 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

Increasing microalgae biomass feedstock by valorizing wine gaseous and liquid residues

Global warming due to greenhouse gases (GHG) has become a serious worldwide concern. The new EU Green Deal aims t0 achieve GHG emissions reduction by at least 55% by 2030 and a climate neutral EU economy by 2050. The deal strongly encourages GHG reducing measures at local, national and European levels. The REDWine project will demonstrate the technical, economic and environmental feasibility of reducing by, at least, 31% of the CO2 eq. emissions produced in the winery industry value chain by utilizing biogenic fermentation CO2 for microalgae biomass production

Analysis of Cabernet Sauvignon and Aglianico winegrape (V. vinifera L.) responses to different pedo-climatic environments in southern Italy

Water deficit is one of the most important effects of climate change able to affect agricultural sectors. In general, it determines a reduction in biomass production, and for some plants, as in the case of grapevine, it can endorse fruit quality. The monitoring and management of plant water stress in the vineyard

A facile and robust method for the quantification of polyphenols in red wine via NMR

Nuclear magnetic resonance spectroscopy (NMR) is a high-tech analytical method that recently found its way into the field of wine analysis with special focus on wine authentication.

Trans-resveratrol concentrations in wines Cabernet Sauvignon from Chile

This study evaluated the levels of trans-resveratrol in commercial wines made from Cabernet Sauvignon grapes from different valleys of Chile stilbenes. The Cabernet Sauvignon is the most planted variety in Chile, being 38% of the total vineyard country. Chile is the fourth largest wine exporter in the world, so it is important to evaluate the Cabernet-Sauvignon wines in their concentration levels of trans-resveratrol and its relation to the benefits provided to human health in moderate consumption. Evaluation comprises commercial wines from different valleys of Chile and its relationship with climatic characteristics, soil and vineyard handling.

Relationships between sensitivity to high temperature, stomatal conductance and vegetative architecture in a set of grapevine varieties

High temperatures influence plant development and induce a large set of physiological responses at the leaf scale. Stomatal closure is one of the most observed responses to high temperatures. This response is commonly considered as an adaptive strategy to reduce water loss and embolism in the vascular system caused by the high evaporative demand.