3,980 research outputs found

    The future of bioethanol

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    Yeasts have been domesticated by mankind before horses. After the mastering of alcoholic fermentation for centuries, yeasts have become the protagonist of one of the most important biotechnological industries worldwide: the production of bioethanol. This chapter will initially present some important challenges to be overcome in this industry, both in first and second generation biofuel production. Then, it will briefly revisit some advances obtained in recent years. Finally, it will present and discuss some opportunities, in the scope of metabolic engineering and synthetic biology, that will likely be present in the future of bioethanol

    A singlet-triplet extension for the Higgs search at LEP and LHC

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    We describe a simple extension of the standard model, containing a scalar singlet and a triplet fermion. The model can explain the possible enhancement in the decay HγγH \rightarrow \gamma \gamma at the LHC together with the excess found in the Higgs boson search at LEP2. The structure of the model is motivated by a recent argument, that was used to explain the number of fermion generations. For the sake of completenes we also considered the contributions from higher multiplets.Comment: 12 pages, 2 figure

    Mitigating stress in industrial yeasts

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    The yeast, Saccharomyces cerevisiae, is the premier fungal cell factory exploited in industrial biotechnology. In particular, ethanol production by yeast fermentation represents the world's foremost biotechnological process, with beverage and fuel ethanol contributing significantly to many countries economic and energy sustainability. During industrial fermentation processes, yeast cells are subjected to several physical, chemical and biological stress factors that can detrimentally affect ethanol yields and overall production efficiency. These stresses include ethanol toxicity, osmostress, nutrient starvation, pH and temperature shock, as well as biotic stress due to contaminating microorganisms. Several cell physiological and genetic approaches to mitigate yeast stress during industrial fermentations can be undertaken, and such approaches will be discussed with reference to stress mitigation in yeasts employed in Brazilian bioethanol processes. This article will highlight the importance of furthering our understanding of key aspects of yeast stress physiology and the beneficial impact this can have more generally on enhancing industrial fungal bioprocesses

    Natural ZZ' model with an inverse seesaw and leptonic dark matter

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    We consider a model for a Z'-boson coupled only to baryon minus lepton number and hypercharge. Besides the usual right-handed neutrinos, we add a pair of fermions with a fractional lepton charge, which we therefore call leptinos. One of the leptinos is taken to be odd under an additional Z_2 charge, the other even. This allows for a natural (inverse) seesaw mechanism for neutrino masses. The odd leptino is a candidate for dark matter, but has to be resonantly annihilated by the Z'-boson or the Higgs-boson responsible for giving mass to the former. Considering collider and cosmological bounds on the model, we find that the Z'-boson and/or the extra Higgs-boson can be seen at the LHC. With more pairs of leptinos leptogenesis is possible.Comment: 29 pages, 9 figures. RGE section moved to appendix and other minor corrections applied to matched published versio

    Plant emergence and maize (Zea mays L.) yield across multiple farmers’ fields

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    Context: Uneven crop stands result from natural variation in emergence time that is related to soil moisture and temperature, and variation of within-row plant-to-plant distance caused during planting operations. Understanding the effect of the spatial and temporal variation of plant emergence on crop yield can help farmers make improved management decisions about planting. Objective: The objectives of this work were to i) compare the timing of maize plant emergence across and within sub-field yield stability zones, ii) evaluate the impact of delayed emergence on crop yield and yield components by yield stability zone, and iii) compare the effect of spatial and temporal variability of plant emergence on crop yield and yield components. Methods: Ten experiments were conducted in farmers’ maize fields in Springport (Michigan, US), Portland (Michigan, US), and Parana (Entre Rios, Argentina). Several years of yield monitored data for each field were used to delimitate yield stability zones (YSZ). Individual plant emergence was recorded daily, across yield stability zones. Emerged plants were tagged and the distance between plants within the row was recorded and used to calculate plant growing space (cm2 plant−1), and to classify them within plant stand as uniform, double or skips. Tagged plants were hand harvested to analyze the individual plant yield, number and weight of grains, and total crop yield. Results: Individual plant emergence time ranged from 3 to 31 days after planting (DAP). The variation in timing of plant emergence had a greater impact than the variation of within-row plant spacing on crop yield and yield components. In general, the impact was larger in stable low yield areas. On average, plant yield was reduced by 7 %, grain number by 6 %, and final crop yield by 8.5 % per day of emergence delay after planting. The greater variation in the days of emergence delay when compared to within-row plant spacing variation can be related to the small overall spatial variability within the rows. Conclusions: Plant emergence temporal variability had a higher impact than within-row plant spatial variability on crop yield and its components. The decrease in maize yield caused by the delay in emergence was not statistically related to yield stability zones. However, a trend of a more negative impact of delayed emergence in the low yield stability zones was observed. Implications: Understanding factors affecting the spatial and temporal plant emergence patterns of crops can help farmers optimize their planting operation and may help them with decisions on using more precise and tailored inputs (such as seed rate and nitrogen fertilizer) on different sub-field yield stability zones. Incorporating emergence data and information into crop models will also help improve yield simulation results.EEA ParanáFil: Albarenque, Susana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; ArgentinaFil: Albarenque, Susana. Michigan State University. Department of Plant, Soil and Microbial Sciences; Estados UnidosFil: Basso, Bruno. Michigan State University. Department of Earth and Environmental Sciences; Estados UnidosFil: Basso, Bruno. Michigan State University. W.K. Kellogg Biological Station; Estados UnidosFil: Davidson, O. Environmental Protection Agency; Estados UnidosFil: Maestrini, B. Wageningen University & Research. Agrosystems Research Group; Países BajosFil: Melchiori, Ricardo Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentin

    Erratum to: Quantitative physiology and elemental composition of Kluyveromyces lactis CBS 2359 during growth on glucose at different specific growth rates

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    In the original publication of the article, the below mentioned errors have appeared. The correct text is provided in this erratum. In the abstract section, the sentence ‘‘This dataset serve’’ should be replaced as ‘‘This dataset serves’’. Also, the reference ‘‘Basso TO, Gomes FS, Lopes ML, et al (2014) Homo- and heterofermentative lactobacilli differently affect sugarcane-based fuel ethanol fermentation.Antonie Van Leeuwenhoek105:169–177. doi:10.1007/s10482-013-0063-6’’ should be replaced as ‘‘Basso TO, Dario MG, Tonso A, Stambuk BU, GombertAK(2010)Insufficienturacilsupplyinfullyaerobic chemostat cultures of Saccharomyces cerevisiae leads torespiro-fermentative metabolism anddouble nutrientlimitation. Biotechnol Lett 32:973–977. doi: 10.1007/ s10529-010-0248-2’’. Finally, in the Table 2 footnote, ‘‘according to (Heijnen 1981)’’ should be replaced as ‘‘according to Heijnen (1981)’’.info:eu-repo/semantics/publishedVersio

    Quantitative physiology and elemental composition of Kluyveromyces lactis CBS 2359 during growth on glucose at different specific growth rates

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    The yeast Kluyveromyces lactis has received attention both from academia and industry due to some important features, such as its capacity to grow in lactose-based media, its safe status, its suitability for large-scale cultivation and for heterologous protein synthesis. It has also been considered as a model organism for genomics and metabolic regulation. Despite this, very few studies were carried out hitherto under strictly controlled conditions, such as those found in a chemostat. Here we report a set of quantitative physiological data generated during chemostat cultivations with the K. lactis CBS 2359 strain, obtained under glucose-limiting and fully aerobic conditions. This dataset serve as a basis for the comparison of K. lactis with the model yeast Saccharomyces cerevisiae in terms of their elemental compositions, as well as for future metabolic flux analysis and metabolic modelling studies with K. lactis.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. T.O.B. would like to express his gratitude for funds provided by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Brasília, Brazil).info:eu-repo/semantics/publishedVersio
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