Precision Vineyard Management Project Seeks to Improve Concord Production Efficiency and Profitability.
Cain Hickey and Terry Bates
The Concord marketplace has not changed much in the last couple decades – profits are attenuated by stable crop prices as input costs continue to increase. The Efficient Vineyard project seeks to increase profitability by way of reducing input costs, and improve ripening and crop production uniformity across vineyards.
The focus of the Efficient Vineyard project is to develop and evaluate geospatially referenced management technologies to improve vineyard management efficiency, focusing on variation throughout vineyards. The project started by adapting off-the-shelf technologies, originally used in row crop production systems, to measure and map variations in vineyard canopy; these sensors are called normalized difference vegetative index (NDVI) sensors and low NDVI equates to lower canopy size (see Fig. 1a). These measurements are then coupled with maps of soil electrical conductivity/magnetic susceptibility (See Fig. 1b). Together, these maps provide researchers and growers information on how vine growth patterns change within a vineyard, and if this variation in vine growth is due to inherent factors (such as changes in soil type) as opposed to management factors (i.e. differential pruning).
In the very simplest sense, these maps could direct growers to “problem areas” of the vineyard (see red areas in Fig. 1a), perhaps to focus management in these areas for tasks such as vine renewal or more intensive nutrient or pruning management. Larger problem areas mean less actual production acreage, which means less income for the grower. The sooner the grower acts to manage these areas, the sooner they will see an increase in net returns.
The focus of the project has switched from canopy and soil sensing, to a more proactive approach of implementing variable rate management strategies to manage against inherent vineyard variation. Small pilot projects were initiated this summer to test the efficacy of GPS-driven variable rate crop load management via crop and shoot thinning. An NDVI map was used to make management classification zones based on vine size (see Fig. 2a for an example of three NDVI-based vine-size management classification zones).
In short, computer programs were used to geospatially change the rate at which crop and shoots were mechanically thinned throughout the management classification zones. Without any manual adjustment by the operator, relatively more crop or shoots were thinned as the tractor was driven into small-vine-regions, and vice-versa for large-vine regions. Our goal is to improve ripening uniformity and increase vine capacity by reducing crop load in parts of the vineyard with small vines. These vineyards have been monitored for differences in canopy development, and will continue to be evaluated for fruit maturation rate and dormant season cane pruning weight.
Recently, the Cornell Lake Erie Research Extension Laboratory (CLEREL) research team has been out taking weekly fruit maturity samples from vineyards that have been scanned with NDVI-canopy and soil sensors throughout the growing season. The eventual goal is to evaluate if and why fruit maturation rate (and, eventually, crop yield and pruning weight) is different between sensor-derived management zones (See Fig. 2a).
For now, we are interested in characterizing fruit maturity. Fruit maturity (juice soluble solids) samples taken in several vineyards within a 50-mile stretch of the Lake Erie Concord region ranged 11.0 to 17.9 °Brix last week. The 6.9 °Brix range was likely a function of several factors, broadly encompassed by differences in vineyard site and management practice. However, our project is interested in characterizing and managing the variation within a vineyard.
Using the management zone classification map in Fig. 2 as an example, soluble solids concentration ranged 11.0 to 14.7 °Brix across the vineyard, and the mean value was 12.3 in the purple zone, 12.7 in the green zone, and 13.2 in the red zone. Berry weight ranged 1.27 to 2.85 grams, and the mean value was 2.2 in the purple zone, 2.5 in the green zone, and 1.5 in the red zone. Thus, the small-canopy vines in the red zone also have smaller berries, which may be partially responsible for the relatively greater juice soluble solids concentration in this compared to the two other zones. The red zone is likely under some soil water or nutrient stress, potentially due to physical limitation of root growth.
Since this vineyard is still in “diagnostic phase”, the take home for now is that vine size, berry weight, and fruit maturity are different across NDVI and soil sensor-defined zones; crop yield and pruning weight will likely also be different. This means sensors are effective at characterizing vineyard variation. The next step is to work with the grower and develop a variable rate management plan to to either improve capacity and yield, and/or rate and uniformity of fruit maturation. Plans will begin to take shape over fall and winter, and be put into action by spring.