By Luke Haggerty and Kevin Martin
Grapes in the U.S. are grown for juice, wine, table, and raisin production. At the farm gate, most grape producers across these industries measure vineyard production through grape yield, typically recorded as tons per acre. Although most growers currently average the yield across a management block, there can often be a 3 – 4 fold yield difference within a vineyard block. For example, the Lake Erie region’s 2016 ‘Concord’ crop was another high yielding harvest with an industry average around 7 tons per acre. However, yield between and within vineyards varied between 1 and 14 tons per acre. Identifying where the high and low yielding areas are located may help highlight economic gains and losses occurring in the production system and aide in differential and more efficient vineyard management.
Senior Research Associate, Dr. Terry Bates from the Cornell Lake Erie Research and Extension Laboratory in Portland, NY, is currently testing electronic yield monitors on mechanical grape harvesters to measure the yield variation within a vineyard block. A yield monitor uses sensors to approximate weight and GPS location in real-time. To calibrate sensor data, actual truck weights are compared to logged sensor data. “Yield maps” provide a visual representation of spatial yield patterns.
Yield differences across a vineyard can be caused by several factors such as differences in soil type and plant nutrient uptake, previous season crop stress, insect or disease pressure, or a cultural practice like pruning level. The spatial vineyard maps are an excellent tool for growers to visualize differences and scout their vineyards to identify the cause of the variation. From there, a vineyard manager can develop a variable rate management strategy to improve the production in weak areas and efficiently maintain production in stronger areas.
Tracking yield variation is just one use of yield maps. Growers can also make data-based decisions with these maps. Crop estimation, thinning and nutrient requirements are all related to yield. Differentially managing these practices is possible with yield maps.
Yield and sensor maps have a potential to add value to an operation when data are used to inform the decisions growers make to manage the vineyard. Sensor data and GPS technology give the grower the ability to manage areas of a vineyard block differentially.
We track the upfront capital cost of the technology and baseline costs of vineyard management. Growers then use yield maps to change production practices or manage a vineyard differentially. When these changes impact baseline costs, we can map them. This map is a net margin map. It serves as a tool to audit the grower’s decisions and analyze the technology benefits.
Figure 2 shows a block that is slightly underperforming similar blocks, when comparing profit margin. Isolated areas of poor performance undermine the economic efficiency of this block. In this particular case investments that decrease variability have the potential to substantially increase profit margins.