Diffuse reflectance Fourier transform infrared spectroscopy for simultaneous quantification of total phenolics and condensed tannins contained in grape seeds

Kyraleou, Maria; Pappas, Christos S.; Voskidi, Eleni; Kotseridis, Yorgos; Basalekou, Marianthi; Tarantilis, Petros Α.; Καλλιθράκα, Σταματίνα

doi:10.1016/j.indcrop.2015.06.016

Cited by 28 publications

(12 citation statements)

References 41 publications

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“…(CLT-2; mulberry, raspberry) are considered moderate sources of extractable and hydrolysable phenols; the third one (CLT-3) comprises just one fruit (blueberry) with a closest similarity to those belonging to the fourth cluster (CLT-4; blackberry, strawberry) but differing in their content in hydrolysable phenols (third) and proanthocyanidins (fourth). In support of this, a more diverse composition of bounded phenolics has been reported for berry fruits (Hager et al, 2008;Boeing et al, 2014;Nile & Park, 2014;Li et al, 2016) when compared to table grapes that are rich in flavan-3-ol oligomers or pomegranate which is rich in ellagitannins (Kyraleou et al, 2015). As previously stated, chemometrics has been used in food science and technology.…”

Section: Chemometricsmentioning

confidence: 58%

“…), following the same criteria identified in principal component analysis: the horizontal axis represents the distance or dissimilarity between clusters, while the vertical axis represents individual fruits and to which cluster (group) they belong to; from top to bottom, the first cluster (CLT‐1) comprises three fruits (green and red globe grapes, pomegranate) with the lowest content of phenolic compounds (extractable and hydrolysable phenols), fruits in the second cluster (CLT‐2; mulberry, raspberry) are considered moderate sources of extractable and hydrolysable phenols; the third one (CLT‐3) comprises just one fruit (blueberry) with a closest similarity to those belonging to the fourth cluster (CLT‐4; blackberry, strawberry) but differing in their content in hydrolysable phenols (third) and proanthocyanidins (fourth). In support of this, a more diverse composition of bounded phenolics has been reported for berry fruits (Hager et al ., ; Boeing et al ., ; Nile & Park, ; Li et al ., ) when compared to table grapes that are rich in flavan‐3‐ol oligomers or pomegranate which is rich in ellagitannins (Kyraleou et al ., ).…”

Section: Resultsmentioning

confidence: 97%

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In vitro digestibility of phenolic compounds from edible fruits: could it be explained by chemometrics?

Olivas-Aguirre

Gaytán–Martínez

Mendoza-Díaz

et al. 2017

Int J of Food Sci Tech

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Summary The health benefits of phenolic compounds depend on the ingested amount, molecular diversity and gastrointestinal digestibility. The phenolic profile of eight fruits (blackberry, blueberry, strawberry, raspberry, mulberry, pomegranate, green and red globe grapes) was chemometrically associated with their in vitro digestibility (oral, gastric, intestinal). Extractable phenols, flavonoids and anthocyanins strongly correlated with each other (r ≥ 0.84), proanthocyanidins with anthocyanins (r = 0.62) and hydrolysable phenols with both extractable phenols (r = 0.45) and proanthocyanidins (r = −0.54). Two principal components explained 93% of the variance [61% (free‐phenols), 32% (bounded‐phenols)], and four clusters were confirmed by hierarchical analysis, based in their phenolic richness (CLT 1‐4: low to high) and molecular diversity. In vitro digestibility of extractable phenols and flavonoids was blackberry (CLT‐4)> raspberry (CLT‐2)> red grape (CLT‐1) related to their phenolic richness (r ≥ 0.96; P < 0.001), but anthocyanins’ digestibility was pH‐dependent. Chemometrics is useful to predict the in vitro digestibility of phenolic compounds in the assayed fruits.

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Section: Chemometricsmentioning

confidence: 58%

Section: Resultsmentioning

confidence: 97%

In vitro digestibility of phenolic compounds from edible fruits: could it be explained by chemometrics?

Olivas-Aguirre

Gaytán–Martínez

Mendoza-Díaz

et al. 2017

Int J of Food Sci Tech

View full text Add to dashboard Cite

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“…Phenolic compounds are the main active ingredients in grape juice (Revilla & Ryan, ). Phenolic compounds are important substances with complex structures, such as procyanidins, catechuic acid, and vitamins (Kyraleou et al., ; Lecce et al, ; Montealegre, Peces, Vozmediano, Gascueña, & Romero, ). The concentration efficiency of phenolic compounds from plant materials depends on several parameters, such as temperature, time, and pressure.…”

Section: Introductionmentioning

confidence: 99%

Exploring the nanofiltration mass transfer characteristic and concentrate process of procyanidins from grape juice

Ma²,

et al. 2019

Food Science & Nutrition

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In order to separate procyanidins from grape juice at room temperature, a separation prediction model was established based on nanofiltration. The mass transfer coefficient was positively correlated with the initial concentration. Nanofiltration performance of procyanidins was affected by filtration conditions, membrane properties, and molecular states. The correlation between mass transfer coefficient and initial concentration was established based on the linear equations of the rejection and mass transfer coefficient. The rejection of procyanidins predicted with the mass transfer model was in accordance with the experimental value, and the antioxidant activity was preserved effectively. The mathematical model could predict the rejection of procyanidins. The nanofiltration technology for procyanidin separation from grape juice was characterized by fast separation, low energy consumption, and zero oxidization loss. The nanofiltration technology could greatly improve the utilization efficiency of food products and decrease the energy consumption.

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“…When combined with multivariate data analysis, such as Partial Least Squares (PLS) regression analysis, they are suitable for correlating the spectral response of a sample with its chemical composition [ 10 ]. The application of both near- and mid-infrared spectroscopic methods to grape and wine analysis has become a valuable alternative to the slow and destructive analytical procedures which are routinely used as the classic UV-Vis and chromatographic techniques [ 11 – 16 ] or even for monitoring wine ageing in barrels [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Red Wine Age Estimation by the Alteration of Its Color Parameters: Fourier Transform Infrared Spectroscopy as a Tool to Monitor Wine Maturation Time

Basalekou

Pappas

Kotseridis

et al. 2017

Journal of Analytical Methods in Chemistry

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Color, phenolic content, and chemical age values of red wines made from Cretan grape varieties (Kotsifali, Mandilari) were evaluated over nine months of maturation in different containers for two vintages. The wines differed greatly on their anthocyanin profiles. Mid-IR spectra were also recorded with the use of a Fourier Transform Infrared Spectrophotometer in ZnSe disk mode. Analysis of Variance was used to explore the parameter's dependency on time. Determination models were developed for the chemical age indexes using Partial Least Squares (PLS) (TQ Analyst software) considering the spectral region 1830–1500 cm−1. The correlation coefficients (r) for chemical age index i were 0.86 for Kotsifali (Root Mean Square Error of Calibration (RMSEC) = 0.067, Root Mean Square Error of Prediction (RMSEP) = 0,115, and Root Mean Square Error of Validation (RMSECV) = 0.164) and 0.90 for Mandilari (RMSEC = 0.050, RMSEP = 0.040, and RMSECV = 0.089). For chemical age index ii the correlation coefficients (r) were 0.86 and 0.97 for Kotsifali (RMSEC 0.044, RMSEP = 0.087, and RMSECV = 0.214) and Mandilari (RMSEC = 0.024, RMSEP = 0.033, and RMSECV = 0.078), respectively. The proposed method is simpler, less time consuming, and more economical and does not require chemical reagents.

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Diffuse reflectance Fourier transform infrared spectroscopy for simultaneous quantification of total phenolics and condensed tannins contained in grape seeds

Cited by 28 publications

References 41 publications

In vitro digestibility of phenolic compounds from edible fruits: could it be explained by chemometrics?

In vitro digestibility of phenolic compounds from edible fruits: could it be explained by chemometrics?

Exploring the nanofiltration mass transfer characteristic and concentrate process of procyanidins from grape juice

Red Wine Age Estimation by the Alteration of Its Color Parameters: Fourier Transform Infrared Spectroscopy as a Tool to Monitor Wine Maturation Time

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