113 research outputs found

    A systematic analysis on tomato powder quality prepared by four conductive drying technologies

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    Four pilot-scale conductive dryers, namely a vacuum drum dryer (VDD), a drum dryer (DD), an agitated thin ïŹlm dryer (ATFD) and a refractance window dryer (RWD), were used to dry tomato puree. Drying induced colour diïŹ€erences between the reconstituted puree and the original puree and strongly aïŹ€ected the volatile and non- volatile proïŹles of the powders. Principal component analysis (PCA) identiïŹed four separated groups corresponding to the diïŹ€erent drying methods, indicating that the drying methods caused signiïŹcant variance in compound proïŹles. Subsequently, pairwise comparison of diïŹ€erent dried powders was performed by partial least square discriminant analysis (PLS-DA). This resulted in a selection of discriminative volatile and non-volatile markers. RWD and VDD produced powders with high volatile markers that may be related to aroma retention. Conversely, DD dried products contained more non-volatile markers that can be related to taste perception. ATFD processed powders had a lower level of discriminant compounds. Industrial relevance: Tomato products are frequently thermally processed and dehydrated. However, processing negatively aïŹ€ects the sensory quality of tomato products. In this study, four conductive drying processes, i.e. vacuum drum drying (VDD), drum drying (DD), agitated thin ïŹlm drying (ATFD) and refractance window drying (RWD) were studied for being energy-eïŹƒcient drying methods, while suitable for mild (e.g. due to the reduced pressure) drying of pastes and slurries, such as tomato puree. The pilot-scale drying experiments and subsequent statistical analyses of results on quality markers contributed to unravel the impact of the diïŹ€erent conductive drying technologies on tomato powder quality. This study may be considered a starting point for selection of conductive drying technologies for the eïŹƒcient production of high quality tomato powders and other vegetable powders

    Controlled oleosome extraction to produce a plant-based mayonnaise-like emulsion using solely rapeseed seeds

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    Oleosomes are oil storage structures in seeds, consisting of triglycerides surrounded by a protein-phospholipid mixed monolayer. They can be extracted aqueously together with other seed components such as proteins and soluble fibers. The co-extracted biomolecules can affect the properties of the extracts. Nevertheless, it is possible to control the electrostatic and hydrophobic interactions between these biomolecules and oleosomes by adjusting the extraction conditions. Hence, our aim was to adjust the extraction conditions in order to recover a natural emulsion with a specific functionality: a plant-based mayonnaise-like product, derived solely from rapeseed seeds. By varying the pH of extraction, the droplet size was customized and by increasing the number of purification steps, the right amount of co-extracted material was removed. A combination of these conditions shifted the rheological properties of the obtained natural emulsion to a range similar to the benchmark mayonnaises. This work shows that it is feasible to produce a plant-based mayonnaise with an oil content ranging from 61.7 g/100g to 72.0 g/100g through a simple and continuous oleosome extraction process by controlling the interactions between oleosomes and co-extracted material.</p

    The effect of monovalent (Na+, K+) and divalent (Ca2+, Mg2+) cations on rapeseed oleosome (oil body) extraction and stability at pH 7

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    Oleosomes are storage vehicles of TAGs in plant seeds. They are protected with a phospholipid-protein monolayer and extracted with alkaline aqueous media; however, pH adjustment intensifies the extraction process. Therefore the aim of this work was to investigate the extraction mechanism of rapeseed oleosomes at pH 7 and at the presence of monovalent and divalent cations (Na+, K+, Mg2+, and Ca+2). The oleosome yield at pH 9.5 was 64 wt%, while the yield at pH 7 with H2O was just 43 wt%. The presence of cations at pH 7, significantly enhanced the yield, with K+ giving the highest yield (64 wt%). The cations affected the oleosome interface and their interactions. The presence of monovalent cations resulted in aggregation and minor coalescence, while divalent cations resulted in extensive coalescence. These results help to understand the interactions of oleosomes in their native matrix and design simple extraction processes at neutral conditions

    Characterisation and use of ÎČ-lactoglobulin fibrils for microencapsulation of lipophilic ingredients and oxidative stability thereof

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    There is a growing interest in using fibrils from food grade protein, e.g. ÎČ-lactoglobulin, as functional ingredients. In the present study, the functionality of fibrillar ÎČ-lactoglobulin from whey protein isolate (WPI) was compared to native WPI in terms of interfacial dilatational rheology and emulsifying activity at acidic conditions (pH 2.0 and 3.0). We report here for the first time data on microencapsulation of fish oil by spray-drying as well as oxidative stability of the oil in emulsions and microcapsules in dependence of WPI conformation. WPI fibrils exerted a significantly higher elasticity at the oil–water (o/w) interface and a better emulsifying activity at a fixed oil content compared to native WPI. Microencapsulation efficiency was also higher with fibrillar WPI (>95%) compared to native WPI (∌90%) at pH 2.0 and a total oil and protein content of 40% and 2.2%, respectively, in the final powder. The oxidative deterioration was lower in emulsions and microcapsules prepared with fibrillar than with native WPI. This was attributed to improved interfacial barrier properties provided by fibrils and antioxidative effects of coexisting unconverted monomers, particularly hydrophilic peptides

    TRY plant trait database – enhanced coverage and open access

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    Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    TRY plant trait database – enhanced coverage and open access

    Get PDF
    Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Rest of authors: Decky Junaedi, Robert R. Junker, Eric Justes, Richard Kabzems, Jeffrey Kane, Zdenek Kaplan, Teja Kattenborn, Lyudmila Kavelenova, Elizabeth Kearsley, Anne Kempel, Tanaka Kenzo, Andrew Kerkhoff, Mohammed I. Khalil, Nicole L. Kinlock, Wilm Daniel Kissling, Kaoru Kitajima, Thomas Kitzberger, Rasmus KjĂžller, Tamir Klein, Michael Kleyer, Jitka KlimeĆĄovĂĄ, Joice Klipel, Brian Kloeppel, Stefan Klotz, Johannes M. H. Knops, Takashi Kohyama, Fumito Koike, Johannes Kollmann, Benjamin Komac, Kimberly Komatsu, Christian König, Nathan J. B. Kraft, Koen Kramer, Holger Kreft, Ingolf KĂŒhn, Dushan Kumarathunge, Jonas Kuppler, Hiroko Kurokawa, Yoko Kurosawa, Shem Kuyah, Jean-Paul Laclau, Benoit Lafleur, Erik Lallai, Eric Lamb, Andrea Lamprecht, Daniel J. Larkin, Daniel Laughlin, Yoann Le Bagousse-Pinguet, Guerric le Maire, Peter C. le Roux, Elizabeth le Roux, Tali Lee, Frederic Lens, Simon L. Lewis, Barbara Lhotsky, Yuanzhi Li, Xine Li, Jeremy W. Lichstein, Mario Liebergesell, Jun Ying Lim, Yan-Shih Lin, Juan Carlos Linares, Chunjiang Liu, Daijun Liu, Udayangani Liu, Stuart Livingstone, Joan LlusiĂ , Madelon Lohbeck, Álvaro LĂłpez-GarcĂ­a, Gabriela Lopez-Gonzalez, Zdeƈka LososovĂĄ, FrĂ©dĂ©rique Louault, BalĂĄzs A. LukĂĄcs, Petr LukeĆĄ, Yunjian Luo, Michele Lussu, Siyan Ma, Camilla Maciel Rabelo Pereira, Michelle Mack, Vincent Maire, Annikki MĂ€kelĂ€, Harri MĂ€kinen, Ana Claudia Mendes Malhado, Azim Mallik, Peter Manning, Stefano Manzoni, Zuleica Marchetti, Luca Marchino, Vinicius Marcilio-Silva, Eric Marcon, Michela Marignani, Lars Markesteijn, Adam Martin, Cristina MartĂ­nez-Garza, Jordi MartĂ­nez-Vilalta, Tereza MaĆĄkovĂĄ, Kelly Mason, Norman Mason, Tara Joy Massad, Jacynthe Masse, Itay Mayrose, James McCarthy, M. Luke McCormack, Katherine McCulloh, Ian R. McFadden, Brian J. McGill, Mara Y. McPartland, Juliana S. Medeiros, Belinda Medlyn, Pierre Meerts, Zia Mehrabi, Patrick Meir, Felipe P. L. Melo, Maurizio Mencuccini, CĂ©line Meredieu, Julie Messier, Ilona MĂ©szĂĄros, Juha Metsaranta, Sean T. Michaletz, Chrysanthi Michelaki, Svetlana Migalina, Ruben Milla, Jesse E. D. Miller, Vanessa Minden, Ray Ming, Karel Mokany, Angela T. Moles, Attila MolnĂĄr V, Jane Molofsky, Martin Molz, Rebecca A. Montgomery, Arnaud Monty, Lenka MoravcovĂĄ, Alvaro Moreno-MartĂ­nez, Marco Moretti, Akira S. Mori, Shigeta Mori, Dave Morris, Jane Morrison, Ladislav Mucina, Sandra Mueller, Christopher D. Muir, Sandra Cristina MĂŒller, François Munoz, Isla H. Myers-Smith, Randall W. Myster, Masahiro Nagano, Shawna Naidu, Ayyappan Narayanan, Balachandran Natesan, Luka Negoita, Andrew S. Nelson, Eike Lena Neuschulz, Jian Ni, Georg Niedrist, Jhon Nieto, Ülo Niinemets, Rachael Nolan, Henning Nottebrock, Yann Nouvellon, Alexander Novakovskiy, The Nutrient Network, Kristin Odden Nystuen, Anthony O'Grady, Kevin O'Hara, Andrew O'Reilly-Nugent, Simon Oakley, Walter Oberhuber, Toshiyuki Ohtsuka, Ricardo Oliveira, Kinga Öllerer, Mark E. Olson, Vladimir Onipchenko, Yusuke Onoda, Renske E. Onstein, Jenny C. Ordonez, Noriyuki Osada, Ivika Ostonen, Gianluigi Ottaviani, Sarah Otto, Gerhard E. Overbeck, Wim A. Ozinga, Anna T. Pahl, C. E. Timothy Paine, Robin J. Pakeman, Aristotelis C. Papageorgiou, Evgeniya Parfionova, Meelis PĂ€rtel, Marco Patacca, Susana Paula, Juraj Paule, Harald Pauli, Juli G. Pausas, Begoña Peco, Josep Penuelas, Antonio Perea, Pablo Luis Peri, Ana Carolina Petisco-Souza, Alessandro Petraglia, Any Mary Petritan, Oliver L. Phillips, Simon Pierce, ValĂ©rio D. Pillar, Jan Pisek, Alexandr Pomogaybin, Hendrik Poorter, Angelika Portsmuth, Peter Poschlod, Catherine Potvin, Devon Pounds, A. Shafer Powell, Sally A. Power, Andreas Prinzing, Giacomo Puglielli, Petr PyĆĄek, Valerie Raevel, Anja Rammig, Johannes Ransijn, Courtenay A. Ray, Peter B. Reich, Markus Reichstein, Douglas E. B. Reid, Maxime RĂ©jou-MĂ©chain, Victor Resco de Dios, Sabina Ribeiro, Sarah Richardson, Kersti Riibak, Matthias C. Rillig, Fiamma Riviera, Elisabeth M. R. Robert, Scott Roberts, Bjorn Robroek, Adam Roddy, Arthur Vinicius Rodrigues, Alistair Rogers, Emily Rollinson, Victor Rolo, Christine Römermann, Dina Ronzhina, Christiane Roscher, Julieta A. Rosell, Milena Fermina Rosenfield, Christian Rossi, David B. Roy, Samuel Royer-Tardif, Nadja RĂŒger, Ricardo Ruiz-Peinado, Sabine B. Rumpf, Graciela M. Rusch, Masahiro Ryo, Lawren Sack, Angela Saldaña, Beatriz Salgado-Negret, Roberto Salguero-Gomez, Ignacio Santa-Regina, Ana Carolina Santacruz-GarcĂ­a, Joaquim Santos, Jordi Sardans, Brandon Schamp, Michael Scherer-Lorenzen, Matthias Schleuning, Bernhard Schmid, Marco Schmidt, Sylvain Schmitt, Julio V. Schneider, Simon D. Schowanek, Julian Schrader, Franziska Schrodt, Bernhard Schuldt, Frank Schurr, Galia Selaya Garvizu, Marina Semchenko, Colleen Seymour, Julia C. Sfair, Joanne M. Sharpe, Christine S. Sheppard, Serge Sheremetiev, Satomi Shiodera, Bill Shipley, Tanvir Ahmed Shovon, Alrun SiebenkĂ€s, Carlos Sierra, Vasco Silva, Mateus Silva, Tommaso Sitzia, Henrik Sjöman, Martijn Slot, Nicholas G. Smith, Darwin Sodhi, Pamela Soltis, Douglas Soltis, Ben Somers, GrĂ©gory Sonnier, Mia Vedel SĂžrensen, Enio Egon Sosinski Jr, Nadejda A. Soudzilovskaia, Alexandre F. Souza, Marko Spasojevic, Marta Gaia Sperandii, Amanda B. Stan, James Stegen, Klaus Steinbauer, Jörg G. Stephan, Frank Sterck, Dejan B. Stojanovic, Tanya Strydom, Maria Laura Suarez, Jens-Christian Svenning, Ivana SvitkovĂĄ, Marek Svitok, Miroslav Svoboda, Emily Swaine, Nathan Swenson, Marcelo Tabarelli, Kentaro Takagi, Ulrike Tappeiner, RubĂ©n Tarifa, Simon Tauugourdeau, Cagatay Tavsanoglu, Mariska te Beest, Leho Tedersoo, Nelson Thiffault, Dominik Thom, Evert Thomas, Ken Thompson, Peter E. Thornton, Wilfried Thuiller, LubomĂ­r TichĂœ, David Tissue, Mark G. Tjoelker, David Yue Phin Tng, Joseph Tobias, PĂ©ter Török, Tonantzin Tarin, JosĂ© M. Torres-Ruiz, BĂ©la TĂłthmĂ©rĂ©sz, Martina Treurnicht, Valeria Trivellone, Franck Trolliet, Volodymyr Trotsiuk, James L. Tsakalos, Ioannis Tsiripidis, Niklas Tysklind, Toru Umehara, Vladimir Usoltsev, Matthew Vadeboncoeur, Jamil Vaezi, Fernando Valladares, Jana Vamosi, Peter M. van Bodegom, Michiel van Breugel, Elisa Van Cleemput, Martine van de Weg, Stephni van der Merwe, Fons van der Plas, Masha T. van der Sande, Mark van Kleunen, Koenraad Van Meerbeek, Mark Vanderwel, Kim AndrĂ© Vanselow, Angelica VĂ„rhammar, Laura Varone, Maribel Yesenia Vasquez Valderrama, Kiril Vassilev, Mark Vellend, Erik J. Veneklaas, Hans Verbeeck, Kris Verheyen, Alexander Vibrans, Ima Vieira, Jaime VillacĂ­s, Cyrille Violle, Pandi Vivek, Katrin Wagner, Matthew Waldram, Anthony Waldron, Anthony P. Walker, Martyn Waller, Gabriel Walther, Han Wang, Feng Wang, Weiqi Wang, Harry Watkins, James Watkins, Ulrich Weber, James T. Weedon, Liping Wei, Patrick Weigelt, Evan Weiher, Aidan W. Wells, Camilla Wellstein, Elizabeth Wenk, Mark Westoby, Alana Westwood, Philip John White, Mark Whitten, Mathew Williams, Daniel E. Winkler, Klaus Winter, Chevonne Womack, Ian J. Wright, S. Joseph Wright, Justin Wright, Bruno X. Pinho, Fabiano Ximenes, Toshihiro Yamada, Keiko Yamaji, Ruth Yanai, Nikolay Yankov, Benjamin Yguel, KĂĄtia Janaina Zanini, Amy E. Zanne, David ZelenĂœ, Yun-Peng Zhao, Jingming Zheng, Ji Zheng, Kasia ZiemiƄska, Chad R. Zirbel, Georg Zizka, IriĂ© Casimir Zo-Bi, Gerhard Zotz, Christian Wirth.Max Planck Institute for Biogeochemistry; Max Planck Society; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; International Programme of Biodiversity Science (DIVERSITAS); International Geosphere-Biosphere Programme (IGBP); Future Earth; French Foundation for Biodiversity Research (FRB); GIS ‘Climat, Environnement et SociĂ©tĂ©'.http://wileyonlinelibrary.com/journal/gcbhj2021Plant Production and Soil Scienc

    Model development for conductive thin film drying processes

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    A heat-transfer governed model is proposed to describe drying in a lab-scale conductive thin film dryer, which was designed to investigate the drying kinetics relevant to drum drying. The model calculations were compared to experimental data from drying experiments with maltodextrin DE12 and potato starch, considering the three distinct periods (heating, boiling and conductive drying) of the lab-scale process. The model uses measured temperatures and evaporation rate during the boiling period as input to calculate the decrease in moisture content during the drying process. Model calculations were evaluated by determining the root-mean-square-error (RMSE) values. The RMSE were very small (2∙K)/W) compared to maltodextrin (~0.0002 (m2∙K)/W). This reflects the formation of larger vapour bubbles in the boiling period impeding the heat transfer for starch films. Subsequently, the model was modified to describe a pilot-scale drum drying process for maltodextrin suspensions. The initial heat transfer coefficient for drum drying of maltodextrin was obtained from the lab-scale experiments. The simulations indicated residual moisture contents and optimal drying times for different drying conditions.</p
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