Crop estimation and forecasting is an essential in precise management in vineyard blocks. Growers forecast or estimate yield to determine how much crop to expect, to ensure berry composition targets are met, and to maintain vine size for next season’s crop forecast. The current methods utilized by growers use historical crop weight data to predict current season’s yield; or utility of lag-phase cluster weights to estimate current season’s yield. Both methods require rigorous sampling and their utility in large vineyards is labor intensive. In collaboration with Carnegie Mellon University, UC Davis is working on a stereovision camera that is able to detect, count, and measure crop size in vineyards. This novel approach uses precision viticulture approaches where cluster architecture is measured based on the image capture by the imaging unit to count number of berries per cluster, berry diameter and weight to determine amount of harvestable fruit per foot of row. The harvestable yield is then interpolated across the vineyard block to determine yield per vine in spatially explicit locations within a vineyard. The stereovision camera registers ten images per second and stores the resultant data that is then processed to generate the yield. This approach is mobile, and can be mounted on a tractor or a utility vehicle to collect the data at speeds up to four miles per hour. The system is being tested at five locations in California in various growing regions.
|Organization||UC Davis Small Farm Program|
|Publisher||Napa Valley Grapegrowers|
|Publication Date||November, 2016|
|Material Type||Written Material|