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- ItemMethane prediction based on individual or groups of milk fatty acids for dairy cows fed rations with or without linseed(New York, NY [u.a.] : Elsevier, 2019) Engelke, Stefanie W.; Daş, Gürbüz; Derno, Michael; Tuchscherer, Armin; Wimmers, Klaus; Rychlik, Michael; Kienberger, Hermine; Berg, Werner; Kuhla, Björn; Metges, Cornelia C.Milk fatty acids (MFA) are a proxy for the prediction of CH4 emission from cows, and prediction differs with diet. Our objectives were (1) to compare the effect of diets on the relation between MFA profile and measured CH4 production, (2) to predict CH4 production based on 6 data sets differing in the number and type of MFA, and (3) to test whether additional inclusion of energy-corrected milk (ECM) yield or dry matter intake (DMI) as explanatory variables improves predictions. Twenty dairy cows were used. Four diets were used based on corn silage (CS) or grass silage (GS) without (L0) or with linseed (LS) supplementation. Ten cows were fed CS-L0 and CS-LS and the other 10 cows were fed GS-L0 and GS-LS in random order. In feeding wk 5 of each diet, CH4 production (L/d) was measured in respiration chambers for 48 h and milk was analyzed for MFA concentrations by gas chromatography. Specific CH4 prediction equations were obtained for L0-, LS-, GS-, and CS-based diets and for all 4 diets collectively and validated by an internal cross-validation. Models were developed containing either 43 identified MFA or a reduced set of 7 groups of biochemically related MFA plus C16:0 and C18:0. The CS and LS diets reduced CH4 production compared with GS and L0 diets, respectively. Methane yield (L/kg of DMI) reduction by LS was higher with CS than GS diets. The concentrations of C18:1 trans and n-3 MFA differed among GS and CS diets. The LS diets resulted in a higher proportion of unsaturated MFA at the expense of saturated MFA. When using the data set of 43 individual MFA to predict CH4 production (L/d), the cross-validation coefficient of determination (R2 CV) ranged from 0.47 to 0.92. When using groups of MFA variables, the R2 CV ranged from 0.31 to 0.84. The fit parameters of the latter models were improved by inclusion of ECM or DMI, but not when added to the data set of 43 MFA for all diets pooled. Models based on GS diets always had a lower prediction potential (R2 CV = 0.31 to 0.71) compared with data from CS diets (R2 CV = 0.56 to 0.92). Models based on LS diets produced lower prediction with data sets with reduced MFA variables (R2 CV = 0.62 to 0.68) compared with L0 diets (R2 CV = 0.67 to 0.80). The MFA C18:1 cis-9 and C24:0 and the monounsaturated FA occurred most often in models. In conclusion, models with a reduced number of MFA variables and ECM or DMI are suitable for CH4 prediction, and CH4 prediction equations based on diets containing linseed resulted in lower prediction accuracy. © 2019 American Dairy Science Association
- ItemThe potential of calcium hydroxide to reduce storage losses: A four months monitoring study of spruce wood chip piles at industrial scale(New York, NY [u.a.] : Elsevier, 2021) Dumfort, Sabrina; Pecenka, Ralf; Ascher-Jenull, Judith; Peintner, Ursula; Insam, Heribert; Lenz, HannesThe objective of this study was to investigate the effect of an alkaline additive on the storage of wood chips from Norway spruce forest residues. Piles of untreated and calcium hydroxide treated wood chips (250 m3) were set up and investigated for four months. It was demonstrated that adding Ca(OH)2 to moist wood chips decreased the dry matter loss by 6%. This was attributed to the increase of the pH to a level of 8, rendering the habitat less suitable for fungal colonisation. The results suggest the set-up storage strategy as a potential alternative method for preserving wood chips when long term storage is required.
- ItemAsh transformation mechanism during combustion of rice husk and rice straw(New York, NY [u.a.] : Elsevier, 2022) Beidaghy Dizaji, Hossein; Zeng, Thomas; Hölzig, Hieronymus; Bauer, Jens; Klöß, Gert; Enke, DirkBiomass is an alternative energy resource to fossil fuels because of its potential to reduce greenhouse gas emissions. However, ash-related problems are serious obstacles for this development, especially for the use in combustion plants. Thus, design and operation of biomass boilers require detailed understanding of ash transformation reactions during thermochemical conversion. To evaluate ash transformation in silica-rich biomass fuels, rice husk and rice straw were selected because of their abundance, limited utilization conflicts with the food sector, as well as their potential in both energy and material applications. This paper reveals ash transformation mechanisms relevant for the ash melting behaviour of silica-rich biomass fuels considering chemical and phase composition of the ashes. In this regard, several advanced spectroscopic methods and diffractometry were employed to characterize the materials. The ash transformation reactions and the viscosity were simulated using thermodynamic equilibrium calculations and a slag viscosity modeling toolbox. The results illustrate the impact of impurities on the atomic structure of the silica resulting in an altered ash melting behaviour and viscosity of the silica-rich ashes. Chemical water washing, acid leaching, and blending of rice straw with rice husk strongly influenced the chemical composition of the ashes and improved ash melting behaviour. The analysis also revealed the correlation between the crystalline fraction and the porosity in silica-rich biomass ashes, as well as a crystallinity threshold. These findings are highly relevant for future investigations in boiler designs and production of biogenic silica for material applications.