Elvis A.Takow 1 , Edward W. Hellman 2 , Andrew G. Birt 1 , Maria D. Tchakerian 1 , Robert N. Coulson 1 Modeling Viticultural Landscapes: An Environmental Viticulture Information System 1 Knowledge Engineering Laboratory, Department of Entomology, Texas A&M University, College Station, TX 77843 USA 2 Texas A&M University, AgriLife Research and Extension Center, 1102 East FM 1294, Lubbock, TX 79403 USA; Department of Plant and Soil Science, Texas Tech University
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Elvis A.Takow1, Edward W. Hellman2, Andrew G. Birt1, Maria D. Tchakerian1,
Robert N. Coulson1
Modeling Viticultural Landscapes: An Environmental Viticulture Information System
1Knowledge Engineering Laboratory, Department of Entomology, Texas A&M University, College Station, TX 77843 USA 2Texas A&M University, AgriLife Research and Extension Center, 1102 East FM 1294, Lubbock, TX 79403 USA; Department of Plant and Soil Science, Texas Tech University
Rationale
• Growing US and Texas wine industry.
• Increased demand for quality grapes and wine.
• Limited knowledge base of varietal suitability in US and Texas in particular.
• Match appropriate grape varieties to existing environmental conditions.
Assumptions
• Grape varieties in established European winegrowing regions are ‘optimal’ for the prevailing climatic and edaphic conditions.
• Relationships between environmental conditions and varieties in the “Old World” can be used as reliable predictor of grape variety selection in new regions.
Goal • Understand the environmental factors that
drive grape variety selection and use this knowledge in the establishment of vineyards in the “New World”.
Objectives
1. Develop a spatial database of environmental information.
2. Develop statistical models that relate environmental conditions to selection of appropriate grape varieties.
3. Deliver a web-based technology for further analysis and interpretation of models towards site selection – Decision Support
Data Sources
• National Climatic Data Center (NCDC)
• World Meteorological Organization (WMO).
• Soil Survey Geographic (SSURGO) Database
• Harmonized World Soil Database (HWSD)
• Topography-US Geological Survey
Raw
• Mean temperature (.1 Fahrenheit)
• Mean dew point (.1 Fahrenheit)
• Mean wind speed (.1 knots)
• Maximum temperature (.1 Fahrenheit)
• Minimum temperature (.1 Fahrenheit)
• Precipitation amount (.01 inches)
Climate Data
• Organic Carbon • pH • Available Water Capacity • Soil Depth • Cation Exchange Capacity • Salinity • Soil Texture Class • Elevation • Slope
Soil/Topography Data
Data
Grape Varieties
• Cabernet Sauvignon
• Chardonnay
• Pinot Noir
• Riesling
• Sangiovese
• Tempranillo
Methodology
• Identify relevant indices of climate, soil and topography suitable to grapevine growth.
• Use quantitative (data driven) statistical methods to analyze location based environmental factors important for grapevine growth.
Statistical Methods Multiple Logistic Regression
• Predict or estimate the probability that variety (Y) can be grown at a particular location.
• Understand the functional relationships between variety and environmental conditions.
• Determine which conditions might be causing the variation in the variety choice.
• Predict variety membership based on a linear combination of environmental variables.
• Observations of conditions at selected locations are used to best separate varieties based on average of the conditions under which that variety is grown.
• A Likelihood function expresses the probability of the observed data as a function of the unknown parameters.