Evaluasi toksisitas Madu hasil produksi lebah yang diberi pakan tambahan ekstrak air Moringa oleifera terhadap larva Artemia salina

Madu dan Moringa oleifera merupakan salah satu bahan alam yang memiliki nilai nutrisi dan potensi sebagai bahan obat yang cukup besar. Penelitian ini bertujuan untuk mengevaluasi toksisitas madu hasil ternak lebah yang diberi pakan sirup sukrosa dengan suplementasi M. oleifera menggunakan Artemia salina sebagai hewan model. Komponen madu kelor (MK) dan M. oleifera mula-mula dianalisis dengan menggunakan sistem HPTLC dengan fase gerak terdiri dari n-heksana dan etil asetat dengan perbandingan 2:1. Toksisitas MK kemudian diuji menggunakan A. salina sebagai model organisme dengan konsentrasi antara 10 hingga 2000 μg / ml dalam media air laut buatan. Tingkat kematian dilaporkan dalam persentase A. salina jumlah larva yang mati terhadap total larva yang diuji. Nilai LC50 dihitung dengan menggunakan analisis probit. Hasil analisis pada penelitian ini menunjukkan bahwa beberapa komponen M. oleifera dapat dideteksi pada MK berdasarkan nilai Rf yang diperoleh dalam analisis HPTLC. Selanjutnya, berdasarkan nilai LC50 dalam penelitian ini, MK dianggap sebagai bahan dengan toksisitas yang rendah. Namun, penelusuran lebih lanjut pada komponen fitokimia yang bertanggung jawab pada toksisitas ini perlu dilakukan untuk melihat korelasinya dengan toksisitas M

Klasifikasi Madu Berdasarkan Jenis Lebah (Apis dorsata versus Apis mellifera) Menggunakan Spektroskopi Ultraviolet dan Kemometrika

In this research, spectral data in UV region (200-400 nm) alongside PCA and SIMCA chemometrics were used to classify two types of honey obtained from different honeybees (Apis dorsata versus Apis mellifera). A total of 200 Durian monofloral honey samples from Apis dorsata and 120 samples for Longan monofloral honey from Apis mellifera were prepared. Therefore, spectral data were recorded based on the following parameters: range of acquisition 200-400 nm, transmittance mode, and interval 1 nm. In addition, the original spectra were transformed using three different algorithms: moving average smoothing with 11 segments, standard normal variate (SNV), and Savitzky-Golay 1st derivative with 11 segments and 2 ordos. The result of PCA using transformed spectra in the range of 250-400 nm explained the possibility of clearly separating Durian and Longan honey along the PC1 axis, with 98% variance, while the SIMCA showed a 100% proper classification rate for all prediction samples. In addition, several important wavelengths were identified alongside high x-loadings values at 270 and 300 nm. These results were closely related to the absorbance of important phenolic compounds in honey, including benzoic, salicylic, and aryl-alyphatic acids. The results demonstrate a probability to establish simple and low-cost honey authentication systems, using UV spectroscopy and chemometrics on free-chemical in sample preparations. Keywords: authentication, Apis dorsata, Apis mellifera, SIMCA, UV spectroscop

Caracterización fenólica de miel de mielada

La miel es la sustancia natural dulce producida por la abeja Apis mellifera a partir del néctar de plantas o de secreciones de partes vivas de plantas o de excreciones de insectos chupadores presentes en las partes vivas de plantas, que las abejas recolectan, transforman combinándolas con sustancias específicas propias, depositan, deshidratan, almacenan y dejan en colmenas para que madure. La miel de mielada es aquella que procede en su mayor parte de excreciones de insectos chupadores de plantas (hemípteros) presentes en las partes vivas de las plantas o de secreciones de las partes vivas de las plantas. Las principales diferencias entre la miel de néctar y de mielada son en la de conductividad eléctrica, el pH y la acidez. A lo largo del tiempo, la miel ha sido utilizada no solamente por sus propiedades nutritivas sino también por sus propiedades beneficiosas para la salud como son su acción antibacteriana, antifúngica, antiinflamatoria, antiséptica y cicatrizante Los compuestos fenólicos además de contribuir a las características sensoriales de la miel participan junto a otro grupo de constituyentes minoritarios en la actividad antioxidante. La determinación de los compuestos fenólicos se lleva a cabo mediante técnicas de separación, primero se realiza una extracción en fase sólida seguida de una extracción líquido-líquido y posteriormente el extracto se analiza en un cromatógrafo de líquidos. El proceso analítico puede entenderse como un proceso de tres etapas distintas que se construyen en relación con la etapa central de medida. Estas etapas son: toma y preparación de la muestra, medida de la señal analítica y toma de datos y el tratamiento de datos y la expresión de resultados. Mediante la calibración metodológica realizamos el tratamiento de datos estableciendo una relación entre la respuesta de un instrumento obtenida del cromatógrafo y la concentración analítica. En este estudio se han identificado distintos ácidos hidroxibenzoicos como son: el ácido gálico, protocatéquico, vainillico, siríngico y p-hidroxibenzoico y derivados del ácido siringico y p-hidroxibenzoico, ácidos hidroxicinámicos como ácidos p-cumárico y cafeico y por último galangina, naringenina, crisina y pinocembrina como flavonoides. Palabras claves: miel de mielada, compuestos fenólicos, tratamiento de datos.Universidad de Sevilla. Grado en Farmaci

Novel approach for the characterisation of Sicilian honeys based on the correlation of physico-chemical parameters and artificial senses

The aim of this work was to characterise some of the most representative Sicilian honeys. Sugars, pH and minerals were determined with conventional analyses. Chestnut honeys showed the lowest sugar content, with a fructose and glucose sum of 62.31\u2009g/100g. Citrus and Eucalyptus honeys showed the highest fructose content (38.08 and 38.04\u2009g/100g), while Citrus and Sulla honeys had the highest sucrose content (3.16 and 3.92\u2009g/100g). The highest fructose to glucose ratio was 1.59, found for Chestnut honeys, which had also the highest pH-value of 4.98. Potassium is the most abundant element in honey and the highest values were found for Chestnut and Eucalyptus honey (4.412 and 1.956\u2009mg/g). Among micro-minerals, Zinc showed the highest concentration, ranging from 4.64 to 7.16 \ub5g/g. Alongside physicochemical analyses, E-tongue and computer vision was used to estimate the organoleptic proprieties of honey. In particular, Pearson\u2019s correlation was used to study the relationship between the electrical E-tongue\u2019 signals, pH and sugars content, which have a major influence on the main taste attributes investigated in honey. Chestnut honeys scored the lowest values for the sweet and sour taste, being the bitterest among the samples evaluated. On the other hand, Sulla and Citrus honeys were the sweetest and the sourest. The colour of honey was examined with machine vision and the weight of the different minerals on the colour parameters was disclosed, resulting in dark colours correlated to sodium and microelements, and in a light colour that showed a negative correlation with potassium and magnesium

Honey as an Adjuvant in the Treatment of COVID-19 Infection: A Review

Since ancestor times, honey has been used to promote human health due to its medicinal, and nutritious properties, mainly due to bioactive compounds present, such as phenolic compounds. The emergence of COVID-19, caused by the SARS-CoV-2 virus, led to the pursuit of solutions for the treatment of symptoms and/or disease. Honey has proven to be effective against viral infections, principally due to its potential antioxidant and anti-inflammatory activities that attenuate oxidative damage induced by pathogens, and by improving the immune system. Therefore, the aim of this review is to overview the abilities of honey to attenuate different COVID-19 symptoms, highlighting the mechanisms associated with these actions and relating the with the different bioactive compounds present. A brief, detailed approach to SARS-CoV-2 mechanism of action is first overviewed to allow readers a deep understanding. Additionally, the compounds and beneficial properties of honey, and its previously application in other similar diseases, are detailed in depth. Despite the already reported efficacy of honey against different viruses and their complications, further studies are urgently needed to explain the molecular mechanisms of activity against COVID-19 and, most importantly, clinical trials enrolling COVID-19 patients.This research was funded by MTS/SAS/0077/2020—Honey+—New reasons to care honey from the Natural Park of Montesinho: A bioindicator of environmental quality & its therapeutic potential, and by the projects UIDB/50006/2020, UIDP/50006/2020, and LA/P/0008/2020, all supported by Fundação para a Ciência e a Tecnologia (FCT)/Ministério da Ciência, Tecnologia e Ensino Superior (MCTES). We are thankful to the Fundação para a Ciência e a Tecnologia (Portugal) through project MTS/SAS/0077/2020—Honey+—New reasons to care honey from the Natural Park of Montesinho: A bioindicator of environmental quality & its therapeutic potential. This work was also financially supported by Portuguese national funds through projects UIDB/50006/2020, UIDP/50006/2020, UIDB/04033/2020 and LA/P/0008/2020, from the Fundação para a Ciência e a Tecnologia (FCT)/Ministério da Ciência, Tecnologia e Ensino Superior (MCTES). Francisca Rodrigues and Clara Grosso are thankful for their contracts (CEECIND/01886/2020 and CEECIND/03436/2020) financed by FCT/MCTES—CEEC Individual 2020 Program Contract. Juliana Garcia is grateful to FCT and BPI La Caixa Foundation, within the project titled ‘AquaeVitae—Água Termal Como Fonte de Vida e Saúde”—“PROMOVE—O futuro do Interior” call 2020 and “AquaValor—Centro de Valorização e Transferência de Tecnologia da Água” (NORTE-01-0246-FEDER-000053), supported by Norte Portugal Regional Operational Programme (NORTE 2020) under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF).info:eu-repo/semantics/publishedVersio

Honeys from the Argentine Phytogeographic Provinces Chaqueña and Monte in Catamarca and La Rioja

The characterization of Argentinean honeys from the vegetation units (VUs) of the phytogeographical provinces located in Catamarca and La Rioja was performed with the analysis used for honey quality control: sugar profile, free acidity, pH, electrical conductivity (EC), color and contents of moisture, ash, total soluble solids, and hydroxymethylfurfural (HMF). Honeys were authentic and traceable, and complied with the specifications of national and/or international standards, verifying their blossom origin, high quality, good maturity, and freshness. Honeys from VU-9 and VU-23 presented significantly distinctive physicochemical parameters, evidencing the influence of the flora and pedoclimatic conditions of these VUs. Honeys from VU-23 presented significantly higher contents of glucose and total reducing sugars (F + G), and lower EC, ash contents, fructose/glucose ratio, and concentrations of turanose and maltose than those from VU-9. Honeys from VU-23 in La Rioja also exhibited characteristic lighter colors and lower pH and ºBrix values and turanose amounts; and honeys from VU-9 in La Rioja exhibited highest pH values. Catamarca honeys were characterized by high free acidity and high amounts of turanose, regardless of the VUs. The contents of sugars and total soluble solids, moisture, pH, EC, and color of honeys from Catamarca and La Rioja are published here for the first time. This study contributes to the typification of honeys from these provinces, which will provide them an added value and allow them to access newer markets.Fil: Poliero, Aimará Ayelen. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Química. Grupo de Investigación en Ingeniería en Alimentos; ArgentinaFil: Aubone, Ines. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Amadei Enghelmayer, Marisa. Nexco, S.a.; ArgentinaFil: Rosso, Valeria Soledad. Nexco, S.a.; ArgentinaFil: Fuselli, Sandra Rosa. Universidad Nacional de Mar del Plata. Instituto de Investigaciones en Producción, Sanidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Producción, Sanidad y Ambiente; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones en Sanidad Producción y Ambiente. - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires. Instituto de Investigaciones en Sanidad Producción y Ambiente; ArgentinaFil: Alonso Salces, Rosa Maria. Universidad Nacional de Mar del Plata. Instituto de Investigaciones En Produccion, Sanidad y Ambiente. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Mar del Plata. Instituto de Investigaciones En Produccion, Sanidad y Ambiente.; Argentin

Comparative study of several machine learning algorithms for classification of unifloral honeys

Unifloral honeys are highly demanded by honey consumers, especially in Europe. To ensure that a honey belongs to a very appreciated botanical class, the classical methodology is palynological analysis to identify and count pollen grains. Highly trained personnel are needed to perform this task, which complicates the characterization of honey botanical origins. Organoleptic assessment of honey by expert personnel helps to confirm such classification. In this study, the ability of different machine learning (ML) algorithms to correctly classify seven types of Spanish honeys of single botanical origins (rosemary, citrus, lavender, sunflower, eucalyptus, heather and forest honeydew) was investigated comparatively. The botanical origin of the samples was ascertained by pollen analysis complemented with organoleptic assessment. Physicochemical parameters such as electrical conductivity, pH, water content, carbohydrates and color of unifloral honeys were used to build the dataset. The following ML algorithms were tested: penalized discriminant analysis (PDA), shrinkage discriminant analysis (SDA), high-dimensional discriminant analysis (HDDA), nearest shrunken centroids (PAM), partial least squares (PLS), C5.0 tree, extremely randomized trees (ET), weighted k-nearest neighbors (KKNN), artificial neural networks (ANN), random forest (RF), support vector machine (SVM) with linear and radial kernels and extreme gradient boosting trees (XGBoost). The ML models were optimized by repeated 10-fold cross-validation primarily on the basis of log loss or accuracy metrics, and their performance was compared on a test set in order to select the best predicting model. Built models using PDA produced the best results in terms of overall accuracy on the test set. ANN, ET, RF and XGBoost models also provided good results, while SVM proved to be the worst

In Vitro Antibacterial and Antibiofilm Activity of Hungarian Honeys against Respiratory Tract Bacteria

Honey is a rich source of carbohydrates, while minor compounds such as amino acids and polyphenols contribute to its health-promoting effects. Honey is one of the oldest traditional remedies applied for microbial infections, due to its antibacterial, anti-inflammatory, and antioxidant properties. The aim of this study was to investigate the antibacterial and antibiofilm effects of Hungarian black locust, linden, and sunflower honeys against the most common biofilm-forming respiratory tract pathogens Haemophilus spp., Pseudomonas aeruginosa, and Streptococcus pneumoniae. The unifloral character of all three honey types was confirmed by melissopalynological analysis. The antibacterial activity of each honey sample against each bacterium strain was proven with agar well diffusion assay and thin layer chromatography—direct bioautography. Kinetics and mechanisms of antibacterial action were clarified with time-kill assay and membrane degradation study. The anti-biofilm activity was evidenced using crystal violet assay. In each assay, linden honey was the most effective, followed by sunflower and black locust honey. In addition, each honey sample had greater potential to suppress respiratory tract bacteria, compared to major sugar components. In conclusion, honey in general and linden honey in particular, can have a role in the treatment of respiratory tract infections caused by biofilm-forming bacteria

Recent trends in the analysis of honey constituents

Producción CientíficaThe main goal of this article is to present an overview of the analytical methodologies employed in recent years (2015–2021) to determine several honey constituents, and, specifically, those with health-promoting effects and nutritional value, like phenolic compounds, sugars, amino acids and proteins, vitamins, lipids, minerals, and organic acids. The review is structured according to the different families of compounds, and they will be discussed along with the main extraction and analytical techniques used for their determination. Phenolic compounds, sugars and amino acids have been the main compounds determined in honey. The analytical methods (sample treatment and determination techniques) are strongly dependent on the compound. Nevertheless, it can be concluded that high-performance liquid chromatography was predominantly selected for determining honey constituents; while, in relation to the sample treatment, the preferred option was a dilution of the honey with water or a buffer.Ministerio de Economía y Competitividad y el Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (project numbers RTA 2015-00013-C03-03

Composición físico-química y calidad microbiológica de la miel

La miel es un alimento que cuenta con una larga historia en la dieta de los seres humanos. Se ha utilizado en innumerables alimentos y bebidas, bien sea como agente edulcorante o como saborizaste. Desde la antigüedad se han reconocido sus valores nutritivos y terapéuticos como agente antiinflamatorio, antioxidante y antibacteriano. Su ingrediente más importante es la fracción hidrocarbonada, principalmente los monosacáridos fructosa y glucosa, Neri también contiene entro otros compuestos principales enzimas, aminoácidos, trazas de vitaminas del grupo B, minerales y compuestos fenólicos. La composición fisicoquímica de la miel permite evaluar su calidad mediante determinación de algunos parámetros como el contenido de agua (influye en su grado de conservación), azúcares (determinan su dulzor e influye en su higroscopicidad, viscosidad y baja actividad de agua), conductividad eléctrica (diferente según sea miel de néctar o de melada), acidez (relacionada con la fermentación y el envejecimiento), cenizas (discrimina origen botánico y color), color (varía según origen botánico), entre otros. La contaminación de la miel puede ocurrir a través De Fuentes primarias (polen, néctar floral, polvo, tierra, agua y abejas) o por fuentes secundarias, durante la extracción, procesado y almacenamiento. Ciertos microorganismos hacen que la miel fermente, acidificándola y modificando el sabor así como el aspecto de la misma. La contaminaciónpuede evitarse mediante la ejecución de unas buenas prácticas por parte del apicultor o por la implementación de programas de control de calidad. La calidad de la miel cuenta con distintas normativas, tanto nacionales como internacionales, que abordan las características de composición, así como indicaciones en cuanto a la higiene, los contaminantes y los métodos de análisis.<br /