E.&J. Gallo Winery

Analytics help conserve water and increase fertilizing efficiency for greater crop yield

Published on 6 Aug 2014

The solution provides a precise and environmentally conscious method of increasing our grape yield and fruit quality while conserving water.

Luis Sanchez, senior research scientist

E.&J. Gallo Winery

Consumer Products

Deployment country
United States


Gallo Winery, headquartered in Modesto, California, is the world's largest family-owned winery and the largest exporter of California wines.

Business need
Uniform watering and fertilization across a vineyard with varying soil characteristics can result in producing grapes that are anything but uniform in quality. This winemaker wanted to increase the quality and quantity of its crops while maintaining sustainable irrigation and fertilization practices.

Gallo Winery is bringing together innovative sensing technologies, physics and big data analytics to increase crop yield and conserve water. Advanced analytics calculate optimum water and fertilization needs by plant, rather than vineyard, based on soil mapping, high-resolution satellite data and farm-level observations. Then a fully automated irrigation system delivers water and fertilizer precisely when and where needed.

After one growing season using these new methods in a proof of concept (POC), the winery substantially reduced the water consumption in the test vineyard by 20 percent, with an expected 10 to 20 percent crop yield increase. The precise watering and fertilizing methodology provides better control of vine canopy greening, yielding better quality and more consistent grapes. The solution contains the potential for widespread agricultural application, helping sustain tomorrow's population with today's limited farm lands and an ever-diminishing water supply.


IBM products and services that were used in this case study

GBS AD&I - CS Complex Systems Integration Services, GBS AD&I - ADM - AMS SI/SO - Testing Services, GBS BCS EA - SAP

IBM Analytics, IBM Research, , IBM Analytics - Internet of Things

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