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…

Making sense of available information for climate change adaptation and building resilience into wine production systems across the world

Effects of climate change on viticulture systems and winemaking processes are being felt across the world. The IPCC 6thAssessment Report concluded widespread and rapid changes have occurred, the scale of recent changes being unprecedented over many centuries to many thousands of years. These changes will continue under all emission scenarios considered, including increases in frequency and intensity of hot extremes, heatwaves, heavy precipitation and droughts. Wine companies need tools and models allowing to peer into the future and identify the moment for intervention and measures for mitigation and/or avoidance. Previously, we presented conceptual guidelines for a 5-stage framework for defining adaptation strategies for wine businesses. That framework allows for direct comparison of different solutions to mitigate perceived climate change risks. Recent global climatic evolution and multiple reports of severe events since then (smoke taint, heatwave and droughts, frost, hail and floods, rising sea levels) imply urgency in providing effective tools to tackle the multiple perceived risks. A coordinated drive towards a higher level of resilience is therefore required. Recent publications such as the Australian Wine Future Climate Atlas and results from projects such as H2020 MED-GOLD inform on expected climate change impacts to the wine sector, foreseeing the climate to expect at regional and vineyard scale in coming decades. We present examples of practical application of the Climate Change Adaptation Framework (CCAF) to impacts affecting wine production in two wine regions: Barossa (Australia) and Douro (Portugal). We demonstrate feasibility of the framework for climate adaptation from available data and tools to estimate historical climate-induced profitability loss, to project it in the future and to identify critical moments when disruptions may occur if timely measures are not implemented. Finally, we discuss adaptation measures and respective timeframes for successful mitigation of disruptive risk while enhancing resilience of wine systems.

Permanent cover cropping with reduced tillage increased resiliency of wine grape vineyards to climate change

Majority of California’s vineyards rely on supplemental irrigation to overcome abiotic stressors. In the context of climate change, increases in growing season temperatures and crop evapotranspiration pose a risk to adaptation of viticulture to climate change. Vineyard cover crops may mitigate soil erosion and preserve water resources; but there is a lack of information on how they contribute to vineyard resiliency under tillage systems. The aim of this study was to identify the optimum combination of cover crop sand tillage without adversely affecting productivity while preserving plant water status. Two experiments in two contrasting climatic regions were conducted with two cover crops, including a permanent short stature grass (P. bulbosa hybrid), barley (Hordeum spp), and resident vegetation under till vs. no-till systems in a Ruby Cabernet (V. vinifera spp.) (Fresno) and a Cabernet Sauvingon (Napa) vineyard. Results indicated that permanent grass under no-till preserved plant available water until E-L stage 17. Consequently, net carbon assimilation of the permanent grass under no-till system was enhanced compared to those with barley and resident vegetation. On the other hand, the barley under no-till system reduced grapevine net carbon assimilation during berry ripening that led to lower content of nonstructural carbohydrates in shoots at dormancy. Components of yield and berry composition including flavonoid profile at either site were not adversely affected by factors studied. Switching to a permanent cover crop under a no-till system also provided a 9% and 3% benefit in cultural practices costs in Fresno and Napa, respectively. The results of this work provides fundamental information to growers in preserving resiliency of vineyard systems in hot and warm climate regions under context of climate change.

The impact of leaf canopy management on eco-physiology, wood chemical properties and microbial communities in root, trunk and cordon of Riesling grapevines (Vitis vinifera L.)

In the last decades, climate change required already adaptation of vineyard management. Increase in temperature and unexpected weather events cause changes in all phenological stages requiring new management tools. For example, defoliation can be a useful tool to reduce the sugar content in the berries creating differences in the wine profiles. In a ten-year field experiment using Riesling (Vitis vinifera L, planted 1986, Geisenheim, Germany), various mechanical defoliation strategies and different intensities were trialed until 2016 before the vineyard was uprooted. Wood was sampled from the plant compartments root, trunk, cordon and shoot for analyses of physicochemical properties (e.g. lignin and element content, pH, diameter), nonstructural carbohydrates and the microbial communities. The aim of the study was to investigate the influence of reduced canopy leaf area on the sink-source allocation into different compartments and potential changes of the fungal and prokaryotic wood-inhabiting community using a metabarcoding approach. Severe summer pruning (SSP) of the canopy and mechanical defoliation (MDC) above the bunch zone decreased the leaf area by 50% compared to control (C). SSP reduced the photosynthetic capacity, which resulted in an altered source-sink allocation and carbohydrate storage. With lower leaf area, less carbohydrates are allocated. This for example resulted in a decreased trunk diameter. Further, it affected the composition of the grapevine wood microbiota. SSP and MDC management changed significantly the prokaryotic community composition in wood of the root samples, but had no effect in other compartments. In general, this study found strong compartment and less management effects of the microbial community composition and associated physicochemical properties. The highest microbial diversities were identified in the wood of the trunk, and several species were recorded the first time in grapevine.

Climate, Viticulture, and Wine … my how things have changed!

The planet is warmer than at any time in our recorded past and increasing greenhouse emissions and persistence in the climate system means that continued warming is highly likely. Climate change has already altered the basic framework of growing grapes for wine production worldwide and will likely continue to do so for years to come. The wine sector can continue to play an important role in leading the agricultural sector in addressing climate change. From developing on…

A better understanding of the climate effect on anthocyanin accumulation in grapes using a machine learning approach

The current climate changes are directly threatening the balance of the vineyard at harvest time. The maturation period of the grapes is shifted to the middle of the summer, at a time when radiation and air temperature are at their maximum. In this context, the implementation of corrective practices becomes problematic. Unfortunately, our knowledge of the climate effect on the quality of different grape varieties remains very incomplete to guide these choices. During the Innovine project, original experiments were carried out on Syrah to study the combined effects of normal or high air temperature and varying degrees of exposure of the berries to the sun. Berries subjected to these different conditions were sampled and analyzed throughout the maturation period. Several quality characteristics were determined, including anthocyanin content. The objective of the experiments was to investigate which climatic determinants were most important for anthocyanin accumulation in the berries. Temperature and irradiance data, observed over time with a very thin discretization step, are called functional data in statistics. We developed the procedure SpiceFP (Sparse and Structured Procedure to Identify Combined Effects of Functional Predictors) to explain the variations of a scalar response variable (a grape berry quality variable for example) by two or three functional predictors (as temperature and irradiance) in a context of joint influence of these predictors. Particular attention was paid to the interpretability of the results. Analysis of the data using SpiceFP identified a negative impact of morning combinations of low irradiance (lower than about 100 μmol m−2 s−1 or 45 μmol m−2 s−1 depending on the advanced-delayed state of the berries) and high temperature (higher than 25oC). A slight difference associated with overnight temperature occurred between these effects identified in the morning.