Carlos Alberto Fuenmayor

Encapsulation of volatiles in nanofibrous polysaccharide membranes for humidity-triggered release

A single-step electrospinning process will be applied to a blend of edible carbohydrate polymers (pullulan and β-cyclodextrin) to encapsulate bioactive aroma compounds and allow a humidity-triggered release. The encapsulation is rapid and efficient and the final product is an active nanofibrous membrane that can be directly used for food or active packaging applications. The membrane hosts small and homogeneously dispersed crystals of cyclodextrin-aroma complexes which are formed during the electrospinning. With this type of structure, the release of aroma compound is negligible at ambient conditions (23 °C and 55% UR) even at high temperature (up to 230 °C), and it occurs beyond a given relative humidity threshold (90%), useful for food packaging applications. The mass fraction of free aroma released is directly related to the water activity of the system, namely, φ=aW(n)/(aW(n)+Kapp) explaining the observed key role played by the relative humidity on the release of the aroma compounds.

Polymer Composites Containing Gated Mesoporous Materials for On-Command Controlled Release

Polyamidic nanofibrous membranes containing gated silica mesoporous particles, acting as carriers, are described as novel hybrid composite materials for encapsulation and on-command delivery of garlic extracts. The carrier system consists of MCM-41 solids functionalized in the outer surface, with linear polyamines (solid P1) and with hydrolyzed starch (solid P2), both acting as molecular gates. Those particles were adsorbed on electospun nylon-6 nanofibrous membranes yielding to composite materials M1 and M2. FE-SEM analysis confirmed the presence of particles incorporated on the nylon nanofibers. The release of the entrapped molecules (garlic extract) from the P1, P2, M1, and M2 materials was evaluated using cyclic voltammetry measurements. Electrochemical studies showed that at acidic pH P1 and M1 were unable to release their entrapped cargo (closed gate), whereas at neutral pH both materials release their loading (open gate). Dealing with P2 and M2 materials, in the absence of pancreatin a negligible release is observed (closed gate), whereas in the presence of enzyme the load is freely to diffuse to the solution. These newly developed composite nanomaterials, provide a homogeneous easy-to-handle system with controlled delivery and bioactive-protective features, having potential applications on pharmacology, medical and engineering fields.

Honey of Colombian Stingless Bees: Nutritional Characteristics and Physicochemical Quality Indicators

The geographic location of Colombia and its mega-biodiversity have been identified as advantages for meliponiculture. This study analyzed pot-honey samples from different genera native from different regions of Colombia. The number of analyzed honey samples varies according to the genus and the species (Frieseomelitta sp., Melipona compressipes, Melipona favosa, Melipona eburnea, Melipona sp., Nannotrigona testaceicornis, Nannotrigona sp., Paratrigona sp., Partamona sp., Plebeia sp., Scaptotrigona limae, Scaptotrigona sp., Tetragona sp., and Tetragonisca angustula). The largest number of samples corresponds to the genera Melipona and Tetragonisca because there is ample breeding of those species. Physicochemical analyses performed were: moisture and carbohydrate (glucose, fructose and disaccharides), ash and mineral contents, color, pH, free acidity, diastase activity, HMF, conductivity and specific rotation. This chapter summarizes existing information regarding the physicochemical properties, nutritional information and quality of Colombian pot-honey. The ranges for physicochemical features of Melipona genus were: moisture (24.8–27.6 g/100 g), fructose (36.7–39.3 g/100 g), glucose (30.9–38.5 g/100 g), disaccharides (3.1–6 g/100 g), ash (0.01–0.20 g/100 g), color (34.4–80 mm Pfund) and the ranges for physicochemical features of T. angustula were as follows: moisture (22–26.6 g/100 g), fructose (24.7–35.6 g/100 g), glucose (17.1–29.9 g/100 g), disaccharides (1.8–6.4 g/100 g), ash (0.21–0.28 g/100 g), color (49–70 mm Pfund), pH (4.2–4.5), free acidity (39.2–62.1 meq/kg), diastase activity (16.7–25.9 DN), HMF (1.3–3.3 mg/kg), conductivity (601–715 μS/cm), and specific rotation (1.3–3.9). It is necessary to continue the characterization process that leads to a better knowledge of this valuable product, and the establishment of laws that regulate falsification and adulteration.

An Electronic Nose and Physicochemical Analysis to Differentiate Colombian Stingless Bee Pot-Honey

Fifty-five samples of honey from Colombian stingless bees Melipona, Tetragona, Melipona compressipes, Melipona favosa, and Melipona eburnea were analyzed with an “electronic nose.” The electronic nose instrument, equipped with ten metal oxide semiconductor (MOS) sensors, was used to generate a pattern of the volatile compounds in honey samples. Physicochemical analysis such as moisture and sugars (glucose, fructose, and disaccharides) characterized the honey. Data were evaluated by partial least squares-discriminant analysis (PLS-DA) and found adequate to guarantee the quality and authenticity of bee origin of honey.

Analysis of Multifloral Bee Pollen Pellets by Advanced Digital Imaging Applied to Functional Food Ingredients

Bee pollen is a hive product, resulting from floral pollen agglutination by worker bees and it is characterized by its excellent bioactive and nutritional composition. Currently, research is focused on bee pollen applications on food industry, because this product has been considered an excellent source of compounds for human nutrition. It is also important in some industries, where color and particle size are important characteristics for production. Due to the granular nature of bee pollen, conventional colorimetry does not allow describing color correctly; thus, digital image analysis is a better alternative. This technique could also allow classifying bee pollen according to its appearance beyond the color. Consequently, the aim of this work was to develop a novel methodology for image data processing to classify bee pollen as ingredient in food industry. Seven color groups in samples were established regarding harvest month and particle size. It was possible to calculate the percentage of each color group in all samples. This methodology also allowed selecting each fraction for different applications in food industry using colorimetry, granulometry and the relationship between both of them.