By Franka Gabler The United States is the fifth largest producer of table grapes in the world. California – which supplies approximately 99 percent of the U.S. production has 95,437 acres of table grapes and in 2016 produced 939,294 metric tons of grapes, valued at $1.85 billion.
Before the imaging sensor/technology was developed by the Carnegie Mellon University research team, as part of Efficient Vineyard SCRI and earlier research funded by grape industries, there was no tool to measure and map crop size and crop color within a table grape vineyard. Although the sensor has been used only as part of research projects, and therefore is not yet commercially available, the benefits to growers and potential use of the technology for table grape vineyard management can easily be envisioned. Unlike juice and winegrape vineyards that utilize mechanized harvest and can estimate and map yield by employing grape harvesting machinery equipped with yield monitors and GPS, table grape vineyards are carefully harvested by crews. The closest growers got to mapping yield is through recording numbers of harvested grape boxes per vineyard row – which has insufficient resolution for measuring and mapping vineyard variability.
Red table grape varieties are harvested when grape cluster color is fully developed and fruit has accumulated sufficient sugar. Often, the color development lags sugar accumulation. Color is rarely uniform throughout a vineyard block; therefore, grapes are usually harvested in several passes. Harvest is the costliest operation in table grape vineyards. By mapping the percent of harvestable fruit among vineyard blocks using the imaging sensor/technology, growers will be able to make informed decisions regarding harvest scheduling. Furthermore, mapping the color within a particular vineyard block will enable directing of harvest crews into well-colored area of the vineyard, for maximum efficiency – where they will be able to pick the most fruit.
Yield and color mapping, in conjunction with soil and canopy vigor mapping – for which technology already exists, will also serve to further characterize variability within a vineyard block. Characterizing variability will help with determining potential differential management zones for minimizing vineyard variability – such as variable rate irrigation.