The investment provided by the American Vineyard Foundation in 2002 was used to purchase a Fourier Transform Infra Red (FTIR) Spectrometer from FOSS North America. We were able to use the money to leverage significant educational discounts from FOSS. We received the instrument in the summer, and were able to put it into operational condition with the help of FOSS personnel. We did experience one significant software problem that hindered progress. The cause was recently identified by FOSS personnel in Europe and relates to a software upgrade that has now been solved. In our case, FOSS North America moved swiftly to correct problems and spent significant periods of time training us in the use of the software. We are indebted to Constellation Wine Company for extensive support we received from their Principal Chemist, Mr. Steve Kupina. Mr. Kupina?s experience with the Winescan software and the reference chemistry he was able to provide on grape juices, were invaluable in the calibration of the Grapes can software. We also received significant reference chemistry assistance from Mr. Randy Asher of McCalls Winery & Distillery for Must under Fermentation software calibration. The instrument is now being used extensively by the Faculty on a number of research projects:(a) Evaluation of the effect of six different irrigation treatments on yield and quality of Cabernet Sauvignon grape produced in the San Joaquin Valley. (b) Evaluation of the effects of timing and differential nitrogen applications on the quality and nutritional status and wine quality of Cabernet Sauvignon grapes. © Comparison of fruit and wine quality characteristics of Cabernet Sauvignon grapes produced in three regions of California and one region in Washington State. (d) Effect of Messenger on Leaf Photosynthesis, Vine Performance, Fermentation Potential, and Wine Chemistry in Cabernet Sauvignon Grapevines. (e) Develop and implement control methods for Eutypa dieback disease. (f) Wine composition prior to and during study of micro oxidation. (g) Wine composition during study of utilization of fermentable nitrogen. (h) Effect of wine closures (cork and manufactured) on wine composition. (i) Differences in chemical composition of oleate versus non-oleate treated raisins. (j) Chemical analysis of juice fermentations by different strains of yeast.

We are developing an optimization method for wine processing based on historical winery data and artificial neural networks (ANNs). This method will allow winemakers to fully use the information collected in their wineries over the years in order to produce a final product which has the qualities that they desire, even as grape characteristics vary from year to year. To date, we have established that ANNs can be used successfully to correlate wine processing inputs with chemical and sensory properties of the finished wine. In particular, we have been able to predict primary and malolactic fermentation kinetics based solely on grape characteristics and intended processing. This result is the basis of using the methodology developed in the Long-Term AVF Grant on Sluggish and Stuck Fermentations. We have also used this data to evaluate how well the neural network can interpolate and extrapolate with data not used in training. In addition, we have been able to predict how the color of Cabernet Sauvignon wines that we have made is a function of the fermentation temperature, skin contact time, and macerating enzyme addition, as well as extending our knowledge of the effects of these treatments on the final phenolic profile of the wine. Using neural networks trained with the data from the wines produced here, we have evaluated several types of optimization methods for choosing optimal processing inputs to achieve the desired outputs. These include gradient methods, simulated annealing, and genetic algorithms. Of these, genetic algorithms look the most promising for wine processing cases. The optimization methodology developed to date has been used for several optimization case studies, including Sauvignon blanc processing, Cabernet Sauvignon processing, blending of Chardonnay wines, and the effect of field temperature profiles on Cabernet Sauvignon quality.

To date we have evaluated the qualitative abilities of three commercially available, organophilic adsorbent resins for the purpose of removing protein-complex precursors and colored compounds from grape juice. Data have been generated towards chemically characterizing the specific amounts of protein and other constituents removed, as well as characterizing what compounds (sugars, acids, etc.) have not been removed. Resin technology appears to be promising, as the treated juice did not retain the haze forming proteins as determined in the control sample by traditional heat stability analysis and “Coomassie blue” protein analysis. The protein results are similar to those from previous efforts in which we evaluated adsorbent resins for preliminary unstable protein removal from apple juice. Resin treated juices had measured NTU values of less than 1.0 compared to a value of over 20 NTU in the non-resin treated control juice subjected to the same heat treatment. Using the “Coomassie blue” chemical analysis for proteins, over 90% of the proteins detected by this method were removed. Phenolics levels have also been reduced in the processed juices by values of 33% or 85% depending upon which resin was used. At the same time that these constituents were being removed, other data indicate essentially no changes in original Brix or pH of the juice upon being subjected to resin treatment. In separate experiments, dark colored white grape juice samples were decolorized using the three resins. These experiments were run to 100 bed volume and the degree of decolorization was quantitatively measured as %Transmittance at 430 nm. After 100 bed volumes two resins significantly improved the transmittance of the dark colored white grape juice by 20 units of %Transmittance over the starting juice. The untreated juice in this experiment had significant color and measured only 42%T. Our pilot scale studies have been conducted using 2.54 cm (1″) x 183 cm (6′) columns so that the results better reflect what would occur during production scale operations. The columns are operated using pumped flow, again to mimic production conditions. A peristaltic pump connected to the inlet line is used for delivering all juice, conditioning, and regenerating solutions.