the ripening process at the berry level.
Research that we have conducted in the Deluc Lab found different ripening rates of berries within the same cluster. There is inherent variability within the cluster, the vine, and between vines. However, this is reduced as berries approach maturity in some cultivars. In examining how vineyard practices and changing environments affect fruit composition, we may be able to consider ripening within the cluster and the potential impact on ripening uniformity toward harvest, which we believe to be an indicator of increased quality. Within the Deluc Lab, we are researching the variability of individual berries during ripening to determine if this provides a more accurate depiction of the ripening process. We are collaborating with Drs. James Osborne and Elizabeth Tomasino to further study the effects that persistent berry variability has on fruit and wine composition and perceived wine quality.
During mid-véraison, there is significant variability of the berries within the cluster. Berries differ in size, softness, sugar content, and color. As grapes develop color near harvest, it may appear that variability is reduced. It is not clear whether or not variability is gone by harvest as this has not been researched extensively. A study conducted by Long (1987) revealed that the quality and complexity of a wine was dependent upon the average berry composition. Cluster heterogeneity at maturity was found to increase green characteristics from less ripe berries or jam-like characteristics from over-mature berries in wines produced. Likewise, this diversity of ripening states of berries within a cluster influenced phenolic maturity and wine composition at commercial harvest (Kontoudakis et al. 2012). In theory, we believe uniform cluster composition to be desirable for winemaking (Keller 2010). However, few studies have defined metrics for a “uniform” cluster. This is no simple task given that there are thousands of metabolites that comprise a grape berry and potentially contribute to fruit and wine quality.
The Deluc and Tomasino Labs conducted a research project in 2012 at OSU’s Woodhall Vineyard to estimate the influence of berry variability on Merlot wine composition. At mid-véraison, 100 clusters were used to monitor the progression of berries that were either green or red at that time point. The pedicels of these two berry classes were tagged with paint. Each cluster was harvested six weeks after mid-véraison, and berries were sorted based on the initial tagging as the green or red groups. Non-tagged berries that represented the intermediate ripening stages between green and red berries were used as the control group. Each group of berries was fermented separately using micro-ferments.
Chemical analysis of wine esters showed significant differences between the red and green berry groups as well as differences to the control. The wine made from the green group contained lower concentrations of some esters, and wine made from the red group contained higher concentrations of different esters. Differences in esters correspond to red- and black-berry aromas in Merlot (Pineau et al. 2009). Wine sensory analysis also resulted in significant differences with control wines having more intense floral, jam, and spice aromas, and greater in-mouth fruit density. Wines from the green berry class had more intense herbal and green aromas, and wines of the red berry class had more intense dark fruit, red fruit, and spice aromas. When wines were assessed for quality using a scale of 1 (low) to 3 (high), control and green berry wine were ranked as higher quality than the red berry wine. We concluded that berry variability present in Merlot at harvest affects the sensory characteristics and chemical composition of the wine. Further experiments to quantify non-volatile compounds (anthocyanins, tannins, and other phenolic compounds) will be performed on these wines using the OSU Mass Spectrometry Facility to complement our sensory and volatile chemical data.
To better understand the mechanisms of grape ripening, we are faced with a myriad of questions about the source, regulation, and mediation of asynchronous ripening. Although we assume that homogeneity of berries is best and that a heterogeneous crop (more variably ripe berries) would result in poorer wines, the interpretation of what level of variability is acceptable for optimum wine quality is unknown. There are many avenues to pursue in this research, as cultural practices and environmental factors may exacerbate or reduce the amount of variability during berry development. Furthermore, the amount of berry variability within the cluster at harvest may differ among cultivars.
Literature Cited
Keller, M. 2010. Managing grapevines to optimize fruit development in a challenging environment: A climate change primer for viticulturists. Aust. J. Grape Wine Res. 16:56-69.
Kontoudakis, N., M. Esteruelas, F. Fort, J.M. Canals, V. De Freitas, and F. Zamora. 2011. Influence of the heterogeneity of grape phenolic maturity on wine composition and quality. Food Chem. 124:767-774.
Long, Z.R. 1987. Manipulation of grape flavour in the vineyard: California, North Coast region. In Proceedings of the Sixth Australian Wine Industry Technical Conference, Adelaide, July 1986. T.H. Lee (ed.), pp. 82-88. Australian Industrial Publishers, Adelaide.
Pineau, B., J.C. Barbe, C.V. Leeuwen, and D. Dubourdiea. 2009. Examples of perceptive interactions involved in specific “Red-” and “Black-berry”aromas in red wines. J. Agric. Food. Chem. 57:3702-3708.
Selvaraj, Y., D.K. Pal, R. Singh, and T.K. Roy. 1995. Biochemistry of uneven ripening in Gulabi grape. J. Food Biochem. 18:325-340.
Grape berry development involves natural biological programs that occur in succession during the growing season. These biological programs are what direct cell division, growth, and fruit ripening. Environmental factors such as light, temperature, water, and nutrient status of the vine affect the development of berries in this process. Within the grapevine, many hormones interact in response to environmental stimuli and coordinate the processes of fruit ripening. However, all berries within a cluster do not go through the ripening process at the same rate. At any given time, some berries will be more developed than others. This phenomenon of uneven ripening is called “asynchrony,” and the variability among berries is most noticeable during mid-véraison.
To understand this phenomenon of asynchrony, we conducted research in Pinot Noir across four years (2010 to 2013). Berries were classified into four groups based on their level of development at mid-véraison as measured by color and softness. These classes include green-hard, green-soft, pink-soft, and red-soft. These berries were at different ripeness states and represented the transition of berries during véraison. Those green berries that were lagging behind in development had transitioned through pink and then red stages at a later time.
To determine ripening development, we monitored individual berries as they advanced from the various stages to the red-soft stage on intervals of 6, 10, and 13 days for pink-soft, green-soft, and green-hard berry classes, respectively. We found that once the lagging berry classes reach their corresponding red-soft stage, they develop at a faster rate during the two weeks following mid-véraison than their riper counterparts. This enhancement in the ripening rate of lagging berries resulted in reduced variability within a cluster at harvest with respect to sugar and pigments (color). This mechanism is known as “ripening synchronicity,” and it involves changes in gene expression and hormones involved in ripening, suggesting that a coordinated mechanism of control is occurring at the genetic level (Gouthu et al., in progress).
Vineyard management practices such as cluster-zone leaf removal, cluster thinning, and deficit irrigation have been used for decades to improve fruit quality and achieve more uniform ripening. Several genomic studies focused on understanding the changes in gene expression of berries within a cluster due to selective defoliation (Pastore et al. 2013), cluster thinning (Pastore et al. 2011) and water deficit (Deluc et al. 2009). However, no study has investigated the naturally occurring changes in gene expression associated with the reduction of uneven ripening without modifying viticulture practices in the vineyard. We believe that uniform ripening is potentially important for grape growers and winemakers, and understanding the plasticity of grape berry ripening could be beneficial in adapting cultivars to a specific growing region, vineyard management practice, or wine style. From an ecological point of view, the grapevine benefits from having a more coordinated ripening of the berries to entice birds and other animals to feed and disperse seeds. As a result, cool climate cultivars may have adapted to complete this process more quickly to survive. Short growing seasons and advanced phenological stages have been reported in several regions across the world (Fraga et al., 2013). The ability to ripen more quickly is an interesting genetic trait to research as we seek better methods for grape production and face climate change.
Identifying developmental and environmental factors that control synchronized ripening through genomic research will increase our knowledge of ripening processes within grape berries. This information may allow us to combine applied and basic research methods to determine if there are viticulture practices that can be used to improve cluster ripening uniformity and wine quality. For example, since we know hormones play a critical role in the ripening process, we may be able to conduct more detailed research on the use of plant hormone sprays during véraison to achieve more uniform berry composition at harvest. Also, we can study the genomic and physiological response of berry ripening synchronicity with traditional vineyard management practices (canopy management, regulated deficit irrigation, and fertilization). These types of partnered applied and basic studies have not been conducted to date. Future short-term research projects to be conducted at OSU will focus on determining specific contributions of ripening-related hormones in the control of this mechanism. We hope to determine field applications that prevent or eliminate uneven ripening in the vineyards. Basic research will focus on the identification of the genes responsible for this regulatory mechanism within such applied projects. Finally, these findings may be helpful in developing large-scale genetic studies to determine the genetic makeup of cultivars such as Merlot, Cabernet Sauvignon, and Zinfandel that exhibit persisting levels of ripeness heterogeneity at harvest.
Literature Cited
Pastore, C., S., Zenoni, GB., Tornielli, G., Allegro, S., Dal Santo, G. Valentini, C., Intrieri, M., Pezzotti, and I. Filipetti. 2011. Increasing the source/sink ratio in Vitis vinifera (cv Sangiovese) induces extensive transcriptome reprogramming and modifies berry ripening. BMC Genomics 12:631
Pastore, C., S., Zenoni, M., Fasoli, M., Pezzotti, GB., Tornielli, and I., Filipetti. 2013. Selective defoliation affects plant growth, fruit transcriptional ripening program and flavonoid metabolism in grapevine. BMC Plant Biology 13:30
Deluc, L.G., D.R. Quilici, A. Decendit, J. Grimplet, M.D. Wheatley, K.A. Schlauch, J.M. Mérillon , J.C. Cushman, and G.R. Cramer. 2009. Water deficit alters differentially metabolic pathways affecting important flavor and quality traits in grape berries of Cabernet Sauvignon and Chardonnay. BMC Genomics 10: 212.
Fraga, H., A.C. Malheiro, J. Moutinho-Pereira, and J.A. Santos. 2013. An overview of climate change impacts on European viticulture. Food Energy Secur. 1: 94-110.
Dr. Patty Skinkis, Associate Professor & Viticulture Extension Specialist
Back in July, our vision of the 2013 growing season was one of easy success. We had limited rain and advanced grape development across the state, something that had been rare in recent years. However, September proved challenging due to shifts in weather which led to berry cracking and increased fruit rots across much of western Oregon. Questions poured in from industry professionals seeking information on Botrytis bunch rot management and more. Most growers were already using proper preventative measures–appropriately timed fungicide applications combined with judicious cluster-zone leaf removal. As harvest neared and rains began to fall, heightened concern over fungicide use and pre-harvest intervals (PHI) developed, leading to discussions about cultural management techniques such as leaf removal and culling damaged fruit.
Leaf removal has been well-studied in Oregon and world-wide by numerous researchers, including my lab at Oregon State University. Those studies varied from the impacts of leaf removal on vine growth to impacts on fruit ripening, berry composition, wine quality, and disease potential. A trial where we compared manual and mechanical leaf removal was of particular interest to industry this season for several reasons: sunburn/heat damage, disease management, and labor shortages. Many growers in Oregon have shifted to mechanical leaf removal over the past few years because it can reduce costs. We estimate manual leaf removal to cost approximately $270 per acre on average density vineyards (1,245 vines per acre) (Julian et al. 2008). Vierra (2005) reported mechanical leaf removal costs of $25 per acre compared to $130 per acre for manual leaf removal in California’s Central Coast vineyards with vine densities ranging from 908 to 1,089 vines per acre. Drawbacks to mechanical leaf removal, which may be either real or perceived, include damage to clusters, reduced precision compared to hand-removal, and the potential for leaves to remain lodged in dense canopies. Development of new leaf removal technology and equipment has reduced many of these concerns.
However, applied research is needed to determine how mechanical leaf removal affects key aspects of vineyard production so that growers can make informed management decisions when shifting practices from manual to mechanical methods. This article summarizes salient findings of a trial conducted to compare manual and mechanical leaf removal in Pinot noir during 2011, one of our coolest and wettest years in recent history.
Prior to 2011, research was conducted across several commercial vineyards in the Willamette Valley (2008 to 2011) to determine impact of early season leaf removal on powdery mildew (Erisyphe necator) and Botrytis bunch rot (Botrytis cinerea). Results showed that early season leaf removal reduced powdery mildew and Botrytis incidence and severity of clusters when compared to no leaf removal (Skinkis and Mahaffee, unpublished). That research evaluated manual leaf removal only. Since many growers are switching to mechanical leaf removal, concerns have been raised about applicability of mechanical leaf removal early in the season (bloom or fruit set) without resulting in cluster and berry damage. This led us to evaluate whether hand and mechanical leaf removal would cause cluster damage, and influence fruit set, yield, fruit composition, and disease incidence when applied at different time points during the 2011 season.
Mechanical and manual (hand) leaf removal methods were compared in a commercial vineyard in the Dundee Hills AVA. The vineyard was planted to Pinot noir (clone 777) grafted to Riparia Gloire rootstock in 1997 at a vine density of 3,015 vines per acre. Vines were oriented in north-south rows and trained to a vertically shoot positioned canopy. Leaf removal was conducted at three time points: bloom, pea-size, and bunch closure. Leaves were removed from both the east and west side of the cluster zone at each of the three time points by using hand labor or mechanically using an Avidor leaf puller attached to an over-the-row tractor. Treatments were applied to plots of 12 vines in a randomized complete block design with six replicates. Due to the nature of the season and the commercial vineyard’s management policy restricting the use of specific fungicides for Botrytis control, a non-leaf removal treatment was not implemented. However, a third treatment where leaves were removed at bunch closure from only the east side of the cluster zone was implemented for comparison (an industry standard practice), and leaves were removed either manually or mechanically. Leaf removal was performed at the start of each time point with clean-up passes to remove new leaves or laterals produced in the cluster zone during each successive time point in the study. Vine growth parameters were monitored including fruit set, leaf area, yield, yield components (cluster weights, berries per cluster, etc.), and pruning weights. Fruit maturity, berry phenolics, and incidence of Botrytis bunch rot at harvest were also measured.
Results
Results from this one-year trial indicate that there is little difference between hand and mechanical leaf removal in terms of level of disease incidence on fruit, vine productivity, and fruit quality. Beginning leaf removal too early in the season raises concerns about reduced fruit set resulting from potentially lower carbohydrate availability to developing flowers or from mechanical damage to inflorescences. Mechanical leaf removal conducted at bloom reduced fruit set by 11% compared to hand leaf removal at bloom and all other time points using either method. This was not a major concern as fruit set was generally high across all treatments, and yield at harvest did not differ among any treatments. Despite similar yields across the trial, average cluster weight was lower for treatments where mechanical leaf removal was conducted at bloom (125 g) compared to manual leaf removal at bloom or later time points of leaf removal by either method (137 g and 140 g for both hand and mechanical leaf removal at pea-size and bunch close, respectively).
When comparing the timing of leaf removal conducted on both sides of the canopy, there was no difference in the percent of clusters with Botrytis or the percent of berries within the cluster with Botrytis infection. This suggests that earlier leaf removal did not help reduce the presence of the disease. When comparing the impact of side (east only versus east and west) and method (hand versus mechanical) of leaf removal at bunch closure, method of leaf removal had greater impact on the incidence of Botrytis at bunch closure (p=0.0436) than the leaf removal on a particular side of the canopy (p=1.0000). Hand leaf removal resulted in 10% lower incidence than mechanical leaf removal at that time point. However, when looking within infested clusters, there was no difference in the percent of berries within cluster that were damaged when comparing between hand and mechanical leaf removal. On average, both hand and mechanical leaf removal treatments had 13% of berries showing signs of Botrytis infection at harvest.
Applying mechanical leaf removal early in berry development is a concern, as it may cause physical damage to clusters, particularly in early development stages such as bloom. To address this concern, we quantified the number of damaged clusters following each leaf removal pass. The type of damage caused by the mechanical leaf puller varied with the timing of leaf removal. Bloom leaf removal resulted in the removal of tips of some clusters, and leaf removal at pea-size or bunch closure resulted in berry splitting on only the smallest clusters. No clusters were completely removed by the mechanical leaf puller. Damage to clusters appeared to be lower when leaf removal was initiated at later stages of development, but this was not statistically significant (p=0.1607). Physical damage was greater in the mechanical leaf removal treatments with 6.9% of clusters per vine damaged on average than in hand removal treatments which had only 0.5% of clusters damaged (p<0.0001). At most, only two clusters per vine were damaged in the mechanical treatments which we considered to be of little practical concern.
When visually comparing vineyards that are mechanically and manually leaf removed, the two often appear quite different with respect to the openness of the cluster zone, particularly when trying to clear both sides of the canopy. However, when we quantified the amount of leaf area remaining on vines after each time point of leaf removal in our study, there was no difference in hand versus mechanical leaf removal except during the earliest time point (bloom). Hand leaf removal vines had 28% lower leaf area per shoot (p=0.0109) than vines receiving mechanical leaf removal at the bloom time point (Figure 1).
Figure 1. Leaf removal conducted at bloom in 2011: (A) before leaf removal, (B) mechanical leaf removal on the east and west side of the cluster zone, and (C) leaf removal by hand on the east and west side of the cluster zone.
This is likely due to the smaller canopy size as compared to later stages. Later in summer we quantified shoot leaf area at bunch closure, and there were no differences between the leaf area remaining by timing or method of leaf removal. As expected, there were no differences in vine pruning weight at the end of the growing season. Adequate canopy was maintained in all treatments, and vine vigor was not impacted by the level of leaf removal performed.
The leaf removal method and timing did not influence berry ripening in 2011. There were no differences in basic maturity indices (TSS, pH, or TA) or in berry anthocyanin, phenolic, or tannin concentrations at harvest. Other leaf removal studies conducted from 2008 to 2012 found similar results with respect to fruit maturity. Results of the 2011 trial highlighted here did not show differences in anthocyanins (color) with earlier leaf removal. Research conducted by Lee and Skinkis et al. 2013 where leaf removal was conducted at different time points on both sides of the canopy showed greater anthocyanins with bloom time leaf removal when compared to removal at bunch closure. Differences may be due to vine canopy differences, season, or clone.
Considerations
Leaf removal is an important practice in vineyard management. However, the best use of this technique depends on production goals and site-specific characteristics of the vineyard. Based on four years of leaf removal research conducted in the Willamette Valley, it is apparent that conducting leaf removal earlier in the season can keep fungal pathogens at bay (Skinkis and Mahaffee, unpublished). The greatest impact on fungal diseases was found in years with high disease pressure (2010 and 2011). In years like 2013 where we started out dry and warm, less aggressive leaf removal was generally applied to avoid berry sunburn or heat exposure. This may have made conditions for Botrytis worse later in the season with reduced fungicide penetration or airflow into the cluster zone. While hand leaf removal still seems to be the preferred method for clearing the cluster zone by premium winegrape producers, realities of labor shortages have become a major concern to getting these practices done in a timely fashion, if at all. Alternatively, some growers who utilize both mechanical and manual leaf removal reported that labor crews were less willing to harvest fruit from vineyards or blocks where mechanical leaf removal was used, as it was harder for them to see clusters and efficiently work compared to blocks where hand leaf removal resulted in better exposed fruit. The combined results from numerous leaf removal projects conducted over the last four years indicate that there is flexibility in the timing of leaf removal based on achieving desired fruit parameters at harvest. However, initial leaf removal should be conducted no later than bunch closure to avoid late season sunburn issues and to enhance disease management.
This experiment was part of a larger project funded in part by the Oregon Wine Board and the Viticulture Consortium-West.
