996 resultados para Honey -- Analysis
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Stingless bee honey samples were evaluated by sensory descriptive analysis using free choice profile methodology. Appearance, flavor, and aroma were described and the data were treated with Generalized Procrustes Analysis. Individual descriptive terms ranged from 8 to 20. Plotting the samples in a bidimensional plan indicated that appearance attributes (color and viscosity) and sweet, sour and acid flavor were strongly correlated with x axis (Dimension 1) while coconut, wood, acid, sour, and sweet flavor aroma attributes were correlated with y axis (Dimension 2). The affective test was also performed and with the exception of the Melipona scutellaris honey, all the other samples showed good acceptance. Honeys that were described as sweeter and less acid were preferred by nontrained assessors, indicating that the regular consumer recognizes honey produced by Apis mellifera bee as a standard.
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This work presents a RP-HPLC method for the simultaneous quantification of free amino acids and biogenic amines in liquid food matrices and the results of the application to honey and wine samples obtained from different production processes and geographic origins. The developed methodology is based on a pre-column derivatization with o-phthaldialdehyde carried out in the sample injection loop. The compounds were separated in a Nova-Pack RP-C18 column (150 mm × 3.9 mm, 4 μm) at 35 °C. The mobile phase used was a mixture of phase A: 10 mM sodium phosphate buffer (pH 7.3), methanol and tetrahydrofuran (91:8:1); and phase B: methanol and phosphate buffer (80:20), with a flow rate of 1.0 ml/min. Fluorescence detection was used at an excitation wavelength of 335 nm and an emission wavelength of 440 nm. The separation and quantification of 19 amino acids and 6 amines was carried out in a single run as their OPA/MCE derivatives elute within 80 min, ensuring a reproducible quantification. The method showed to be adequate for the purpose, with an average RSD of 2% for the different amino acids; detection limits varying between 0.71 mg/l (Asn) and 8.26 mg/l (Lys) and recovery rates between 63.0% (Cad) and 98.0% (Asp). The amino acids present at the highest concentration in honey and wine samples were phenylalanine and arginine, respectively. Only residual levels of biogenic amines were detected in the analysed samples.
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An analytical procedure using supercritical fluid extraction (SFE) and capillary gas chromatography with electron-capture detection was developed to determine simultaneously residues of different pesticides (organochlorine, organophosphorus, organonitrogen and pyrethroid) in honey samples. Fortification experiments were conducted to test conventional extraction (liquid-liquid) and optimize the extraction procedure in SFE by varying the CO2-modifier, temperature, extraction time and pressure. Best efficiency was achieved at 400 bar using acetonitrile as modifier at 90 degreesC. For the clean-up step, Florisil cartridges were used for both methods LLE and SFE. Recoveries for majority of pesticides from fortified samples of honey at fortification level of 0.01-0.10 mg/kg ranged 75-94% from both methods. Limits of detection found were less than 0.01 mg/kg for ECD and confirmation of pesticide identity was performed by gas chromatography-mass spectrometry in selected-ion monitoring mode. The multiresidue methods in real honey samples were applied and the results of developed methods were compared. (C) 2004 Elsevier B.V. All rights reserved.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In recent years, studies based on isoenzymatic patterns of geographic variation have revealed that what is usually called the Africanized honey bee does not constitute a single population. Instead, several local populations exist with various degrees of admixture with European honey bees. In this paper, we evaluated new data on morphometric patterns of Africanized honey bees collected at 42 localities in Brazil, using univariate and multivariate (canonical) trend surface and spatial autocorrelation analyses. The clinal patterns of variation found for genetically independent characters (wing size characters and some wing venation angles) are concordant with previous studies of malate dehydrogenase (MDH) allelic frequencies and support the hypothesis that larger honey bees in southern and southeastern Brazil originated by racial admixture in the initial phases of African honey bee colonization. Geographic variation patterns of Africanized honey bee populations reflect a demic diffusion process in which European genes were gradually lost because of the higher fitness of the African gene pool in Neotropical environmental conditions.
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The purpose of this study was to evaluate the antioxidant activity of honey from different entomological sources which were harvested in the dry season of 2008-2009 from distinct mesoregions of the State of Alagoas in the North East of Brazil. Honey produced by five different species of bees, even from the same region and season, showed a statistically significant difference (p <0.05) in the content of phenols, flavonoids and antioxidants, with higher levels of these compounds found in honey produced by Plebeia spp. and A. mellifera. Honey from stingless bees was quite different from that of A. mellifera, especially from the Plebeia spp. A dendrogram of the five species of bees showed the formation of 3 groups, one being formed by Apis mellifera, one by the genus Melipona (M. subnitida, M. quadrifasciata and M. scutellaris) and another formed by Plebeia spp.
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Abstract Background The ongoing efforts to sequence the honey bee genome require additional initiatives to define its transcriptome. Towards this end, we employed the Open Reading frame ESTs (ORESTES) strategy to generate profiles for the life cycle of Apis mellifera workers. Results Of the 5,021 ORESTES, 35.2% matched with previously deposited Apis ESTs. The analysis of the remaining sequences defined a set of putative orthologs whose majority had their best-match hits with Anopheles and Drosophila genes. CAP3 assembly of the Apis ORESTES with the already existing 15,500 Apis ESTs generated 3,408 contigs. BLASTX comparison of these contigs with protein sets of organisms representing distinct phylogenetic clades revealed a total of 1,629 contigs that Apis mellifera shares with different taxa. Most (41%) represent genes that are in common to all taxa, another 21% are shared between metazoans (Bilateria), and 16% are shared only within the Insecta clade. A set of 23 putative genes presented a best match with human genes, many of which encode factors related to cell signaling/signal transduction. 1,779 contigs (52%) did not match any known sequence. Applying a correction factor deduced from a parallel analysis performed with Drosophila melanogaster ORESTES, we estimate that approximately half of these no-match ESTs contigs (22%) should represent Apis-specific genes. Conclusions The versatile and cost-efficient ORESTES approach produced minilibraries for honey bee life cycle stages. Such information on central gene regions contributes to genome annotation and also lends itself to cross-transcriptome comparisons to reveal evolutionary trends in insect genomes.
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Date of Acceptance: 20/12/2015 This work was funded by BBSRC-LINK grant # BB/J01009X/1 and Vita Europe Ltd. We are grateful to the Scottish Beekeepers Association, especially Mr Phil McAnespie in supporting this work at its inception. We acknowledge partial funding from a Genesis Faraday SPARK Award, part of a Scottish Government SEEKIT project for the early part of this work. We are grateful to Prof David Evans for his advice on Varroa destructor viruses.
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We describe an investigation into how Massey University’s Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University’s pollen reference collection (2,890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set.We additionally work through a real world case study where we assess the ability of the system to determine the pollen make-up of samples of New Zealand honey. In addition to the Classifynder’s native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples.
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Honey Gold mango is a new Australian variety owned by a Queensland company, and in high demand because of very good flavour and appearance. It develops under skin browning (USB) when grown in hot areas. It appears after packing and the fruit need to be re-sorted at the markets to remove affected fruit. Production and postharvest treatments will be developed to reduce USB and increase profitability. Other production and harvest factors causing quality loss will be also be identified through a commercial downgrade analysis program in the packhouse. Grower training will reduce downgrades and improve the percentage of fruit in premium grade.
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Report of field observations April 2007 to September 2011
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Reproductive isolation between closely related species is often incomplete. The Western honey bee, Apis mellifera, and the Eastern hive bee, A. cerana have been allopatric for millions of years, but are nonetheless similar in morphology and behaviour. During the last century the two species were brought into contact anthropogenically, providing potential opportunities for interspecific matings. Hybrids between A. mellifera and A. cerana are inviable, so natural interspecific matings are of concern because they may reduce the viability of A. cerana and A. mellifera populations – two of the world's most important pollinators. We examined the mating behaviour of A. mellifera and A. cerana queens and drones from Caoba Basin, China and Cairns, Australia. Drone mating flight times overlap in both areas. Analysis of the spermathecal contents of queens with species-specific genetic markers indicated that in Caoba Basin, 14% of A. mellifera queens mated with at least one A. cerana male, but we detected no A. cerana queens that had mated with A. mellifera males. Similarly, in Cairns, no A. cerana queens carried A. mellifera sperm, but one third of A. mellifera queens had mated with at least one A. cerana male. No hybrid embryos were detected in eggs laid by interspecifically-mated A. mellifera queens in either location. However A. mellifera queens artificially inseminated with A. cerana sperm produced inviable hybrid eggs, or unfertilised drones. This suggests that reproductive interference will impact the viability of honey bee populations wherever A. cerana and A. mellifera are in contact. This article is protected by copyright. All rights reserved.
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A swarm is a temporary structure formed when several thousand honey bees leave their hive and settle on some object such as the branch of a tree. They remain in this position until a suitable site for a new home is located by the scout bees. A continuum model based on heat conduction and heat generation is used to predict temperature profiles in swarms. Since internal convection is neglected, the model is applicable only at low values of the ambient temperature T-a. Guided by the experimental observations of Heinrich (1981a-c, J. Exp. Biol. 91, 25-55; Science 212, 565-566; Sci. Am. 244, 147-160), the analysis is carried out mainly for non-spherical swarms. The effective thermal conductivity is estimated using the data of Heinrich (1981a, J. Exp. Biol. 91, 25-55) for dead bees. For T-a = 5 and 9 degrees C, results based on a modified version of the heat generation function due to Southwick (1991, The Behaviour and Physiology of Bees, PP 28-47. C.A.B. International, London) are in reasonable agreement with measurements. Results obtained with the heat generation function of Myerscough (1993, J. Theor. Biol. 162, 381-393) are qualitatively similar to those obtained with Southwick's function, but the error is more in the former case. The results suggest that the bees near the periphery generate more heat than those near the core, in accord with the conjecture of Heinrich (1981c, Sci. Am. 244, 147-160). On the other hand, for T-a = 5 degrees C, the heat generation function of Omholt and Lonvik (1986, J. Theor. Biol. 120, 447-456) leads to a trivial steady state where the entire swarm is at the ambient temperature. Therefore an acceptable heat generation function must result in a steady state which is both non-trivial and stable with respect to small perturbations. Omholt and Lonvik's function satisfies the first requirement, but not the second. For T-a = 15 degrees C, there is a considerable difference between predicted and measured values, probably due to the neglect of internal convection in the model.