In order to better understand their impact on ethanol tolerance in Saccharomyces cerevisiae, six individual genes were overexpressed in two different commercial wine yeast strains, Montrachet and Elixir, and fermented in a high brix, defined, wine-like medium. These genes mainly consisted of those involved in the production of unsaturated fatty acids, although genes dealing with glycerol efflux and reactive oxygen species sequestration were also evaluated. The fermentations were monitored for brix, biomass, and nitrogen utilization. HPLC analysis of hexose sugars, glycerol, and ethanol was reserved for the most interesting of these genes, FPS1 and FAS1, in order to further understand the metabolism associated with these genetic changes. A final fermentation was then run using mutants lacking the FPS1 gene, and mutants overexpressing both components of the FAS complex, FAS1 and FAS2. The results showed a clear trend of greater ethanol tolerance, measured as the amount of ethanol produced before the cessation of fermentation, with less expression of FPS1 in Montrachet, but little result in Elixir. The FPS1 deletion mutant for the Montrachet strain developed higher biomass, utilized more sugar, and produced more ethanol compared to the control. Likewise, overexpression of the FAS complex showed a deleterious effect on the same ethanol tolerance proxies of Elixir, with more muted results in Montrachet. FAS overexpression caused reduced biomass and more sluggish fermentation. These responses demonstrate not only the potential of leveraging these genes for the production of novel commercial strains of S. cerevisiae, but also the interesting strain dependent responses associated with their differential expression.

The economic contributions from yeast (Saccharomyces cerevisiae) alcoholic fermentation are vital to the Californian economy by contributing to over $43.6 billion in sales in 2019. Alcoholic fermentation is a dynamic and intricate process where yeast cells are exposed to many changing stress conditions such as hyperosmotic shock, nutrient limitation, temperature variations, and ethanol toxicity. Environmental conditions and genetic traits dictate yeast's metabolic activities, thus significantly impacting the overall fermentation performance. Two crucial metabolic activities relevant to wine fermentations, nutrient utilization efficiency (NUE) and volatile organic compound (VOC) (i.e., aroma compounds) formation, are poorly understood. Therefore, it is essential for fermentation industries as well as beneficial for the broader scientific community to investigate the pathways responsible for regulating NUE and production of VOCs. Overall, this dissertation provides insights for improving the quality and efficiency of VOC production by improving the understanding of yeast cellular metabolism.To gain necessary insight about metabolic mechanisms, several methods rooted in systems biology were used in this work. This dissertation focuses on curating and expanding current yeast genome-scale metabolic models (GSMMs) and employing the GSMM to understand the underlying metabolic differences regarding aroma production under two different growth conditions. Furthermore, the advances and remaining limitations of this expanded GSMM to simulate the metabolism and production of aroma impact molecules under enological conditions were explored. In a subsequent study in the dissertation, quantitative analysis of key VOCs and nitrogenous compounds from various commercial yeast strains over multiple time points at different phases of fermentation was performed. This analysis provided a unique insight into these strains' specific aroma production profiles and how they change over time and between strains. Multivariate statistics coupled with genome-scale modeling were used to identify several essential amino acids as well as their metabolic routes known to be involved in forming essential VOCs that are desired in wines. Consequently, it was determined that glycine, tyrosine, leucine, and lysine, were positively correlated with fusel alcohols and acetate esters concentrations during wine fermentation. In addition, these nitrogen utilization routes govern strain-specific variation in aroma profiles. In the following work, an experimentally- validated genome-scale dynamic flux balance analysis model was developed that can be used to predict fermentation kinetic behavior under enological conditions. The model was validated using experimental data for fermentation profiles and final concentrations of fermentation products of Enoferm T306 strain yeast grown under low nitrogen conditions (123 mg/L) in synthetic minimal must media (MMM). Furthermore, it was observed that not only are the biomass coefficients within the biomass equation crucial for accurate model predictions using dFBA, but so are the kinetic constraints, especially the maximum sugar uptake rate (υ_smax) and production yield of ethanol (f_ethanol). Finally, a metabolic modeling approach (random flux sampling) was applied to analyze and compare the various intracellular metabolic flux states of commercial yeast strains during enological fermentation. The intracellular predictions show qualitative agreement with the specific variation found from performing principal component analysis. These results indicated which gene-associated reactions are responsible for key strain variations. From the fluctuating degrees of variation among the strains from gene-associated reactions, a comparison of differences in GPR activity was evaluated. Thus, probable gene similarity could be inferred among the strains, and targets could be explored for genetic modification.

This work navigates some of the challenges in optimizing cell culture media for cultivated meat production, aiming to help overcome barriers hindering large-scale commercialization. Beginning with a review of the current state of the science of animal cell culture media, it draws concepts from conventional biomedical applications and microbial fermentation processes for application to cultivated meat. The subsequent experimental studies delve into the intricacies of tailoring media for diverse cell types, exploring the impact of serum-free culture on cellular nutrient requirements, and assessing plant and yeast hydrolysates as alternative nitrogen sources for scalable and cost-effective media formulations. Collectively, the research advocates for tailored and rigorous “white box” media optimization approaches to be used alongside innovative and efficient black box methods. It emphasizes the continued need for nuanced strategies to optimize media for varied cell types, reconcile challenges transitioning to animal component-free formulations, and identify alternative nutrient sources for economically viable cultivated meat production.

Grape phenolics represent a class of compounds of primary interest for winemaking, as they are responsible for main sensory characteristics and important physiochemical interactions with other chemicals. These compounds are extracted from the solid phase of the berry, such as skin and seeds, throughout the alcoholic fermentation and can be adsorbed by insoluble solids, such as plant cell walls (CW) and on the surface of seeds and yeast cells. The extent and rate of these molecules’ extraction strongly depend on temperature, alcohol concentration, and juice-mixing procedures. CW composition of grape skin has also been shown to play a key role in determining the extractability of grape phenolics.In this study we investigated the relationship between grape skin cell wall composition and the extraction of grape phenolic compounds. While doing so, we evaluated the opportunity of applying spectral methods to quickly and non-destructively predict cell wall composition and/or extractability of phenolics. Grapes were collected and micro-fermentations carried out at standardized conditions. Grape phenolic composition was analyzed by exhaustive extraction and high-performance liquid chromatography (HPLC). Wine phenolic profile was characterized by HPLC. CW material was isolated from berry skins as alcohol-insoluble residue and characterized. Protein, phenolics and pectin (analyzed as uronic acid) were determined applying colorimetric procedures. Klason lignin was measured gravimetrically. Intact berries were then scanned with Ocean Insight spectrometers, working on a wavelength bandwidth range from 350 to 2,200 nm. Grape phenolics and their extractabilities were found to mainly depend on the variety, the site and its climate. The relative amount of isolated cell wall material was found to follow a variety-dependent trend. A similar effect was found for CW proteins and phenolics, whose content negatively impacted anthocyanin and phenolic extractability. Isolated cell wall, CW lignin and pectin did not seem to correlate with phenolic extractability. With the data analysis carried out, wavelengths in the range 1004.7-1007.0 nm were found to be successful candidates to predict polymeric pigments content and extractability in wine.

Because of laboratory constraints posed by the pandemic, two projects are included as part of this thesis, a theoretical prediction of barrel sanitization and an experimental exploration of phenolic extraction in columns.Oak barrels are often used to give wine, beer, and distilled beverages flavors and colors. However, microorganisms can penetrate into the wood, making cleaning and sterilization difficult. This can lead to undesired microbial growth in the contents of the barrel during subsequent use. Information on heat penetration into barrel staves during steam treatment and associated thermal inactivation rates is scarce. Therefore, we incorporated heat transfer and Arrhenius-type death kinetics to build a mathematical model to predict the killing rate of the microorganisms when steam sterilizing a wooden barrel. First, we use this model to predict temperature profiles in barrel staves as a function of distance from the steamed surface and time of steaming. Next, we evaluated the thermal inactivation of microorganisms at 0.8 cm into the stave (the maximum wine penetration depth into a stave) to calculate the time needed to achieve 5-log reduction in live cells. Using this approach, we found that the required sterilization times for Brettanomyces bruxellensis, Saccharomyces cerevisiae, and Leuconostoc mesenteroides are 9 minutes, 12 minutes, and 200 minutes, respectively. This result is useful for winemakers to determine how long they desire to steam a barrel to prevent growth and contamination of key microbes in their wine. Phenolic extraction is essential for red winemaking. Fermentation along with phenolic extraction usually takes 7 to 14 days, although the tannin extraction can continue for weeks until an equilibrium is reached. Yet process intensification would allow winery equipment to be used multiple times during harvest, thus decreasing capital investment. While previous work showed the potential to speed up the conversion of sugar to alcohol considerably, this methodology will only be truly useful for red winemaking if phenolic extraction can be completed more rapidly and with more control. In this work, we performed phenolic extraction from grape solids in a column setup and let juice or wine flow through the column to model a continuous extraction. The effect of four different factors was tested: column temperature, liquid ethanol concentration, flow rate through the column, and column diameter using a design of experiments approach. We found that liquid flow rate is the most significant factor, and the temperature and ethanol concentration had minor effects but not statistically significant. With all optimized factors, we were able to reach the same concentration as the bucket control for the final extraction in 86 hours on the bench scale compared to 144 hours for the control process. Both the pigment concentration and tannin concentration were similar. This work shows the potential to achieve process intensification and more control of the phenolic values in the finished wine.

As the global human population grows, the water demands of agriculture will likewise increase. Currently, over half of the world's water consumption is due to crop irrigation. Therefore, improving irrigation is essential to alleviating the effects of these rising demands. Developing low-cost technology for custom water delivery to individual or small groups of vines is a critical next step to advance precision irrigation. Current systems for estimating evapotranspiration (ET), or plant water use, work on the scale of a full vineyard (e.g., 3-5 acres) or the scale of a single vine, but at a cost that prohibits monitoring past a small number of representative vines. An ideal irrigation system, on the other hand, would rely on measurements of water demand—defined by both water use and water status indicators—and provide water to plants in response to these measurements.Meeting this challenge would require a multidisciplinary effort over multiple years, but that is the goal of this dissertation, to develop a comprehensive single plant water use sensing and delivery system. First, three new ET models based on first principles or simple correlations are introduced and the results of a multi-year trial at RMI vineyard are presented to illustrate the performance of each of the novel High Resolution Irrigation (HRI) models. Results suggest the three models perform well, with single vine ET measurements from all three models consistently showing a strong relationship with ground truth ET measurements. Though these early results showed HRI is possible (range in r2 = 0.07 - 0.92), in order to make this technology generalizable to any vine, it must be possible to measure the area term in each model directly from observations. This is the focus of the second chapter, in which vine physical characteristics were measured on a weekly basis throughout the season, then compared to area terms experimentally calculated periodically throughout the season using ground truth data and HRI model estimates. Multiple linear regression and principal component analyses suggest a significant relationship (p-value < 0.05, r2 = 0.58 - 0.80) between two of the model area terms and vine physical parameters including canopy superficial area, canopy polygon area and fraction of absorbed photosynthetically active radiation (fPAR). With these results it is possible to test the HRI ET models in a commercial agriculture context. Then a new low-cost biometeorological sensor is introduced, tested against reference sensors, then used to test the three HRI models in a commercial vineyard alongside research grade flux tower sensors. The Cube sensors showed strong correlation with the research grade reference sensors, fulfilling one of the early project goals of developing a low-cost biometeorological sensor for HRI and testing it in a commercial context. In the final chapter the new Leaf Area Tool image analysis pipeline is introduced, supporting HRI with new tools for extracting vine parameters related to model area terms from raw data. This field ready, fast (300x to 1400x faster than other methods tested) and accurate (r2 = 0.94 - 0.99) method for the quantification of leaf area from digital images is tested on a diverse dataset of broad leaves.