Application of multivariate data analysis for food quality investigations: An example-based review

Buvé, Carolien; Saeys, Wouter; Rasmussen, Morten; Neckebroeck, B.; Hendrickx, Marc; Grauwet, Tara; Loey, Ann Van

doi:10.1016/j.foodres.2021.110878

Cited by 30 publications

(22 citation statements)

References 76 publications

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“…By using PCA analyses, the similarity and, thus, the potential substitution of one variety for another in the use of basil aromas can so clearly be determined without the need for a trained olfactory specialist. Furthermore, this successful chemometric approach enables investigations into food or drug fraud …”

Section: Resultsmentioning

confidence: 99%

Detection and Quantification of Terpenes and Terpenoids in Different Basil Species and Cultivars

Beck

2022

ACS Agric. Sci. Technol.

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Basil is used as a herb/spice and medical remedy all over the world. Various cultivars are been known to be rich in terpenes and terpenoids. However, the specific concentrations within leaves are not known, as typically only essential oils are analyzed. In order to investigate basil leaves directly, these were dried and terpenes and terpenoids were extracted with isooctane. Resulting extracts were subjected to chemical analyses. By using gas chromatography−mass spectrometry in combination with mass spectral database searches, we have identified 52 terpenes and terpenoids directly from leaf extracts. Furthermore, we employed 17 chemical standards to verify the correct identification of these substances and utilize these as standards in gas chromatography-flame ionization detection analyses to absolutely quantify these 17 terpenes and terpenoids from 11 different basil varieties for the first time. Here, terpene and terpenoid contents in the nanogram per milligram of leaf material range were observed. The most abundantly quantified substances proved to be β-myrcene, eucalyptol, linalool, eugenol, methyleugenol, and neophytadiene, while the determined concentrations varied significantly between investigated species/cultivars that might aid olfactory or medical applications in the future. Furthermore, principal component analyses were carried out with gas chromatography−mass spectrometry data. Here, 4 distinct groups of basil species/cultivars were identified and all 11 investigated basil varieties spanned these groups that were termed citrus, cinnamon/clove, spicy, and common. The successful separation into distinct groups in principal component analyses might lead to applications in food/drug fraud investigations in the future. Further insights into the phytochemical diversity of basil varieties have been obtained.

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Section: Resultsmentioning

confidence: 99%

Detection and Quantification of Terpenes and Terpenoids in Different Basil Species and Cultivars

Beck

2022

ACS Agric. Sci. Technol.

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“…The data are stored on a local computer/online platform for further analysis. Due to the multivariate data obtained from the gas sensor array of the E-nose system, data analysis is usually performed via supervised/unsupervised machine learning algorithms with statistical methods such as principal component analysis (PCA) [49][50][51], hierarchical cluster analysis (CA) [52,53], analysis of variance (ANOVA) [54], linear discriminant analysis (LDA) [55], partial least squares discriminant analysis (PLS-DA) [56], simple visualization techniques [57], multivariate data analysis [58], artificial neural networks (ANNs) [59][60][61], artificial intelligence (AI) [62] and F-test [63]. A photograph and schematic diagram of a prototype portable E-nose system are displayed in Figure 3.…”

Section: History and Basic Principle Of E-nosementioning

confidence: 99%

“…analysis (PCA) [49][50][51], hierarchical cluster analysis (CA) [52,53], analysis of variance (ANOVA) [54], linear discriminant analysis (LDA) [55], partial least squares discriminant analysis (PLS-DA) [56], simple visualization techniques [57], multivariate data analysis [58], artificial neural networks (ANNs) [59][60][61], artificial intelligence (AI) [62] and F-test [63]. A photograph and schematic diagram of a prototype portable E-nose system are displayed in Figure 3.…”

Section: History and Basic Principle Of E-nosementioning

confidence: 99%

Recent Progress in Electronic Noses for Fermented Foods and Beverages Applications

Seesaard

Wongchoosuk

2022

Fermentation

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Fermented foods and beverages have become a part of daily diets in several societies around the world. Emitted volatile organic compounds play an important role in the determination of the chemical composition and other information of fermented foods and beverages. Electronic nose (E-nose) technologies enable non-destructive measurement and fast analysis, have low operating costs and simplicity, and have been employed for this purpose over the past decades. In this work, a comprehensive review of the recent progress in E-noses is presented according to the end products of the main fermentation types, including alcohol fermentation, lactic acid fermentation, acetic acid fermentation and alkaline fermentation. The benefits, research directions, limitations and challenges of current E-nose systems are investigated and highlighted for fermented foods and beverage applications.

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“…Principal component analysis (PCA) is a powerful data analysis method, which can extract information from multivariate data sets to discover the overall trend changes. Then, the univariate score is compared with the whole to show whether the univariate description of the whole is reasonable (Buve et al., 2022). Therefore, the relationship between LF‐NMR, FD, and the quality of tilapia fillets can be studied by PCA to evaluate the feasibility of these two methods as a rapid assessment of water changes in tilapia fillets.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the water state and microfractal dimension of tilapia fillets during freezing and thawing

Luo

Lin

et al. 2023

Journal of Food Science

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To study the effects of freezing and thawing times and freezing temperatures on the water state and microstructure of tilapia fillets, experiments on tilapia fillets were carried out at –4 and –18°C with one to four freezing and thawing cycles (FTCs). Low‐field nuclear magnetic resonance (LF‐NMR) and nuclear magnetic resonance imaging were used to observe the water state after different treatments, and scanning electron microscopy (SEM) and frozen sections were used to observe the microstructure changes. Fractal dimension (FD) was used to quantitatively characterize the microstructure of the fish tissue, and the correlation between FD and fish fillet quality parameters was studied by principal component analysis (PCA). The findings showed that with the increase of FTCs, the thawing loss increased, and the water holding capacity (WHC) fell. FTCs cause a decrease in immobilized water and an increase in free water in the fillet. This indicates the migration of immobilized water to free water. SEM and frozen slice images showed that the growth of ice crystals led to the destruction of myogenic fibers. A decrease in freezing temperature inhibited ice crystal growth. The FD value dropped in accordance with an increase in FTCs. PCA demonstrated that the WHC, NMR data, and FD value had a strong correlation with the quality changes in the tilapia fillets. Therefore, FD and water state can reflect the quality characteristics of tilapia fillets. Practical Application The water migration in tilapia fillets is detected with LF‐NMR, and the microscopic image may be quantified using the FD value. Both approaches can offer fresh perspectives on how to assess the quality of tilapia fillets and reflect changes in their quality.

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Application of multivariate data analysis for food quality investigations: An example-based review

Cited by 30 publications

References 76 publications

Detection and Quantification of Terpenes and Terpenoids in Different Basil Species and Cultivars

Detection and Quantification of Terpenes and Terpenoids in Different Basil Species and Cultivars

Recent Progress in Electronic Noses for Fermented Foods and Beverages Applications

Analysis of the water state and microfractal dimension of tilapia fillets during freezing and thawing

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