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2017 ASHS Annual Conference

Assessing Variability in the Vineyard through a Spatially Explicit Selective Harvest Approach

Wednesday, September 20, 2017: 8:00 AM
Kohala 4 (Hilton Waikoloa Village)
Kaan Kurtural, University of California Davis, Davis, CA
Terence R. Bates, Cornell Lake Erie Research and Extension Lab, Portland, NY, United States
Plant water stress affects grape (Vitis vinifera L. cv. Cabernet Sauvignon) berry composition and is variable in space due to variations in the physical environment at the growing site. We monitored the natural variability of grapevine water stress by stem water potential (Ystem) and leaf gas exchange in an equi-distant grid in a commercial vineyard. Spatial differences were measured and related to topographical variation by modeling. Geospatial analysis and clustering allowed to differentiate the vineyard block into two distinct zones having severe and moderate water stress where it varied by 0.2 MPa. Differences in stem water potential affected stomatal conductance, net carbon assimilation, and intrinsic water use efficiency that were different in all measurement dates. The two zones were selectively sampled at harvest for measurements of berry chemistry. The water status zones did not affect berry mass or yield per vine. Significant difference in TSS was observed (3.56 Brix), and in TA, thus indicating a direct effect of water stress on ripening acceleration. Berry skin flavonol and anthocyanin composition and concentration were measured by C18 reversed-phased HPLC. The anthocyanins were most affected by the two water stress zones. The di-hydroxylated anthocyanins were more affected than tri-hydroxylated, therefore the ratio of the two forms increased. Flavonols were different in total amounts, but hydroxylation patterns were not affected. Proanthocyanidin isolates were characterized by acid-catalysis in the presence of excess phloroglucinol followed by reversed-phase HPLC Proanthocyanidins showed the least significant difference, although (+)- catechin terminal subunits was an important predictor in a PLS models used to summarize the multivariate relationships, predicting Ystem or the management zone. The results provide fundamental information on vineyard water status to discriminate harvest or direction to vineyard operators to alter applied water amounts to equilibrate berry composition at harvest.