Determination of target compounds in cava quality using liquid chromatography. Application of chemometric tools in data analysis

Wine growing has proven to be a development opportunity for agribusiness in several new regions of brazil, including the federal district. There are more than ten existing wineries, established in the last five years. Through the double pruning system, which consists of trimming the growing shoots in the summer and positioning the ripening of the fruits in a cooler period of the season, the grapes are sought to ripen more completely. The syrah variety has shown excellent adaptation to this cycle management model.

The assessment of wine authenticity is of great importance for consumers, producers and regulatory agencies to guarantee the geographical origin of wines and grape variety as well. Since mid-infrared (MIR) spectroscopy with chemometrics represent a suitable tool to ascertain the wine composition, including features associated with the polyphenolic compounds, the aim of this study was to generate MIR spectra of red wines to be exploited for classification of red wines based on the relationship between grape variety and wine composition. Several multivariate data analyses were used, including Principal Component Analysis (PCA), Discriminant Analysis (DA), Support Vector Machine (SVM), and Soft Intelligent Modelling of Class Analogy (SIMCA).

The main goal of the current study is the development of a cost-effective and easy-to-use method suitable for use in the laboratory of commercial wineries to analyze wine aroma. Additionally, this study attempted to establish a prediction model for wine quality gradings based on their aroma, which could reveal the important aroma compounds that correlate well with different grades of perceived quality METHODS: Parameters of the SHS−GC−IMS instrument were first optimized to acquire the most desirable chromatographic resolution and signal intensities. Method stability was then exhibited by repeatability and reproducibility. Subsequently, compound identification was conducted. After method development, a total of 143 end-ferment wine samples of three different quality gradings from vintage 2020 were analyzed with the SHS−GC−IMS instrument. Six machine learning methods were employed to process the results and construct a quality prediction model. Techniques that aim to explain the model to extract useful insights were also applied.

Grapevine (Vitis spp.) is greatly influenced by climatic conditions and its economic value is therefore directly linked to environmental factors. Among these factors, temperature plays a critical role in vine phenology and fruit composition. In such conditions, elucidating the mechanisms employed by the vine to cope with heat waves becomes urgent. For the past few years, our research team has been producing molecular and metabolic data to highlight the molecular players involved in the response of the vine and the fruit to high temperatures [1]. Some of these temperature-sensitive genes are currently undergoing characterization using transgenesis approaches coupled or not with genome editing, taking advantage of the Microvine genotype [2].

Microplastics can alter physicochemical and biogeochemical processes in the soil, but whether these changes have further effects on soil fertility, and if so, whether these effects vary depending on the type of soil in the vineyard and the type of plastic used in the vineyard. Knowing what types of plastics are currently used in vineyards in Slovenian viticultural regions as strings to tie vines to the stake, the aim of our study was to assess the effects of microplastic particles from polypropylene (PP) and polyvinyl chloride (PVC) on the availability of macro (potassium (K), Potassium (K), calcium (Ca), magnesium (Mg) and phosphate (P)) and micronutrients (iron (Fe), copper (Cu), manganese (Mn) and zinc (Zn)) in two vineyard soils contrasting in pH and mineralogy. For this purpose, a short-term soil incubation experiment (120 days) was carried out in which the soil samples were enriched with micro-PP and micro-PVC particles. After the incubation period, macro- and micronutrient availability were measured.