Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2023
Forfattere
Salvatore Raniolo Laura Maretto Elena Benedetti del Rio Sylvie Cournut Maeva Cremilleux Benjamin Nowak Audrey Michaud Vibeke Lind Giuseppe Concheri Piergiorgio Stevanato Andrea Squartini Maurizio Ramazin Enrico SturaroSammendrag
Grasslands represent key functional ecosystems due to their global contribution to macronutrients cycling and their role as reservoirs of microbial diversity. The strategic importance of these habitats rests on their involvement in carbon and nitrogen fluxes from the atmosphere to the soil, while at the same time offering extensive sites for livestock rearing. In this study the management type, differentiated in pasture or meadow, was investigated as a variable for its possible effects on overall bacterial diversity and specific genes related to functional guilds. Its contribution was compared to that of other variables such as region, soil pH, and soil organic carbon, to rank their respective hierarchies in shaping microbial community structure. A latitudinal gradient across the European continent was studied, with three sampling groups located in Norway, France, and Northern Italy. The applied methods involved 16S DNA metabarcoding for taxonomic classification and determination of the relative abundance of the bacterial component, and quantitative PCR for the genetic determinants of bacterial and archaeal nitrification, intermediate or terminal denitrification, and nitrogen fixation. Results indicated that soil pH exerted the dominant role, affecting high taxonomy ranks and functions, along with organic carbon and region, with whom it partly covaried. In contrast, management type had no significant influence on microbial community structure and quantitative counts of functional genes. This suggests an ecological equivalence between the impacts of pasture and meadow practices, which are both perturbations that share the aspect of vegetation withdrawal by browsing or cutting, respectively.
Forfattere
Bikal GhimireSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Urban Česnik Mitja Martelanc Ingunn Øvsthus Tatjana Radovanovic Vukajlović Ahmad Hosseini Branka Mozetič Vodopivec Lorena ButinarSammendrag
Saccharomyces cerevisiae is commonly used for the production of alcoholic beverages, including cider. In this study, we examined indigenous S. cerevisiae and S. uvarum strains, both species commonly found in cider from Hardanger (Norway), for their strain-specific abilities to produce volatile and non-volatile compounds. Small-scale fermentation of apple juice with 20 Saccharomyces strains was performed to evaluate their aroma-producing potential as a function of amino acids (AAs) and other physicochemical parameters under the same experimental conditions. After fermentation, sugars, organic acids, AAs, and biogenic amines (BAs) were quantified using the HPLC–UV/RI system. A new analytical method was developed for the simultaneous determination of nineteen AAs and four BAs in a single run using HPLC–UV with prior sample derivatization. Volatile compounds were determined using HS-SPME-GC-MS. Based on 54 parameters and after the removal of outliers, the nineteen strains were classified into four groups. In addition, we used PLS regression to establish a relationship between aroma compounds and predictor variables (AAs, BAs, organic acids, sugars, hydrogen sulfide (H2S) production, CO2 release) of all 19 strains tested. The results of the VIP show that the main predictor variables affecting the aroma compounds produced by the selected yeasts are 16, belonging mainly to AAs.
Forfattere
Camille S. Delavaux Thomas W. Crowther Constantin M. Zohner Niamh M. Robmann Thomas Lauber Johan van den Hoogen Sara Kuebbing Jingjing Liang Sergio de-Miguel Gert-Jan Nabuurs Peter B. Reich Meinrad Abegg Yves C. Adou Yao Giorgio Alberti Angelica M. Almeyda Zambrano Braulio Vilchez Alvarado Esteban Alvarez-Dávila Patricia Alvarez-Loayza Luciana F. Alves Christian Ammer Clara Antón Fernandéz Alejandro Araujo-Murakami Luzmila Arroyo Valerio Avitabile Gerardo A. Aymard Timothy R. Baker Radomir Bałazy Olaf Banki Jorcely G. Barroso Meredith L. Bastian Jean-Francois Bastin Luca Birigazzi Philippe Birnbaum Robert Bitariho Pascal Boeckx Frans Bongers Olivier Bouriaud Pedro H. S. Brancalion Susanne Brandl Roel Brienen Eben N. Broadbent Helge Bruelheide Filippo Bussotti Roberto Cazzolla Gatti Ricardo G. César Goran Cesljar Robin Chazdon Han Y. H. Chen Chelsea Chisholm Hyunkook Cho Emil Cienciala Connie Clark David Clark Gabriel D. Colletta David A. Coomes Fernando Cornejo Valverde José J. Corral-Rivas Philip M. Crim Jonathan R. Cumming Selvadurai Dayanandan André L. de Gasper Mathieu Decuyper Géraldine Derroire Ben DeVries Ilija Djordjevic Jiri Dolezal Aurélie Dourdain Nestor Laurier Engone Obiang Brian J. Enquist Teresa J. Eyre Adandé Belarmain Fandohan Tom M. Fayle Ted R. Feldpausch Leandro V. Ferreira Markus Fischer Christine Fletcher Lorenzo Frizzera Javier G. P. Gamarra Damiano Gianelle Henry B. Glick David J. Harris Andrew Hector Andreas Hemp Geerten Hengeveld Bruno Hérault John L. Herbohn Martin Herold Annika Hillers Eurídice N. Honorio Coronado Cang Hui Thomas T. Ibanez Iêda Amaral Nobuo Imai Andrzej M. Jagodziński Bogdan Jaroszewicz Vivian Kvist Johannsen Carlos A. Joly Tommaso Jucker Ilbin Jung Viktor Karminov Kuswata Kartawinata Elizabeth Kearsley David Kenfack Deborah K. Kennard Sebastian Kepfer-Rojas Gunnar Keppel Mohammed Latif Khan Timothy J. Killeen Hyun Seok Kim Kanehiro Kitayama Michael Köhl Henn Korjus Florian Kraxner Diana Laarmann Mait Lang Simon L. Lewis Huicui Lu Natalia V. Lukina Brian S. Maitner Yadvinder Malhi Eric Marcon Beatriz Schwantes Marimon Ben Hur Marimon-Junior Andrew R. Marshall Emanuel H. Martin Olga Martynenko Jorge A. Meave Omar Melo-Cruz Casimiro Mendoza Cory Merow Abel Monteagudo Mendoza Vanessa S. Moreno Sharif A. Mukul Philip Mundhenk María Guadalupe Nava-Miranda David Neill Victor J. Neldner Radovan V. Nevenic Michael R. Ngugi Pascal A. Niklaus Jacek Oleksyn Petr Ontikov Edgar Ortiz-Malavasi Yude Pan Alain Paquette Alexander Parada-Gutierrez Elena I. Parfenova Minjee Park Marc Parren Narayanaswamy Parthasarathy Pablo L. Peri Sebastian Pfautsch Oliver L. Phillips Nicolas Picard Maria Teresa T. F. Piedade Daniel Piotto Nigel C. A. Pitman Irina Polo Lourens Poorter Axel Dalberg Poulsen Hans Pretzsch Freddy Ramirez Arevalo Zorayda Restrepo-Correa Mirco Rodeghiero Samir G. Rolim Anand Roopsind Francesco Rovero Ervan Rutishauser Purabi Saikia Christian Salas-Eljatib Philippe Saner Peter Schall Dmitry Schepaschenko Michael Scherer-Lorenzen Bernhard Schmid Jochen Schöngart Eric B. Searle Vladimír Seben Josep M. Serra-Diaz Douglas Sheil Anatoly Z. Shvidenko Javier E. Silva-Espejo Marcos Silveira James Singh Plinio Sist Ferry Slik Bonaventure Sonké Alexandre F. Souza Stanislaw Miscicki Krzysztof J. Stereńczak Jens-Christian Svenning Miroslav Svoboda Ben Swanepoel Natalia Targhetta Nadja Tchebakova Hans ter Steege Raquel Thomas Elena Tikhonova Peter M. Umunay Vladimir A. Usoltsev Renato Valencia Fernando Valladares Fons van der Plas Tran Van Do Michael E. van Nuland Rodolfo M. Vasquez Hans Verbeeck Helder Viana Alexander C. Vibrans Simone Vieira Klaus von Gadow Hua-Feng Wang James V. Watson Gijsbert D. A. Werner Susan K. Wiser Florian Wittmann Hannsjoerg Woell Verginia Wortel Roderik Zagt Tomasz Zawiła-Niedźwiecki Chunyu Zhang Xiuhai Zhao Mo Zhou Zhi-Xin Zhu Irie C. Zo-Bi Daniel S. MaynardSammendrag
Det er ikke registrert sammendrag
Sammendrag
Nutrient uptake and transport depend on the root system of a tree. Various apple rootstock genotypes may interact fruit tree nutrition. In 2017, two multi-location apple rootstock trials were established at 16 sites in 12 European countries. The evaluations are performed by members of the EUFRIN (European Fruit Research Institute Network) Apple & Pear Variety & Rootstock Testing Working Group. Following rootstocks are included in the tests: G.11, G.41, G.202 and G.935 (US), EM_01, EM_02, EM_03, EM_04, EM_05 and EM_06 (UK), 62-396-B10® (Russia), P 67 (Poland), NZ-A, NZ-B, NZ-C and NZ-D (New Zealand) and Cepiland-Pajam®2 as control. The effect of rootstocks on the mineral content of leaf and fruit was studied at the Institute of Horticulture, Lithuanian Research Centre for Agriculture and Forestry in 2019-2020. The leaf and fruit mineral concentration of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), and leaf mineral content of copper (Cu), zinc (Zn), iron (Fe), manganese (Mn) and boron (B) were measured. Significant rootstock effect was established on leaf P, Mg, Zn, Mn, B, and fruit Ca and Mg content. Rootstocks EM_01 and G.41 were the most efficient in leaf mineral uptake, while G.935 had the lowest content of all leaf macro nutrients. Rootstocks EM_06 and P 67 were the most efficient in fruit mineral uptake, while EM_02 had the lowest content of three nutrients. Current research reveals differences among rootstocks and their capacity to absorb separate minerals and enables creation of rootstock specific nutrition management.
Forfattere
Yi Zhang Zhangmu Jing Yijing Feng Shuo Chen Yeqing Li Yongming Han Lu Feng Junting Pan Mahmoud Mazarji Hongjun Zhou Xiaonan Wang Chunming XuSammendrag
Exploring key factors has important guidance for understanding complex anaerobic digestion (AD) systems. This study proposed a multi-layer automated machine learning framework to understand the complex interactions in AD systems and explore key factors at the environmental factor, microorganisms and system levels. The first layer of the framework identified hydraulic residence time (HRT) as the most important environmental factor, with an optimal range of 33–45 d. In the second layer of the framework, Methanocelleus (optimal relative abundance (ORA) = 3.0%) and Candidatus_Caldatribacterium (ORA = 1.7%) were found to be the key archaea and bacteria, respectively. Furthermore, the prediction of key microorganisms based on environmental factors and remaining microbial data showed the essential roles of Methanothermobacter and Acetomicrobium. The third layer for finding the optimal combination of data variables for predicting biogas production demonstrated that combined Archaea genera and environmental factors should be achieved for the most accurate prediction (root mean square error (RMSE) = 84.21). GBM had the best model performance and prediction accuracy among all the built-in models. Based on the optimal GBM model, the analysis at the system level showed that HRT was the most important variable. However the most important microorganism, Methanocelleus, within the appropriate survival range is also essential to achieve optimal biogas production. This research explores key parameters at various levels through automated machine learning techniques, which are expected to provide guidance in understanding the complex architecture of industrial and laboratory AD systems.
Forfattere
Damaris Marina Matten Ida Marielle Mienna Vanessa Carina Bieker Brent D. Mishler Victoria Stornes Moen Malene Østreng Nygård Katariina Elsa M Vuorinen Mika Bendiksby Michael David Martin James David Mervyn SpeedSammendrag
Paid open access
Sammendrag
Det er ikke registrert sammendrag