 IVES 9 IVES Conference Series 9 Data fusion approaches for sensory and multimodal chemistry data applied to storage conditions

Data fusion approaches for sensory and multimodal chemistry data applied to storage conditions

Abstract

AIM: The need to combine multimodal data for complex samples is due to the different information captured in each of the techniques (modes). The aim of the study was to provide a critical evaluation of two approaches to fusing multi-modal chemistry and sensory data, namely, multiblock multiple factor analysis (MFA) and concatenation using principal component analysis (PCA).

METHODS: Wines were submitted to sensory analysis using Pivot©Profile (Thuillier et al. 2015) and chemical analysis in four modes: antioxidant measurements (AM), volatile compounds composition (VCC), ultraviolet-visible light (UV-Vis) spectrophotometry (Mafata et al. 2019), and infra-red (IR) spectroscopy. Correspondence analysis (CA), principal component analysis (PCA), and multiple factor analysis (MFA) were used to model data under the data analysis steps involving data cleaning, visualizing, modelling and evaluation (Pagès 2004). Percentage explained variation (%EV) and regression vector (RV) coefficients were used as comparative evaluation parameters between data models (Abdi 2007).

RESULTS: IR spectral data were used as an example of the assessment of the need for data cleaning/pre-processing. Similarities in MFA and high RV coefficients indicated that the raw (unprocessed data) could be used for the data fusion. High RV coefficients and MFA proximity between the antioxidants and UV-Vis measurements indicated an overlap between the type of information contained in the two. The differences between the information captured in each of the five modes can be seen in the different measurements, from the knowledge of the theory/ ontext behind the technique, and statistically. Statistically, the differences are measured and visualised by a lack of overlap (redundancy) in the MFA and its accompanying cluster analysis.

CONCLUSIONS

The %EV when performing PCA are higher than with MFA, a consequence of fusing big data sets from various modes and not necessarily a direct result of the relationships among the data sets. Therefore, the %EV was ruled out as a reliable measure of the differences in informational value between MFA and PCA fusion strategies. RV coefficients, of which MFA were highest, were the best measurements of the performance of data fusion approaches. MFA demonstrated greater appropriateness as a statistical tool for fusing multi-modal data.

DOI:

Publication date: September 13, 2021

Issue: Macrowine 2021

Type: Article

Authors

Jeanne Brand

South African Grape and Wine Research Institute, Department of Viticulture and Oenology, Stellenbosch University, South Africa,Mpho, MAFATA, South African Grape and Wine Research Institute, Department of Viticulture and Oenology, Stellenbosch University, South Africa Martin, KIDD, Centre for Statistical Consultation, Stellenbosch University, South Africa Andrei, MEDVEDOVICI, Faculty of Chemistry, University of Bucharest, Romania Astrid, BUICA, South African Grape and Wine Research Institute, Department of Viticulture and Oenology, Stellenbosch University, South Africa

Contact the author

Keywords

data fusion; sensory evaluation; chemical composition; white wines; storage

Citation

Ancient and recent construction of Terroirs

The local wine as an area identified and recognized is a complex socio-historical reality that calls an effort of observation and theoretical reflection using various social sciences

How to deal with the Green Deal – Resistant grapevine varieties to reduce the use of pesticides in the EU

With its Farm-to-Fork Strategy, which is a part of the European Green Deal, the European Union aims at reducing the amount of pesticides used in agriculture by 50% until 2030. As viticulture uses around 70% of the fungicides in the EU, there is substantial pressure on winemakers to reduce their pesticide input. On top of the political goal, winegrowers face increased pressure from the public demanding a more sustainable production of wine.

Effect of different plant fibers on the elimination of undesirable compounds in red wine

The presence of undesirable compounds in wines, such as ota, biogenic amines and pesticides residues, affects wine quality and can cause health problems for the consumer. Additionally, an excess of tannins can produce an undesirable increase in the astringency and bitterness of the wine, so tannins are also a target for reduction. The main tool that a winemaker has to reduce their content in the wine is fining. However, some of the fining agents commonly used in the winery can cause allergies or even increase the protein content in the wine, increasing the turbidity.

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.

1H-NMR-based Untargeted Metabolomics to assess the impact of soil type on the chemical composition of Mediterranean red wines

Untargeted metabolomics has proven to be an effective method to study the impact of the terroir on metabolic profile of wines. In this context, the aim of this study was to evaluate the effects of different soil types on the chemical composition of Mediterranean red wines, through 1H-NMR metabolomics combined with chemometrics.Grapes from Nero d’Avola L. red cultivar cultivated on four different soil types were separately vinified to obtain four different red wines.One milliliter of raw wine was analyzed by means of a Bruker Avance II 400 spectrometer operating at 400.15 MHz