Volatile Organic Compounds Profiles to Determine Authenticity of Sweet Orange Juice Using Head Space Gas Chromatography Coupled with Multivariate Analysis

Overview of industrial food fraud and authentication through chromatography technique and its impact on public health

Food fraud is widespread nowadays in the food products supply chain, from raw materials processing to the final product and during storage and transport. The most frequent fraud is practiced in staple food commodities like cereals. Their origin, variety, genotype, and bioactive compounds are altered to deceive consumers. Similarly, in various food sectors like beverage, baking, and confectionary, items like melamine, flour improver, and food colors are used in the market to temple consumers. To tackle food fraud and authentication, non-destructive techniques are being used. These techniques have limitations like lack of standardization, interference from multiple absorbing species, ambiguous results, and time-consuming to perform, depending on the type, size, and location of the system proved difficult to quantify the samples of adulteration. Chromatography has been introduced as an effective technique. It serves to safeguard public health due to its detection capabilities. Chromatography proved a crucial tool against fraudulent practices to preserve consumer trust.

Novel Method Based on Ion Mobility Spectrometry Combined with Machine Learning for the Discrimination of Fruit Juices

Fruit juices are one of the most widely consumed beverages worldwide, and their production is subject to strict regulations. Therefore, this study presents a methodology based on the use of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) in combination with machine-learning algorithms for the characterization juices of different raw material (orange, pineapple, or apple and grape). For this purpose, the ion mobility sum spectrum (IMSS) was used. First, an optimization of the most important conditions in generating the HS was carried out using a Box-Behnken design coupled with a response surface methodology. The following factors were studied: temperature, time, and sample volume. The optimum values were 46.3 °C, 5 min, and 750 µL, respectively. Once the conditions were optimized, 76 samples of the different types of juices were analyzed and the IMSS was combined with different machine-learning algorithms for its characterization. The exploratory analysis by hierarchical cluster analysis (HCA) and principal component analysis (PCA) revealed a clear tendency to group the samples according to the type of fruit juice and, to a lesser extent, the commercial brand. The combination of IMSS with supervised classification techniques reported an excellent result with 100% accuracy on the test set for support vector machines (SVM) and random forest (RF) models regarding the specific fruit used. Nevertheless, all the models have proven to be an effective alternative for characterizing and classifying the different types of juices.

Review on Sensor Array-Based Analytical Technologies for Quality Control of Food and Beverages

Food quality control is an important area to address, as it directly impacts the health of the whole population. To evaluate the food authenticity and quality, the organoleptic feature of the food aroma is very important, such that the composition of volatile organic compounds (VOC) is unique in each aroma, providing a basis to predict the food quality. Different types of analytical approaches have been used to assess the VOC biomarkers and other parameters in the food. The conventional approaches are based on targeted analyses using chromatography and spectroscopies coupled with chemometrics, which are highly sensitive, selective, and accurate to predict food authenticity, ageing, and geographical origin. However, these methods require passive sampling, are expensive, time-consuming, and lack real-time measurements. Alternately, gas sensor-based devices, such as the electronic nose (e-nose), bring a potential solution for the existing limitations of conventional methods, offering a real-time and cheaper point-of-care analysis of food quality assessment. Currently, research advancement in this field involves mainly metal oxide semiconductor-based chemiresistive gas sensors, which are highly sensitive, partially selective, have a short response time, and utilize diverse pattern recognition methods for the classification and identification of biomarkers. Further research interests are emerging in the use of organic nanomaterials in e-noses, which are cheaper and operable at room temperature.

Monitoring Volatile Organic Compounds in Different Pear Cultivars during Storage Using HS-SPME with GC-MS

Aroma, which plays an essential role in food perception and acceptability, depends on various mixture of volatile organic compounds (VOCs). Meanwhile, as a field of metabolomics, VOC analysis is highly important for aroma improvement and discrimination purposes. In this work, VOCs in pear fruits were determined via headspace solid-phase micro-extraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC-MS) to study variations among different cultivars and storage stages. In 12 cultivars of pear fruits, a total of 121 VOCs were quantified, including 40 esters, 32 alcohols, 16 aldehydes, 13 alkenes, 11 ketones, 4 acids, and 5 other compounds. The types and amounts of VOCs in different cultivars varied dramatically, which were in the range of 13-71 and 3.63-55.65 mg/kg FW (fresh weight), respectively. The Dr. Guyot cultivar showed the highest level of VOCs, both in type and amount. After 21 days storage at 4 °C, total concentration of VOCs increased from initial levels of 50.76 to 101.33 mg/kg FW. Storage at 20 °C made a larger contribution to production for VOCs than that at 4 °C, resulting in the maximum content of VOCs (117.96 mg/kg FW) in fruit after 14 days storage at 4 °C plus 7 days at 20 °C. During storage, the content of esters showed a gradual increase, while the content of alcohols and aldehydes decreased. Based on the results presented, related alcohols were recognized as the intermediates of conversion from aldehydes to esters.

Citrus juice off-flavor during different processing and storage: Review of odorants, formation pathways, and analytical techniques

As the most widespread juice produced and consumed globally, citrus juice (mandarin juice, orange juice, and grapefruit juice) is appreciated for its attractive and distinct aroma. While the decrease of characteristic aroma-active compounds and the formation of off-flavor compounds are easy to occur in processing and storage conditions. This review provides a comprehensive literature of recent research and discovery on citrus juice off-flavor, primarily focusing on off-flavor compounds induced during processing and storage (i.e., thermal, storage, light, oxygen, package, fruit maturity, diseases, centrifugal pretreatment, and debittering process), formation pathways (i.e., terpene acid-catalyzed hydration, caramelization reaction, Maillard reaction, Strecker degradation, and other oxidative degradation) of the off-flavor compounds, effective inhibitor pathway to off-flavor (i.e., electrical treatments, high pressure processing, microwave processing, ultrasound processing, and chemical treatment), as well as odor assessment techniques based on molecular sensory science. The possible precursors (terpenes, sulfur-containing amino acids, carbohydrates, carotenoids, vitamins, and phenolic acids) of citrus juice off-flavor are listed and are also proposed. This review intends to unravel the regularities of aroma variations and even off-flavor formation of citrus juice during processing and storage. Future aroma analysis techniques will evolve toward a colorimetric sensor array for odor visualization to obtain a "marker" of off-flavor in citrus juice.

Targeted Metabolomics With a Chemometric Study of Oxygenated Heterocyclic Aglycones as a Tool for Preliminary Authenticity Assessment of Orange and Grapefruit Juices

Profiles of citrus juice oxygenated heterocyclic aglycones (OHAs), which are notable marker secondary metabolites, were used to assess the authenticity of sweet orange and grapefruit juices in situations where mandarin and pomelo juices might be adulterants. Thirty-nine known OHAs, including 10 methoxyflavones, 13 coumarins, and 16 furanocoumarins, as well as 13 tentatively screened OHAs, were analyzed in orange, mandarin, grapefruit and pomelo juices using our newly developed high-resolution HPLC-UV and fluorescence detection method. Quantitative OHA profiles from 158 pure juice samples were obtained to establish a purity discriminant model using an omics strategy. Reduction of OHA variables showed that three important methoxyflavones, i.e. isosinensetin, tangeretin and sinensetin provided the best discrimination ability between sweet orange and mandarin juices. There are two subtypes of pomelos, Shatianyou Group and Wendan Group, of which juices should be separately compared to grapefruit juice. Five OHAs, namely meranzin, 3,5,6,7,8,3',4'-heptamethoxyflavone, osthole, 6',7'-epoxybergamottin, and bergamottin were found to discriminate Shatianyou Group of pomelo juice from grapefruit juice; whereas three OHAs, namely bergaptol, isomeranzin, and 6',7'-dihydroxybergamottin were able to discriminate Wendan Group of pomelo juice from grapefruit juice. The established partial least squares discriminant analysis (PLS-DA) models were capable of detecting as little as 10% mandarin juice in sweet orange juice and 10% pomelo juice in grapefruit juice, allowing for fast prescreening of excess addition with good reliability (root mean square error of prediction, RMSEP < 5%).

Evaluation of Nutritional Substances and Investigation of Antioxidant and Antimicrobial Potentials of Boerhavia diffusa with in Silico Molecular Docking

Boerhavia diffusa L. Nyctanginaceae (B. diffusa) is a medicinal herb commonly considered as a weed. The exploration of phytochemicals in different parts of B. diffusa with different solvents will create awareness, along with the suitable solvent and method for extraction of pharmaceutical compounds. Hence, the present study focuses on phytochemical analysis of B. diffusa leaves, stems, and roots in various solvents with hot and cold extraction. The decoctions performed well in most of the qualitative and quantitative tests, along with the DPPH assay. The aqueous extract showed a good result in the FRAP assay and ABTS assay. In the antimicrobial test, the B. diffusa root ethanol extract inhibited the growth of Pseudomonas aeruginosa and Staphylococcus aureus with zones of inhibition of about 8 mm and 20 mm at 200 µg concentration, respectively. Using a molecular docking approach, the top four ranked molecules from the crude extract of B. diffusa profiled from GC–MS spectroscopy in terms of growth inhibition of the pathogenic bacterium P. aeruginosa were selected; among them, 2-(1,2 dihydroxyethyl)-5-[[2,5,7,8-tetramethyl-2-(4,8,12-trimethyltridecyl)-3,4-dihydrochromen-6-yl]oxy]oxolane-3,4-diol exhibited the minimum binding score, revealing high affinity in complex. B. diffusa is highly nutritious, and the maceration and decoction extracts were similar except for the chloroform extract that was found to be weak.

Analysis of the molecular heterogeneity of poly(lactic acid)/poly(butylene succinate-co-adipate) blends by hyphenating size exclusion chromatography with nuclear magnetic resonance and infrared spectroscopy

The compositional and stereochemical heterogeneity of copolymers are key molecular metrics, and their knowledge is of pivotal importance for evidence based material development. Yet, while it is state of the art to determine these parameters for many petroleum based polymers, little insight exists in that regard for bio-based materials. Towards this end, size exclusion chromatography (SEC) was hyphenated with nuclear magnetic resonance spectroscopy (NMR) in an offline manner and a blend of poly(lactic acid) (PLA) and poly(butylene succinate-co-adipate) (PBSA) investigated. Thus, the microstructural heterogeneity could be shown with regard to tacticity of the PLA and regioregularity of the PBSA component. The results show, that the highest molar mass fraction differs in stereochemical composition from the others. It may be assumed that this is the result of misinsertions with regard to stereochemistry occurring during the catalytic polymerization of the lactide. While the content of both constituent polymers along the molar mass axis could be well studied using a univariate analysis of the infrared (IR) spectra, this method failed to profile the adipate and succinate content individually. For this purpose, SEC was coupled to IR spectroscopy in online mode and the spectra were evaluated by a multivariate protocol. Thus, the content of each monomer along the molar mass distribution could be mapped with high chromatographic resolution.