Paul K. Boss’s research while affiliated with University of Adelaide and other places

Methoxypyrazines (MPs) are potent aroma compounds that have been predominately studied in grape berries but can also be detected in other vine tissues. The synthesis of MPs in berries from hydroxypyrazines by VvOMT3 is well established, but the origin of MPs in vine tissues that have negligible VvOMT3 gene expression is unknown. This research gap was addressed through the application of stable isotope tracer 3-isobutyl-2-hydroxy-[2H2]-pyrazine (d2-IBHP) to the roots of Pinot Meunier L1 microvines and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) quantification of HPs from grapevine tissues following a novel solid-phase extraction method. Four weeks post-application, d2-IBHP and its O-methylated product 3-isobutyl-2-methoxy-[2H2]-pyrazine (d2-IBMP) were present in excised cane, berry, leaf, root, and rachis material. Translocation of d2-IBHP and d2-IBMP was investigated, but results were inconclusive. Nonetheless, knowledge that d2-IBHP, and potentially d2-IBMP, are translocated from roots to other vine organs, including the berries, could provide opportunities for controlling MP accumulation in grapevine tissues pertinent to winemaking.

Rootstock can significantly alter the concentration of methoxypyrazines (MPs) in the bunch stem (rachis) of Vitis vinifera L. cv. Cabernet Sauvignon and Shiraz, which has implications for winemaking and wine style. The distribution of MPs across the rachis is an important consideration, but such information was not available. This study aimed to address this research question by comparing MP concentrations in different rachis components throughout grape maturation and in the absence of ambient light. Shiraz and Cabernet Sauvignon bunches were sampled throughout development, segmented into four components (peduncle, top rachis, bottom rachis, and pedicel), and 3-isobutyl-2-methoxypyrazine (IBMP) was quantified in each. For both cultivars, IBMP showed a negative correlation with grape maturity, with concentrations in pedicel at harvest being significantly higher than other rachis components. Additionally, light exclusion significantly increased IBMP concentrations in all rachis segments. The concentration of IBMP varied significantly between different rachis components. The greatest concentrations were measured in the pedicel, which also contributed the largest proportion among the components to total rachis by weight. Due to elevated IBMP concentrations in rachis and the difficulties in excluding matter other than grape from a fermentor, the presence of pedicel during fermentation could produce Shiraz and Cabernet Sauvignon wines with higher concentrations of MPs, thereby potentially increasing vegetal sensory characteristics.

Uniform grape maturity can be sought by producers to minimise underripe and/or overripe proportions of fruit and limit any undesirable effects on wine quality. Considering that grape heterogeneity is a multifaceted phenomenon, a composite index summarising overall grape heterogeneity was developed to benefit vineyard management and harvest date decisions. A grape heterogeneity index (GHI) was constructed by aggregating the sum of absolute residuals multiplied by the range of values from measurements of total soluble solids, pH, fresh weight, total tannins, absorbance at 520 nm (red colour), 3-isobutyl-2-methoxypyrazine, and malic acid. Management of grape heterogeneity was also studied, using Cabernet Sauvignon grapes grown under four viticultural regimes (normal/low crop load, full/deficit irrigation) during the 2019/2020 and 2020/2021 seasons. Comparisons of GHI scores showed grape variability decreased throughout ripening in both vintages, then significantly increased at the harvest time point in 2020, but plateaued on sample dates nearing the harvest date in 2021. Irrigation and crop load had no effect on grape heterogeneity by the time of harvest in both vintages. Larger vine yield, leaf area index, and pruning weight significantly increased GHI score early in ripening, but no significant relationship was found at the time of harvest. Differences in the Ravaz index, normalised difference vegetation index, and soil electrical conductivity did not significantly change the GHI score.

Generations of sensors have been developed for predicting food sensory profiles to circumvent the use of a human sensory panel, but a technology that can rapidly predict a suite of sensory attributes from one spectral measurement remains unavailable. Using spectra from grape extracts, this novel study aimed to address this challenge by exploring the use of a machine learning algorithm, extreme gradient boosting (XGBoost), to predict twenty-two wine sensory attribute scores from five sensory stimuli: aroma, colour, taste, flavour, and mouthfeel. Two datasets were obtained from absorbance-transmission and fluorescence excitation-emission matrix (A-TEEM) spectroscopy with different fusion methods: variable-level data fusion of absorbance and fluorescence spectral fingerprints, and feature-level data fusion of A-TEEM and CIELAB datasets. The results for externally validated models showed slightly better performance using only A-TEEM data, predicting five out of twenty-two wine sensory attributes with R2 values above 0.7 and fifteen with R2 values above 0.5. Considering the complex biotransformation involved in processing grapes to wine, the ability to predict sensory properties based on underlying chemical composition in this way suggests that the approach could be more broadly applicable to the agri-food sector and other transformed foodstuffs to predict a product’s sensory characteristics from raw material spectral attributes.

Vitis vinifera L. cv Shiraz appears unable to synthesise 3-alkyl-2-methoxypyrazines (MPs) in the berry, but can still produce significant concentrations in rachis. MPs are readily extracted from rachis during fermentation, producing Shiraz wines with uncharacteristic "green" flavours. Recently, rootstocks were shown to significantly alter MP concentrations in Cabernet Sauvignon rachis compared to own-rooted varieties, but whether Shiraz followed a similar trend required investigation. This study considered the effect of thirteen rootstocks on the concentrations of 3-isobutyl-2-methoxypyrazine (IBMP), 3-isopropyl-2-methoxypyrazine (IPMP), and 3-sec-butyl-2-methoxypyrazine (SBMP) in the rachis of Shiraz bunches sampled during multiple vintages across several Australian growing regions. Although IBMP was the most abundant, all measured MP concentrations were significantly affected by vintage, rootstock, and region. In addition, vine vigour showed positive correlations with IBMP, which were attributed to changes in canopy coverage impacting rachis light exposure. This hypothesis was explored with light exclusion trials, which significantly increased rachis IBMP concentrations.

Absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy was investigated as a rapid method for predicting maturity indices using Cabernet Sauvignon grapes produced under four viticulture treatments during two growing seasons. Machine learning models were developed with fused spectral data to predict 3-isobutyl-2-methoxypyrazine (IBMP), pH, total tannins (Tannin), total soluble solids (TSS), and malic and tartaric acids based on the results from traditional analysis methods. Extreme gradient boosting (XGB) regression yielded R² values of 0.92-0.96 for IBMP, malic acid, pH, and TSS for externally validated (Test) models, with partial least squares regression being superior for TSS prediction (R² = 0.97). R² values of 0.64-0.81 were achieved with either approach for tartaric acid and Tannin predictions. Classification of grape maturity, defined by quantile ranges for red colour, IBMP, malic acid, and TSS, was investigated using XGB discriminant analysis, providing an average of 78 % correctly classified samples for the Test model.

Poster session displayed at the 18th AWITC from 26-29 June, 2022 in Adelaide, South Australia.

In wine fermentation, improved wine complexity and sensorial properties can arise from the use of non-Saccharomyces yeast. Generally less alcohol tolerant, such strains often do not finish fermentation, therefore requiring a second inoculation with the more robust Saccharomyces cerevisiae, usually added on Day 3. This sequential approach affords non-Saccharomyces time to make an impact before being overtaken by S. cerevisiae. However, two inoculations are inconvenient; therefore the identification of a slow growing S. cerevisiae strain that can be used in a single co-inoculation with the non-Saccharomyces yeast is highly attractive. In this study we investigated the use of the naturally occurring ‘loss of function’ SER1 variant, identified in a Sake yeast, for the purposes of carrying out co-inoculated wine fermentations. The SER1-232(G > C; G78R) change was introduced into the commonly used wine strain, EC1118, via CRISPR/Cas9 editing. In a chemically defined grape juice medium, the SER1(G78R) mutant grew and fermented more slowly and increased acetic acid, succinic acid and glycerol concentrations. Simultaneous inoculation with the slower-growing mutant with a Metschnikowia pulcherrima or Lachancea thermotolerans strain in sterile Sauvignon blanc juice resulted in differences in sensorial compounds, most likely derived from the presence of non-Saccharomyces yeasts. The EC1118 SER1 (G78R) mutant completed fermentation with M. pulcherrima, MP2, and in fact improved the viability of MP2 compared to when it was used as a monoculture. The SER1 (G78R) mutant also promoted both the growth of the SO2-sensitive L. thermotolerans strain, Viniflora® Concerto™, in a juice high in SO2 and its subsequent dominance during fermentation. In co-fermentations with wild-type EC1118, the Concerto™ population was substantially reduced with no significant changes in wine properties. This research adds to our understanding of the use of a novel slow-growing S. cerevisiae yeast in wine fermentations co-inoculated with non-Saccharomyces strains.