Chapter 5
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Contribution of Phenolic Compounds to Sensory Profiles of Blackcurrant Juices Oskar Laaksonen and Baoru Yang* Food Chemistry and Food Development, Department of Biochemistry, University of Turku, FI-20014, Turku Finland *E-mail:
[email protected].
Blackcurrant (Ribes nigrum) juice was produced with or without enzymatic assistance in laboratory and industrial scales. Phenolic profiles (proanthocyanidins, anthocyanins, flavonols, hydroxycinnamic acids) and taste (sweetness, sourness, bitterness) and astringent (mouthdrying, puckering) characteristics of the juice were analyzed. The compositional and sensory data were processed with multivariate regression models. Compared with the non-enzymatic process, the enzyme-aided process resulted in higher contents of phenolic compounds along with higher astringencies and bitterness in juices produced at both laboratorial and industrial scales. The mouth-drying astringency of the juices was positively associated with the contents of all subgroups of phenolic compounds and molecular size of proanthocyanidins but negatively with the procyanidin/prodelphinidin ratio. Puckering astringency correlated with sourness and lower juice pH as well as with phenolic variables. High pectin content may have masked the astringency of the non-enzymatic juices. Increased astringency and bitterness as a result of the enzymatic process may affect negatively the consumer acceptance of blackcurrant juices.
© 2015 American Chemical Society Guthrie et al.; The Chemical Sensory Informatics of Food: Measurement, Analysis, Integration ACS Symposium Series; American Chemical Society: Washington, DC, 2015.
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Introduction Berries, fruits and vegetables form an important part of a healthy human diet. They are rich in dietary fiber, micronutrients, and potential bioactive constituents. Dietary patterns rich in these elements may be associated with lower risk of most chronic diseases. However, despite their health benefits, daily intakes of fruits and vegetables remain inadequate. Western-type dietary patterns are characterized by high consumption of meat and products with low content of essential nutrients and high content of salt. Various health authorities around the world recommend increase in consumption of berries, fruits and vegetables. Sensory properties characterized by high intensities of astringency and bitterness are often factors limiting the use of berries and berry products by the consumers. Phenolic compounds are commonly associated with astringency and bitterness in food. Astringency can be described as drying, puckering and rough sensation in oral cavity (1–3). A commonly accepted hypothesis is that polymeric tannins in food bind and precipitate salivary proteins resulting in astringent sensation in the mucous membranes. The structural characteristics of tannin molecules affect the binding to proteins (4) and therefore the sensory properties of food. Some phenolic compounds, such as flavonol glycosides, do not bind to salivary proteins, but elicit the astringent sensation by different mechanisms (5). Flavonols (quercetin, myricetin and kaempferol) and flavan-3-ols ((+)-catechin, (–)-epicatechin and (–)epigallocatechin) can activate the human bitter taste receptors (6, 7). Additionally, a procyanidin trimer activated some bitter receptors whereas a dimer did not (7). The sensory properties of food are influenced by not only the content of individual compounds but also the interactions between different components as well as with food matrixes. Blackcurrant (Ribes nigrum) is the second largest cultivated berries in Europe, just after strawberry. The health benefits of blackcurrant berries are supported by traditional use and modern research. Juice pressing is the most important industrial processing of blackcurrant berries. In this study, we aim to investigate the effects of cultivars and processing technologies on the composition and sensory properties of blackcurrant juices with multivariate statistical models. Special attention was paid to different groups of phenolic compounds and correlation of these compounds with astringencies and bitterness that are often perceived as negative attributes of blackcurrant juices.
Materials and Methods Samples The juice samples were produced in laboratory scale from five different Finnish blackcurrant cultivars, four commercial cultivars ‘Mortti’, ‘Mikael’, ‘Marski’, ‘Ola’ and a new breed, ‘Breed15’ (8, 9). Berries were harvested in 2010 from southern Finland from the test filed of MTT Piikkiö, Agrifood Research Finland. Two juice processing methods were applied for each cultivar. The first process was carried out without enzymes and the second with the aid of a 58 Guthrie et al.; The Chemical Sensory Informatics of Food: Measurement, Analysis, Integration ACS Symposium Series; American Chemical Society: Washington, DC, 2015.
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commercial enzyme product, Pectinase 714L (Biocatalysts Ltd, Cardiff, UK). The juice processing in laboratory scale did not include pasteurization. All juice samples were frozen at -20 °C right after the processing until analyses. For the industry-scale processing (10), blackcurrant berries of the cultivar ‘Mortti’ were harvested from the cultivation field of Saarioinen Oy (Huittinen, Finland) in 2011 and processed with facilities of Saarioinen Oy. Four different juices were produced: two without the aid of enzymes (No enzymes juices 1 and 2) and two with enzymes (Enzyme juices 3 and 4) The juices were pasteurized and bottled in Marjajaloste Meritalo Oy (Salo, Finland). Thereafter the juices were stored in dark at +4 °C for further analyses. Compositional Analyses Anthocyanins, flavonol glycosides (and possible flavonol aglycons) and hydroxycinnamic acids in the juice samples were analyzed using methods as described previously (11, 12). For qualitative and quantitative analyses of proanthocyanidins, a method reported by Engström and colleagues was used (13). Sugars and acids were analyzed by gas chromatography as trimethylsilyl derivatives in duplicates using the method previously applied in our laboratory (14). All results from aforementioned analyses are presented as sums of individual compounds (total contents) of each group or as their ratios. Sensory Evaluation Sensory characteristics of the juice samples were evaluated using generic descriptive analysis by two panels (8, 10). The sensory evaluation was focused on taste (sourness, sweetness and bitterness) and two astringency (mouthdrying and puckering) attributes. The intensities of these attributes were rated on a continuous graphical scale from 0 (none) to 10 (very strong) with references. Reference samples were water solutions of citric acid (0.1%) for sourness, fructose (0.07%) for sweetness, caffeine (0.07%) for bitterness, ammonium aluminum sulphate (0.2%) for mouth-drying astringency and aluminum sulphate (0.2%) for puckering astringency. The panelists were trained to focus on the sub-qualities of the astringency references instead of the whole astringent sensation. The data were collected using Compusense-five software (Compusense Inc., Guelph, Canada). Statistical Analyses Partial least squares regression (PLS) method was applied for standardized data with X-variables (predictors) as chemical compound sums and their ratios and Y-variables (responses) as the sensory properties. The models are shown as correlations loading plots where the outer ellipse indicates 100% of explained variance and the inner 50% and the samples are presented as downweighted variables. Full cross validation was used to estimate the number of factors for a statistically reliable model. Multivariate models were conducted using Unscrambler 10.3 (Camo Process AS, Oslo, Norway). 59 Guthrie et al.; The Chemical Sensory Informatics of Food: Measurement, Analysis, Integration ACS Symposium Series; American Chemical Society: Washington, DC, 2015.
Results and Discussion
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Chemical Profiles of the Juices
Table 1 presents the averaged juice yields and compositional profiles of the blackcurrant juices pressed from berries of different cultivars. The main differences between averaged juices were observed between non-enzyme and enzyme juices rather than between laboratory and industry scales. Juice yields were notably higher in the processes with enzymatic assistance than in those without the use of enzyme. In the laboratory processing (8), the yields varied among the five cultivars with the highest yields obtained from berries of the cultivar ‘Mikael’ in both enzyme-aided and non-enzymatic processes. Viscosity of the juice of ‘Mikael’ was the lowest, whereas that of ‘Mortti’ was the highest with the lower yield. In the industrial scale processing (10), the yields were calculated based on the amounts of press residues. The juice yield for non-enzymatic pressing was approximated 31 % (No enzyme 1). Part of this juice was further processed by clarification and filtration to produce the second juice of the non-enzymatic pressing (No enzyme 2). Due to the high viscosity, some water was added to the juice during the filtration and clarification. The use of alternative cultivars with lower viscosity may increase the yields of non-enzymatic processing in industrial scale. Although there was not notable difference in sugar contents between juices from the two processes in the laboratory scale, in industry scale pressing the nonenzymatic process resulted in higher contents of sugars than the enzymatic process. Contrary to this, more variation was found in the acid content among laboratory scale juices. All in all, the ratio between sugars and acids was lower in enzymeaided juices than in non-enzymatic juices. The enzyme-aided juices had significantly higher contents of all phenolic compound subclasses than the non-enzymatic juices (Table 1). Cultivars ‘Mortti’ and ‘Ola’ had the highest contents of phenolic compounds among the five cultivars in spite of the process. Flavonol aglycons do not typically exist in free form in abundance, but can be released due to hydrolysis caused by different processes. No free flavonol aglycons were detected in the laboratory-scale juices which were not pasteurized. However, in corresponding industry-scale juices, free flavonol aglycones were observed indicating that heat-treatment may have broken the glycosidic bonds. Mean degree of polymerization (Table 1) indicates the average number of flavanol monomeric units present in the numerous oligomeric and polymeric condensed tannins present in the juice samples. The mDP value of proanthocyanidins was significantly higher in enzyme-aided juices than in the non-enzymatic juices (Table 1). The PC:PD was also higher in enzyme-aided juices, which indicated the higher PD contents compared to PC in the skins compared to the flesh of blackcurrant berries.
60 Guthrie et al.; The Chemical Sensory Informatics of Food: Measurement, Analysis, Integration ACS Symposium Series; American Chemical Society: Washington, DC, 2015.
Table 1. Chemical Characteristics of Juices Averaged within Processes. Data Are from References (8–10).
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Laboratory scale
a
Industry scale
a
No enzymes
Enzymes
No enzymes
Enzymes
Juice yield (%)
62–70
71–77
approx. 31
80–91
pH
2.8
3.0
3.0
3.0
°Brix
16.4
15.0
12.8
13.0
Sugars (SUG)
9950 ± 725
9960 ± 1450
8770 ± 1470
7550 ± 150
Acids (ACID)
2850 ± 290
3530 ± 600
2540 ± 410
2670 ± 80
Phen.compounds (PHE) b
68
416
179
411
Anthocyanins (ANT)
44.6 ± 27
275 ± 50
138 ± 9.8
227 ± 2.6
Flavonol glycosides (FG)
2.5 ± 1.5
8.2 ± 2.3
6.5 ± 0.6
8.7 ± 0.5
Free flavonol aglycons (FG)
-
1.1 ± 0.7
0.9 ± 0.2
1.0 ± 0.4
Hydroxycinnamic acids (HCA)
2.5 ± 0.9
5.3 ± 1.3
3.9 ± 0.6
5.5 ± 0.2
Proanthocyanidins (PA) b
16.7
126
29.7
169
Procyanidins (PC)
6.9 ± 1.7
17.9 ± 7.7
11.7 ± 0.4
21.9 ± 6.6
Prodelphinidins (PD)
9.8 ± 7.8
108 ± 35
18.0 ± 1.5
146 ± 48
Mean degree of polymerization (mDP)
5.2
13.3
4.0
21.1
Contents presented as mg/100 mL. Averages of five cultivar juices in laboratory scale; averages of two juices in industrial scale b Phenolic compounds, PHE, is the sum of phenolic compound classes; proanthocyanidins, PA, is the sum of PC and PD.
a
Sensory Profiles of the Juices Taste and astringency profiles of juices from different processes are shown in Figure 1. The results are averages of five cultivars. All juices were significantly sour, and this attribute was not affected by the processes. Sweetness was rated lower in enzyme-aided juices than in the non-enzyme juices, but statistical difference was found only between juices from industry scale processing. Enzyme-aided juices were significantly more bitter, mouthdrying astringent and puckering astringent. 61 Guthrie et al.; The Chemical Sensory Informatics of Food: Measurement, Analysis, Integration ACS Symposium Series; American Chemical Society: Washington, DC, 2015.
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Figure 1. Sensory profiles of averaged juices (2×5 juices in laboratory process; 2×2 juices in industrial process). Original ratings on the line scale between 0–10. * Significant difference between enzymatic and nonenzymatic processes; ** difference only between juices from industrial scale processing (t-test, p
