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Sustainable Winegrowing with Vineyard Team

Sustainable Winegrowing with the Vineyard Team brings you the latest in science and research for the wine industry. This on-the-go, sustainable farming educational resource provides in-depth technical information on topics like integrated pest management, fruit quality, water conservation, and nutrient management from experts like Dr. Mark Fuchs of Cornell University, Dr. Michelle Moyer of Washington State University, Cooperative Extension Specialists, veteran growers, and more. Our podcasts will help you make smarter, sustainable vineyard management decisions to increase efficiency, conserve resources, and maximize fruit quality.

Oct 19, 2017

Many factors influence the number of people coming to the U.S. to work including the cost and danger of crossing the border and improved economic conditions in Mexico. Dr. Philip Martin, Ph.D. Professor of Agricultural and Resource Economics- UC Davis, discusses some of the reasons there are not enough workers to...


Oct 5, 2017

Sustainable Agriculture Research and Education (SARE) is a grant program of the U.S.D.A. to find solutions to problems identified by growers. By providing funding to growers for original research, demonstrations, and other projects new sustainable innovations are discovered and promoted. Western SARE Communications...


Sep 21, 2017

Dr. Marc Fuchs researches the biology and ecology of the Grapevine Red Blotch associated Virus. His work investigates the transmission and spread of the virus, its possible vectors, how the virus affects vines, and optimal management strategies.

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Sep 7, 2017

The California Department of Food and Agriculture appropriated funds to develop and administer a new incentive and demonstration program from the Greenhouse Gas Reduction Fund. The objective of this new Healthy Soils Program is to build soil carbon and reduce agricultural greenhouse gas (GHG) emissions.

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Aug 17, 2017

NDVI imagery is analyzed by software which tells the grower where to go in the vineyard to take samples that will best represent the ripeness of the crop. This method could save tremendous amounts of time and generates much smaller samples for processing.

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