Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2019
Authors
Inge Stupak Tat Smith Nicholas Clarke Teodorita Al-Seadi Lina Beniušienė Niclas Scott Bentsen Quentin Cheung Virginia Dale Jinke van Dam Rocio Diaz-Chavez Uwe Fritsche Martyn Futter Jianbang Gan Kaija Hakala Thomas Horschig Martin Junginger Yoko Kitigawa Brian Kittler Keith Kline Charles Lalonde Søren Larsen Dagnija Lazdina Thuy P. T. Mai-Moulin Maha Mansoor Edmund Mupondwa Shyam Nair Nathaniel Newlands Liviu Nichiforel Marjo Palviainen John Stanturf Kay Schaubach Johanny Arilexis Perez Sierra Vita Tilvikiene Brian Titus Daniela Thrän Sergio Ugarte Liisa Ukonmaanaho Iveta Varnagiryte-Kabasinskiene Maria WellischAbstract
No abstract has been registered
Authors
Ning Wang Huan Peng Shi-ming Liu Wen-kun Huang Ricardo Holgado Jihong Liu Clarke De-liang PengAbstract
Soybean cyst nematode (SCN, Heterodera glycines (I.)) is one of the most important soil-borne pathogens for soybeans. In plant parasitic nematodes, including SCN, lysozyme plays important roles in the innate defense system. In this study, two new lysozyme genes (Hg-lys1 and Hg-lys2) from SCN were cloned and characterized. The in situ hybridization analyses indicated that the transcripts of both Hg-lys1 and Hg-lys2 accumulated in the intestine of SCN. The qRT-PCR analyses showed that both Hg-lys1 and Hg-lys2 were upregulated after SCN second stage juveniles (J2s) were exposed to the Gram-positive bacteria Bacillus thuringiensis, Bacillus subtilis or Staphylococcus aureus. Knockdown of the identified lysozyme genes by in vitro RNA interference caused a significant decrease in the survival rate of SCN. All of the obtained results indicate that lysozyme is very important in the defense system and survival of SCN.
Conference lecture – A female plant biotechnologist’s journey: never stop dreaming
Jihong Liu Clarke
Authors
Jihong Liu ClarkeAbstract
No abstract has been registered
Conference lecture – Green plant factory for the production of high value proteins
Jihong Liu Clarke
Authors
Jihong Liu ClarkeAbstract
No abstract has been registered
Authors
Jihong Liu ClarkeAbstract
No abstract has been registered
Authors
Jyrki Jauhiainen Jukka Alm Brynhildur Bjarnadottir Ingeborg Callesen Jesper R Christiansen Nicholas Clarke Lise Dalsgaard Hongxing He Sabine Jordan Vaiva Kazanavičiūtė Leif Klemedtsson Ari Laurén Andis Lazdiņš Aleksi Lehtonen Annalea Lohila Ainars Lupikis Ülo Mander Kari Minkkinen Åsa Kasimir Mats Olsson Paavo Ojanen Hlynur Óskarsson Bjarni D. Sigurdsson Gunnhild Søgaard Kaido Soosaar Lars Vesterdal Raija LaihoAbstract
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Authors
Junbin ZhaoAbstract
As the main drivers of climate change, greenhouse gas (e.g., CO2 and CH4) emissions have been monitored intensively across the globe. The static chamber is one of the most commonly used approaches for measuring greenhouse gas fluxes from ecosystems (e.g., stem/soil respiration, CH4 emission, etc.) because of its easy implementation, high accuracy and low cost (Pumpanen et al., 2004). To perform the measurements, a gas analyzer is usually used to measure the changes of greenhouse gas concentrations within a closed chamber that covers an area of interest (e.g., soil surface) over a certain period of time (usually several minutes). The flux rates (F) are then calculated from the recorded gas concentrations assuming that the changing rate is linear: F = vol/(R · T a · area) · dG/dt where vol is the volume of the chamber (l), R is the universal gas constant (l atm K-1 mol-1), Ta is the ambient temperature (K), area is the area of the chamber base (m2 ), and dG/dt is the rate of the measured gas concentration change over time t (ppm s-1) (i.e., the slope of the linear regression).