Mitigating aflatoxin B1 in high-moisture sorghum silage: Aspergillus flavus growth and aflatoxin B1 prediction

Aspergillus flavus (A. flavus), a frequent contaminant in silage, is a significant producer of aflatoxins, notably the potent carcinogen aflatoxin B1. This contaminant poses a potential risk during the initial aerobic phase of ensiling. The present work studied the impact of temperature on A. flavus growth and aflatoxin B1 production in laboratory-scale sorghum silos during the initial aerobic phase. Growth curves of A. flavus were generated at various temperatures and modeled with the Gompertz model. Results indicated that the optimal temperature range for the maximum growth rate in sorghum mini-silos is between 25 and 30°C. Mold biomass and aflatoxin B1 levels were quantified using qPCR and HPLC, respectively. A predictive model for aflatoxin B1 synthesis in the initial ensiling phase was established, in function of grain moisture, external temperature, and time. Within the studied range, A. flavus’s initial concentration did not significantly influence aflatoxin B1 production. According to the model maximum aflatoxin production is expected at 30% moisture and 25°C temperature, after 6 days in the aerobic phase. Aflatoxin B1 production in such conditions was corroborated experimentally. Growth curves and aflatoxin B1 production highlighted that at 48 h of incubation under optimal conditions, aflatoxin B1 concentrations in mini-silos exceeded national legislation limits, reaching values close to 100 ppb. These results underscore the risk associated with A. flavus presence in ensiling material, emphasizing the importance of controlling its development in sorghum silos

Prediction of annual weed seed emergence in garlic (Allium sativum L.) using soil thermal time

Avena fatua L. and Polygonum aviculare L. are two competitive weeds in garlic (Allium sativum L.) fields. Knowledge of the temporal pattern emergence will contribute to optimizing the timing of control measures, thus maximizing efficacy. The development of predictive models can contribute to control measures at early growth stages. The objective of this study was to develop and validate predictive empirical models of emergence for A. fatua and P. aviculare based on thermal time. Cumulative seedling emergence data were obtained during two years from a garlic field and used to develop and validate the models. The relationship between cumulative seedling emergences and cumulative thermal time (TT) under field conditions was analyzed using the Gompertz function. The models accounted for 98% and 96% of the variation observed in A. fatua and P. aviculare, respectively. Model validation performed well in predicting the seedling emergence of both species. According to this model, A. fatua emergence started at 381 TT after sowing and reached 50% and 90% of total emergence at 407 and 478 TT, respectively, with a soil base temperature of 1. °C. P. aviculare started emergence at 410 TT after sowing and reached 50% and 90% of total emergence at 505 and 590 TT, respectively, with a base temperature of 0. °C. Results indicate that these models could be useful as predictive tool contributing to a effective control of A. fatua and P. aviculare populations in garlic crops. © 2014 Elsevier B.V.LG-A was supported by FEDER and the Spanish Ministry of Economy and Competitiveness funds (AGL2009-07883).Peer Reviewe

The nuclear receptor LXRα controls the functional specialization of splenic macrophages.

Macrophages are professional phagocytic cells that orchestrate innate immune responses and have considerable phenotypic diversity at different anatomical locations. However, the mechanisms that control the heterogeneity of tissue macrophages are not well characterized. Here we found that the nuclear receptor LXRα was essential for the differentiation of macrophages in the marginal zone (MZ) of the spleen. LXR-deficient mice were defective in the generation of MZ and metallophilic macrophages, which resulted in abnormal responses to blood-borne antigens. Myeloid-specific expression of LXRα or adoptive transfer of wild-type monocytes restored the MZ microenvironment in LXRα-deficient mice. Our results demonstrate that signaling via LXRα in myeloid cells is crucial for the generation of splenic MZ macrophages and identify an unprecedented role for a nuclear receptor in the generation of specialized macrophage subsets

TRY plant trait database – enhanced coverage and open access

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

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 Kjøller, Tamir Klein, Michael Kleyer, Jitka Klimešová, 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 Kühn, 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 Llusià, Madelon Lohbeck, Álvaro López-García, Gabriela Lopez-Gonzalez, Zdeňka Lososová, Frédérique Louault, Balázs A. Lukács, Petr Lukeš, Yunjian Luo, Michele Lussu, Siyan Ma, Camilla Maciel Rabelo Pereira, Michelle Mack, Vincent Maire, Annikki Mäkelä, Harri Mäkinen, 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 Martínez-Garza, Jordi Martínez-Vilalta, Tereza Mašková, 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, Céline Meredieu, Julie Messier, Ilona Mészáros, 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 Molnár V, Jane Molofsky, Martin Molz, Rebecca A. Montgomery, Arnaud Monty, Lenka Moravcová, Alvaro Moreno-Martínez, Marco Moretti, Akira S. Mori, Shigeta Mori, Dave Morris, Jane Morrison, Ladislav Mucina, Sandra Mueller, Christopher D. Muir, Sandra Cristina Müller, 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 Pärtel, 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, Valério 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 Pyšek, Valerie Raevel, Anja Rammig, Johannes Ransijn, Courtenay A. Ray, Peter B. Reich, Markus Reichstein, Douglas E. B. Reid, Maxime Réjou-Méchain, 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 Rüger, 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-García, 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 Siebenkäs, Carlos Sierra, Vasco Silva, Mateus Silva, Tommaso Sitzia, Henrik Sjöman, Martijn Slot, Nicholas G. Smith, Darwin Sodhi, Pamela Soltis, Douglas Soltis, Ben Somers, Grégory Sonnier, Mia Vedel Sørensen, 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 Svitková, Marek Svitok, Miroslav Svoboda, Emily Swaine, Nathan Swenson, Marcelo Tabarelli, Kentaro Takagi, Ulrike Tappeiner, Rubén Tarifa, Simon Tauugourdeau, Cagatay Tavsanoglu, Mariska te Beest, Leho Tedersoo, Nelson Thiffault, Dominik Thom, Evert Thomas, Ken Thompson, Peter E. Thornton, Wilfried Thuiller, Lubomír Tichý, David Tissue, Mark G. Tjoelker, David Yue Phin Tng, Joseph Tobias, Péter Török, Tonantzin Tarin, José M. Torres-Ruiz, Béla Tóthmérész, 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 André Vanselow, Angelica Vårhammar, Laura Varone, Maribel Yesenia Vasquez Valderrama, Kiril Vassilev, Mark Vellend, Erik J. Veneklaas, Hans Verbeeck, Kris Verheyen, Alexander Vibrans, Ima Vieira, Jaime Villacís, 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, Kátia Janaina Zanini, Amy E. Zanne, David Zelený, Yun-Peng Zhao, Jingming Zheng, Ji Zheng, Kasia Ziemińska, Chad R. Zirbel, Georg Zizka, Irié 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 Société'.http://wileyonlinelibrary.com/journal/gcbhj2021Plant Production and Soil Scienc

Integrated Weed Management: A Shift towards More Sustainable and Holistic Practices

Feeding more people sustainably is among humanity’s biggest challenges in the next few decades [...

An Overview of Environmental Cues That Affect Germination of Nondormant Seeds

For a successful germination and plant growth, seeds must germinate at the right time. Seeds must become nondormant and must fulfill the seed germination requirements. These requirements include light/dark, moisture, temperature, and other environmental cues (e.g., ethylene, exudate from host roots, or chemicals from fire) in the habitat. Seeds come out from dormancy in response to environmental cues, but depending on the species, they may need to be exposed to a second set of environmental cue to germinate. That is, nondormant seeds require specific temperature and water conditions to germination, and sometimes unfavorable temperature and water conditions will cause seeds to enter secondary dormancy. There are still mysteries about how/what environmental cues help seeds detect the right time/conditions for germination after dormancy is broken. Our knowledge of species-specific conditions is incomplete and further studies are needed

Quantifying and Disentangling the Competition Effect of a Weed Community in a Long-Term Biennial Cereal-Legume Rotation

Weeds are a permanent constraint on crop productivity in agriculture. Due to the importance of the effect of weeds on the crop, there has been great interest in establishing the competitive ability of each species to optimize its control. This work presents a new methodology approach to determining the relative competitiveness of weed species based on population dynamics theory, which is applied to establish the competitiveness of Papaver rhoeas L. (PAP), Veronica hederifolia L. (VER), Descurainia sophia L. (DES) and Fumaria spp. (FUM) infesting a biennial cereal-legume rotation under conventional tillage. Data to fit the nonlinear population dynamic models were obtained from a long-term experiment (32 years) in Mediterranean drylands. The results showed asymmetric competitive interactions, and the competitive ability of weeds was crop specific. In cereals, the competitiveness ranking order was FUM > PAP > VER > DES, with strong interspecific competition; in legumes, it was VER > FUM > DES > PAP, with weak interspecific competition intensity. Overall, intraspecific competition was stronger than interspecific competition in the rotation system. The information gained in these studies can provide insights into the role of the intraspecific and interspecific competition in weed communities and help identify weed species that are relatively poor competitors in given crops

Weed community changes in saffron+chickpea intercropping under different irrigation management.

Saffron (Crocus sativus L.) is among the world's most expensive crops; nevertheless, it struggles to compete with weeds. Non-chemical farming practices, such as intercropping and reduced irrigation, can help to decrease weed problems. Therefore, this study aimed to evaluate the changes in the weed density, biomass and weed diversity under saffron-chickpea intercropping system with two irrigation regimes. The study's treatments included two irrigation regimes, namely one-time irrigation and conventional irrigation (carried out four times from October through May), and six planting ratios of saffron and chickpea, namely saffron sole-crop (C1), chickpea sole-crop (C2) in eight rows, 1:1 (C3), 2:2 (C4), 2:1 (C5), and 3:1 (C6)] as main and sub-plots, respectively. The result showed that the conventional irrigation regimes increased weed diversity, however, it didn't affect the Pielou index. Intercropping ratios decreased weed diversity compared to saffron and chickpea mono-cropping systems. The interaction effect of treatments was significant for weed density and weed biomass. In most intercropping ratios, weed density and weed biomass decreased under one-time irrigation regimes. The lowest values for weed density and biomass were observed with an average of 15.5 plants/m2 and 37.51 g/m2, respectively, under the one-time irrigation regime with C4 intercropping systems. This intercropping system did not show a significant difference with C3. Overall, the results indicate that a one-time irrigation regime and intercropping with chickpea, specifically with a 1:1 saffron-chickpea ratio (C3) and a 2:2 saffron-chickpea ratio (C4), could be effective strategies for weed management in saffron in semiarid cropping systems

Economical Evaluation of Reduced Herbicide Doses Application Rates to Control Phalaris brachystachys (Short-Spiked Canary Grass) in a Biennial Wheat–Sunflower Rotation in Mediterranean Dryland: A Modelling Approach

Phalaris brachystachys (short-spiked canary grass) is considered to be among the most troublesome cereal weeds in Mediterranean areas. A bioeconomic model, based on population dynamics, competition and economic sub-models, was developed to simulate the long-term economic consequence of using herbicide-based strategies: no herbicide application, full herbicide dose (standard rate) and two reduced dose rates (75 and 50% of the standard rate) to control P. brachystachys in a biennial wheat–sunflower rotation. Simulation results indicated that only herbicide application at a full dose (90% control) and 3/4 dose (80% control) produced positive economic results, with the full dose being the best strategy (EUR 98.65 ha−1 year−1). A sensitivity analysis showed that the economic outcome, in terms of annualized net return, was strongly influenced by changes in yield, price, and fixed costs. In addition, the annualized net return was more sensitive to parameter changes at reduced herbicide doses than at full rate. In the wheat–sunflower rotation system, the application of the full dose of herbicide was the most economical and stable strategy in the long-term. Reduced doses are not a recommended option from an economic point of view. Bioeconomic models provide practical insight into different management approaches for effective weed control