Front-Face Fluorescence of Honey of Different Botanic Origin: A Case Study from Tuscany (Italy)

Sugar detection in adulterated honey using hyper-spectral imaging with stacking generalization method

This paper develops a new hybrid, automated, and non-invasive approach by combining hyper-spectral imaging, Savitzky-Golay (SG) Filter, Principal Components Analysis (PCA), Machine Learning (ML) classifiers/regressors, and stacking generalization methods to detect sugar in honey. First, the 32 different sugar concentration levels in honey were predicted using various ML regressors. Second, the six ranges of sugar were classified using various classifiers. Third, the 11 types of honey and 100% sugar were classified using classifiers. The stacking model (STM) obtained R2: 0.999, RMSE: 0.493 ml (v/v), RPD: 40.2, a 10-fold average R2: 0.996 and RMSE: 1.27 ml (v/v) for predicting 32 sugar concentrations. The STM achieved a Matthews Correlation Coefficient (MCC) of 99.7% and a Kappa score of 99.7%, a 10-fold average MCC of 98.9% and a Kappa score of 98.9% for classifying the six sugar ranges and 12 categories of honey types and a sugar.

Analyzing Tear Fluid Composition by Synchronous Fluorescence for Diagnosing Dry Eye Disease and the Role of Phytotherapy Intervention

PURPOSE

Tear fluid gained attention as a representative biological fluid. Its simple and non-invasive collection methods as well as richness of candidate biomarkers made it a potential diagnostic tool for different diseases such as dry eye. Synchronous fluorescence spectroscopy is a highly sensitive analytical tool that results in narrowing and enhanced peak resolution, and has a potential role in disease diagnosis, biomarker identification, and therapeutic monitoring. We applied synchronous fluorescence spectroscopy to monitor variations of tear fluid composition during the development of dry eye disease and to evaluate the potential effects of phytotherapy.

METHODS

Dry eye model was induced in Chinchilla rabbits by instillation of 1% atropine sulfate ophthalmic solution. Then, the tear fluid was collected at 3, 7, and 14 days and subjected to synchronous fluorescence spectroscopy. Phytotherapy was achieved by topical instillation of 20 µl of water extracts of pomegranate peel or green tea powders.

RESULTS

The fluorescence results revealed changes in the structure of tear fluid over time and the eye is subjected to toxification due to oxidative stress. In addition, dry eye disease was found to affect the metabolic/energetic state of the eye. On the other hand, phytotherapy led to enhancement of the metabolic/biosynthesis state due to activation of flavin adenine dinucleotide-associated proteins.

CONCLUSION

There was change in the electrical conductivity of tear fluid proteins. In the case of dry eyes, they became electrical insulators, while in the case of treatment with extracts, their electrical conductivity properties improved. The effects of phytotherapy can be related to the high content of ellagic acid and anthocyanin of pomegranate extract, while in green tea, they are related to catechins and phenolic compounds.

Light-Emitting-Diode-Induced Fluorescence from Organic Dyes for Application in Excitation-Emission Fluorescence Spectroscopy for Food System Analysis

An experimental study is presented on the possibility of using the fluorescence from organic dyes as a broadband light source together with a monochromator for applications in excitation-emission matrix (EEM) fluorescence spectroscopy. A high-power single-chip light-emitting diode (LED) was chosen as an excitation source with a central output wavelength at 365 nm to excite a fluorescent solution of Coumarin 1 dye dissolved in ethanol. Two excitation configurations were investigated: direct excitation from the LED and excitation through an optical-fiber-coupled LED. A Czerny-Turner monochromator with a diffraction grating was used for the spectral tuning of the fluorescence. A simple method was investigated for increasing the efficiency of the excitation as well as the fluorescence signal collection by using a diffuse reflector composed of barium sulfate (BaSO4) and polyvinyl alcohol (PVA). As research objects, extra-virgin olive oil (EVOO), Coumarin 6 dye, and Perylene, a polycyclic aromatic hydrocarbon (PAH), were used. The results showed that the light-emitting-diode-induced fluorescence was sufficient to cover the losses on the optical path to the monochromator output, where a detectable signal could be obtained. The obtained results reveal the practical possibility of applying the fluorescence from dyes as a light source for food system analysis by EEM fluorescence spectroscopy.

Combined Application of Fluorescence Spectroscopy and Principal Component Analysis in Characterisation of Selected Herbhoneys

This study reports the use of front-face fluorescence spectroscopy with principal component analysis (PCA) as a tool for the characterisation of selected Polish herbhoneys (raspberry, lemon balm, rose, mint, black current, instant coffee, pine, hawthorn, and nettle). Fluorimetric spectra registered in the ranges ascribed to fluorescence of amino acids, polyphenols, vitamins, and products of Maillard's reaction enabled the comparison of herbhoney compositions. Obtained synchronous spectra combined with PCA were used to investigate potential differences between analysed samples and interactions between compounds present in them. The most substantial influence on the total variance had the intensities of polyphenols fluorescence. These intensities were the main factor differentiated by the analysed products.

Ultraviolet-visible spectroscopy combined with machine learning as a rapid detection method to the predict adulteration of honey

Honey is often adulterated with inexpensive and artificial sweeteners. To overcome the time-consuming honey adulteration tests, which require precision, chemicals, and sample preparation, it is needful to develop trustworthy analytical methods to assure its authenticity. In the present study, the potential of ultraviolet-visible spectroscopy (UV-Vis) in predicting the sucrose content was evaluated by using Support Vector Regression (SVR) and Partial Least Square Regression (PLSR). To predict the sucrose content based on diagnostic wavelengths, a Point Spectro Transfer Function (PSTF) was evaluated using Multiple Linear Regression (MLR). For this purpose, the spectra of authentic (n = 12), commercial (n = 12), and adulterated (n = 16) honey samples were recorded. Four distinguished wavelengths from correlation analysis between sucrose content and spectra absorption were 216, 280, 316, and 603 nm. The SVR performed better calibration model than the PLSR estimations (RMSE = 0.97, and R2 = 0.98). The predictive models result revealed that both models had high accuracy for the sucrose content estimation. This study proved that UV-Vis spectroscopy provides an economical alternative for the rapid quantification of adulterated honey samples with sucrose.

The Importance of Testing the Quality and Authenticity of Food Products: The Example of Honey

The aim of this study was to review methods of honey testing in the assessment of its quality and authenticity. The quality of honey, like other food products, is multidimensional. This quality can be assessed not only on the basis of the characteristics evaluated by the consumer during purchase and consumption, but also on the basis of various physicochemical parameters. A number of research methods are used to verify the quality of honeys and to confirm their authenticity. Obligatory methods of assessing the quality of honey are usually described in legal acts. On the other hand, other, non-normative methods of honey quality assessment are used worldwide; they can be used to determine not only the elementary chemical composition of individual types of honey, but also the biological activity of honey and its components. However, so far, there has been no systematization of these methods together with a discussion of problems encountered when determining the authenticity of honeys. Therefore, the aim of our study was to collect information on the methods of assessing the quality and authenticity of honeys, and to identify the problems that occur during this assessment. As a result, a tabular summary of various research methods was created.

A nomogram model based on the combination of the systemic immune-inflammation index, body mass index, and neutrophil/lymphocyte ratio to predict the risk of preoperative deep venous thrombosis in elderly patients with intertrochanteric femoral fracture: a retrospective cohort study

OBJECTIVES

Deep vein thrombosis (DVT) has been considered as a frequent and serious consequence of intertrochanteric femoral fractures in the elderly. Several negative repercussions of DVT can be considerably mitigated by its timely recognition and treatment. The current work was aimed at exploring the factors independently predicting DVT among cases suffering from intertrochanteric femoral fractures and validate their predictive usefulness in diagnosing DVT.

METHODS

Between April 2017 and July 2022, clinical information from 209 cases showing preoperative DVT for femoral intertrochanteric fractures were retrospectively evaluated. In patients with femoral intertrochanteric fractures, logistic regression analysis with a backward stepwise method was adopted for detecting independent predictors for the diagnosis of preoperative DVT. Using multivariate logistic regression, a nomogram prediction model was developed and verified with the testing group.

RESULTS

According to multivariate logistic regression model, body mass index (BMI) (OR 0.79, 95% CI 0.63-0.99, P = 0.042), neutrophil/lymphocyte ratio (NLR) (OR 7.29, 95% CI 1.53, 34.64, P = 0.0012), and systemic immune-inflammation index (SII) (OR 6.61, 95% CI 2.35, 18.59, P = 0.001) were independent predictors for DVT before surgery among cases developing intertrochanteric femoral fracture. AUC values were 0.862 and 0.767 for training and testing groups, separately, while their mean errors in the calibration curve were 0.027 and 0.038 separately. Decision curve analysis (DCA) curve revealed a high value of clinical application for both groups.

CONCLUSION

Upon admission, BMI, NLR, and SII are independent predictors of DVT before surgery among cases developing intertrochanteric femoral fractures. Additionally, the nomogram based on the BMI, NLR, and SII can assist clinicians in determining if preventive and symptomatic therapies are required to improve DVT prognosis and reduce its associated mortality.

Calluna vulgaris as a Valuable Source of Bioactive Compounds: Exploring Its Phytochemical Profile, Biological Activities and Apitherapeutic Potential

Calluna vulgaris, belonging to the Ericaceae family, is an invasive plant that has widely spread from Europe all across Asia, North America, Australia and New Zealand. Being able to survive in rigid soil and environmental conditions, it is nowadays considered to be of high nature-conservation value. Known for its nutritional and medicinal properties, C. vulgaris stands out for its varied physiochemical composition, spotlighting a wide range of biological activity. Among the most important bioactive compounds identified in C. vulgaris, the phenolic components found in different parts of this herbaceous plant are the main source of its diverse pro-health properties (antioxidant, anti-inflammatory, antimicrobial, chemoprotective, etc.). Nonetheless, this plant exhibits an excellent nectariferous potential for social insects such as honeybees; therefore, comparing the bioactive compounds observed in the plant and in the final product of the beehive, namely honey, will help us understand and find new insights into the health benefits provided by the consumption of C. vulgaris-related products. Thus, the main interest of this work is to review the nutritional profile, chemical composition and biological activities of the C. vulgaris plant and its related honey in order to encourage the future exploration and use of this health-promoting plant in novel foods, pharmacological products and apitherapy.

Vigna subterranea (L.) Verdc Starch-Soluble Dietary Fibre Potential Nanocomposite: Thermal Behaviour, Morphology and Crystallinity

Bambara groundnut (BGN) starch-soluble dietary fibre nanocomposite (STASOL) was manufactured by grafting 1.95 g BGN soluble dietary fibre (BGN-SDF) onto 15 g BGN starch (BGNS). The particle sizes, functional groups, crystallinity, morphology and thermal properties of BGNS, BGN-SDF and STASOL were studied using a Zetasizer, Fourier transform infrared, X-ray diffraction, scanning electron microscope and differential scanning calorimetry, respectively. STASOL had a particle size and conductivity of 74.01 nm and −57.3 mV, respectively. BGN-SDF and STASOL were amorphous and BGNS was classified as type C starch, typical of legumes. The biopolymers had functional groups in the regions 2900–3600, 1600–1642, 900–1200 and 800–1300 cm−1, which could be attributed to the vibrational stretching of OH groups, vibration of OH groups in the non-crystalline region of starch, vibration of C-O, C-C and C-H-O bonds and the vibration of C-O and C-C bonds, respectively. BGNS had smooth, oval structures while BGN-SDF and STASOL exhibited irregular, polygonal morphologies. STASOL was the most thermally stable biopolymer, disintegrating at 293 °C, therefore suggesting that it would find use in high-temperature food applications such as baking.

UV excited fluorescence image-based non-destructive method for early detection of strawberry (Fragaria × ananassa) spoilage

The soon spoiled strawberries need to be classified from healthy fruits in an early stage. In this research, a machine vision system is proposed for inspecting the quality of strawberries using ultraviolet (UV) light based on the excitation-emission matrix (EEM) results. Among the 100 fruits which were harvested and stored under 10 °C condition for 7 days, 7 fruits were confirmed to be spoiled by using a firmness meter. The EEM results show the fluorescence compound contributes to a whitish surface on the spoiled fruits. Based on the EEM results, UV fluorescence images from the bottom view of strawberries were used to classify the spoiled fruits and healthy fruits within 1 day after harvest. These results demonstrate the UV fluorescence imaging can be a fast, non-destructive, and low-cost method for inspecting the soon spoiled fruits. The proposed index related to the spoiling time can be a new indicator for qualifying strawberry.

Monofloral Honeys as a Potential Source of Natural Antioxidants, Minerals and Medicine

Background: vegetative diversity is based on different climate and geographical origins. In terms of beekeeping, herbal diversity is strongly correlated to the production of a wide variety of honey. Therefore, based on the existing plant diversity in each country, multiple honey varieties are produced with different health characteristics. While beekeeping potential and consumption preferences are reflected in products’ variety, this leads to an increase in the region’s economy and extensive export. In the last years, monofloral honey has gained interest from consumers and especially in the medicinal field due to the presence of phytochemicals which are directly linked to health benefits, wound healing, antioxidant, anticancer and anti-inflammatory activities. Scope and approach: this review aims to highlight the physicochemical properties, mineral profiles and antioxidant activities of selected monofloral honeys based on their botanical and geographical origin. Moreover, this review focuses on the intercorrelation between monofloral honey’s antioxidant compounds and in vitro and in vivo activities, focusing on the apoptosis and cell proliferation inhibition in various cell lines, with a final usage of honey as a potential therapeutic product in the fight towards reducing tumor growth. Key findings and conclusions: multiple studies have demonstrated that monofloral honeys have different physicochemical structures and bioactive compounds. Useful chemical markers to distinguish between monofloral honeys were evidenced, such as: 2-methoxybenzoic acid and trimethoxybenzoic acid are distinctive to Manuka honey while 4-methoxyphenylacetic acid is characteristic to Kanuka honey. Furthermore, resveratrol, epigallocatechin and pinostrobin are markers distinct to Sage honey, whereas carvacrol and thymol are found in Ziziphus honey. Due to their polyphenolic profile, monofloral honeys have significant antioxidant activity, as well as antidiabetic, antimicrobial and anticancer activities. It was demonstrated that Pine honey decreased the MDA and TBARS levels in liver, kidney, heart and brain tissues, whereas Malicia honey reduced the low-density lipoprotein level. Consumption of Clover, Acacia and Gelam honeys reduced the weight and adiposity, as well as trygliceride levels. Furthermore, the antiproliferative effect of chrysin, a natural flavone in Acacia honey, was demonstrated in human (A375) and murine (B16-F1) melanoma cell lines, whereas caffeic acid, a phenolic compound found in Kelulut honey, proves to be significant candidate in the chemoprevention of colon cancer. Based on these features, the use of hiney in the medicinal field (apitherapy), and the widespread usage of natural product consumption, is gaining interest by each year.

The Use of Right Angle Fluorescence Spectroscopy to Distinguish the Botanical Origin of Greek Common Honey Varieties

The standardization of the botanical origin of honey reflects the commercial value and quality of honey. Nowadays, most consumers are looking for a unifloral honey. The aim of the present study was to develop a novel method for honey classification using chemometric models based on phenolic compounds analyzed with right angle fluorescence spectroscopy, coupled with stepwise linear discriminant analysis (LDA). The deconstructed spectrum from three-dimensional-emission excitation matrix (3D-EEM) spectra provided a correct classification score of 94.9% calibration and cross-validation at an excitation wavelength (λex) of 330 nm. Subsequently, a score of 81.4% and 79.7%, respectively, at an excitation wavelength (λex) of 360 nm was achieved. Each chemometric model confirmed its power through the external validation with a score of 82.1% for both. Differentiation could be correlated with hydroxycinnamic and hydroxybenzoic acids, which absorb in this region of the spectrum. Fluorescence spectroscopy constitutes a rapid and sensitive technique, which, when combined with the stepwise algorithm and LDA method, can be used as a reliable and predictive authentication tool for honey. This study indicates that the developed methodology is a promising technique for determination of the botanical origin of common Greek honey varieties. Our long-term ambition is to support producers and suppliers to remain in a competitive national and international market.

The Use of UV Spectroscopy and SIMCA for the Authentication of Indonesian Honeys According to Botanical, Entomological and Geographical Origins

As a functional food, honey is a food product that is exposed to the risk of food fraud. To mitigate this, the establishment of an authentication system for honey is very important in order to protect both producers and consumers from possible economic losses. This research presents a simple analytical method for the authentication and classification of Indonesian honeys according to their botanical, entomological, and geographical origins using ultraviolet (UV) spectroscopy and SIMCA (soft independent modeling of class analogy). The spectral data of a total of 1040 samples, representing six types of Indonesian honey of different botanical, entomological, and geographical origins, were acquired using a benchtop UV-visible spectrometer (190-400 nm). Three different pre-processing algorithms were simultaneously evaluated; namely an 11-point moving average smoothing, mean normalization, and Savitzky-Golay first derivative with 11 points and second-order polynomial fitting (ordo 2), in order to improve the original spectral data. Chemometrics methods, including exploratory analysis of PCA and SIMCA classification method, was used to classify the honey samples. A clear separation of the six different Indonesian honeys, based on botanical, entomological, and geographical origins, was obtained using PCA calculated from pre-processed spectra from 250-400 nm. The SIMCA classification method provided satisfactory results in classifying honey samples according to their botanical, entomological, and geographical origins and achieved 100% accuracy, sensitivity, and specificity. Several wavelengths were identified (266, 270, 280, 290, 300, 335, and 360 nm) as the most sensitive for discriminating between the different Indonesian honey samples.

Chitosan Induces Plant Hormones and Defenses in Tomato Root Exudates

In this work, we use electrophysiological and metabolomic tools to determine the role of chitosan as plant defense elicitor in soil for preventing or manage root pests and diseases sustainably. Root exudates include a wide variety of molecules that plants and root microbiota use to communicate in the rhizosphere. Tomato plants were treated with chitosan. Root exudates from tomato plants were analyzed at 3, 10, 20, and 30 days after planting (dap). We found, using high performance liquid chromatography (HPLC) and excitation emission matrix (EEM) fluorescence, that chitosan induces plant hormones, lipid signaling and defense compounds in tomato root exudates, including phenolics. High doses of chitosan induce membrane depolarization and affect membrane integrity. 1H-NMR showed the dynamic of exudation, detecting the largest number of signals in 20 dap root exudates. Root exudates from plants irrigated with chitosan inhibit ca. twofold growth kinetics of the tomato root parasitic fungus Fusarium oxysporum f. sp. radicis-lycopersici. and reduced ca. 1.5-fold egg hatching of the root-knot nematode Meloidogyne javanica.

Antioxidant, Nutraceutical Properties, and Fluorescence Spectral Profiles of Bee Pollen Samples from Different Botanical Origins

Bee pollen is made by honey bees (Apis Mellifera) from the pollen of plants and flowers and represents an apiary product enriched in essential amino acids, polyphenols, omega-3, and omega-6 fatty acids. This study investigated the botanical origin, micronutrient profile, and antioxidant activity of bee pollen samples (n = 10) harvested in Lucca and Massa Carrara (Tuscany, Italy) between 2016 and 2017. The palynological analysis showed that bee pollen samples were composed of nine botanical families. Front-face fluorescence spectroscopy was performed on bee pollen samples in bulk, without any treatment, and in ethanol extracts to determine the characteristic fluorescent profile and, to identify the main chemical compounds with biological activity. The main chemical compounds detected were polyphenols (mainly flavonoids and phenolic acids), hydro-soluble vitamins (B₂, B₃, B₆, and B₉), amino acids, and pigments. Furthermore, the antioxidant activity was investigated, and one of the two Viburnum pollens resulted in the highest polyphenols and flavonoids content (20.15 ± 0.15 mg GAE/g fw and 23.46 ± 0.08 mg CE/g fw, respectively). However, Prunus and Eucalyptus families showed the highest in vitro (190.27 ± 8.30 µmol Fe²⁺/g) and ex vivo (54.61 ± 8.51 CAA unit) antioxidant capacity, respectively. These results suggested that Tuscan bee pollen, depending on the botanical family, is rich in essential nutrients and potential nutraceutical product.

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.