IVAS 2022 banner
IVES 9 IVES Conference Series 9 IVAS 9 IVAS 2022 9 Use of mathematical modelling and multivariate statistical process control during alcoholic fermentation of red wine

Use of mathematical modelling and multivariate statistical process control during alcoholic fermentation of red wine

Abstract

Cyberphysical systems can be seen in the wine industry in the form of precision oenology. Currently, limitations exist with established infrared chemometric models and first principle mathematical models in that they require a high degree of sample preparation, making it inappropriate for use in-line, or that few oenological parameters are considered. To our knowledge, a system which incorporates a more comprehensive mathematical model as well as in-line spectroscopic monitoring for the purpose of precision oenology has not yet been presented.

The use of first principle mathematical modelling was employed to predict the trends of alcoholic fermentation and oenological parameters in a four-phase model based on initial conditions. The components of interest were sugars, alcohol, biomass, nitrogen, carbon dioxide, phenolic parameters, and pH. The phases considered included the lees, the cap, the must, and an intermediate liquid phase present in the cap. For each phase, a system of ordinary differential equations was developed to describe the change of each of the components listed. Parameters such as mass transfer coefficients and partition coefficients need to be determined via regression during the model development stage. To obtain the necessary data, fermentations using three different cultivars (Shiraz, Merlot, and Cabernet Sauvignon) were conducted using three different temperatures (20oC, 25oC, and 28oC). Samples were taken once per day and chemical analysis took place for each of the components. A functional mathematical model capable of generating accurate forecasts for different oenological components using the chemical composition of grapes was attempted. Additionally, the model should describe the change in parameters due to cap mixing and increasing ethanol concentration. The model includes the boundary conditions which can be used to determine if a fermentation is deviating from desired progression.

To complete this process control system, it is still necessary to utilize partial least squares (PLS) calibration models for real time monitoring. Additionally, outlier identification, caused by abnormal spectra, was performed using statistical analysis allowing samples to be re-analysed. The use of machine learning techniques and the development of local and incremental models was explored to assess a live updating of the PLS models. The expected outcome of this study is a combined system using dynamic modelling to predict the fermentation and extraction trends and the monitoring with real time predictions generated by PLS models

DOI:

Publication date: June 23, 2022

Issue: IVAS 2022

Type: Article

Authors

Lambrecht Kiera Nareece¹, Du Toit Prof. W.J.¹, Louw Prof. T.M.²and Aleixandre Tudo Dr. J.L.¹,³

¹Stellenbosch University, South African Grape and Wine Research Institute, Department of Viticulture and Oenology
²Stellenbosch University, Department of Process Engineering
³Universitat Politecnica de Valencia, Instituto de Ingenieria de Alimentos para el Desarrollo (IIAD), Departamento de Tecnología de Alimentos

Contact the author

Keywords

In-line monitoring, process control, dynamic modelling, chemometrics, live modelling

Tags

IVAS 2022 | IVES Conference Series

Citation

Related articles…

Biodiversity in the vineyard agroecosystem: exploring systemic approaches

Biodiversity conservation and restoration are essential for guarantee the provision of ecosystem services associated to vineyard agroecosystem such as climate regulation trough carbon sequestration and control of pests and diseases. Most of published research dealing with the complexity of the vineyard agroecosystems emphasizes the necessity of innovative approaches, including the integration of information at different temporal and spatial scales and development of systemic analysis based on modelling. A biodiversity survey was conducted in the Franciacorta wine-growing area (Lombardy, Italy), one of the most important Italian wine-growing regions for sparkling wine production, considering a portion of the territory of 112 ha. The area was divided into several Environmental Units (EUs), defined as a whole vineyard or portion of vineyard homogenous in terms of four agronomic characteristics: planting year, planting density, cultivar, and training system. In each EU a set of compartments was identified and characterised by specific variables. The compartments are meteorology, morphology (altitude, slope, aspect, row orientation, and solar irradiance), ecological infrastructures and management. The landscape surrounding EU was also characterised in terms of land-use in a buffer zone of 500 m. For each component a specific methodology was identified and applied. Different statistical approaches were used to evaluate the method to integrate the information related to different compartments within the EU and related to the buffer zone. These approaches were also preliminarily evaluated for their ability to describe the contribution of biodiversity and landscape components to ecosystem services. This methodological exploration provides useful indication for the development of a fully systemic approach to structural and functional biodiversity in vineyard agroecosystems, contributing to promote a multifunctional perspective for the all wine-growing sector.

Geospatial trends of bioclimatic indexes in the topographically complex region of Barolo DOCG

Barolo DOCG is an economically important wine producing region in Northwest Italy. It is a small region of approximately 70 km2 gross area. The topography is very complex with steep sloped hills ranging in elevation from below 200 m to 550 m. Barolo DOCG wine is made exclusively from the Nebbiolo grape. Bioclimatic indexes are often used in viticulture to gain a better understanding of broader climate trends which can be compared temporally and geographically. These indexes are also used for identifying potential phenological timing, growing region suitability, and potential risks associated with expected climatic changes. Understanding how topography influences bioclimatic indexes can help with understanding of mesoscale climate behaviour leading to improved decision making and risk management strategies. The average monthly maximum and minimum temperatures, the Cool Night Index, the Huglin Index, and the monthly diurnal range (from July to October) were calculated using data from 45 weather stations within a 40 km radius of the Barolo DOCG growing area between the years 1996 and 2019. Linear and multiple regression models were developed using independent variables (elevation, aspect, slope) extracted from a digital elevation model to identify significant relationships. Bioclimatic indexes were then kriged with external drift using independent variables that showed significant relationships with the bioclimatic index using a 100 m resolution grid. The maximum monthly temperatures and the Huglin Index showed consistent significant negative relationships with elevation in all years. The minimum monthly temperatures showed no relationship with elevation but in some months a small but significant relationship was observed with aspect. Due to the lack of a relationship between minimum monthly temperatures and elevation compared to the significant relationship between maximum monthly temperatures and elevation, monthly diurnal range had a negative relationship with elevation.

The interplay between grape ripening and weather anomalies – A modeling exercise

Current climate change is increasing inter- and intra-annual variability in atmospheric conditions leading to grapevine phenological shifts as well altered grape ripening and composition at ripeness. This study aims to (i) detect weather anomalies within a long-term time series, (ii) model grape ripening revealing altered traits in time to target specific ripeness thresholds for four Vitis vinifera cultivars, and (iii) establish empirical relationships between ripening and weather anomalies with forecasting purposes. The Day of the Year (DOY) to reach specific grape ripeness targets was determined from time series of sugar concentrations, total acidity and pH collected from a private company in the period 2009-2021 in North-Eastern Italy. Non-linear models for the DOY to reach the specified ripeness thresholds were assessed for model efficiency (EF) and error of prediction (RMSE) in four grapevine cultivars (Merlot, Cabernet Sauvignon, Glera and Garganega). For each vintage and cultivar, advances or delays in DOY to target specified ripeness thresholds were assessed with respect to the average ripening dynamics. Long-term meteorological series monitored at ground weather station by means of hourly air temperature and rainfall data were analyzed. Climate statistics were obtained and for each time period (month, bimester, quarter and year) weather anomalies were identified. A linear regression analysis was performed to assess a possible correlation that may exist between ripening and weather anomalies. For each cultivar, ripeness advances or delays expressed in number of days to target the specific ripening threshold were assessed in relation to registered weather anomalies and the specific reference time period in the vintage. Precipitation of the warmest month and spring quarter are key to understanding the effect of climate change on sugar ripeness. Minimum temperatures of May-June bimester and maximum temperatures of spring quarter best correlate with altered total acidity evolution and pH increment during the ripening process, respectively.

Vineyards and clay minerals: multi-technique analytical approach and correlations with soil properties

Purpose of this research is to quantitatively assess the mineral component of vineyard soils, with particular attention to the mineralogical analysis of clays, which represent an element of high importance in the vineyard culture as well as in general agriculture. An X-ray diffraction (XRD) / thermogravimetric (TG) multi-technique analytical approach was developed, tested on soil samples taken from vineyards around the world. This codified analytical procedure was necessary to obtain precise qualitative and quantitative mineralogical data, globally comparable to distinguish the geopedological identity of the vineyards. Soil samples from vineyards of various locations were analysed, in very different geological conditions. The bulk-rock quantitative phase analysis (QPA) was obtained by the Rietveld method while the detailed composition of the clay-sized fraction was determined by modelling of the oriented X-ray diffraction patterns. The research provided a precise classification of the mineral component of soils, distinguishing the mineral phases of the clays and the so-called mixed-layer clay minerals. We found that the content in mixed layers can be directly correlated with the water retention and the cation exchange capacity ​​of the soil, while the presence of other clayey minerals and phyllosilicates in this research did not affect this CEC parameter, which codes the fertility level of the soils. The study demonstrates that terroir, in particular soils formed in complex or very different geological conditions, can only be effectively interpreted by properly analysing its mineral phases, in particular the mixed-layer clay component. These are characteristic abiotic ecological indicators, which may have specific eco-physiological influences on the plant.

Analysis of some environmental factors and cultural practices that affect the production and quality of the Manto Negro, Callet and Prensal Blanc varieties

45 non irrigated vineyards distributed in the DO (Denomination) Pla i Llevant de Mallorca and the DO Binissalem Mallorca were used to investigate the characteristics of production and quality and their relationships certain environmental factors and cultural practices. The grape varieties investigated are autochthonous to the island of Mallorca, Manto Negro and Callet as red and Prensal Blanc as white. All plants were measured for four consecutive years in the main production and quality parameters. Among the environmental factors, the type of soil has been studied, more specifically its water retention capacity, the planting density, the age of the vineyard and the level of viral infection. The presence or absence of virus seems to have no effect on any component studied in the varieties studied. For the white variety Prensal Blanc age is negatively correlated with production and the number of bunches, nevertheless it does not cause any effect on the required quality parameters. However, for the red varieties Callet and Manto Negro, the age of the plantation is the variable that best correlates with the quality parameters, therefore the old vines should be the object of preservation by the viticulturists and winemakers in order to guarantee its contribution to the quality of the wines made with these varieties.