Quantification of Microbial Rot in Wine
Summary of Major Research Accomplishments and Results (by Objective):
Objective 1: (a) UV-VIS spectra of uninfected grapes and grapes with 0.5,1, 2, 3, 4, and 5%mold can be used to distinguish between moldy and non-moldy grapes. However, it was not possible to distinguish between the different amounts of mold. (b) The initial pass/fail FTIR calibration for mold in Chardonnay and Zinfandel grapes established in the previous funding cycle was strengthened. (c) Differences in the FTIR spectra of infected and uninfected grapes were detected. Analysis using several different approaches including principal component analysis (PCA) and partial least squares (PLS) regression gave excellent prediction values. (d) Differences in the Raman spectra of infected and uninfected grapes were detected. Analysis using several different approaches including principal component analysis (PCA) and partial least squares (PLS) gave excellent prediction values. (e) Changes in methodology to take into account bunch to bunch variation, and the use of fresh or frozen berries did not significantly affect regression and prediction values. (f) Analysis to determine if the FTIR data for Chardonnay and Zinfandel grapes can be combined to give a single quantitative model for rot rather than one for each grape variety looks very promising.
Objective 2: (a) A large number of VOCs produced by molds growing on grapes have been identified by Gas Chromatography ? Mass Spectrometry (GC-MS). (b) GC-MS focus is on the repeatability of detection, i.e., are these VOCs produced every time grapes are infected and are they produced in sufficient quantities that they can be used for quantification of rot.