Mapping Grape Suitability in South West Nova Scotia (SWNS)
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This is a research project outlining the compiled criteria for modelling grape production and disease development in South West Nova Scotia. This was achieved with Geographic Information Systems (GIS) at the Centre of Geographic Sciences (COGS) using data provided by the Applied Geomatics Research Group (AGRG). Microclimates and soil characteristics give Nova Scotia grape growers a unique environment to produce high quality wine grapes, even though it is a cooler climate region for vineyards. There are inherent diseases and stress related threats, but effective planning and management strategies including policy standards assist to mitigate crop damage. Moreover, there exists a potential to recognize improvement to management practices related to seasonal temperature trends.
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Mapping Grape Suitability in South West Nova Scotia (SWNS)
- 1. S I M P L I F I E D M O D E L L I N G F O R D E T E R M I N I N G P O T E N T I A L G R A P E D I S E A S E S Mapping Grape Suitability in South West Nova Scotia (SWNS) Presented by: Kirk Dabols
- 2. Presentation Overview Acknowledgements Brief history of Nova Scotia wine Nova Scotia grapes Nova Scotia grape diseases Disease modelling Suitability modelling Problem context Purpose of research Study area Suitability context Purpose of research Objectives Data sets Data Preparation Study Area Weather Stations DSS Methodology Soil suitability Data processing Station suitability
- 3. Brief History Nova Scotia 2011 French settlers began growing grapes in the 1600’s Wine industry established in 1980’s Increasingly steady growth since 1993 Nova Scotia Grapes Nova Scotia wine industry contributed approximately $200 million dollars to provincial economy Attracted over 100,000 tourists Fourth largest grape producer in Canada, following Ontario, B.C. and Quebec 22 grape growers and 400 acres
- 4. Geography Microclimates Peninsula on Canada’s east coast between Atlantic Ocean and the Bay of Fundy Warm ocean currents, prevailing winds, topographical landscape and extreme tides Unique climate for growing world class grapes Generally cooler climate Characterized by latitude, glacial deposits, geographical landscapes and phenomena Longer frost free periods Increased heat accumulation Wind, temperature and precipitation variation Nova Scotia Grapes
- 5. Wine, Wine, Wine Cultivars Grape variety? Trellis Location Soil Depth Ph Drainage Slope Facing direction Processing Storage Management practices Vineyard management vs. wine making Baco Noir De Chaunac Leon Millot Lucie Kuhlmann Marechal Foch L’Acadie Blanc New York Muscat Seyval Vidal blanc Chardonnay Pinot Noir Riesling Nova Scotia Grapes
- 6. Getting technical L’Acadie Blanc Labruscana Vinifera Vitis vinifera Hybrids 1984 Helen Fisher and Kentville Research Station Kentville White Variety KW94-1 Nova Scotia Grapes
- 7. Nova Scotia GrapesTable 1: Nova Scotia Grape Varieties. Red Hybrids Grape Origin Description Winter Hardiness Baco Noir France (Baco 1) Folle Blanche x V. riparia crossed in 1902 by Francois Baco. Vines are very vigorous and difficult to manage after injurious winter. Should be grown on heavy poorly drained soils. Wine is often deep in colour, fruity and herbaceous. Fair De Chaunac France Vigorous and productive variety. Clusters are large and loose which require thinning to maintain consistent yields and quality. Wine is considered fair in quality. Requires high heat units and good canopy management. Fair Leon Millot (Millot) France (Kulhmann194.2) V. riparia-rupestris x Goldriesling crossed by Eugene Kuhlmann. This is the sister seedling to Marechal Foch. Compared to Foch, vines are more vigorous, produce smaller berries, and ripen a few days earlier with lower acid levels. Wine is similar taste to Foch. Good Lucie Kuhlmann France (Kulhmann 149-1) V. riparia-rupestris x Goldriesling crossed by Eugene Kuhlmann. This is the sister seedling to Marechal Foch. It ripens earlier than Foch and is good for cooler sites. Good – Very Good Marechal Foch (Foch) France (Kulhmann188.2) V. riparia-rupestris x Goldriesling crossed by Eugene Kuhlmann. Most common red wine in Nova Scotia because of reliability and productivity. Wine is described as intense, dark red-violet with distinct complex quality good for producing in cool climates. Very Good White Hybrids L’Acadie blanc (L’Acadie) Canada (V. 53261) Seibel 13053 x Seyve-Villard 14-287 crossed in 1953 by O.A. Bradt of the Horticultural Research Institute of Ontario, Vineland Station. This is the sister seedling to Veeblanc. Wine is described as slightly spicy and has a flowery aroma. Good New York Muscat United States of America Muscat Hamburg x Ontario crossed by Richard Wellington in 1926 at the New York State Agricultural Experiment Station. Vines have low to medium vigor. Productivity is low to medium. Wine has distinct Muscat flavor and is used to make sweet Muscat wines and for blending. Good Seyval France (SV 5276) Seibel 5656 x Seibel 4986 cross made by Seyve-Villard in France. Vines are moderately vigorous and produce large bunches. Prone to over-cropping and winter injury. Crop size control must exist to ensure maturity in Nova Scotia. Fair Vidal blanc (Vidal) France (Vidal 256) Ugni Blanc x Seibel 4986 cross made by J.L. Vidal in France. Vines are vigorous and productive. Vines will suffer winter injury if they become too vigorous on coarse textured soils. Late in ripening and can be potential for ice wine. Quality is good but challenge to grow in Nova Scotia. Fair Vinifera Varieties Chardonnay France Widely grown European grape in Nova Scotia. Moderately vigorous and productive, highly susceptible to many diseases. Winter hardy, yet still requires a good frost free period. Produces high quality with apple and pear flavors. Good Pinot Noir France Considered to be more difficult variety to grow but has the most potential to produce high quality red wine in Nova Scotia’s cool climate. Most susceptible to winter injury but capable of reliably ripening on warm sites. Compact bunches and thin-skinned berries. There are various clones and should be considered as some will ripen earlier and are hardier. Poor Riesling Germany Has a high winter hardiness and suitable for quality wine. Though late ripening season severely affects quality. Has greatest potential for producing high quality sparkling wines and ice wines opposed to still wines. Recommended for Nova Scotia warmest sites only. Good – Very Good (AgraPoint 2008 and AgraPoint 2009)
- 8. Diseases Parameters Downy Mildew Powdery Mildew Anthracnose Grey Mold Black Rot Crown Gall Temperature Precipitation Past-season Relative humidity Nova Scotia Grapes Diseases Carisse, et. al., 2006)
- 9. Nova Scotia Grape Diseases Temperature Season Moisture Carisse, et. al., 2006)
- 10. Management Weather Trends Frost burns Pruning Air disturbance Organic pesticides Growing degree days Frost free period Winter minimum Crop production Nova Scotia Grapes Management 2014, http://www.practicalwinery.com/marapr05/marapr05p48.htm
- 11. Nova Scotia Grapes Diseases Table : Macro Analysis - Weather Conditions Conducive for Major Grape Diseases in Eastern Canada Key Factors Diseases Disease Downy Mildew Fungus: Plasmopara viticola (Mildiou) Powdery Mildew Fungus: Erysiphe necator; (Uncinula necator) (Blanc, Oidium) Black Rot Fungus: Guignardia bidwelli (Pourriture noire) Min-Max Temp: 11°C - 28°C 8°C - 32°C 9°C - 32°C Optimal Temp: 22°C - 26°C 23°C - 27°C 20°C - 25°C Precipitation: Heavy Rainfall > 10 mm Dry (cloudy - humid) 2.5 mm Rainy with light showers, rain with heavy showers and water accumulation on ground 0.25 mm Wetness Duration: 2 -3 hours 12 -15 hours > 6 hours Relative Humidity: > 98 % 97-99 % Not an added factor Duration for Infection: 24 hours 2 -3 weeks Grape Variety (slight susceptibility): Baco Noir L’Acadie Lucie Khulmann Marechal Foch NewYork Muscat Seyval L’Acadie De Chaunac L’Acadie Leon Millot NewYork Muscat Vidal Grape Variety (moderate susceptibility): Vidal Baco Noir De Chaunac Lucie Khulmann Marechal Foch NewYork Muscat Resisling Chardonnay Lucie Khulmann Marechal Foch Seyval Grape Variety (high susceptibility): Chardonnay De Chaunac Leon Millot Pinot Noir Resiling Chardonnay Leon Millot Pinot Noir Seyval Vidal Baco Noir Pinot Noir Reisling (Carisse, et. al., 2006; Craig, 2013)
- 12. Disease Modelling Downy Mildew Predictor - DMCast Model
- 13. Suitability Modelling Table: Climatic Limitations to Wine Grape Production Climate Rating Degree Days above 10°C Frost-free period (days) Winter Minimum (°C) Suitability Rank Most Suitable > 1300 180 -21°C 3 times or less in 10 years. Minimum not less than -23°C. 4 Good Suitability 1100 - 1300 165 -21°C 5 times or less in 10 years. Minimum not lower than -26°C. 3 Fair Suitability 900 – 1100 150 -21°C almost every year. -26°C or lower only once in 10 years. 2 Poor Suitability < 900 130 -23°C 5 times or more in 10 years. -26°C 3 times or more in 10 years. 1 (Lewis et. al., 2008) ASDF Table: Climatic Limitations to Wine Grape Production Soil Rating Potential Rooting Depth (cm) Suitability Rank Most Suitable > 90 4 Good Suitability > 80 3 Fair Suitability > 70 2 Poor Suitability > 60 1 (Lewis et. al., 2008)
- 14. Problem Context Increasingly growing industry WANS and GGANS Vineyard management kits Weather data Soil Data Synthesized results
- 15. Purpose of Research The purpose of the research is to develop a GIS model using historical data to evaluate the susceptibility of grape varieties to weather related parameters and be used for future improvements.
- 16. Objectives 1. Use an established set of criteria for indicating certain crop stress and quality. 2. Create a historical weather model of SWNS using provided data sets. 3. Apply criteria to weather model. 4. Analyze and determine the areas of interest. 5. Evaluate the effectiveness and limitations of the model. The following are research objectives to assist in developing a GIS model:
- 17. Data sets Environment Canada weather stations (69) AGRG weather stations (7) Soil Data (DSS) NS 20m DEM SWNS study area
- 18. Data Preparation SWNS AGRG 2011 SWNS AGRG 2012 SWNS AGRG 2013 SWNS EC 2011 SWNS EC 2012 SWNS EC 2013 Joins Data reduction Clipping Add X,Y
- 19. SWNS Study Area
- 20. Weather Stations
- 21. Detailed Soil Survey DSS V2 DSS V3
- 22. Soil Suitability
- 23. GDD5 2011 Manual selection method Statistics Sum – (Count x 5) (ESRI ArcMap, 2014) Calculations: Est. = 225 x 5°C = 1125°C GDD5= 2736.2°C - 1125°C = 1611.2°C "Station" = 'BACCARO' AND "Year" = 2011 AND "Month" >= 4 AND "Month" <= 11 AND "Mean_Temp" >= 5
- 24. Example script for GDD10 Data Processing
- 25. Station Suitability GDD at 10°C 2011
- 26. Production models Disease models Temperature models GDD5 GDD10 Frost-free Period Time of exposure to extreme cold Winter Minimum Weather conditions Time of exposure Moisture Downy Mildew Powdery Mildew Black Rot Production vs. Disease "Station" = 'GREENWOOD' AND "Month" >=4 AND "Month" <=11 AND "Min_Temp__" >= 8 AND "Max_Temp__" <= 32 AND "Mean_Temp" >=23 AND "Mean_Temp" <=27 AND "Total_Rain" >= '10'
- 27. Methodology AGRG and EC weather trend production models AGRG and EC weather trend disease models Station SUIT = GDD10 SUIT + FFP SUIT + WinMin SUIT + DM SUIT + PM SUIT + BR SUIT SUIT GDD10 FFP WinMin DM PM BR Soil 1 poor poor poor high high high poor 2 fair fair fair moderate moderate moderate fair 3 good good good low low low good 4 most most most least least least most Soil data Python script
- 28. Stations Overall Suitability Existing Model Gaps
- 29. Coastal Stations BR1 vs. BR2 Table 17: Suitability Results for BR1 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1745 3 1878 4 1672 4 11 GDD10 850 1 917 2 767 1 4 Frost Free Period Winter Minimum 000 4 000 4 000 4 12 Downy Mildew 0 0 0 Powdery Mildew 0 0 Black Rot 7 7 7 Soil Table 18: Suitability Results for BR2 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1931 4 2119 4 2001 4 12 GDD10 1030 2 1145 3 1085 2 7 Frost Free Period Winter Minimum 000 4 000 4 100 4 12 Downy Mildew 0 0 2 Powdery Mildew 1 3 2 Black Rot 30 41 22 Soil
- 30. Coastal Stations CH1 CL1 KE1 LI1,3 S100 S120 S80 WE1 YA1 Table 23: Suitability Results for CH1 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1696 4 1912 4 1744 4 12 GDD10 839 1 958 2 839 1 4 Frost Free Period Winter Minimum 000 4 000 4 100 4 12 Downy Mildew 0 0 0 Powdery Mildew 0 0 3 Black Rot 2 9 8 Soil Table 29: Suitability Results for CL1 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1605 4 1797 4 1443 4 12 GDD10 672 1 796 1 488 1 3 Frost Free Period Winter Minimum 000 4 000 4 000 4 12 Downy Mildew 0 0 0 Powdery Mildew 0 0 0 Black Rot 0 0 0 Soil Table 34: Suitability Results for KE1 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1192 4 1879 4 1695 4 12 GDD10 597 1 920 2 780 1 4 Frost Free Period Winter Minimum 000 4 000 4 000 4 12 Downy Mildew 0 1 0 Powdery Mildew 0 0 0 Black Rot 4 5 3 Soil Table 39: Suitability Results for LI1 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1811 4 1959 4 1802 4 12 GDD10 924 2 989 2 886 1 5 Frost Free Period Winter Minimum 000 4 000 4 000 4 12 Downy Mildew 0 0 1 Powdery Mildew 0 1 0 Black Rot 9 14 9 Soil Table 41: Suitability Results for LI3 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1735 4 1859 4 1657 4 12 GDD10 829 1 896 1 748 1 3 Frost Free Period Winter Minimum 000 4 000 4 000 4 12 Downy Mildew 0 0 1 Powdery Mildew 0 0 1 Black Rot 7 9 4 Soil Table 52: Suitability Results for S100 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1440 4 1572 4 1630 4 12 GDD10 554 1 659 1 717 1 3 Frost Free Period Winter Minimum 000 4 000 4 100 4 12 Downy Mildew 0 0 0 Powdery Mildew 0 0 0 Black Rot 0 1 0 Soil Table 53: Suitability Results for S120 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1708 4 1823 4 1712 4 12 GDD10 803 1 918 2 851 1 4 Frost Free Period Winter Minimum 000 4 000 4 100 4 12 Downy Mildew 1 1 4 Powdery Mildew 0 0 2 Black Rot 3 10 13 Soil Table 63: Suitability Results for S80 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1754 4 1537 4 1766 4 12 GDD10 823 2 626 2 840 1 5 Frost Free Period Winter Minimum 000 4 000 4 000 4 12 Downy Mildew 0 0 0 Powdery Mildew 0 0 0 Black Rot 3 0 8 Soil Table 77: Suitability Results for WE1 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1783 4 1977 4 1786 4 12 GDD10 882 1 1000 2 853 1 4 Frost Free Period Winter Minimum 000 4 000 4 000 4 12 Downy Mildew 1 0 0 Powdery Mildew 0 0 1 Black Rot 2 7 7 Soil Table 84: Suitability Results for YA1 Station Processing Procedure Suitability 2011 Suitability Score Suitability 2012 Suitability Score Suitability 2013 Suitability Score Total GDD5 1801 4 1917 4 1699 4 12 GDD10 814 1 936 2 759 1 4 Frost Free Period Winter Minimum 000 4 000 4 000 4 12 Downy Mildew 0 0 1 Powdery Mildew 0 0 0 Black Rot 1 3 3 Soil
- 31. 2012 vs. 2011, 2013 On average 100 GDD10 higher 2013 poor frost free period Results vs. quality of grape 3 years vs. 5 years vs. 10
- 32. Conclusions and Future Considerations AGRG station modifications Site analysis for disease modelling Base criteria for disease development Time factor
- 33. Acknowledgements I would like to thank David Colville from the Applied Geomatics Research Group (AGRG) for his time, commitment and assistance on this project. Also, I would like to thank Wayne Reiger from the AGRG who greatly assisted with providing project data. I would like to thank Josh Horton and Micheal and Jocelyn Lightfoot, from Lightfoot and Wolfville Organic Vineyards (L&W) who were generous to provide private data for this project. I would like to thank Kevin Keys for providing soil related data for this project. I would like to thank Garett Gaudet for his assistance with python programming.
- 34. References AgraPoint. (2009).Recommended grape varieties for Nova Scotia. Retrieved from http://www.google.ca/url?sa=t&rct=j&q=&esrc=s&frm=1&source=web&cd=3&ved=0CDYQFjAC&url=http%3A%2F%2Fwww.perennia.ca%2FFact%2520Sheets%2F Horticulture%2FFruit%2FGrape%2FRecommended_Wine_Grape_Varieties_for_NS.pdf&ei=d878Uo- mIem9yAG0uoHACw&usg=AFQjCNGG8VTnT77Sxku0HFak-wBB_nLPbA Agriculture and Agri-Food Canada. (2014). Download soil name table and soil layer table. Retrieved from http://sis.agr.gc.ca/cansis/nsdb/soil/v2/download.html Carisse, O., Bacon, R., Lasnier, J., & McFadden-Smith, W. Agriculture and Agri-Food Canada. (2006). Identification Guide to the Major Diseases of Grapes. Retrieved from http://www.agr.gc.ca/eng/science-and-innovation/science-publications-and-resources/technical-factsheets/identification-guide-to-the-major-diseases-of- grapes/?id=1210281691267#alt Craig, B. (2013). Grape Management Schedule: A guide to weed, insect and disease management in grapes in Nova Scotia. Perrenia. Retrieved from http://perennia.ca/Pest%20Management%20Guides/Fruits/2013%20Grape%20Insect%20and%20Disease%20Management%20Schedule.pdf Drysdale, C., Webster, T., Mccarthy, C., Ure, D., Kehler D., Spooner I., Brylinsky M., Richard M., Fenech A., Liu8, A., Milne K., Murphy M., Colville D., & Ross A. () Climate Change And Adaptive Resource Management In The Southwest Nova Biosphere Reserve. Government of Canada. (2014). Climate and Tides. Retrieved from http://www.collectionscanada.gc.ca/eppp- archive/100/200/301/ic/can_digital_collections/west_nova/climate.html Gadoury, D. M., Seem, R.C., Wilcox, W.F. Kennelly, M. (2005). Epidemology and Control of Grape Downy Mildew. Hardwick Jones, R., Westra, S., & Sharma, A. (2010). Observed relationships between extreme sub‐daily precipitation, surface temperature, and relative humidity. Geophysical Research Letters, 37(22). Integrated Pest Management. (2004). Degree-day Calculation. Retrieved from https://ipm.illinois.edu/degreedays/calculation.html JOST Vineyards. Grape Growing. Retrieved from http://www.jostwine.com/default.asp?mn=1.25.52
- 35. References Kittilsen, L. (2008). Business Planning and Economics of Wine Grape Production in Nova Scotia. Nova Scotia Department of Agriculture. Retrieved from http://www.perennia.ca/Fact%20Sheets/Horticulture/Fruit/Grape/NSAgricultureEconomicsofWineGrapeProduction.pdf Lewis, J. An introduction to grape growing in Nova Scotia. Retrieved from http://www.perennia.ca/Fact%20Sheets/Horticulture/Fruit/Grape/An%20Intro%20to%20Grape%20Growing%20in%20NS.pdf Lewis, J. C., Jamieson, A., Gordon, R., & Patterson, G. (2008). Opportunities and Challenges for Wine Grape Production in Nova Scotia. http://www.perennia.ca/Fact%20Sheets/Horticulture/Fruit/Grape/Opportunities_and_Challenges_for_wine_grape.pdf Moran, J. (2012). On Nova Scotia Farms: A Teacher’s Guide to Nova Scotia Agriculture. Nova Scotia Department of Agriculture. Retrieved from http://novascotia.ca/agri/documents/education/resources_NSFarmPRF16-sen.pdf Nova Scotia Department of Agriculture. (2007). Nova Scotia Farm Winery Policy. Retrieved from http://www.novascotia.ca/agri/mbd/WineryPolicy.pdf. Pesticide Risk Reduction Program, Pest Management Centre & Agriculture and Agri-Food Canada. (2006) Crop Profile for Grape in Canada. Rimerman, F. (2013). The Economic Impact of the Wine and Grape Industry in Canada 2011. Retrieved from http://winesofnovascotia.ca/wp- content/uploads/2013/04/CVA-WANS-Economic-ImpactStudy.pdf Rieger, W. and Colville, D. (2012). South West Nova Scotia (SWNS) Temperature and Solar Radiation Study: 2012 Project Summary. Soliman, A., Heck, R. J., Brenning, A., Brown, R., & Miller, S. (2013). Remote sensing of soil moisture in vineyards using airborne and ground-based thermal inertia Data. Remote Sensing, 5(8), 3729-3748. VineTech Canada. (2014). Helps & Tips. AE Media Inc. Retrieved from http://www.vinetechcanada.com/help-tips/ Vierra, T. (2005). Mechanized leaf removal shows good results. Retrieved from http://www.practicalwinery.com/marapr05/marapr05p48.htm Warnert, J. (2007). UC Cooperative Extension advisor researches biodynamic grape production. Retrieved from http://ucanr.edu/News/?uid=991&ds=191 Winery Association of Nova Scotia. (2011) Room to Grow: We are rooted in Nova Scotia. Retrieved from http://winesofnovascotia.ca/wp- content/uploads/2013/04/CVA-Study-WANS-Press-Kit.pdf Wines of Canada: Nova Scotia. (2011). Retrieved from http://www.winesofcanada.com/scotia.html
Hinweis der Redaktion
- Hello
- Talk: nova history, increasing industry, the industry is booming, recently it is growing and moreover now in 2014 its is still growing The Nova Scotia wine industry historically began with French settlers in the 1600’s, but it was not until the 1980’s when the industry truly established (Winery Association of Nova Scotia (WANS), 2011). Since, 1993 a steady growth has been observed and economic expansion of the industry has been more recently experienced (StatsCan, 2012 as cited in WANS, 2011). Moving forward, in 2011 the wine industry contributed approximately $200 million dollars to the provincial economy (Erskine, 2013 and Rimerman, 2013) and attracted over 100,000 tourists. Nova Scotia is currently the fourth largest wine grape producer in Canada, behind Ontario, B.C. and Quebec in terms of acreage, tonnage and sales (Rimerman, 2013).
- Part of the history is defined by nova’s microclimate regions. Explain geography This geography provides microclimate regions These micro climate regions provide unique weather conditions Microclimates and soil characteristics give Nova Scotia grape growers a unique environment to produce high quality wine grapes, even though it is a cooler climate region for vineyards. Microclimate regions provide grape growers with a longer frost free period and more heat accumulation where nearby locations may not have similar temperature trends (Lewis et. al., 2008). Microclimates can be produced from various geographic landscapes and phenomena; Nova Scotia is uniquely defined by its latitude, prevailing winds, ocean currents and tides, historical glaciers and topography (Lewis et. al., 2008). Since Nova Scotia has a relatively cooler climate this requires for certain cultivars to be grown over others, however yields an ability to produce high-quality grapes by creating hybrid wines.
- Wine-making vs. Wine producing vs. this project It is important to distinguish winemaking and production from grape growing and vineyard management. Winemaking and production can first be described as, determining a site for a vineyard. A regions relative climate, topography and soil characteristics must all be considered, maintaining these specifications are applicable to the grape variety the winemaker wishes to produce (Lewis et. al., 2008). Additionally, considerations of having a south facing slope, suggested distances between vine stands, suggested acreages ensuring profitability, pesticide use including type, effectiveness and timing of application are also winemaking and production activities. Though these activities may directly influence a vineyard; grape growing refers to the process of crop management. Vineyard management, in simple terms, is the ongoing process of maintaining and observing crop health while intervening in terms of pruning, irrigation and pesticide application, including many other practices. Winemaking and grape growing are very much related but are also separate from one another and must often collaborate to produce effective management and production strategies. This project focuses on grape growing related to vineyard management in terms of disease management associated with climate trends.
- Unique grapes, science, wine technology Grape production, grapes develop differently than others in differnet regions Winter hardy Disease sucesptible L’Acadie Grape variety Continued research on Nova grape winter hardy varieties As mentioned the particular climate of a region is very important when considering a grape variety to grow (Lewis et. al., 2008; AgraPoint, 2009 and WANS 2011). This is because each grape variety will develop differently than one another depending on a number of different factors, as briefly mentioned, soil characteristics, total heat accumulation and vineyard design including others will affect the overall quality of the grape and the yield of the vine. Nova Scotia’s unique and diverse climate allows European grapes to grow rather successfully (Lewis et. al., 2008). This grape variety is called vinifera, as coming from Europe, oppose to labruscana from America. The vinifera grape variety entirely belongs to the species, vitis, which refers to the attributes of the grape (AgraPoint, 2009). Characteristically, vitis vinifera is a high quality grape variety though is not winter hardy and disease susceptible, meaning it is prone to stress under certain conditions (Kittilsen, 2008 and AgraPoint, 2009). Moreover, the labruscana does not produce a quality grape compared to vitis vinifera, though it is more winter hardy and disease resistant. Hybrid wines, on the other hand, combine the attributes of the labruscana, winter hardy and disease resistant, with the first class quality of European vinifera types (Kittilsen, 2008) and are the most widely grown variety in Nova Scotia. Nova Scotia’s distinctly cool climate, rich soils and microclimate regions provides a unique growing season for these grape varieties. Table 1 below describes the “recommended grape varieties for Nova Scotia” compiled by AgraPoint International Inc. The Kentville Research Station is working to breed winter hardy varieties that will make good quality wines. One such line is KW94-1, a high yielding, winter hardy white wine grape that looks very promising. This grape provides a strong acidity base.
- Synthesized table of nova wine stakeholders, This provides ecellent information for new grape growers, prospect grape, growers, and new insights for existing grape growers. As mentioned the particular climate of a region is very important when considering a grape variety to grow (Lewis et. al., 2008; AgraPoint, 2009 and WANS 2011). This is because each grape variety will develop differently than one another depending on a number of different factors, as briefly mentioned, soil characteristics, total heat accumulation and vineyard design including others will affect the overall quality of the grape and the yield of the vine. Nova Scotia’s unique and diverse climate allows European grapes to grow rather successfully (Lewis et. al., 2008). This grape variety is called vinifera, as coming from Europe, oppose to labruscana from America. The vinifera grape variety entirely belongs to the species, vitis, which refers to the attributes of the grape (AgraPoint, 2009). Characteristically, vitis vinifera is a high quality grape variety though is not winter hardy and disease susceptible, meaning it is prone to stress under certain conditions (Kittilsen, 2008 and AgraPoint, 2009). Moreover, the labruscana does not produce a quality grape compared to vitis vinifera, though it is more winter hardy and disease resistant. This table will help to relate a specific disease to a particular grape variety. Hybrid wines, on the other hand, combine the attributes of the labruscana, winter hardy and disease resistant, with the first class quality of European vinifera types (Kittilsen, 2008) and are the most widely grown variety in Nova Scotia. Nova Scotia’s distinctly cool climate, rich soils and microclimate regions provides a unique growing season for these grape varieties. Table 1 below describes the “recommended grape varieties for Nova Scotia” compiled by AgraPoint International Inc. The Kentville Research Station is working to breed winter hardy varieties that will make good quality wines. One such line is KW94-1, a high yielding, winter hardy white wine grape that looks very promising. This grape provides a strong acidity base.
- Though, As mentioned certain weather conditions produce stressful exposure to disease development. Common diseases across Canada and mores pecifically in Nova Scotia …. These parameters have been determined from Carisse et. al There is an important relationship between quality of the grape, often measured in sugar content or brix, and yield of the vines (Kittilsen, 2008). As grape vines become stressed, caused by weather related fluctuations, the extent of the damage must be determined to ensure the amount of yield achievable will be appropriate to attain the desired brix. Moreover, it can be said to increase the sugar content the yield must be reduced (Kittilsen, 2008). The level of damage that can occur can vary between, the specific grape variety, the current, recent and historical health of the vine, soil characteristics and pesticide strategies. Additionally, the quality of a grape is highly influenced by weather trends in terms of growing days, degree-days, frost-free days, and minimum and maximum winter temperatures (Lewis et. al., 2008). Considering these weather trend analysis we can determine historical trends and correlate them to the resulting wine quality.
- Downy mildew Powdery mildew Anthracanose Grey mold Black rot Crown gall Min and max Optimal Seasonal risk*** FFP Min and max Moisture risk
- Here’s how suitability mapping is done. Do all of these measurements, rank them on a scale of 1-? And calculate totals for each stations. But this is a point based analysis. This information will be used accordingly to populate criteria values. For instance, daily data will be used for obtaining the minimum and maximum daily temperature values. Whereas, hourly data will be used to determine how long a particular parameter such as, optimal temperature and wetness duration was occurring. If for example, the optimal temperature range and precipitation parameters were held relevant to the time of duration for infection, then that value would be accepted at a certain level of suitability. The closer or more precise each parameter is to the established criteria the lower the suitability rank will be. Thus, a high suitability will be representative of locations that have weather parameters most favourable to areas of low susceptibility. Unfortunately, access to hourly data was limited and therefore could not be incorporated into the model. As mentioned, there are a few concerns regarding the provided data sets and the criteria that have been established. The duration for infection parameter indicates that under certain conditions it will take a certain amount of time for a disease to develop and infect a grape. However, similar to how grape vines have different stages of growth; diseases also have stages of development, sporulation, and infection. Additionally, for some diseases such as crown gall, this can exist within soil systems up to 5 years following an infestation. Though, other diseases may recede and ultimately die off under unfavourable weather conditions for its particular survival. This duration parameter is very difficult to determine because of the lack of knowledge which can accurately predict timing factors related to disease development. Moreover, it can very difficult to collect data with a high enough accuracy to perform an assessment of these criteria. After reviewing the research an established set of criteria will be used for the model. As discussed growing days, frost-free days and winter minimums are grape vine stress indicators. The following figure illustrates the most suitable to least suitable desires for these temperature considerations. After reviewing the research concerning soil characteristics in Nova Scotia, internal drainage and potential rooting depth are important considerations (Kittilsen, 2008 & Lewis et. al., 2010). Though, internal drainage is linked to many other characteristics such as soil type, density, coarseness, etc. As mentioned, soil is one criterion a vineyard manager can modify, by changing the soil, adding more depth or more or less base. However, this can be cost expensive, which is why a naturally well drained soil is more favourable. The potential rooting depth is also an important consideration which will determine the longevity of the vine stock. Also, some soils are characteristically suited for agricultural purposes providing ideal conditions for growth. Using a provided soil vector layer, the following table illustrates the relative ranking scheme soil suitability. Unfortunately, this ranking system was derived from background research relative to soil types, meaning certain soil types generally have a particular depth, drainage and capability. Suitability scores for disease models must be derived by the time it takes for diseases to develop. Again this exposure time can be different depending on the grape and the disease. Moreover, disease models should score moderate suitabilities for stations that meet the observed exposure time which causes disease development. High would indicate that infection rates are increased at these locations, whereas least indicates infection rates will be at a minimum.
- The goal of this project was to provide suitability scores for each station in terms of their relative GDD at 5, GDD at 10, frost-free period, winter minimum, downy mildew, powdery mildew, black rot and soil. This was not achieved because of data limitations which inhibited the models ability to accurately estimate or generate suitability scores. Therefore, suitability scores for frost-free period, and the disease models, downy mildew, powdery mildew and black rot were not included in the tables. Though, considering the model that was performed, some interesting observations can be made.
- The tables below show the calculated values for all stations and years including the relative suitability scores. However, since this project did not achieve an accurate model for producing the desired results, certain suitability scores have been left blank. This project recognizes that filling in these scores would be misrepresentative of suitability mapping. Rather the tables should be reviewed for interesting results; which they show. Coastal stations have significantly lower temperatures than inland stations. However, there are also some coastal stations which do not comply with this trend. This station is found in Annapolis Royal where the topographical landscape protects the area from cool winds off of the Bay.
- The goals of this project were to develop a GIS model for determining the suitability of a particular location with respect grape crops and their potential health and potential for developing a disease. Unfortunately, because of data limitations this was not achievable. However, some interesting insights and considerations for future models can certainly be made. As mentioned it is understood that grapes thrive off of high growing temperatures. Yet, also understood grapes under certain weather conditions can develop diseases. Thus, a year of good growing temperatures does not necessarily indicate a good year, if the crop has been under stress. This is why an accurate model is needed in order to investigate areas where preferred weather conditions and weather trends occur oppose to undesirable trends. Undesirable trends indicate that these areas have trends which have a high potential for disease development. Since a disease development model requires certain weather data, the model should also consider other measurements as shown in this project. Rather than measuring only the potential risk, using the same data, the model can incorporate potential health or quality of a grape, which leads to the next suggested point. This project set out to develop model which would incorporate specific Nova Scotia grape varieties in order to relate weather station results to the susceptibility of a grape to a particular disease. This would be highly beneficial to grape growers as it would further highlight areas which are more preferred for specific grapes. The data must be able to meet the model, so to speak. The model needs relative humidity for measuring diseases. Therefore, it requires rain gauges. The stations with missing rain gauges, for the scope of this project cannot be interpolated or estimated at a high enough accuracy. The model requires actual data to ensure the results will be reflective of the actual conditions. Fortunately, the AGRG is implementing improvements to the existing weather stations. These improvements include replacing the current temperature gauge with a gauge which records both temperature and relative humidity. Additionally, they will be adding precipitation sensors to the existing stations also including wind speed and direction sensors. These improvements are essential for continued research focusing on the agricultural The DMCast model provided some interesting considerations. Perhaps the model should be developed first for a particular disease on a specific grape variety. This would allow the stages of crop and disease development to be observed which plays an important factor in determining the potential for disease development. These models however, require accurate timing intervals, in order to measure small changes over time. For instance, disease development can occur is moisture, dew, wetness or rainfall however, depending on other weather conditions and the duration of certain conditions, the development of a particular stage of disease may or may not occur.