Influence of drying process and particle size of persimmon fibre on its physicochemical, antioxidant, hydration and emulsifying properties

[EN] Persimmon, given its current surplus production, could be an alternative source for the extraction of certain interesting ingredients for the food industry and human health, such as fibre. Thus, the aim of this study was to analyse the influence of hot air and freeze-drying, as well as the particle size of fibre extracted from persimmon peels or pulp on their physicochemical, antioxidant, hydration and emulsifying properties, compared to commercial fibres (from peach, lemon, orange and apple). The results showed that both freeze-dried persimmon pulp and freeze-dried peel had better hydration properties and oil holding capacity than other fibres analysed, although the swelling capacity was higher for lemon fibre. Freeze-dried persimmon peel fibre showed higher values of emulsion stability than commercial fibres. Finally, the antioxidant activity of the smallest sized persimmon peel fibre obtained by freeze-drying was higher than that for lemon, orange and peach fibre.The authors acknowledge the support of the Universtitat Politecnica de Valencia and certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.Martínez-Las Heras, R.; Landines, E.; Heredia Gutiérrez, AB.; Castelló Gómez, ML.; Andrés Grau, AM. (2017). Influence of drying process and particle size of persimmon fibre on its physicochemical, antioxidant, hydration and emulsifying properties. Journal of Food Science and Technology. 54(9):1-11. doi:10.1007/s13197-017-2728-zS111549Abdul-Hamid A, Luan YS (2000) Functional properties of dietary fibre prepared from defatted rice bran. Food Chem 68:15–19Adams MR, Moss MO (1997) Microbiología de los alimentos. 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Chemical, functional, and structural properties of spent coffee grounds and coffee silverskin

Spent coffee grounds (SCG) and coffee silverskin (CS) represent a great pollution hazard if discharged into the environment. Taking this fact into account, the purpose of this study was to evaluate the chemical composition, functional properties, and structural characteristics of these agro-industrial residues in order to identify the characteristics that allow their reutilization in industrial processes. According to the results, SCG and CS are both of lignocellulosic nature. Sugars polymerized to their cellulose and hemicellulose fractions correspond to 51.5 and 40.45 % w/w, respectively; however, the hemicellulose sugars and their composition significantly differ from one residue to another. SCG and CS particles differ in terms of morphology and crystallinity, but both materials have very low porosity and similar melting point. In terms of functional properties, SCG and CS present good water and oil holding capacities, emulsion activity and stability, and antioxidant potential, being therefore great candidates for use on food and pharmaceutical fields.The authors acknowledge the financial support of the Science and Technology Foundation of Portugal (FCT) through the grant SFRH/BD/80948/2011 and the Strategic Project PEst-OE/EQB/LA0023/2013. The authors also thank the Project "BioInd - Biotechnology and Bioengineering for improved Industrial and Agro-Food processes", REF. NORTE-07-0124-FEDER-000028 co-funded by the Programa Operacional Regional do Norte (ON.2-O Novo Norte), QREN, FEDER. Thanks are also given to Prof. Jose J.M. Orfao, from the Department of Chemical Engineering, Universidade do Porto (Portugal), for his assistance with the porosity analyses

The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis

<p>Abstract</p> <p>Background</p> <p>The final article in a series of three publications examining the global distribution of 41 dominant vector species (DVS) of malaria is presented here. The first publication examined the DVS from the Americas, with the second covering those species present in Africa, Europe and the Middle East. Here we discuss the 19 DVS of the Asian-Pacific region. This region experiences a high diversity of vector species, many occurring sympatrically, which, combined with the occurrence of a high number of species complexes and suspected species complexes, and behavioural plasticity of many of these major vectors, adds a level of entomological complexity not comparable elsewhere globally. To try and untangle the intricacy of the vectors of this region and to increase the effectiveness of vector control interventions, an understanding of the contemporary distribution of each species, combined with a synthesis of the current knowledge of their behaviour and ecology is needed.</p> <p>Results</p> <p>Expert opinion (EO) range maps, created with the most up-to-date expert knowledge of each DVS distribution, were combined with a contemporary database of occurrence data and a suite of open access, environmental and climatic variables. Using the Boosted Regression Tree (BRT) modelling method, distribution maps of each DVS were produced. The occurrence data were abstracted from the formal, published literature, plus other relevant sources, resulting in the collation of DVS occurrence at 10116 locations across 31 countries, of which 8853 were successfully geo-referenced and 7430 were resolved to spatial areas that could be included in the BRT model. A detailed summary of the information on the bionomics of each species and species complex is also presented.</p> <p>Conclusions</p> <p>This article concludes a project aimed to establish the contemporary global distribution of the DVS of malaria. The three articles produced are intended as a detailed reference for scientists continuing research into the aspects of taxonomy, biology and ecology relevant to species-specific vector control. This research is particularly relevant to help unravel the complicated taxonomic status, ecology and epidemiology of the vectors of the Asia-Pacific region. All the occurrence data, predictive maps and EO-shape files generated during the production of these publications will be made available in the public domain. We hope that this will encourage data sharing to improve future iterations of the distribution maps.</p

Biocontrol Potential of Forest Tree Endophytes

Peer reviewe

Rule extraction for classification of acoustic emission signals using Ant Colony Optimisation

Ant Colony Optimization (ACO) is used to obtain rules that can classify the data into pre-defined classes. It can be used to classify acoustic emission (AE) signals to their respective sources. ACO based technique has an advantage over conventional statistical techniques like maximum likelihood estimate, nearest neighbor classifier, etc., because they are distribution free, i.e., no knowledge is required about the distribution of data. AE test is carried Out using pulse, pencil and spark signal source on the surface of solid steel block. The signal parameters are measured using AET 5000 system. Classification of AE signal is done using Ant Colony Optimization, and the simplicity of the rules generated is emphasized

Tool wear monitoring using ant behaviour

In this paper we show the applicability of Ant Colony Optimisation (ACO) techniques for pattern classification problem that arises in tool wear monitoring. In an earlier study, artificial neural networks and genetic programming have been successfully applied to tool wear monitoring problem. ACO is a recent addition to evolutionary computation technique that has gained attention for its ability to extract the underlying data relationships and express them in form of simple rules. Rules are extracted for data classification using training set of data points. These rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in ACO based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The classification accuracy obtained in ACO based approach is as good as obtained in other biologically inspired techniques

ANTIFUNGAL EFFICIENCY OF COPPER OXYCHLORIDE-CONJUGATED SILVER NANOPARTICLES AGAINST COLLETOTRICHUM GLOEOSPORIOIDES WHICH CAUSES ANTHRACNOSE DISEASE

Objectives: Anthracnose disease is caused by Colletotrichum gloeosporioides, affecting most of the fruit and vegetable plants. The present study is aimed to synthesize silver nanoparticles (AgNPs) using neem extract and conjugate then with fungicide to check the antifungal activity against anthracnose disease. Methods: In the current study, we have synthesized copper oxychloride-conjugated AgNPs (COC-AgNPs) by a biological method using neem extract and have tested their effectiveness against C. gloeosporioides. The COC-AgNPs were characterized by UV–visible spectroscopy, fourier-transform infrared, scanning electron microscopy, and X-ray diffraction analysis, and in vitro antifungal activity was investigated. Results: The shape of COC-AgNPs was found to be spherical with an average particle size of 21–25 nm. The fungicide-conjugated AgNPs exhibited highest growth inhibition of C. gloeosporioides (~187%) as compared to fungicide copper oxychloride. Conclusion: These results indicate that the COC-AgNPs could be effectively used to control anthracnose disease in mango and in other crops. These COC-AgNPs can drastically reduce the amount of fungicide currently used which will reduce the environmental pollution caused by the fungicide

Acoustic Emission Signal Classification Using Fuzzy C-means Clustering

Fuzzy C-means (FCM) clustering is used to classify the acoustic emission (AE) signal to different sources of signals. FCM has the ability to discover the cluster among the data, even when the boundaries between the subgroup are overlapping, FCM based technique has an advantage over conventional statistical technique like maximum likelihood estimate, nearest neighbor classifier etc, because they are distribution free (i.e.) no knowledge is required about the distribution of data. AE test is carried out using pulse, pencil and spark signal source on the surface of solid steel block. Four parameters-event duration $(E_d)$, peak amplitude $(P_a)$, rise time $(R_t)$ and ring down count $(R_d)$ are measured using AET 5000 system. These data's are used to train and validate the FCM based classification