Comparison of the Fruit Volatile Profiles of Five Muscadine Grape Cultivars (Vitis rotundifolia Michx.) Using HS-SPME-GC/MS Combined With Multivariate Statistical Analysis

Changes of Volatile Organic Compounds of Different Flesh Texture Pears during Shelf Life Based on Headspace Solid-Phase Microextraction with Gas Chromatography-Mass Spectrometry

Aroma is an important sensory factor in evaluating the quality of pear fruits. This study used headspace solid-phase microextraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC-MS) to analyze the volatile organic compounds (VOCs) of three crispy pears and five soft pears during shelf life, and the changes in soluble solids content (SSC) were analyzed. The results showed that the SSC of the soft pears such as Nanguoli, Jingbaili and Louis was always higher than that of the crispy pears throughout shelf life. A total of 160 VOCs were detected in the eight pear varieties. Orthogonal partial least squares discriminant analysis (OPLS-DA) and hierarchical cluster analysis (HCA) combined with predictor variable importance projection (VIP) showed that the eight pear varieties could be obviously classified into six groups according to the differences in their VOCs, and 31 differential VOCs were screened out, which could be used to differentiate between pears with different flesh textures. The results of clustering heat map analysis showed that, with the extension of shelf life, the content of each different VOC did not change much in crispy pears, whereas the difference in soft pears was larger. This study confirmed the potential of determining the optimal shelf life of different pear varieties about aroma evaluation and studying the mechanism of differences in VOCs in the future.

Tracing the volatilomic fingerprint of grape pomace as a powerful approach for its valorization

The huge amount of grape pomace (GP) generated every year worldwide, particularly in Europe, creates negative impacts at the economic and environmental levels. As far as we know, scarce research has been done on the volatilomic fingerprint of GP. To meet consumer demand for healthy foods, there is a growing interest in the characterization of particular volatile organic metabolites (VOMS) in GP that can be used for industrial applications, including the food industry. In this study, the volatilomic fingerprint of GP obtained from different Vitis vinifera L. grapes was established by solid phase microextraction (HS-SPME) combined to gas chromatography-mass spectrometry (GC-MS), to explore the properties of most dominant VOMs in a context of its application on marketable products. A total of 52 VOMs belonging to different chemical families were identified. Alcohols, carbonyl compounds, and esters, are the most dominant, representing 38.8, 29.3, and 24.2% of the total volatile profile of the investigated GP, respectively. Esters (e.g., isoamyl acetate, hexyl acetate, ethyl hexanoate) and alcohols (e.g., 3-methyl butan-2-ol, hexan-1-ol) can be used as flavoring agents with potential use in the food industry, and in the cosmetic industry, for fragrances production. In addition, the identified terpenoids (e.g., menthol, ylangene, limonene) exhibit antioxidant, antimicrobial, and anticancer, biological properties, among others, boosting their potential application in the pharmaceutical industry. The obtained results revealed the potential of some VOMs from GP to replace synthetic antioxidants, colorants, and antimicrobials used in the food industry, and in the cosmetic and pharmaceutical industry, meeting the increasing consumer demand for natural alternative compounds.

Spotting of Volatile Signatures through GC-MS Analysis of Bacterial and Fungal Infections in Stored Potatoes (Solanum tuberosum L.)

Potatoes inoculated with Pectobacterium carotovorum spp., Aspergillus flavus and Aspergillus niger, along with healthy (control) samples, were stored at different storage temperatures (4 ± 1 °C, 8 ± 1 °C, 25 ± 1 °C) for three weeks. Volatile organic compounds (VOCs) were mapped using the headspace gas analysis through solid phase micro extraction-gas chromatography-mass spectroscopy every week. The VOC data were arranged into different groups and classified using principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) models. Based on a variable importance in projection (VIP) score > 2 and the heat map, prominent VOCs were identified as 1-butanol and 1-hexanol, which can act as biomarkers for Pectobacter related bacterial spoilage during storage of potatoes in different conditions. Meanwhile, hexadecanoic acid and acetic acid were signature VOCs for A. flavus, and hexadecane, undecane, tetracosane, octadecanoic acid, tridecene and undecene were associated with A. niger. The PLS-DA model performed better at classifying the VOCs of the three different species of infection and the control sample compared to PCA, with high values of R² (96-99%) and Q² (0.18-0.65). The model was also found to be reliable for predictability during random permutation test-based validation. This approach can be adopted for fast and accurate diagnosis of pathogenic invasion of potatoes during storage.

Characterization of volatiles in flowers from four Rosa chinensis cultivars by HS-SPME-GC × GC-QTOFMS

Rosa chinensis cultivars with volatile aromas are important resources in the perfume industry. The four rose cultivars introduced to Guizhou province are rich in volatile substances. In this study, volatiles from four Rosa chinensis cultivars were extracted using headspace-solid phase microextraction (HS-SPME), and analyzed with two-dimensional gas chromatography quadrupole time of flight mass spectrometry (GC × GC-QTOFMS). A total of 122 volatiles were identified; the main compounds in these samples were benzyl alcohol, phenylethyl alcohol, citronellol, beta-myrcene and limonene. A total of 68, 78, 71, and 56 volatile compounds were identified in Rosa 'Blue River' (RBR), Rosa 'Crimson Glory' (RCG), Rosa 'Pink Panther' (RPP), and Rosa 'Funkuhr' (RF) samples, respectively. The total volatile contents were in the following order: RBR > RCG > RPP > RF. Four cultivars exhibited similar volatility profiles, with alcohols, alkanes, and esters as the major chemical groups, followed by aldehydes, aromatic hydrocarbons, ketones, benzene, and other compounds. Alcohols and aldehydes were quantitatively the two most abundant chemical groups that included the highest number and highest content of compounds. Different cultivars have different aromas, and RCG had high contents of phenyl acetate, rose oxide, trans-rose oxide, phenylethyl alcohol and 1,3,5-trimethoxybenzene, characterized by floral and rose descriptors. RBR contained a high content of phenylethyl alcohol, and RF contained a high content of 3,5-dimethoxytoluene. Hierarchical cluster analysis (HCA) of all volatiles showed that the three cultivars (RCG, RPP, and RF) had similar volatile characteristics and were significantly different from RBR. Differential metabolites among cultivars were screened based on the OPLS-DA model, and there were six main enriched pathways of differential metabolites: biosynthesis of secondary metabolites, monoterpenoid biosynthesis, metabolic pathways, limonene and pinene degradation, sesquiterpenoid and triterpenoid biosynthesis, and alpha-linolenic acid metabolism. The biosynthesis of secondary metabolites is the most differential metabolic pathway.

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.

Comparison of Volatile Compositions among Four Related Ligusticum chuanxiong Herbs by HS-SPME-GC-MS

Chuanxiong (CX, Ligusticum chuanxiong), Japanese Chuanxiong (JCX, Cnidium officinale), Fuxiong (FX, Ligusticum sinense ‘Fuxiong’), and Jinxiong (JX, Ligusticum sinense ‘Jinxiong’) are aromatic herbs used in China, Japan, and other regions. Their morphology and aromatic odor are similar, resulting in confused and mixed uses. This study compares the volatile compositions of these herbs for defining their medical uses. Headspace solid-phase microextraction–gas chromatography–triple quadrupole–mass spectrometry was employed to separate, identify, and quantify the compounds in the volatile gas of the four herbs. A total of 128 volatile compounds were identified and quantified in 23 these herbal samples. The sums of 106, 115, 116, and 120 compounds were detected in the volatile gas of CX, JCX, FX, and JX, with the mean contents of 4.80, 7.12, 7.67, and 12.0 μg/g, respectively. Types and contents of the main compounds were found to be different in the volatile gas of these herbs. The orthogonal partial least squares discriminant analysis and hierarchical clustering analysis showed the four herbs located in different confined areas or clusters. It is concluded that the volatile compositions in the four herbs are generally similar, but the contents of main volatile compounds are different. These herbs should be clearly differentiated in medical use.

Optimization of a static headspace GC-MS method and its application in metabolic fingerprinting of the leaf volatiles of 42 citrus cultivars

Citrus leaves, which are a rich source of plant volatiles, have the beneficial attributes of rapid growth, large biomass, and availability throughout the year. Establishing the leaf volatile profiles of different citrus genotypes would make a valuable contribution to citrus species identification and chemotaxonomic studies. In this study, we developed an efficient and convenient static headspace (HS) sampling technique combined with gas chromatography-mass spectrometry (GC-MS) analysis and optimized the extraction conditions (a 15-min incubation at 100 ˚C without the addition of salt). Using a large set of 42 citrus cultivars, we validated the applicability of the optimized HS-GC-MS system in determining leaf volatile profiles. A total of 83 volatile metabolites, including monoterpene hydrocarbons, alcohols, sesquiterpene hydrocarbons, aldehydes, monoterpenoids, esters, and ketones were identified and quantified. Multivariate statistical analysis and hierarchical clustering revealed that mandarin (Citrus reticulata Blanco) and orange (Citrus sinensis L. Osbeck) groups exhibited notably differential volatile profiles, and that the mandarin group cultivars were characterized by the complex volatile profiles, thereby indicating the complex nature and diversity of these mandarin cultivars. We also identified those volatile compounds deemed to be the most useful in discriminating amongst citrus cultivars. This method developed in this study provides a rapid, simple, and reliable approach for the extraction and identification of citrus leaf volatile organic compound, and based on this methodology, we propose a leaf volatile profile-based classification model for citrus.

Integrative quantitative and qualitative analysis for the quality evaluation and monitoring of Danshen medicines from different sources using HPLC-DAD and NIR combined with chemometrics

The root and rhizome of Salvia miltiorrhiza (Danshen in short) is a well-known herbal medicine used to treat cardiovascular diseases in the world. In China, the roots and rhizomes of several other Salvia species (Non-Danshen in short) are also used as this medicine in traditional folk medicine by local herbalists. Differences have been reported in these medicines originating from different sources, and their quality variation needs to be clearly investigated for effective clinical application. This study presented a comprehensive quality evaluation and monitoring for Danshen from 27 sampling sites and Non-Danshen from other 5 Salvia species based on a high-performance liquid chromatography-diode array detector (HPLC-DAD) and near-infrared (NIR), with the combination of chemometric models. The results showed that cryptotanshinone, tanshinone IIA, tanshinone I, salvianolic acid B, salvianic acid A sodium, dihydrotanshinone I, and rosmarinic acid in these medicines from different sources exhibited great variations. Referring to the standards in Chinese Pharmacopoeia (CP), European Pharmacopeia (EP), and United States Pharmacopeia (USP), Non-Danshen from S. brachyloma, S. castanea, S. trijuga, S. bowleyana, and S. przewalskii were assessed as unqualified, and Danshen in the Shandong Province had the best quality due to the high qualified rate. Based on random forest (RF) and partial least-squares discriminant analysis (PLS-DA), NIR technique could successfully monitor the quality of these medicines by discriminating the species and regions with the accuracies of 100.00 and 99.60%, respectively. Additionally, modified partial least-squares regression (MPLSR) models were successfully constructed to investigate the feasibility of NIR fingerprints for the prediction of the quality indicators in these medicines. The optimized models obtained the best results for the total of tanshinone IIA, tanshinone I, and cryptotanshinone (TTC), tanshinone IIA, and salvianolic acid B, with the relative prediction deviation (RPD) of 4.08, 3.92, and 2.46, respectively. In summary, this study demonstrated that HPLC-DAD and NIR techniques can complement each other and could be simultaneously applied for evaluating and monitoring the quality of Danshen medicines.

Patterns of Volatile Diversity Yield Insights Into the Genetics and Biochemistry of the Date Palm Fruit Volatilome

Volatile organic compounds are key components of the fruit metabolome that contribute to traits such as aroma and taste. Here we report on the diversity of 90 flavor-related fruit traits in date palms (Phoenix dactylifera L.) including 80 volatile organic compounds, which collectively represent the fruit volatilome, as well as 6 organic acids, and 4 sugars in tree-ripened fruits. We characterize these traits in 148 date palms representing 135 varieties using headspace solid-phase microextraction gas chromatography. We discovered new volatile compounds unknown in date palm including 2-methoxy-4-vinylphenol, an attractant of the red palm weevil (Rhynchophorus ferrugineus Olivier), a key pest that threatens the date palm crop. Associations between volatile composition and sugar and moisture content suggest that differences among fruits in these traits may be characterized by system-wide differences in fruit metabolism. Correlations between volatiles indicate medium chain and long chain fatty acid ester volatiles are regulated independently, possibly reflecting differences in the biochemistry of fatty acid precursors. Finally, we took advantage of date palm clones in our analysis to estimate broad-sense heritabilities of volatiles and demonstrate that at least some of volatile diversity has a genetic basis.