Yaniv Lupo,* Andrew McElrone, and Luis Diaz-Garcia
*University of California, Davis, Department of Viticulture and Enology, One Shields Avenue, Davis, CA, 95616 (ylupo@ucdavis.edu)

Boron serves as an essential micronutrient for plants, yet at elevated concentrations, it becomes toxic. In grapevines, boron toxicity triggers leaf senescence, reduces yield, and can ultimately lead to plant death. Among different grapevine species, there is variation in the ability to exclude boron from the shoots. This trait is a crucial component of boron tolerance and a valuable target for rootstock breeding. Our research leverages an extensive grapevine germplasm collection at the University of California, Davis, which includes wild Vitis species and breeding selections with natural variation in boron tolerance. Considering the low throughput and high costs associated with current methods for assessing boron tolerance, we are developing a new high-throughput phenotyping pipeline that integrates hyperspectral proximal sensing and machine learning modeling to predict boron content in different plant tissues. This method will significantly reduce the time required to identify grapevines with improved boron tolerance and eliminate the need for plant tissue collection. We will use this method to screen a large diversity panel genotyped with approximately one million molecular markers for genome-wide association mapping of boron tolerance traits and to identify genes responsible for boron exclusion. This research will provide insights into the adaptive mechanisms of grapevine boron tolerance and facilitate development of more resilient rootstocks for viticulture through the application of phenomics and molecular breeding.

Funding Support: Vaadia-BARD Postdoctoral Fellowship and University of California, Davis