Rapid differentiation of commercial juices and blends by using sugar profiles obtained by capillary zone electrophoresis with indirect UV detection

Fermentation in Pineapple Juice Significantly Enhances Ornithine and Citrulline Production in Lactococcus lactis MSC-3G Isolated from Sugarcane

Lactic acid bacterial (LAB) fermentation of functional amino acids using fruit juices as a cultivation medium is not well-documented. In the present study, we successfully isolated a high ornithine- and citrulline-producing Lactococcus lactis strain, designated MSC-3G, from sugarcane and investigated the ornithine and citrulline production profile using various fruit juices as a cultivation medium. Among fruit juices, pineapple juice exhibited the highest potentiality to initiate ornithine production (56 mM), while the highest citrulline yield was obtained during lime juice cultivation (34.5 mM). Under the optimal cultivation condition, the highest yield of ornithine and citrulline in pineapple juice reached 98.9 ± 2.2 mM and 211.1 ± 35.7 mM, respectively, both of which were significantly higher than that in the well-known industrial strain of Corynebacterium (C.) glutamicum. Additionally, citrulline production was dependent on oxygen supplementation and increased twofold when grown aerobically. Whole genome sequencing showed that the MSC-3G genome possesses the arginine deiminase (ADI) gene cluster arcABD1C1C2TD2. The results of the ADI pathway enzyme activities of MSC-3G showed a significant increase in arginine deiminase activity, while ornithine carbamoyl transferase activity was decreased, which in turn indicates the high citrulline-accumulation ability of MSC-3G when cultivated in pineapple juice.

The chemical composition of two kinds of grape juice with medicinal plant addition

The safety of plant-based food with an herbal origin is a priority for producers and final consumers these days. The interest in the high biological value of the final food products enriched with herbal ingredients is rising. We focused on the study of physico-chemical composition and antioxidant activity of two kinds of grape juice with medicinal plant addition in our study. We used 2 varieties of grapes - Welschriesling and Cabernet Sauvignon, six species of medicinal plants - Calendula officinalis L., Ginkgo biloba, Thymus serpyllum, Matricaria recutita, Salvia officinalis L., and Mentha aquatica var. citrata in our experiment. There were14 samples prepared, two of them were control samples and 12 samples were treated with medicinal plants. We tested each of the selected parameters triplicate with an interval of one week. We evaluated the results statistically in 4 levels of significance p <0,01, p <0,001, p <0,0001 and p <0,00001. The content of fructose, glucose, dry matter, density, malic acid, pH, potential alcohol, total acids, and total sugars in the treated samples was significantly lower compared to the control sample, which was probably due to the degree of dilution of grape juice with extracts gained from medicinal plants. The antioxidant effect was demonstrably higher in the samples enriched with medicinal plants than in the control samples. The highest antioxidant effect was measured in the second test in the samples with the addition of Thymus serpyllum (80.93 % - white grape must, 82.33 % - blue grape must), Calendula officinalis L. (79.29 % - white grape must, 80.49 % - blue grape must) and Ginkgo biloba (79.10 % - white grape must, 83.3 % - blue grape must). Generally, we found out that the selected medicinal plants increase the biological quality of grape juice.

Volatilomic Profiling of Citrus Juices by Dual-Detection HS-GC-MS-IMS and Machine Learning-An Alternative Authentication Approach

A prototype dual-detection headspace-gas chromatography-mass spectrometry-ion mobility spectrometry (HS-GC-MS-IMS) system was used for the analysis of the volatile profile of 47 Citrus juices including grapefruit, blood orange, and common sweet orange juices without requiring any sample pretreatment. Next to reduced measurement times, substance identification could be improved substantially in case of co-elution by considering the characteristic drift times and m/z ratios obtained by IMS and MS. To discriminate the volatile profiles of the different juice types, extensive data analysis was performed with both datasets, respectively. By principal component analysis (PCA), a distinct separation between grapefruit and orange juices was observed. While in the IMS data grapefruit juices not from fruit juice concentrate could be separated from grapefruit juices reconstituted from fruit juice concentrate, in the MS data, the blood orange juices could be differentiated from the orange juices. This observation leads to the assumption that the IMS and MS data contain different information about the composition of the volatile profile. Subsequently, linear discriminant analysis (LDA), support vector machines (SVM), and the k-nearest-neighbor (kNN) algorithm were applied to the PCA data as supervised classification methods. Best results were obtained by LDA after repeated cross-validation for both datasets, with an overall classification and prediction ability of 96.9 and 91.5% for the IMS data and 94.5 and 87.9% for the MS data, respectively, which confirms the results obtained by PCA. Additional data fusion could not generally improve the model prediction ability compared to the single data, but rather for certain juice classes. Consequently, depending on the juice class, the most suitable dataset should be considered for the prediction of the class membership. This volatilomic approach based on the dual detection by HS-GC-MS-IMS and machine learning tools represent a simple and promising alternative for future authenticity control of Citrus juices.

Profiles of Sugar and Organic Acid of Fruit Juices: A Comparative Study and Implication for Authentication

A comparison of sugar and organic acid profiles among different fruit juices (including apple, pear, peach, grape, sweet cherry, strawberry, and blueberry with various varieties) was performed to assess the possibility for authentication coupled with chemometrics. It was found that the distribution of each sugar and organic acid in juices showed some specific characteristics related to fruit species, despite the fact that great differences in the content existed among different varieties. Sucrose was the most abundant sugar in peach juice, accounting for 58.26–77.11% of the total sugar content. However, in grape, blueberry, and sweet cherry juice, glucose and fructose were the predominant sugars. Pear juice contained the highest level of sorbitol, which contributed to 15.02–43.07% of the total sugar content. Tartaric acid was detected only in grape juice among the seven species of fruit juice, with a proportion of 57.95–89.68% in the total acid content. Malic acid was the predominant organic acid in apple and sweet cherry juice, accounting for 69.92–88.30% and 97.51–98.73% of the total acid content of each species. Citric acid was the predominant organic acid in strawberry and blueberry juice, which contributed to 62.39–83.73% and 73.36–89.56% of the total acid content of each species. With the aid of principal component analysis and linear discriminant analysis (LDA), the juice samples could be successfully classified according to fruit species by using the sugar and/or organic acid composition as analytical data. Combination of sugar and organic acid composition gave the best differentiation of these seven species of juices, with a 100% correct classification rate for both the original and the cross-validation method in LDA. Adding malic/citric into the dataset of the organic acid content may also improve the differentiation effect. Furthermore, the adulteration of sweet cherry juice, blueberry juice, raspberry juice, and grape juice with apple juice, pear juice, or peach juice could also be distinguished from their corresponding pure juices based on sugar and organic acid composition by LDA.

Quality and Authenticity Control of Fruit Juices-A Review

Food fraud, being the act of intentional adulteration of food for financial advantage, has vexed the consumers and the food industry throughout history. According to the European Committee on the Environment, Public Health and Food Safety, fruit juices are included in the top 10 food products that are most at risk of food fraud. Therefore, reliable, efficient, sensitive and cost-effective analytical methodologies need to be developed continuously to guarantee fruit juice quality and safety. This review covers the latest advances in the past ten years concerning the targeted and non-targeted methodologies that have been developed to assure fruit juice authenticity and to preclude adulteration. Emphasis is placed on the use of hyphenated techniques and on the constantly-growing role of MS-based metabolomics in fruit juice quality control area.

Capillary Electrophoresis Separations of Glycans

Capillary electrophoresis has emerged as a powerful approach for carbohydrate analyses since 2014. The method provides high resolution capable of separating carbohydrates by charge-to-size ratio. Principle applications are heavily focused on N-glycans, which are highly relevant to biological therapeutics and biomarker research. Advances in techniques used for N-glycan structural identification include migration time indexing and exoglycosidase and lectin profiling, as well as mass spectrometry. Capillary electrophoresis methods have been developed that are capable of separating glycans with the same monosaccharide sequence but different positional isomers, as well as determining whether monosaccharides composing a glycan are alpha or beta linked. Significant applications of capillary electrophoresis to the analyses of N-glycans in biomarker discovery and biological therapeutics are emphasized with a brief discussion included on carbohydrate analyses of glycosaminoglycans and mono-, di-, and oligosaccharides relevant to food and plant products. Innovative, emerging techniques in the field are highlighted and the future direction of the technology is projected based on the significant contributions of capillary electrophoresis to glycoscience from 2014 to the present as discussed in this review.

Association between Type, Amount, and Pattern of Carbohydrate Consumption with Dental Caries in 12-Year-Olds in Puerto Rico

OBJECTIVE

To identify the types, food sources, and pattern of carbohydrates that significantly contribute to dental caries in Puerto Rican children.

METHODS

As part of an island-wide cross-sectional oral health study in 1,587 twelve-year-olds, diet intake was assessed in a representative subset (n = 801) with a 24-hour dietary recall. Carbohydrate intake was quantified using a computer-based diet analysis program. Caries was assessed using the National Institute of Dental and Craniofacial Research diagnostic criteria. Odds ratios were used to associate carbohydrate intake quartiles with caries, after controlling for important confounders.

RESULTS

A total of 723 subjects had complete data. Most were females (54%) and attended public schools (77%). The caries prevalence was 33%. The highest quartile intake for the following sugars significantly increased the odds of caries compared to the lowest quartile: total carbohydrates (OR = 1.93, 95% CI = 1.08-3.46), total sugars (OR = 1.88, 95% CI = 1.01-351), sucrose (OR = 2.05, 95% CI = 1.13-3.70), fructose (OR = 1.95, 95% CI = 1.05-3.62), and inositol (OR = 2.52, 95% CI = 1.38-4.63). The main food sources of these sugars were juices, including natural juices with no added sugars, and sweetened beverages. The odds of caries also increased significantly in children whose 10% of total energy intake was from total sugars (OR = 3.76, 95% CI = 1.03-13.7).

CONCLUSION

After adjusting for important caries risk factors, total carbohydrates, total sugars, ≥10% kilocaloric energy from total sugars, and sucrose, fructose, and inositol intake significantly increased caries risk. Our findings can help raise awareness about the potential caries risk from the main sources of these sugars, natural fruit juices and sweetened beverages, which are consumed in great quantities in many societies.

Targeted and non-targeted detection of lemon juice adulteration by LC-MS and chemometrics

Economically motivated adulteration (EMA) of lemon juice was detected by LC-MS and principal component analysis (PCA). Twenty-two batches of freshly squeezed lemon juice were adulterated by adding an aqueous solution containing 5% citric acid and 6% sucrose to pure lemon juice to obtain 30%, 60% and 100% lemon juice samples. Their total titratable acidities, °Brix and pH values were measured, and then all the lemon juice samples were subject to LC-MS analysis. Concentrations of hesperidin and eriocitrin, major phenolic components of lemon juice, were quantified. The PCA score plots for LC-MS datasets were used to preview the classification of pure and adulterated lemon juice samples. Results showed a large inherent variability in the chemical properties among 22 batches of 100% lemon juice samples. Measurement or quantitation of one or several chemical properties (targeted detection) was not effective in detecting lemon juice adulteration. However, by using the LC-MS datasets, including both chromatographic and mass spectrometric information, 100% lemon juice samples were successfully differentiated from adulterated samples containing 30% lemon juice in the PCA score plot. LC-MS coupled with chemometric analysis can be a complement to existing methods for detecting juice adulteration.