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…

A multidisciplinary approach to evaluate the effects of the training system on the performance of “Aglianico del Vulture” vineyards

Vineyards are complex agro-ecosystems with high spatial and temporal variability. An efficient training system may counteract the adverse effects of this variability. Moreover, considering the climate change issues, choosing an efficient training system that enhances water use and protects the vines from radiative thermal stress has become a priority for the farmers. A multidisciplinary approach that assesses the soil-crop-yield-wine relationships of vineyards in a distributed and holistic way could bring added knowledge on the behavior of the different training systems. This ongoing research aimed to implement a multidisciplinary approach to study the behavior of “Aglianico del Vulture” grapevines trained with two different systems: a spurred cordon (SC) and an “Alberello in parete” (AL), grown in a high-quality wine production area of Basilicata region (Italy). The approach merged several methods and scales of soil, ecophysiology, must/wine quality, and spectral data collection to assess the influence of the training system. Homogeneous zones (HZs) in both training systems were defined through a procedure based on geomorphological classification, unmanned aerial vehicles (UAV) images analysis, and a traditional soil survey supported by geophysical scanning. During the 2021 season, TDR probes monitored soil water content, while grapevine health status was assessed using eco-physiological measurements (LWP, chlorophyll content, PSII photosynthetic efficiency, LAI, and point-based field spectroscopy). These grapevine in-vivo measurements validated the spectral vegetation indexes (NDVI, RENDVI, CVI, and TVI) derived from the UAV multispectral imagery, which monitored the grapevine status in a distributed and non-invasive way. Grape yield, quality of berries, must and wine were measured to assess the effects of the training systems. The first experimental year results showed the variability of the vineyards and revealed relationships among soil parameters, crop characteristics, and vegetation indices of the SC and AL training systems. This multidisciplinary study could bring new insights into the vineyard training system’s effects on grape yield and wine quality.

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…

Postveraison shoot trimming in Tannat and Merlot: preliminary results on yield components, plant balance and berry composition

There is currently a trend towards the production of wines with low alcohol content. To achieve this, grapes with low sugar content must be used. There are techniques at the vineyard level that can delay ripening and avoid excessive sugar accumulation without, a priori, affecting the final polyphenol content. Postveraison shoot trimming (PVST) is experimentally evaluated for these purposes, but its impact under Uruguayan climatic conditions with high interannual variability is not known. The aim of this work is to assess the PVST in Tannat and Merlot cultivars and their impact on yield components, plant balance and berry primary composition. In this study, two commercial vineyards of 10 years old Tannat and Merlot (grafted on SO4) at Canelones Department were selected. During the 2020-201 growing season, grapevines were submitted to PVST when grapes reached 15º Brix. In a randomized block, trimmed (T) and control (C) plants were evaluated with three repetitions each cultivar. Evaluation of the evolution of primary berry composition during ripening, measurement of yield components and plant balance were performed. For both cultivars, PVST did not affect yield components. Merlot reached 5.4 kg per plant and Tannat 7.1 kg, with not statistical significance between treatments. However, statistical differences were observed in terms of plant balance. In Merlot Ravaz Index reached a difference of 5.3 (12.0 in T and 6.7 in C) meanwhile Tannat reached 3.5 of statistical difference (13.7 in T and 10.2 in C). The tendency to imbalance for the treated plants had an impact on the final grape composition. Merlot grapes showed statistical difference in final total acidity (0.3 g of difference between treatments) while treatments impact final sugar content on Tannat grapes (10.0 g of difference between treatments). Further studies are needed to assess the impact of different canopy management techniques in our conditions.

Grapevine yield estimation in a context of climate change: the GraY model

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.

Influence of climatic conditions on grape composition of Tempranillo in La Mancha DO (Spain)

The aim of this work was to analyze the variability in grape composition of the Tempranillo cultivar related to climatic conditions, in La Mancha Designation of Origin. Grape composition (sugar content, total acidity, pH, malic acid, and total and extractable anthocyanins) recorded during ripening, were analysed for the period 2000-2019. The weather conditions at daily time scale, recorded during the same period, were also evaluated. The relationships between grape parameters with climatic variables related to temperature and to water deficits, referring different periods between phenological events along the growing cycle, were evaluated using regression analysis. High variability in grape composition was observed in the period analysed. Total acidity varied between 3.7 and 7.3 gL-1 while malic acid varied between 1.2 and 4 gL-1. The extractable anthocyanins ranged between 526 and 972 mgL-1, and total anthocyanins ranged between 922 and 1388 mgL-1, being the lowest values recorded in the hottest year (2017). Total acidity decreased 0.77 gL-1 for an increase of 100 GDD, while malic acid decrease in 0.42 gL-1 for the same GDD increase, being the period between veraison and harvest the one that seemed to have higher influence on acidity. In addition, it was confirmed that increasing water deficits decreased acidity. Total and extractable anthocyanins increased in about 210 and 105 mgL-1, respectively, with an increase of 100 GDD from veraison to harvest, and the increase in water deficits favour the increase of anthocyanins, both total and extractable anthocyanins. Total and extractable anthocyanins concentration increased in 35 and 22 mgL-1 per an increase of 10 mm in the water deficit. These results can be of interest to understand the potential changes that grapes composition may suffer under future warmer climates.