Effects of processing and storage conditions on volatile composition and odor characteristics of blackcurrant (Ribes nigrum) juices

An analytical approach to determine the health benefits and health risks of consuming berry juices

Food products composition analysis is a prerequisite for verification of product quality, fulfillment of regulatory enforcements, checking compliance with national and international food standards, contracting specifications, and nutrient labeling requirements and providing quality assurance for use of the product for the supplementation of other foods. These aspects also apply to the berry fruit and berry juice. It also must be noted that even though fruit juices are generally considered healthy, there are many risks associated with mishandling both fruits and juices themselves. The review gathers information related with the health benefits and risk associated with the consumption of berry fruit juices. Moreover, the focus was paid to the quality assurance of berry fruit juice. Thus, the analytical methods used for determination of compounds influencing the sensory and nutritional characteristics of fruit juice as well as potential contaminants or adulterations.

Efficient extraction based on a polydimethylsiloxane/bimetallic ZnCo-MOF carbonization sponge coupled with GC-MS for the rapid analysis of volatile compounds in cumin

A novel porous polydimethylsiloxane/bimetallic ZnCo-MOF carbonization (PDMS/ZnCo-MOF@C) sponge was successfully fabricated, followed by its utilization in GC-MS for the high efficiency extraction and determination of volatile compounds in cumin. The PDMS/ZnCo-MOF@C sponge exhibits outstanding properties with a considerable adsorption capacity, high surface area, and large pore volume and has shown potential as an ideal adsorbent for the separation and preconcentration of trace volatile compounds. The effect of different parameters on the extraction efficiency were investigated. Excellent analytical performances were achieved for the representative compounds (β-pinene, p-cymene, γ-terpinene, cuminaldehyde, and linalyl acetate), including wide linearity (2.31-440.1 ng) with high correlation coefficients (R2 ≥ 0.9979), low LODs (1.02-3.11 ng) and LOQs (2.45-7.08 ng), and satisfactory precision (intra-day RSDs ≤ 2.89% and inter-day RSDs ≤ 4.14%). The optimal method was applied for the analysis of cumin from different regions and 44 volatile compounds were identified. The correlation between the different regions of cumin and volatile compounds was explored using multivariate statistical analysis. These results demonstrated that PDMS/ZnCo-MOF@C is an efficient, simple and sensitive material for use in the pretreatment technique for the determination of the volatile compounds in aromatic plants.

Determination of volatile components in cumin by microwave-assisted PDMS/GO/DES headspace solid phase extraction combined with GC-MS

A novel approach based on polydimethylsiloxane/graphene oxide/deep eutectic solvent (PDMS/GO/DES) sponge headspace solid phase extraction followed by GC-MS was successfully developed to determine the volatile components in cumin. The PDMS/GO/DES exhibits outstanding properties with high adsorption capacity and good chemical stability, and has shown its potentiality as an ideal adsorbent for the extraction of volatile compounds. The influence factors of the extraction process were investigated. Excellent analytical performances were achieved, including wide linearity (0.60-107.72 ng) with high correlation coefficients (R² ≥ 0.9951), low LODs (0.23-9.23 ng) and LOQs (0.54-18.47 ng), satisfactory precision (intra-day RSDs ≤ 2.85% and inter-day RSDs ≤ 3.92%). Under the optimal extraction conditions, the volatile components in 17 cumin samples from four origins in Xinjiang were analyzed and 31 compounds were identified. PCA was used to establish the relationship between the origins and the volatile compounds for further discriminant analysis. The results showed that the PDMS/GO/DES method was a rapid, simple and sensitive technique for the analysis of volatile components in spices.

Application of Imaging and Artificial Intelligence for Quality Monitoring of Stored Black Currant (Ribes nigrum L.)

The objective of this study was to assess the influence of storage under different storage conditions on black currant quality in a non-destructive and inexpensive manner using image processing and artificial intelligence. Black currants were stored at a room temperature of 20 ± 1 °C and a temperature of 3 °C (refrigerator). The images of black currants directly after harvest and fruit stored for one and two weeks were obtained using a digital camera. Then, texture parameters were computed from the images converted to color channels R (red), G (green), B (blue), L (lightness component from black to white), a (green for negative and red for positive values), b (blue for negative and yellow for positive values), X (component with color information), Y (lightness), and Z (component with color information). Models for the classification of black currants were built using various machine learning algorithms based on selected textures for RGB, Lab, and XYZ color spaces. Models built using the IBk, multilayer perceptron, and multiclass classifier for textures from RGB color space, and the IBk algorithm for textures from Lab color space distinguished unstored black currants and samples stored in the room for one and two weeks with an average accuracy of 100%, and the kappa statistic and weighted averages of precision, recall, Matthews correlation coefficient (MCC), receiver operating characteristic (ROC) area, and precision-recall (PRC) area equal to 1.000. This indicated a very distinct change in the external structure of the fruit after the first week and more and more visible changes in quality with increasing storage time. A classification accuracy reaching 98.67% (multilayer perceptron, Lab color space) for the samples stored in the refrigerator may indicate smaller quality changes caused by storage at a low temperature. The approach combining image textures and artificial intelligence turned out to be promising to monitor the quality changes in black currants during storage.

Comparison of volatile compounds and sensory profiles of alcoholic black currant (Ribes nigrum) beverages produced with Saccharomyces, Torulaspora, and Metschnikowia yeasts

Black currants (Ribes nigrum) were fermented with Saccharomyces and non-Saccharomyces yeasts without added sugar to yield low-ethanol-content beverages. The effects of yeasts on the volatile compounds and sensory characteristics were analysed by HS-SPME-GC-MS, GC-O, and generic descriptive analysis. Ninety-eight volatile compounds were identified from the black currant juice and fermented beverages. Significant increases in the contents of esters (131 %), higher alcohols (391 %), and fatty acids (not present in juice sample) compared to initial juice were observed depending on the yeasts used. GC-O analysis revealed the higher impact of esters on the sensory properties of Saccharomyces bayanus-fermented beverage compared to the Torulaspora delbrueckii-fermented beverage. In the sensory evaluation, non-Saccharomyces yeasts resulted in a higher 'black currant odour'. However, all beverages were intensely sour, which can be a significant challenge in the development of alcoholic berry beverages.

Identification of Volatile Compounds in Blackcurrant Berries: Differences among Cultivars

Berries of blackcurrant are known to produce a strong flavor. Some previous studies have reported that a given cultivar of blackcurrant can produce berries with a specific profile of volatile compounds. For the Burgundy region in France, the Noir de Bourgogne cultivar is especially important because it is the main ingredient of a liquor with a designation of origin. The aim of the present study was to characterize the volatile fractions of berries from 15 cultivars in order to explore the possibility of using different cultivars for liquor production. The plants were cultivated under the same conditions and harvested in the same year. The volatile fractions of the harvested berries were analyzed using HS-SPME-GC-MS. Thorough univariate statistical analysis and multivariate analysis were applied to the dataset, which made it possible to identify groups within cultivars. The Rosenthal cultivar exhibited a quite flat profile; the Lositkia, Ben Tiran, and Barchatnaia cultivars shared common features; the Noir de Bourgogne cultivar showed the highest amounts of molecules such as 3-carene, limonene, β-phellandrene, ocimene, α-terpinolene, and bicyclogermacrene. None of the studied varieties were close to the Noir de Bourgogne on the basis of VOC analysis.

Influence of enzymatic treatment on the chemical composition of lingonberry (Vaccinium vitis-idaea) juice

The effects of different enzymes, their dosages, and incubation times on juice yield and chemical composition of lingonberry juice were assessed. Nonvolatile composition including sugars, acids and phenolic compounds (anthocyanins, hydroxycinnamic acids, flavonols and flavan-3-ols) was analyzed using GC-FID, LC-DAD and LC-MS methods, whereas the volatile compound profile was examined using HS-SPME-GC-MS. Selection of the enzyme had a significant effect on the juice yield by increasing it from 70% without enzyme treatment up to 81%. Enzymes significantly increased the contents of most of the phenolic compounds in the juices but had little impact on the contents of sugars and acids. Heat treatment without enzyme addition also significantly affected the composition. Generally, increasing incubation time increased the contents of various phenolic compounds, especially flavan-3-ols and hydroxycinnamic acids, whereas the effects of dosage were mostly negligible. Enzyme treatment increased the contents of volatile compounds, regardless of dosage or incubation time.

Impact of storage on sensory quality of blackcurrant juices prepared with or without enzymatic treatment at industrial scale

Blackcurrant juices prepared with or without enzyme treatment at industrial scale were stored at room temperature or + 4 °C for 1 year, and their sensory profiles, chemical composition and rheological properties were investigated. The juice without enzyme treatment had less intense colour and it was perceived and measured as more viscose than the juice produced with enzyme assistance. Content of monomeric anthocyanins decreased significantly during storage in both juice types under both storing conditions. However, changes in colour intensity were observed only in the non-enzymatic juices. In the discrimination tests based on the appearance, the stored samples were detected as significantly different. Storage resulted in significant changes in contents of hydroxycinnamic acids and flavonols, but this did not have an impact on the bitterness or astringency of the juices. Moreover, sugar and acid contents were mainly unchanged during storage. Storage resulted in a decrease in dynamic viscosity and greater differences in viscoelastic properties for the juice with enzymatic assistance. This study provides important information about the stability of juices typically stored at room temperature for a long time.