Search Results (19)

This study aimed to investigate the content of major bioactive compounds and characterize the volatile and sensory profiles of Coffea canephora flowers and their infusions. Dried flowers from six selected genotypes of C. canephora trees and their infusions were analyzed for bioactive compounds using HPLC–DAD, while volatile organic compounds (VOC) were analyzed using GC–MS. Eight chlorogenic acids (CGA), seven phenolic acids, and the alkaloids caffeine and trigonelline were quantified in all methanolic flower extracts. Total CGA, phenolic acids, caffeine, and trigonelline contents in the methanolic extracts ranged between 342.8 and 1079.4 mg/100 g, 27.1 and 41.0 mg/100 g, 515.6 and 745.9 mg/100 g, and 453.8 and 645.2 mg/100 g, respectively. CGA, caffeine, and trigonelline were well extracted (84%, 91%, and 74%, respectively) when the flowers were infused in hot water. No free phenolic acids were identified in the infusions. Eighty-five VOC were identified in the flowers. Aldehydes, monoterpenes, esters, alcohols, monoterpene alcohols, acids, and ketones prevailed in order of the number of compounds. In the infusions, 38 VOC were accurately identified. Monoterpenes and monoterpene alcohols prevailed. In general, floral, jasmine and orange blossom, herbal, green coffee, woody, and sweet were the most cited sensory attributes for fragrance, aroma, and flavor. Considering the typically weak aroma of C. canephora seeds, the aroma and flavor of the flower’s infusions were surprisingly strong and pleasant, showing great marketing potential. Full article

Bitter orange (Citrus aurantium L.), a member of the Rutaceae family, finds global utility in both the treatment of various ailments and its role as a rootstock for Citrus species in agriculture. Various parts of Citrus aurantium L. have been employed in traditional medicine due to their multifarious therapeutic potential. The blossom of this plant serves as a rich source of bioactive compounds, notably polyphenols, alkaloids, and terpenes. Additionally, it harbors substantial quantities of functional, nutritive, and biologically active compounds, which manifest their presence through antioxidant, antidiabetic, anticancer, antimicrobial, cardiovascular, and neuroprotective properties. The recovery of bioactive compounds is significantly affected by extraction methods. Many conventional methods have been explored for the recovering of bioactive compounds from bitter orange flowers. However, in response to the limitations of conventional techniques, green extraction methods, characterized by their ability to significantly increase the yield and reduce the time, energy, and solvent requirements, have also been assessed for this matrix. Therefore, the study of the functionalities of bitter orange blossoms represents a domain with unexplored research opportunities. Consequently, this review aims to offer a comprehensive insight into the biological properties and medicinal applications of the active compounds found within C. aurantium. Full article

(2S,7S)-2,7-Nonanediyl dibutyrate is the sex pheromone of Sitodiplosis mosellana (Géhin). In this study, this sex pheromone and its three stereoisomers were prepared. Central to this strategy was the ring opening of chiral epoxide with an alkynyllithium and the hydrogenation of the triple bond. Moreover, this approach consisted of six steps, and the total yields were 59–64%. Full article

This article introduces a novel approach to detecting honey adulteration by combining ultra-fast gas chromatography (UF-GC) with advanced machine learning techniques. Machine learning models, particularly support vector regression (SVR) and least absolute shrinkage and selection operator (LASSO), were applied to predict adulteration in orange blossom (OB) and sunflower (SF) honeys. The SVR model achieved R² values above 0.90 for combined honey types. Treating OB and SF honeys separately resulted in a significant accuracy improvement, with R² values exceeding 0.99. LASSO proved especially effective when honey types were treated individually. The integration of UF-GC with machine learning not only provides a reliable method for detecting honey adulteration, but also sets a precedent for future research in the application of this technique to other food products, potentially enhancing food authenticity across the industry. Full article

As the cultural importance of universities continues to grow, university museums have become key platforms for promoting university heritage and values. However, enhancing the visitor experience in these museums remains challenging. This study examines the effectiveness of smellscape in enhancing the visitor experience in university history museums, with a focus on how various scents impact visitors’ emotions. Using the Fuzhou University History Museum as a case study, the museum was divided into three distinct zones: the Historical Evolution Zone (HEZ), the Contemporary Development Zone (CDZ), and the Thematic Exhibition Zone (TEZ). Specific scents were selected for each area to evaluate their emotional impact, and data were gathered using electroencephalography (EEG) indicators, emotional questionnaires, and scent pleasure scales. The results indicated that calming scents like sandalwood and agarwood, used in the HEZ, convey a sense of historical depth but may also evoke negative emotions, whereas sage enhances positive feelings. In the CDZ, rosemary and mint significantly improve emotional states, while lemongrass exhibits weaker pleasantness and appears less suited for this area. In the TEZ, scents such as patchouli and orange blossom align well with future-oriented themes, demonstrating high levels of pleasantness and emotional value. Smellwalk interviews further validated the experimental results, revealing notable differences in the emotional impact of smellscape across different exhibit zones. A thoughtful selection of scents can enhance the cultural expression of spaces and effectively regulate visitors’ emotional experiences, strengthening the cultural resonance of museum environments. Future designers may consider incorporating olfactory elements into landscape design. Full article

Honey differentiation based on the botanical origin is crucial to guarantee product authenticity, especially considering the increasing number of fraud cases. This study assessed the metabolomic differences arising from various botanical origins in honey products sold in Spanish markets, focusing on two goals: (1) discrimination within monofloral samples (eucalyptus, rosemary, and orange blossom honey) and (2) differentiation between multifloral vs. monofloral honey samples. An omics strategy based on ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap-high-resolution mass spectrometry (UHPLC-Q-Orbitrap-HRMS) was applied for the reliable identification of specific honey markers selected by orthogonal partial least squares discriminant analysis (OPLS-DA) (R²Y = 0.929–0.981 and Q² = 0.868–0.952), followed by the variable importance in projection (VIP) approach. Key amino acid, alkaloid, and trisaccharide markers were identified to distinguish between honey samples. Some Amadori compounds were highlighted as eucalyptus honey markers, suggesting their potential use for honey aging and botanical origin differentiation. L-phenylalanine and raffinose were markers of rosemary honey. Four markers (e.g., trigonelline, L-isoleucine, and N-(1-deoxy-1-fructosyl)isoleucine) were found in higher levels in multifloral samples, indicating a greater availability of amino acids, potentially increasing the Maillard reaction. This research is the first to address the botanical origin’s impact on honey by identifying novel markers not previously described. Full article

The citrus cultivar ‘Local Juhong’, which has historically been used as a traditional Chinese medicinal material, originated in Yuanjiang County, Hunan Province.Its parental type and genetic background are indistinct as of yet. Morphological observation shows that ‘Local Juhong’ has a slight oblateness in fruit shape, a relatively smooth pericarp, a fine and slightly raised oil vacuole, and an inward concave at the blossom end. The tree form and fruit and leaf morphology of ‘Local Juhong’ are similar to those of ‘Huangpi’ sour orange. To reveal the genetic background of ‘Local Juhong’, 21 citrus accessions were evaluated using nuclear and chloroplast SSR markers and whole-genome SNP information. ‘Local Juhong’ was grouped with mandarins and sub-grouped with ‘Miyagawa Wase’ and ‘Yanxi Wanlu’ in a nuclear SSR analysis, which indicated that its pollen parent might be mandarins. It was closely clustered with orange and pummelo in the chloroplast SSR analysis. The genomic sequence similarity rate of ‘Local Juhong’ with mandarin and pummelo heterozygosity was 70.88%; the main part was the heterozygosity, except for the unknown (19.66%), mandarin (8.73%), and pummelo (3.9%) parts. Thus, ‘Local Juhong’ may be an F₁ hybrid with pummelo as the female parent and mandarin as the male parent, sharing sisterhood with ‘Huangpi’ sour orange. Full article

The effects of a five-day treatment with low light intensity on tomato plants—Ailsa Craig and tangerine mutant—at normal and low temperatures and after recovery for three days under control conditions were investigated. The tangerine tomato, which has orange fruits, yellowish young leaves, and pale blossoms, accumulates prolycopene rather than all-trans lycopene. We investigated the impact of low light at normal and low temperatures on the functioning and effectiveness of photosynthetic apparatuses of both plants. The photochemical activities of Photosystem I (PSI) and Photosystem II (PSII) were assessed, and the alterations in PSII antenna size were characterized by evaluating the abundance of PSII-associated proteins Lhcb1, Lhcb2, CP43, and CP47. Alterations in energy distribution and interaction of both photosystems were analyzed using 77K fluorescence. In Aisla Craig plants, an increase in thylakoid membrane fluidity was detected during treatment with low light at a low temperature, while for the tangerine mutant, no significant change was observed. The PSII activity of thylakoids from mutant tangerine was more strongly inhibited by treatment with low light at a low temperature while low light barely affected PSII in Aisla Craig. The obtained data indicated that the observed differences in the responses of photosynthetic apparatuses of Ailsa Craig and tangerine when exposed to low light intensity and suboptimal temperature were mainly related to the differences in sensitivity and antenna complexes of PSII. Full article

Honey is one of the most adulterated foods, usually through the addition of sweeteners or low-cost honeys. This study presents a method based on visible near infrared spectroscopy (Vis-NIRs), in combination with machine learning (ML) algorithms, for the correct identification and quantification of adulterants in honey. Honey samples from two botanical origins (orange blossom and sunflower) were evaluated and adulterated with low-cost honey in different percentages (5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, and 50%). The results of the exploratory analysis showed a tendency to group the samples according to botanical origin, as well as the presence of adulteration. A supervised analysis was performed to detect the presence of adulterations. The best performance with 100% accuracy was achieved by support vector machines (SVM) and random forests (RF). A regression study was also carried out to quantify the percentage of adulteration. The best result was obtained by support vector regression (SVR) with a coefficient of determination (R²) of 0.991 and a root mean squared error (RMSE) of 1.894. These results demonstrate the potential of combining ML with spectroscopic data as a method for the automated quality control of honey. Full article

The botanical origin of honey determines its composition and hence properties and product quality. As a highly valued food product worldwide, assurance of the authenticity of honey is required to prevent potential fraud. In this work, the characterisation of Spanish honeys from 11 different botanical origins was carried out by headspace gas chromatography coupled with mass spectrometry (HS-GC-MS). A total of 27 volatile compounds were monitored, including aldehydes, alcohols, ketones, carboxylic acids, esters and monoterpenes. Samples were grouped into five categories of botanical origins: rosemary, orange blossom, albaida, thousand flower and “others” (the remaining origins studied, due to the limitation of samples available). Method validation was performed based on linearity and limits of detection and quantification, allowing the quantification of 21 compounds in the different honeys studied. Furthermore, an orthogonal partial least squares-discriminant analysis (OPLS-DA) chemometric model allowed the classification of honey into the five established categories, achieving a 100% and 91.67% classification and validation success rate, respectively. The application of the proposed methodology was tested by analysing 16 honey samples of unknown floral origin, classifying 4 as orange blossom, 4 as thousand flower and 8 as belonging to other botanical origins. Full article

(1) Background: Citrus honey constitutes a unique monofloral honey characterized by a distinctive aroma and unique taste. The non-targeted chemical analysis can provide pivotal information on chemical markers that differentiate honey based on its geographical and botanical origin. (2) Methods: Within the PRIMA project “PLANT-B”, a metabolomics workflow was established to unveil potential chemical markers of orange blossom honey produced in case study areas of Egypt, Italy, and Greece. In some of these areas, aromatic medicinal plants were cultivated to enhance biodiversity and attract pollinators. The non-targeted chemical analysis and metabolomics were conducted using ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS). (3) Results: Forty compounds were disclosed as potential chemical markers, enabling the differentiation of the three orange blossom honeys according to geographical origin. Italian honey showed a preponderance of flavonoids, while in Greek honey, terpenoids and iridoids were more abundant than flavonoids, except for hesperidin. In Egyptian honey, suberic acid and a fatty acid ester derivative emerged as chemical markers. New, for honey, furan derivatives were identified using GC-MS in Greek samples. (4) Conclusions: The application of UHPLC-HRMS metabolomics combined with an elaborate melissopalynological analysis managed to unveil several potential markers of Mediterranean citrus honey potentially associated with citrus crop varieties and the local indigenous flora. Full article

Long noncoding RNAs (lncRNAs) are a diverse class of noncoding RNAs that are typically longer than 200 nucleotides but lack coding potentials. Advances in deep sequencing technologies enabled a better exploration of this type of noncoding transcripts. The poor sequence conservation, however, complicates the identification and annotation of lncRNAs at a large scale. Wheat is among the leading food staples worldwide whose production is threatened by both biotic and abiotic stressors. Here, we identified putative lncRNAs from durum wheat varieties that differ in stem solidness, a major source of defense against wheat stem sawfly, a devastating insect pest. We also analyzed and annotated lncRNAs from two bread wheat varieties, resistant and susceptible to another destructive pest, orange wheat blossom midge, with and without infestation. Several putative lncRNAs contained potential precursor sequences and/or target regions for microRNAs, another type of regulatory noncoding RNAs, which may indicate functional networks. Interestingly, in contrast to lncRNAs themselves, microRNAs with potential precursors within the lncRNA sequences appeared to be highly conserved at the sequence and family levels. We also observed a few putative lncRNAs that have perfect to near-perfect matches to organellar genomes, supporting the recent observations that organellar genomes may contribute to the noncoding transcript pool of the cell. Full article

A non-targeted LC–HRMS fingerprinting methodology based on a C18 reversed-phase mode under universal gradient elution using an Orbitrap mass analyzer was developed to characterize and classify Spanish honey samples. A simple sample treatment consisting of honey dissolution with water and a 1:1 dilution with methanol was proposed. A total of 136 honey samples belonging to different blossom and honeydew honeys from different botanical varieties produced in different Spanish geographical regions were analyzed. The obtained LC–HRMS fingerprints were employed as sample chemical descriptors for honey pattern recognition by principal component analysis (PCA) and partial least squares–discriminant analysis (PLS–DA). The results demonstrated a superior honey classification and discrimination capability with respect to previous non-targeted HPLC–UV fingerprinting approaches, with them being able to discriminate and authenticate the honey samples according to their botanical origins. Overall, noteworthy cross-validation multiclass predictions were accomplished with sensitivity and specificity values higher than 96.2%, except for orange/lemon blossom (BL) and rosemary (RO) blossom-honeys. The proposed methodology was also able to classify and authenticate the climatic geographical production region of the analyzed honey samples, with cross-validation sensitivity and specificity values higher than 87.1% and classification errors below 10.5%. Full article

In this paper, new suspended-membrane double-ohmic-contact RF-MEMS switch configurations are proposed. Double-diagonal (DDG) beam suspensions, with either two or three anchoring points, are designed and optimized to minimize membrane deformation due to residual fabrication stresses, thus exhibiting smaller mechanical deformation and a higher stiffness with more release force than previously designed single diagonal beam suspensions. The two-anchor DDGs are designed in two different orientations, in-line and 90°-rotated. The membrane may include a window to minimize the coupling to the lower electrode. The devices are integrated in a coplanar-waveguide transmission structure and fabricated using an eight-mask surface-micro-machining process on high-resistivity silicon, with dielectric-free actuation electrodes, and including glass protective caps. The RF-MEMS switch behavior is assessed from measurements of the device S parameters in ON and OFF states. The fabricated devices feature a measured pull-in voltage of 76.5 V/60 V for the windowed/not-windowed two-anchor DDG membranes, and 54 V/49.5 V for the windowed/not-windowed three-anchor DDG membranes, with a good agreement with mechanical 3D simulations. The measured ON-state insertion loss is better than 0.7 dB/0.8 dB and the isolation in the OFF state is better than 40 dB/31 dB up to 20 GHz for the in-line/90°-rotated devices, also in good agreement with 2.5D electromagnetic simulations. Full article

The feasibility of non-targeted off-line SPE LC-LRMS polyphenolic fingerprints to address the classification and authentication of Spanish honey samples based on both botanical origin (blossom and honeydew honeys) and geographical production region was evaluated. With this aim, 136 honey samples belonging to different botanical varieties (multifloral and monofloral) obtained from different Spanish geographical regions with specific climatic conditions were analyzed. Polyphenolic compounds were extracted by off-line solid-phase extraction (SPE) using HLB (3 mL, 60 mg) cartridges. The obtained extracts were then analyzed by C18 reversed-phase LC coupled to low-resolution mass spectrometry in a hybrid quadrupole-linear ion trap mass analyzer and using electrospray in negative ionization mode. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were employed to assess the pattern recognition capabilities of the obtained fingerprints to address honey classification and authentication. In general, a good sample discrimination was accomplished by PLS-DA, being able to differentiate both blossom-honey and honeydew-honey samples according to botanical varieties. Multiclass predictions by cross-validation for the set of blossom-honey samples showed sensitivity, specificity, and classification ratios higher than 60%, 85%, and 87%, respectively. Better results were obtained for the set of honeydew-honey samples, exhibiting 100% sensitivity, specificity, and classification ratio values. The proposed fingerprints also demonstrated that they were good honey chemical descriptors to deal with climatic and geographical issues. Characteristic polyphenols of each botanical variety were tentatively identified by LC-MS/MS in multiple-reaction monitoring mode to propose possible honey markers for future experiments (i.e., naringin for orange/lemon blossom honeys, syringic acid in thyme honeys, or galangin in rosemary honeys). Full article